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The Obama Jobs Recession Continues — Labor Participation Rate of 62.8% with 145.8 Million Employed in May 2014 vs. 66% Labor Participation Rate with 146.6 Million Employed in November 2007 — Videos

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Story 1: The Obama Jobs Recession Continues — Labor Participation Rate of 62.8% with 145.8 Million Employed in May 2014 vs. 66% Labor Participation Rate with 146.6 Million Employed in November 2007 — Videos

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Labor Secretary Dismisses Historical Drop in Labor Participation Rate

Labor Force Participation Rate

Labor participation rate is down to unprecedented levels

BLS Commissioner Groshen on drop in job participation rate- “It’s certainly not a sign of strength.”

Will The Unemployment Rate Stall

 

Employment Level

145,814,000

 

employment_level

 

Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual
2000 136559(1) 136598 136701 137270 136630 136940 136531 136662 136893 137088 137322 137614
2001 137778 137612 137783 137299 137092 136873 137071 136241 136846 136392 136238 136047
2002 135701 136438 136177 136126 136539 136415 136413 136705 137302 137008 136521 136426
2003 137417(1) 137482 137434 137633 137544 137790 137474 137549 137609 137984 138424 138411
2004 138472(1) 138542 138453 138680 138852 139174 139556 139573 139487 139732 140231 140125
2005 140245(1) 140385 140654 141254 141609 141714 142026 142434 142401 142548 142499 142752
2006 143150(1) 143457 143741 143761 144089 144353 144202 144625 144815 145314 145534 145970
2007 146028(1) 146057 146320 145586 145903 146063 145905 145682 146244 145946 146595 146273
2008 146378(1) 146156 146086 146132 145908 145737 145532 145203 145076 144802 144100 143369
2009 142152(1) 141640 140707 140656 140248 140009 139901 139492 138818 138432 138659 138013
2010 138451(1) 138599 138752 139309 139247 139148 139179 139427 139393 139111 139030 139266
2011 139287(1) 139422 139655 139622 139653 139409 139524 139904 140154 140335 140747 140836
2012 141677(1) 141943 142079 141963 142257 142432 142272 142204 142947 143369 143233 143212
2013 143384(1) 143464 143393 143676 143919 144075 144285 144179 144270 143485 144443 144586
2014 145224(1) 145266 145742 145669 145814
1 : Data affected by changes in population controls.

Civilian Labor Force

155,613,000

Civilain Labor force

Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual
2000 142267(1) 142456 142434 142751 142388 142591 142278 142514 142518 142622 142962 143248
2001 143800 143701 143924 143569 143318 143357 143654 143284 143989 144086 144240 144305
2002 143883 144653 144481 144725 144938 144808 144803 145009 145552 145314 145041 145066
2003 145937(1) 146100 146022 146474 146500 147056 146485 146445 146530 146716 147000 146729
2004 146842(1) 146709 146944 146850 147065 147460 147692 147564 147415 147793 148162 148059
2005 148029(1) 148364 148391 148926 149261 149238 149432 149779 149954 150001 150065 150030
2006 150214(1) 150641 150813 150881 151069 151354 151377 151716 151662 152041 152406 152732
2007 153144(1) 152983 153051 152435 152670 153041 153054 152749 153414 153183 153835 153918
2008 154063(1) 153653 153908 153769 154303 154313 154469 154641 154570 154876 154639 154655
2009 154210(1) 154538 154133 154509 154747 154716 154502 154307 153827 153784 153878 153111
2010 153404(1) 153720 153964 154642 154106 153631 153706 154087 153971 153631 154127 153639
2011 153198(1) 153280 153403 153566 153526 153379 153309 153724 154059 153940 154072 153927
2012 154328(1) 154826 154811 154565 154946 155134 154970 154669 155018 155507 155279 155485
2013 155699(1) 155511 155099 155359 155609 155822 155693 155435 155473 154625 155284 154937
2014 155460(1) 155724 156227 155421 155613
1 : Data affected by changes in population controls.

 

Labor Participation Rate

62.8%

Labor Participation Rate

Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual
2000 67.3 67.3 67.3 67.3 67.1 67.1 66.9 66.9 66.9 66.8 66.9 67.0
2001 67.2 67.1 67.2 66.9 66.7 66.7 66.8 66.5 66.8 66.7 66.7 66.7
2002 66.5 66.8 66.6 66.7 66.7 66.6 66.5 66.6 66.7 66.6 66.4 66.3
2003 66.4 66.4 66.3 66.4 66.4 66.5 66.2 66.1 66.1 66.1 66.1 65.9
2004 66.1 66.0 66.0 65.9 66.0 66.1 66.1 66.0 65.8 65.9 66.0 65.9
2005 65.8 65.9 65.9 66.1 66.1 66.1 66.1 66.2 66.1 66.1 66.0 66.0
2006 66.0 66.1 66.2 66.1 66.1 66.2 66.1 66.2 66.1 66.2 66.3 66.4
2007 66.4 66.3 66.2 65.9 66.0 66.0 66.0 65.8 66.0 65.8 66.0 66.0
2008 66.2 66.0 66.1 65.9 66.1 66.1 66.1 66.1 66.0 66.0 65.9 65.8
2009 65.7 65.8 65.6 65.7 65.7 65.7 65.5 65.4 65.1 65.0 65.0 64.6
2010 64.8 64.9 64.9 65.2 64.9 64.6 64.6 64.7 64.6 64.4 64.6 64.3
2011 64.2 64.2 64.2 64.2 64.2 64.0 64.0 64.1 64.2 64.1 64.1 64.0
2012 63.7 63.9 63.8 63.7 63.8 63.8 63.7 63.5 63.6 63.7 63.6 63.6
2013 63.6 63.5 63.3 63.4 63.4 63.5 63.4 63.2 63.2 62.8 63.0 62.8
2014 63.0 63.0 63.2 62.8 62.8

Unemployment Level

9,799,000

unemployment level

 

Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual
2000 5708 5858 5733 5481 5758 5651 5747 5853 5625 5534 5639 5634
2001 6023 6089 6141 6271 6226 6484 6583 7042 7142 7694 8003 8258
2002 8182 8215 8304 8599 8399 8393 8390 8304 8251 8307 8520 8640
2003 8520 8618 8588 8842 8957 9266 9011 8896 8921 8732 8576 8317
2004 8370 8167 8491 8170 8212 8286 8136 7990 7927 8061 7932 7934
2005 7784 7980 7737 7672 7651 7524 7406 7345 7553 7453 7566 7279
2006 7064 7184 7072 7120 6980 7001 7175 7091 6847 6727 6872 6762
2007 7116 6927 6731 6850 6766 6979 7149 7067 7170 7237 7240 7645
2008 7685 7497 7822 7637 8395 8575 8937 9438 9494 10074 10538 11286
2009 12058 12898 13426 13853 14499 14707 14601 14814 15009 15352 15219 15098
2010 14953 15121 15212 15333 14858 14483 14527 14660 14578 14520 15097 14373
2011 13910 13858 13748 13944 13873 13971 13785 13820 13905 13604 13326 13090
2012 12650 12883 12732 12603 12689 12702 12698 12464 12070 12138 12045 12273
2013 12315 12047 11706 11683 11690 11747 11408 11256 11203 11140 10841 10351
2014 10236 10459 10486 9753 9799

Unemployment Rate U-3

6.3%

unemployment rate U 3

Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual
2000 4.0 4.1 4.0 3.8 4.0 4.0 4.0 4.1 3.9 3.9 3.9 3.9
2001 4.2 4.2 4.3 4.4 4.3 4.5 4.6 4.9 5.0 5.3 5.5 5.7
2002 5.7 5.7 5.7 5.9 5.8 5.8 5.8 5.7 5.7 5.7 5.9 6.0
2003 5.8 5.9 5.9 6.0 6.1 6.3 6.2 6.1 6.1 6.0 5.8 5.7
2004 5.7 5.6 5.8 5.6 5.6 5.6 5.5 5.4 5.4 5.5 5.4 5.4
2005 5.3 5.4 5.2 5.2 5.1 5.0 5.0 4.9 5.0 5.0 5.0 4.9
2006 4.7 4.8 4.7 4.7 4.6 4.6 4.7 4.7 4.5 4.4 4.5 4.4
2007 4.6 4.5 4.4 4.5 4.4 4.6 4.7 4.6 4.7 4.7 4.7 5.0
2008 5.0 4.9 5.1 5.0 5.4 5.6 5.8 6.1 6.1 6.5 6.8 7.3
2009 7.8 8.3 8.7 9.0 9.4 9.5 9.5 9.6 9.8 10.0 9.9 9.9
2010 9.7 9.8 9.9 9.9 9.6 9.4 9.5 9.5 9.5 9.5 9.8 9.4
2011 9.1 9.0 9.0 9.1 9.0 9.1 9.0 9.0 9.0 8.8 8.6 8.5
2012 8.2 8.3 8.2 8.2 8.2 8.2 8.2 8.1 7.8 7.8 7.8 7.9
2013 7.9 7.7 7.5 7.5 7.5 7.5 7.3 7.2 7.2 7.2 7.0 6.7
2014 6.6 6.7 6.7 6.3 6.3

Unemployment Rate U-6

12.2%

unemployment rate u 6

Employment Situation Summary

Transmission of material in this release is embargoed until                    USDL-14-0987
8:30 a.m. (EDT) Friday, June 6, 2014

Technical information: 
  Household data:     (202) 691-6378  •  cpsinfo@bls.gov  •  www.bls.gov/cps
  Establishment data: (202) 691-6555  •  cesinfo@bls.gov  •  www.bls.gov/ces

Media contact:        (202) 691-5902  •  PressOffice@bls.gov


                            THE EMPLOYMENT SITUATION -- MAY 2014


Total nonfarm payroll employment rose by 217,000 in May, and the unemployment rate was
unchanged at 6.3 percent, the U.S. Bureau of Labor Statistics reported today. Employment
increased in professional and business services, health care and social assistance, food
services and drinking places, and transportation and warehousing. 

Household Survey Data

The unemployment rate held at 6.3 percent in May, following a decline of 0.4 percentage
point in April. The number of unemployed persons was unchanged in May at 9.8 million.
Over the year, the unemployment rate and the number of unemployed persons declined by
1.2 percentage points and 1.9 million, respectively. (See table A-1.)

Among the major worker groups, the unemployment rates for adult men (5.9 percent),
adult women (5.7 percent), teenagers (19.2 percent), whites (5.4 percent), blacks
(11.5 percent), and Hispanics (7.7 percent) showed little or no change in May. The
jobless rate for Asians was 5.3 percent (not seasonally adjusted), little changed
from a year earlier. (See tables A-1, A-2, and A-3.)

Among the unemployed, the number of job losers and persons who completed temporary
jobs declined by 218,000 in May. The number of unemployed reentrants increased by
237,000 over the month, partially offsetting a large decrease in April. (Reentrants
are persons who previously worked but were not in the labor force prior to beginning
their current job search.) (See table A-11.)

The number of long-term unemployed (those jobless for 27 weeks or more) was essentially
unchanged at 3.4 million in May. These individuals accounted for 34.6 percent of the
unemployed. Over the past 12 months, the number of long-term unemployed has declined by
979,000. (See table A-12.)

The civilian labor force participation rate was unchanged in May, at 62.8 percent.
The participation rate has shown no clear trend since this past October but is down by 0.6
percentage point over the year. The employment-population ratio, at 58.9 percent, was
also unchanged in May and has changed little over the year. (See table A-1.)

The number of persons employed part time for economic reasons (sometimes referred to as
involuntary part-time workers), at 7.3 million, changed little in May. These individuals
were working part time because their hours had been cut back or because they were unable
to find a full-time job. (See table A-8.)

In May, 2.1 million persons were marginally attached to the labor force, essentially
unchanged from a year earlier. (The data are not seasonally adjusted.) These individuals
were not in the labor force, wanted and were available for work, and had looked for a
job sometime in the prior 12 months. They were not counted as unemployed because they
had not searched for work in the 4 weeks preceding the survey. (See table A-16.)

Among the marginally attached, there were 697,000 discouraged workers in May, little
different from a year earlier. (The data are not seasonally adjusted.) Discouraged
workers are persons not currently looking for work because they believe no jobs are
available for them. The remaining 1.4 million persons marginally attached to the labor
force in May had not searched for work for reasons such as school attendance or family
responsibilities. (See table A-16.)

Establishment Survey Data

Total nonfarm payroll employment increased by 217,000 in May, with gains in professional
and business services, health care and social assistance, food services and drinking
places, and transportation and warehousing. Over the prior 12 months, nonfarm payroll
employment growth had averaged 197,000 per month. (See table B-1.)

Professional and business services added 55,000 jobs in May, the same as its average
monthly job gain over the prior 12 months. In May, the industry added 7,000 jobs each in
computer systems design and related services and in management and technical consulting.
Employment in temporary help services continued to trend up (+14,000) and has grown by
224,000 over the past year.

In May, health care and social assistance added 55,000 jobs. The health care industry
added 34,000 jobs over the month, twice its average monthly gain for the prior 12 months.
Within health care, employment rose in May by 23,000 in ambulatory health care services
(which includes offices of physicians, outpatient care centers, and home health care
services) and by 7,000 in hospitals. Employment rose by 21,000 in social assistance,
compared with an average gain of 7,000 per month over the prior 12 months.

Within leisure and hospitality, employment in food services and drinking places continued
to grow, increasing by 32,000 in May and by 311,000 over the past year.

Transportation and warehousing employment rose by 16,000 in May. Over the prior 12
months, the industry had added an average of 9,000 jobs per month. In May, employment
growth occurred in support activities for transportation (+6,000) and couriers and
messengers (+4,000).

Manufacturing employment changed little over the month but has added 105,000 jobs over
the past year. Within the industry, durable goods added 17,000 jobs in May and has
accounted for the net job gain in manufacturing over the past 12 months.

Employment in other major industries, including mining and logging, construction,
wholesale trade, retail trade, information, financial activities, and government,
showed little change over the month.

The average workweek for all employees on private nonfarm payrolls was unchanged at 34.5
hours in May. The manufacturing workweek increased by 0.2 hour in May to 41.1 hours, and
factory overtime was unchanged at 3.5 hours. The average workweek for production and
nonsupervisory employees on private nonfarm payrolls was unchanged at 33.7 hours. (See
tables B-2 and B-7.)

In May, average hourly earnings for all employees on private nonfarm payrolls rose by
5 cents to $24.38. Over the past 12 months, average hourly earnings have risen by 2.1
percent. In May, average hourly earnings of private-sector production and nonsupervisory
employees increased by 3 cents to $20.54. (See tables B-3 and B-8.)

After revision, the change in total nonfarm employment for March remained +203,000, and the
change for April was revised from +288,000 to +282,000. With these revisions, employment
gains in March and April were 6,000 lower than previously reported.

_____________
The Employment Situation for June is scheduled to be released on Thursday, July 3, 2014,
at 8:30 a.m. (EDT).


  ________________________________________________________________________________________
 |                                                                                        |
 |                       Upcoming Changes to the Establishment Survey Data                |
 |                                                                                        |
 |Effective with the release of July 2014 data on August 1, 2014, the establishment survey|
 |will implement new sample units into production on a quarterly basis, replacing the     |
 |current practice of implementing new sample units annually. There is no change to the   |
 |establishment survey sample design. More information about the quarterly sample         |
 |implementation is available at www.bls.gov/ces/cesqsi.htm.                              |
 |________________________________________________________________________________________|



 

  • Access to historical data for the “A” tables of the Employment Situation Release
  • Access to historical data for the “B” tables of the Employment Situation Release
  • HTML version of the entire news release
  • Employment Situation Summary Table A. Household data, seasonally adjusted

    HOUSEHOLD DATA
    Summary table A. Household data, seasonally adjusted

    [Numbers in thousands]

    Category May
    2013
    Mar.
    2014
    Apr.
    2014
    May
    2014
    Change from:
    Apr.
    2014-
    May
    2014

    Employment status

    Civilian noninstitutional population

    245,363 247,258 247,439 247,622 183

    Civilian labor force

    155,609 156,227 155,421 155,613 192

    Participation rate

    63.4 63.2 62.8 62.8 0.0

    Employed

    143,919 145,742 145,669 145,814 145

    Employment-population ratio

    58.7 58.9 58.9 58.9 0.0

    Unemployed

    11,690 10,486 9,753 9,799 46

    Unemployment rate

    7.5 6.7 6.3 6.3 0.0

    Not in labor force

    89,754 91,030 92,018 92,009 -9

    Unemployment rates

    Total, 16 years and over

    7.5 6.7 6.3 6.3 0.0

    Adult men (20 years and over)

    7.2 6.2 5.9 5.9 0.0

    Adult women (20 years and over)

    6.5 6.2 5.7 5.7 0.0

    Teenagers (16 to 19 years)

    24.1 20.9 19.1 19.2 0.1

    White

    6.6 5.8 5.3 5.4 0.1

    Black or African American

    13.5 12.4 11.6 11.5 -0.1

    Asian (not seasonally adjusted)

    4.3 5.4 5.7 5.3 -

    Hispanic or Latino ethnicity

    9.1 7.9 7.3 7.7 0.4

    Total, 25 years and over

    6.1 5.4 5.2 5.2 0.0

    Less than a high school diploma

    11.0 9.6 8.9 9.1 0.2

    High school graduates, no college

    7.4 6.3 6.3 6.5 0.2

    Some college or associate degree

    6.5 6.1 5.7 5.5 -0.2

    Bachelor’s degree and higher

    3.8 3.4 3.3 3.2 -0.1

    Reason for unemployment

    Job losers and persons who completed temporary jobs

    6,094 5,489 5,236 5,018 -218

    Job leavers

    944 815 784 875 91

    Reentrants

    3,326 3,037 2,620 2,857 237

    New entrants

    1,257 1,169 1,043 1,062 19

    Duration of unemployment

    Less than 5 weeks

    2,704 2,461 2,447 2,559 112

    5 to 14 weeks

    2,642 2,581 2,359 2,390 31

    15 to 26 weeks

    1,934 1,677 1,533 1,441 -92

    27 weeks and over

    4,353 3,739 3,452 3,374 -78

    Employed persons at work part time

    Part time for economic reasons

    7,917 7,411 7,465 7,269 -196

    Slack work or business conditions

    4,837 4,512 4,555 4,453 -102

    Could only find part-time work

    2,697 2,731 2,669 2,537 -132

    Part time for noneconomic reasons

    18,957 19,216 18,886 19,040 154

    Persons not in the labor force (not seasonally adjusted)

    Marginally attached to the labor force

    2,164 2,168 2,160 2,130 -

    Discouraged workers

    780 698 783 697 -

    - Over-the-month changes are not displayed for not seasonally adjusted data.
    NOTE: Persons whose ethnicity is identified as Hispanic or Latino may be of any race. Detail for the seasonally adjusted data shown in this table will not necessarily add to totals because of the independent seasonal adjustment of the various series. Updated population controls are introduced annually with the release of January data.

 

 

ESTABLISHMENT DATA
Summary table B. Establishment data, seasonally adjusted

Category May
2013
Mar.
2014
Apr.
2014(p)
May
2014(p)

EMPLOYMENT BY SELECTED INDUSTRY
(Over-the-month change, in thousands)

Total nonfarm

199 203 282 217

Total private

222 200 270 216

Goods-producing

2 21 46 18

Mining and logging

4 4 8 2

Construction

5 13 34 6

Manufacturing

-7 4 4 10

Durable goods(1)

-2 14 6 17

Motor vehicles and parts

5.0 -0.5 0.3 5.0

Nondurable goods

-5 -10 -2 -7

Private service-providing(1)

220 179 224 198

Wholesale trade

7.7 7.8 16.2 9.9

Retail trade

34.7 28.9 43.1 12.5

Transportation and warehousing

-1.5 13.9 12.1 16.4

Information

-2 -1 1 -5

Financial activities

9 0 6 3

Professional and business services(1)

77 47 71 55

Temporary help services

23.3 22.1 16.0 14.3

Education and health services(1)

29 40 39 63

Health care and social assistance

18.9 34.9 28.5 54.9

Leisure and hospitality

53 31 24 39

Other services

12 9 13 4

Government

-23 3 12 1

WOMEN AND PRODUCTION AND NONSUPERVISORY EMPLOYEES(2)
AS A PERCENT OF ALL EMPLOYEES

Total nonfarm women employees

49.4 49.4 49.4 49.4

Total private women employees

48.0 48.0 48.0 48.0

Total private production and nonsupervisory employees

82.6 82.7 82.7 82.7

HOURS AND EARNINGS
ALL EMPLOYEES

Total private

Average weekly hours

34.5 34.5 34.5 34.5

Average hourly earnings

$23.89 $24.32 $24.33 $24.38

Average weekly earnings

$824.21 $839.04 $839.39 $841.11

Index of aggregate weekly hours (2007=100)(3)

98.5 100.1 100.4 100.6

Over-the-month percent change

0.5 0.7 0.3 0.2

Index of aggregate weekly payrolls (2007=100)(4)

112.3 116.2 116.5 117.0

Over-the-month percent change

0.6 0.9 0.3 0.4

HOURS AND EARNINGS
PRODUCTION AND NONSUPERVISORY EMPLOYEES

Total private

Average weekly hours

33.7 33.7 33.7 33.7

Average hourly earnings

$20.06 $20.48 $20.51 $20.54

Average weekly earnings

$676.02 $690.18 $691.19 $692.20

Index of aggregate weekly hours (2002=100)(3)

106.0 107.8 108.1 108.3

Over-the-month percent change

0.2 1.1 0.3 0.2

Index of aggregate weekly payrolls (2002=100)(4)

142.0 147.5 148.1 148.6

Over-the-month percent change

0.3 1.0 0.4 0.3

DIFFUSION INDEX(5)
(Over 1-month span)

Total private (264 industries)

61.6 59.7 65.9 62.7

Manufacturing (81 industries)

48.8 53.7 53.7 55.6

Footnotes
(1) Includes other industries, not shown separately.
(2) Data relate to production employees in mining and logging and manufacturing, construction employees in construction, and nonsupervisory employees in the service-providing industries.
(3) The indexes of aggregate weekly hours are calculated by dividing the current month’s estimates of aggregate hours by the corresponding annual average aggregate hours.
(4) The indexes of aggregate weekly payrolls are calculated by dividing the current month’s estimates of aggregate weekly payrolls by the corresponding annual average aggregate weekly payrolls.
(5) Figures are the percent of industries with employment increasing plus one-half of the industries with unchanged employment, where 50 percent indicates an equal balance between industries with increasing and decreasing employment.
(p) Preliminary

 

 

37.2%: Percentage Not in Labor Force Remains at 36-Year High

June 6, 2014 – 8:05 AM

By Ali Meyer

The percentage of American civilians 16 or older who do not have a job and are not actively seeking one remained at a 36-year high in May, according to the Bureau of Labor Statistics.

In December, April, and now May, the labor force participation rate has been 62.8 percent. That means that 37.2 percent were not participating in the labor force during those months.

Before December, the last time the labor force participation rate sunk as low as 62.8 percent was February 1978, when it was also 62.8 percent. At that time, Jimmy Carter was president.

In April, the number of those not in the labor force hit a record high of 92,018,000. In May, that number declined by 9,000 to 92,009,000. Yet, the participation rate remained the same from April to May at 62.8 percent.

The labor force, according to BLS, is that part of the civilian noninstitutional population that either has a job or has actively sought one in the last four weeks. The civilian noninstitutional population consists of people 16 or older, who are not on active duty in the military or in an institution such as a prison, nursing home, or mental hospital.

jobs

In May, according to BLS, the nation’s civilian noninstitutional population, consisting of all people 16 or older who were not in the military or an institution, hit 247,622,000. Of those, 155,613,000 participated in the labor force by either holding a job or actively seeking one.

The 155,613,000 who participated in the labor force equaled only 62.8 percent of the 247,622,000 civilian noninstitutional population, matching (along with the 62.8 percent rate in May) the lowest labor force participation rate in 36 years.

At no time during the presidencies of Ronald Reagan, George H.W. Bush, Bill Clinton or George W. Bush, did such a small percentage of the civilian non-institutional population either hold a job or at least actively seek one.

When President Barack Obama took office in January 2009, the labor force participation rate was 65.7 percent. By the beginning of 2013, the start of Obama’s second term, it had dropped to 63.6 percent. Since January 2014, when the participation rate was 63.0,it has continued to decline, hitting a 36-year low of 62.8 percent in May.

People in the civilian noninstitutional population who did not have a job and did not actively seek one in the last four weeks are considered “not in the labor force.” The number of Americans not in the labor force has climbed by 11,480,000 since Obama took office, rising from 80,529,000 in January 2009 to 92,009,000 in May 2014.

 

http://www.cnsnews.com/news/article/ali-meyer/372-percentage-not-labor-force-remains-36-year-high

 

Sessions: 7 Million Have Left Workforce Since Obama Took Office

 BY DANIEL HALPER

Senator Jeff Sessions has released a statement that says, “7 Million People Have Left The Workforce Since The President Took Office.” The statement is in response to today’s jobs numbers.

“Today’s jobs numbers are only enough to tread even with population growth, maintaining unemployment at 6.3 percent. When you include discouraged workers, the unemployment rate doubles to an alarming 12.2 percent. There are still 3.2 million fewer full-time employed persons than there were in 2007,” says Sessions.

“Since President Obama came into office in 2009, 7.2 million people have left the workforce entirely. One out of every six men aged 25–54 is not working. Employment in this group fell by 72,000 last month, while the number of employed women aged 25–54 fell by 37,000. Meanwhile, the workforce participation rate for women is at its lowest level in 23 years. Median household income is down almost $2,300 from what it was when the President took office. Real wages are lower than they were in 1999. Growth in the first quarter of this year was negative.

“These numbers are grim and make clear that this economy is nowhere close to performing at an acceptable level.”

 

http://www.weeklystandard.com/blogs/sessions-7-million-have-left-workforce-obama-took-office_794443.html

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When will Bureau of Land Management (BLM) Roundup 2,000 Plus Wild Horses On Utah Rangeland? — The BLM Should Do Its Job and Not Harass Neveda Ranchers! — BLM’s Appropriate Management Level (AML) of 27,000 Wild Horses and Over 40,000 Wild Horses Nationally Plus Over 50,000 in Feed Lost Costing The American Taxpayer Millions! — Herd Size Doubles Every 4 Years — Sell The Wild Horses To China and Mexico — Beef and Food Prices Soaring — Connect The Dots People — Videos

Posted on April 13, 2014. Filed under: Agriculture, American History, Beef, Blogroll, Bread, Business, College, Communications, Data, Demographics, Diasters, Economics, Education, Employment, Faith, Family, Famine, Farming, Federal Government, Federal Government Budget, Fiscal Policy, Food, Freedom, Friends, Fruit, government, government spending, history, Language, Law, liberty, Life, Links, media, Milk, People, Philosophy, Photos, Rants, Raves, Regulations, Resources, Security, Transportation, Vegetables | Tags: , , , , , , , , , , , , , , , , , |

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Wild Horses on Public Lands and the impact on Ranching and Communities

We took the show to Beaver County this week to get an on the ground look at how wild horses impact the range. In Utah the population of wild horses is over the Appropriate Management Level (AML) by 1,300 animals. Nationally the problem of dealing with the number of wild horses increases to 14,000 beyond the AML. The management of wild horses costs the BLM tens of millions of dollars every year but despite the efforts to gather wild horses off the range; the numbers keep increasing.
Chad Booth talks to Beaver County Commissioner, Mark Whitney; Iron County Commissioner, David Miller; and local rancher Mark Winch about the impacts on ranchers and the ultimate impact it has on the economies of rural Utah.

Transfer of Public Lands

Public Lands in Utah County Seat Season3, Episode 8

In recent years there has been a public outcry from Utahans asking the State to take a more active role in how management decisions are made on public lands. The take back Utah movement has looked at the history of public lands in the United States and began to ask why hasn’t Utah received the same treatment as other states in the Union. Utah has about 67% of its lands controlled and managed by the federal government. Some counties in the state are about 90% federally owned which creates a burden on the local governments because there is no property tax base to pay for the services that citizens need.

Last year Utah passed the Utah Public Lands Transfer Act, HB148; which basically asks the federal government to dispose of the remaining unallocated federal lands within the state by 2014. HB148 has opened up a conversation about what the proper role of the federal government should be in the management of public lands. Today’s show takes a look at the issues from a federal, state, and county perspective.

 

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Don’t Fence Me In – Roy Rogers & The Sons of the Pioneers –

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Wild horses targeted for roundup in Utah rangeland clash

Reuters
Two of a band of wild horses graze in the Nephi Wash area outside Enterprise, Utah

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Two of a band of wild horses graze in the Nephi Wash area outside Enterprise, Utah, April 10, 2014. REUTERS/Jim …

By Jennifer Dobner

ENTERPRISE, Utah (Reuters) – A Utah county, angry over the destruction of federal rangeland that ranchers use to graze cattle, has started a bid to round up federally protected wild horses it blames for the problem in the latest dustup over land management in the U.S. West.

Close to 2,000 wild horses are roaming southern Utah’s Iron County, well over the 300 the U.S. Bureau of Land Management has dubbed as appropriate for the rural area’s nine designated herd management zones, County Commissioner David Miller said.

County officials complain the burgeoning herd is destroying vegetation crucial to ranchers who pay to graze their cattle on the land, and who have already been asked to reduce their herds to cope with an anticipated drought.

Wild horse preservation groups say any attempt to remove the horses would be a federal crime.

On Thursday county workers, accompanied by a Bureau of Land Management staffer, set up the first in a series of metal corrals designed to trap and hold the horses on private land abutting the federal range until they can be moved to BLM facilities for adoption.

“There’s been no management of the animals and they keep reproducing,” Miller said in an interview. “The rangeland just can’t sustain it.”

The conflict reflects broader tension between ranchers, who have traditionally grazed cattle on public lands and held sway over land-use decisions, and environmentalists and land managers facing competing demands on the same land.

The Iron County roundup comes on the heels of an incident in neighboring Nevada in which authorities sent in helicopters and wranglers on horseback to confiscate the cattle herd of a rancher they say is illegally grazing livestock on public land.

In Utah, county commissioners warned federal land managers in a letter last month that the county would act independently to remove the horses if no mitigation efforts were launched.

“We charge you to fulfill your responsibility,” commissioners wrote. “Inaction and no-management practices pose an imminent threat to ranchers.”

The operation was expected to last weeks or months.

“The BLM is actively working with Iron County to address the horse issue,” Utah-based BLM spokeswoman Megan Crandall said, declining to comment further.

Attorneys for wild horse preservation groups sent a letter this week to Iron County commissioners and the BLM saying the BLM, under federal law, cannot round up horses on public lands without proper analysis and disclosure.

“The BLM must stop caving to the private financial interests of livestock owners whenever they complain about the protected wild horses using limited resources that are available on such lands,” wrote Katherine Meyer of Meyer, Glitzenstein and Crystal a Washington, DC-based public interest law firm representing the advocates.

LONG-RUNNING PROBLEM

The BLM puts the free-roaming wild horse and burro population across western states at more than 40,600, which it says on its website exceeds by nearly 14,000 the number of animals it believes “can exist in balance with other public rangeland resources and uses.”

Wild horse advocates point out that the tens of thousands of wild horses on BLM property pales into comparison with the millions of private livestock grazing on public lands managed by the agency.

Wild horses have not been culled due to budget constraints, according to Utah BLM officials, who say their herds grow by roughly 20 percent per year.

Pressure on rangeland from the horses may worsen this summer due to a drought that could dry up the already sparse available food supply, according to Miller.

“We’re going to see those horses starving to death out on the range,” he said. “The humane thing is to get this going now.”

Adding to frustration is BLM pressure on ranchers to cut their cattle herds by as much as 50 percent to cope with the drought, Miller said.

A tour of Iron County rangeland, not far from the Nevada border, illustrates the unchecked herds’ impact on the land, said Jeremy Hunt, a fourth generation Utah rancher whose cattle graze in the summer in a management area split through its middle by a barbed wire fence.

On the cattle side of the fence, the sagebrush and grass landscape is thick and green. The other, where a group of horses was seen on Thursday, is scattered with barren patches of dirt and sparse vegetation.

“This land is being literally destroyed because they are not following the laws that they set up to govern themselves,” said Hunt, who also works as a farmhand to make ends meet for his family of six.

“I want the land to be healthy and I want be a good steward of the land,” he added. “But you have to manage both sides of the fence.”

 

 

Wholesale Prices in U.S. Rise on Services as Goods Stagnate

 

Wholesale prices in the U.S. rose in March as the cost of services climbed by the most in four years while commodities stagnated.

The 0.5 percent advance in the producer-price index was the biggest since June and followed a 0.1 percent decrease the prior month, the Labor Department reported today in Washington. The recent inclusion of services may contribute to the gauge’s volatility from month-to-month, which will make it more difficult to determine underlying trends.

Rising prices at clothing and jewelry retailers and food wholesalers accounted for much of the jump in services, even as energy costs retreated, signaling slowing growth in emerging markets such as China will keep price pressures muted. With inflation running well below the Federal Reserve’s goal, the central bank is likely to keep borrowing costs low in an effort to spur growth.

“Every six months or so service prices seem to pop, but over the year, service prices tend to dampen inflation more often than not,” Jay Morelock, an economist at FTN Financial in New York, wrote in a note. “One month of price gains is not indicative of a trend.”

Also today, consumer confidence climbed this month to the highest level since July, a sign an improving job market is lifting Americans’ spirits. The Thomson Reuters/University of Michigan preliminary April sentiment index rose to 82.6 from 80 a month earlier.

 
Photographer: Craig Warga/Bloomberg

Rising prices at clothing and jewelry retailers and food wholesalers accounted for much… Read More

Shares Fall

Stocks dropped, with the Standard & Poor’s 500 Index heading for its biggest weekly decline since January, as disappointing results from JPMorgan Chase & Co. fueled concern that corporate earnings will be weak. The S&P 500 fell 0.4 percent to 1,826.29 at 10:02 a.m. in New York.

Today’s PPI report is the third to use an expanded index that measures 75 percent of the economy, compared to about a third for the old metric, which tallied the costs of goods alone. After its first major overhaul since 1978, PPI now measures prices received for services, government purchases, exports and construction.

Estimates for the PPI in the Bloomberg survey of 72 economists ranged from a drop of 0.2 percent to a 0.3 percent gain.

Core wholesale prices, which exclude volatile food and energy categories, climbed 0.6 percent, the biggest gain since March 2011, exceeding the projected 0.2 percent advance of economists surveyed by Bloomberg. They dropped 0.2 percent in February.

Past Year

The year-to-year gain in producer prices was the biggest since August and followed a 0.9 percent increase in the 12 months to February. Excluding food and energy, the index also increased 1.4 percent year to year following a 1.1 percent year-to-year gain in February.

The cost of services climbed 0.7 percent in March, the biggest gain since January 2010. Goods prices were unchanged and were up 1.1 percent over the past 12 months.

Wholesale food costs climbed 1.1 percent in March, led by higher costs for meats, including pork and sausage. Energy costs fell 1.2 percent last month.

Food producers and restaurants say they’re paying more for beef, poultry, dairy and shrimp. At General Mills Inc. (GIS), maker of Yoplait yogurt, Cheerios cereal and other brands, rising dairy prices helped push retail profit down 11 percent in the third quarter, said Ken Powell, chairman and chief executive officer of the Minneapolis-based company. Powell called the inflation “manageable.”

Food Prices

“While the economy is improving slowly and incomes are strengthening slowly, they are improving,” Powell said on a March 19 earnings call. “As incomes continue to grow and consumers gain confidence that will be a positive sign for our category.”

Today’s PPI report provides a glimpse into the consumer-price index, the broadest of three inflation measures released by the Labor Department. The CPI, due to be released April 15, probably climbed 0.1 percent in March, according to the median forecast in a Bloomberg survey.

The wholesale price report also offers an advance look into the personal consumption expenditures deflator, a gauge monitored closely by the Fed. Health care prices make up the largest share of the core PCE index, which excludes food and energy costs. The next PCE report is due from the Commerce Department May 1.

This week, Fed policy makers played down their own predictions that interest rates might rise faster than they had forecast, according to minutes of the Federal Open Market Committee’s March meeting. The minutes bolstered remarks made by last month by Chair Janet Yellen.

“If inflation is persistently running below our 2 percent objective, that is a very good reason to hold the funds rate at its present range for longer,” Yellen said at a March 19 press conference following the committee meeting.

 

http://www.bloomberg.com/news/2014-04-11/wholesale-prices-in-u-s-rise-more-than-forecast-on-services.html

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President Obama’s Trust Gap Widens — The Unbelievable President Loses Support of American People and World Leaders — The Decline and Fall of President Obama — Lame Duck — Videos

Posted on March 31, 2014. Filed under: American History, Blogroll, Central Intelligence Agency (CIA), College, Communications, Computers, Culture, Economics, Education, Employment, Federal Bureau of Investigation (FBI), Federal Government, Federal Government Budget, Fiscal Policy, Foreign Policy, Freedom, Friends, government, government spending, Health Care, history, IRS, Language, Law, liberty, Life, Links, Literacy, media, National Security Agency (NSA_, Obamacare, People, Philosophy, Photos, Politics, Raves, Regulations, Security, Strategy, Talk Radio, Tax Policy, Taxes, Technology, Terrorism, Transportation, Unemployment, Vacations, Video, War, Wealth, Wisdom | Tags: , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |

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Pronk Pops Show 234: March 28, 2014

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Story 1: President Obama’s Trust Gap Widens — The Unbelievable President Loses Support of American People and World Leaders — The Decline and Fall of President Obama — Lame Duck — Videos

motuslame duck dynasty

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Judge Pirro Calls Out Obama – The Man CANNOT be Trusted!!!

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White House Woes! Poll Most Americans Losing Trust In Obama Admin Megyn Kelly

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All False statements involving Barack Obama

Mistrust overshadows Obama’s Saudi trip

US President Barack Obama meets Saudi King Abdullah Friday as mistrust fuelled by differences over Iran and Syria overshadows a decades-long alliance between their countries.

Obama, who is due to arrive in Saudi Arabia late in the afternoon on a flight from Italy, is expected to hold evening talks with the monarch on a royal estate outside Riyadh.

Saudi Arabia has strong reservations about efforts by Washington and other major world powers to negotiate a deal with Iran on its nuclear programme.

It is also disappointed over Obama’s 11th-hour decision last year not to take military action against the Syrian regime over chemical weapons attacks.

Saudi analyst Abdel Aziz al-Sagr, who heads the Gulf Research Centre, said Saudi-US relations are “tense due to Washington’s stances” on the Middle East, especially Iran.

The recent rapprochement between Tehran and Washington “must not take place at the expense of relations with Riyadh,” Sagr told AFP.

Sunni Muslim Saudi Arabia, long wary of Shiite Iran’s regional ambitions, views a November deal between world powers and Iran over the latter’s nuclear programme as a risky venture that could embolden Tehran.

The interim agreement curbs Iran’s controversial nuclear activities in exchange for limited sanctions relief, and is aimed at buying time to negotiate a comprehensive accord.

But Sagr said “arming the Syrian opposition will top the agenda” during Obama’s visit, his second since his election in 2009.

Analyst Khaled al-Dakhil spoke of “major differences” with Washington, adding that Obama will focus on easing “Saudi fears on Iran and on regional security.”

Saudi Arabia, the largest power in the six-nation Gulf Cooperation Council, fears that a possible US withdrawal from the Middle East and a diplomatic overture towards Iran would further feed Tehran’s regional ambitions.

Iranian-Saudi rivalry crystallised with the Syrian conflict: Tehran backs President Bashar al-Assad’s regime, while several GCC states support the rebellion against him.

- ‘Clearing the air’ -

Obama’s stances towards events reshaping the region “have strained (Saudi-US) relations but without causing a complete break,” said Anwar Eshki, head of the Jeddah-based Middle East Centre for Strategic and Legal Studies.

US security and energy specialist professor Paul Sullivan said Obama meeting King Abdullah could “help clear the air on some misunderstandings.”

“However, I would be quite surprised if there were any major policy changes during this visit. This is also partly a reassurance visit,” he added.

White House spokesman Jay Carney has said that “whatever differences we may have do not alter the fact that this is a very important and close partnership”.

However, Riyadh seems to be reaching out more towards Asia, including China, in an apparent bid to rebalance its international relations.

Crown Prince Salman bin Abdulaziz visited China, Pakistan, Japan and India this month, reportedly to strengthen ties.

The US-Saudi relationship dates to the end of World War II and was founded on an agreement for Washington to defend the Gulf state in exchange for oil contracts.

OPEC kingpin Saudi Arabia is the world’s top producer and exporter of oil.

Obama and the king are also expected to discuss deadlocked US-brokered Israeli-Palestinian peace talks.

They will also discuss Egypt, another bone of contention since the 2011 uprising that ousted Hosni Mubarak, who was a staunch US and Saudi ally.

The kingdom was dismayed by the partial freezing of US aid to Egypt after the army toppled Islamist president Mohamed Morsi last July — a move hailed by Riyadh.

On Thursday, Egypt’s Field Marshal Abdel Fattah al-Sisi resigned as defence minister after announcing he would stand for president.

Meanwhile, dozens of US lawmakers have urged Obama in a letter to publicly address Saudi Arabia’s “systematic human rights violations,” including efforts by women activists to challenge its ban on female drivers.

And rights group Amnesty International said Obama “must break the US administration’s silence on Saudi Arabia’s human rights record by taking a strong public stand against the systematic violations in the kingdom.”

“It is crucial that President Obama sends a strong message to the government of Saudi Arabia that its gross human rights violations and systematic discrimination are unacceptable,” said Hassiba Hadj Sahraoui, Amnesty’s deputy director for the Middle East and North Africa.

“A failure to do so would undermine the human rights principles the USA purports to stand for,” she added in a statement.

Amnesty also urged Obama to express “dismay” at the kingdom’s ban on women driving as his visit coincides with a local campaign to end the globally unique ban.

http://news.yahoo.com/mistrust-overshadows-obamas-saudi-trip-055623617.html

The Pronk Pops Show Podcasts Portfolio

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The Plane — The Plane — Where is the plane? — Crashed Landed — Where? Where? — Fantasy Island! Fantasy Island? — New Reality TV Series Publicity Stunt — Reality: Malaysia Airlines Flight 370 Hijacked — Destination Unknown — Malaysian Prime Minister News Conference — Videos

Posted on March 15, 2014. Filed under: Airplanes, American History, Blogroll, College, Communications, Computers, Constitution, Crashed, Crime, Culture, Diasters, Economics, Education, Faith, Federal Government, Foreign Policy, Freedom, history, Islam, Language, Law, liberty, Life, Links, media, People, Philosophy, Photos, Politics, Press, Psychology, Radio, Rants, Raves, Terrorism, Transportation, Video, War, Weather, Wisdom, Writing | Tags: , , , , , , , |

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Malaysia Airlines Mystery: How Does a Plane Vanish?

Officials Investigate Stolen Passports Used on Missing Malaysia Airlines Flight

Missing airliner may have flown on for 7 hours

By , and , Updated: Saturday, March 15, 12:40 PM

KUALA LUMPUR, Malaysia — Malaysian Prime Minister Najib Razak said Saturday that a missing passenger jet was steered off course after its communications systems were intentionally disabled and could have potentially flown for seven additional hours.

In the most comprehensive account to date of the plane’s fate, Najib drew an ominous picture of what happened aboard Malaysia Airlines Flight 370, saying investigators had determined there was “deliberate action by someone on the plane.”

Najib said the investigation had “refocused” to look at the crew and passengers. A Malaysia Airlines representative, speaking to relatives of passengers in Beijing, said the Malaysian government had opened a criminal investigation into the plane’s disappearance.

(See: New map shows possible search corridors for the Malaysia Airlines flight.)

The plane’s whereabouts remain unknown one week after it disappeared from civilian radar shortly after takeoff from Kuala Lumpur. But Najib, citing newly analyzed satellite data, said the plane could have last made contact anywhere along one of two corridors: one stretching from northern Thailand toward the Kazakhstan-Turkmenistan border, the other, more southern corridor stretching from Indonesia to the remote Indian Ocean.

U.S. officials previously said they believed the plane could have remained in the air for several extra hours, and Najib said Saturday that the flight was still communicating with satellites until 8:11 a.m. — 7 ½ hours after takeoff, and more than 90 minutes after it was due in Beijing. There was no further communication with the plane after that time, Najib said. If the plane was still in the air, it would have been nearing its fuel limit.

“Due to the type of satellite data,” Najib said, “we are unable to confirm the precise location of the plane when it last made contact with the satellite.”

A U.S. official with knowledge of the investigation on Friday said the only thing the satellite can tell is how much it would need to adjust its antenna to get the strongest signal from the plane. It cannot provide the plane’s exact position or which direction it flew, just how far the plane is, roughly, from the last good data-transmission location when the digital datalink system was actually sending data up to the satellite.

The U.S. official said the search area is somewhere along the arc or circumference of a circle with a diameter of thousands of miles.

The new leads about the plane’s end point, though ambiguous, have drastically changed a search operation involving more than a dozen nations. Malaysia on Saturday said that efforts would be terminated in the Gulf of Thailand and the South China Sea, the spot where the plane first disappeared from civilian radar.

Malaysian authorities are now likely to look for help from other countries in Southeast and South Asia, seeking mysterious or unidentified readings that their radar systems might have picked up.

The plane, based on one potential end point, could have spent nearly all its flight time over the Indian Ocean as it headed to an area west of Australia. But if the plane traveled in the direction of Kazakhstan or Turkmenistan, it would present a more perplexing scenario in which it would have evaded detection for hours while flying through a volatile region where airspace is heavily monitored: Burma, Pakistan, India and Afghanistan and western China are all in the neighborhood of that path, as is the United States’ Bagram air base, which is in Afghanistan.

U.S. officials in Afghanistan would not comment on the possibility that the plane had flown over that country, but that scenario seems unlikely given the tight western control over Afghan airspace.

Afghan officials said they rely on Americans on such matters. “We do not know what has happened to the plane or if it has overflown Afghan air space. We do not have a radar. Go and ask the Americans,” said a senior Afghan official.

A Pakistani official said his country has not yet been asked by Malaysia to share its radar data, but will provide them if asked.

“Given the strong radar system that we have, and also that India and other countries in the region have, it’s very difficult for a plane to fly undetected for so long,” said Abid Qaimkhan, a spokesman for Pakistan’s Civil Aviation Authority.

Malaysia has confirmed that a previously unknown radar trail picked up by its military was indeed MH370. That blip suggests the plane had cut west, across the Malaysian peninsula, after severing contact with the ground. Malaysia received help in analyzing that radar data from the United States’ National Transportation Safety Board, Federal Aviation Administration, and the British Air Accident Investigation Branch.

Malaysian investigators now believe that the Boeing-777 airliner, bound for Beijing with 227 passengers, deliberately cut a series of communications systems as it headed toward the boundary of Malaysian airspace. U.S. officials and aviation experts say the plane could have been hijacked by somebody with aviation knowledge or sabotaged by a crew member.

Investigators have not yet presented a clear scenario of what could have happened on board. Reuters reported that Malaysian police on Saturday searched the home of the plane’s captain, Zaharie Ahmad Shah, 53, who had more than three decades of commercial flight experience. A senior Malaysian police official refused to confirm the search.

Zaharie had a flight simulator at his home, something that appeared in a YouTube video posted from his unconfirmed YouTube account. Malaysia Airlines chief executive Ahmad Jauhari Yahya said Friday that “everyone is free to do their own hobby” and that it isn’t unusual for pilots to have home simulators.

U.S. officials have said that the plane, shortly after being diverted, reached an altitude of 45,000 feet and “jumped around a lot.” But the airplane otherwise appeared to operate normally. Significantly, the transponder and a satellite-based communication system did not stop at the same time, as they would if the plane had exploded, disintegrated or crashed into the ocean.

Najib said Saturday that the Aircraft Communications Addressing and Reporting System, or ACARS, was disabled just as MH370 reached the eastern coast of Malaysia. The transponder was then switched off, Najib said, as the aircraft neared the border between Malaysian and Vietnamese airspace.

According to the Malaysian government, a satellite that tracked the aircraft was located more than 22,000 miles above sea level. Even after the ACARS system was disconnected, the satellite still received some basic signal from the plane — what one U.S. official described as a “handshake.” Though no data was being transmitted, the satellite continued to reach out to the plane on an hourly basis and received confirmation that the plane was still flying.

“There’s no circuit breaker that would allow you to shut off the handshake,” the official said.

That satellite handshake took place on a system operated by Inmarsat, a British satellite company that provides global mobile telecommunications services.

U.S. officials declined to say how closely that handshake allowed them to track the path of the missing plane. But one U.S. official explained that the satellite wasn’t able to read the plane’s exact location or even what direction it flew. Instead, the satellite was able to determine how far the plane had traveled since the last known spot where ACARS was transmitting data. That could explain how Malaysia created two possible arcs where the plane might have traveled.

Najib said Saturday that the search for MH370 had entered a “new phase.” The U.S. Navy, already positioned to the west of the Malaysian peninsula, was planning to meet tonight to discuss whether and how to redeploy its assets, spokesman Cmdr. William Marks said.

Indian officials said Saturday morning that they were still awaiting new orders in response to the Malaysian prime minister’s statement that the official search focus shift from the South China Sea to the two “corridors” west of Malaysia.

“Nothing is certain. These are all probabilities,” said Captain D.K. Sharma, a spokesman for the India Navy. “Let the new orders come. Let’s see how we respond.”

India has now expanded its search from the area around the Andaman and Nicobar Islands — where five vessels and four planes have been deployed — to the north and west, by adding four additional aircraft to scour the massive Bay of Bengal — two P-8I anti-submarine and electronic intelligence planes and three other military aircraft, including a C-130J and two Dorniers. Search teams from the Indian military had spent much of the day Friday searching the jungles on remote islands of the Andaman and Nicobar archipelago, most of which are uninhabited, but so far have come up empty.

Other nations along the Bay of Bengal are now the expanding search as well. Gowher Rizvi, an adviser to Bangladesh’s prime minister Sheikh Hasina, said that country had deployed two aircraft and two frigates in the Bay of Bengal.

Harlan reported from Kuala Lumpur, and Gowen reported from New Delhi. Liu Liu contributed from Beijing. Tim Craig contributed from Pakistan, Joel Achenbach, Adam Goldman and Sari Horwitz contributed from Washington and Rama Lakshmi contributed from New Delhi.

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Ukraine People vs. Russia — USA Response — Absolutely Nothing! — Videos

Posted on March 3, 2014. Filed under: American History, Blogroll, College, Communications, Diasters, Economics, Education, European History, Federal Government, Federal Government Budget, Fiscal Policy, Food, Foreign Policy, Freedom, Friends, Genocide, government, government spending, history, Law, liberty, Life, Links, media, Natural Gas, Oil, People, Philosophy, Politics, Radio, Radio, Rants, Raves, Resources, Security, Strategy, Talk Radio, Technology, Terrorism, Transportation, Video, War, Wealth, Weapons, Wisdom | Tags: , , , , , , , , , , , , , , , , , , , , , |

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The Pronk Pops Show Podcasts

Pronk Pops Show 220: February 27, 2014

Pronk Pops Show 219: February 26, 2014

Pronk Pops Show 218: February 25, 2014

Pronk Pops Show 217: February 24, 2014

Pronk Pops Show 216: February 21, 2014

Pronk Pops Show 215: February 20, 2014

Pronk Pops Show 214: February 19, 2014

Pronk Pops Show 213: February 18, 2014

Pronk Pops Show 212: February 17, 2014

Pronk Pops Show 211: February 14, 2014 

Pronk Pops Show 210: February 13, 2014

Pronk Pops Show 209: February 12, 2014

Pronk Pops Show 208: February 11, 2014

Pronk Pops Show 207: February 10, 2014

Pronk Pops Show 206: February 7, 2014

Pronk Pops Show 205: February 5, 2014

Pronk Pops Show 204: February 4, 2014

Pronk Pops Show 203: February 3, 2014

Pronk Pops Show 202: January 31, 2014

Pronk Pops Show 201: January 30, 2014

Pronk Pops Show 200: January 29, 2014

Pronk Pops Show 199: January 28, 2014

Pronk Pops Show 198: January 27, 2014

Pronk Pops Show 197: January 24, 2014

Pronk Pops Show 196: January 22, 2014

Pronk Pops Show 195: January 21, 2014

Pronk Pops Show 194: January 17, 2014

Pronk Pops Show 193: January 16, 2014

Pronk Pops Show 192: January 14, 2014

Pronk Pops Show 191: January 13, 2014

Pronk Pops Show 190: January 10, 2014

Pronk Pops Show 189: January 9, 2014

Pronk Pops Show 188: January 8, 2014

Pronk Pops Show 187: January 7, 2014

Pronk Pops Show 186: January 6, 2014

Pronk Pops Show 185: January 3, 2014

Pronk Pops Show 184: December 19, 2013

Pronk Pops Show 183: December 17, 2013

Pronk Pops Show 182: December 16, 2013

Pronk Pops Show 181: December 13, 2013

Pronk Pops Show 180: December 12, 2013

Pronk Pops Show 179: December 11, 2013

Pronk Pops Show 178: December 5, 2013

Pronk Pops Show 177: December 2, 2013

The Pronk Pops Show Podcasts Portfolio

Listen To Pronk Pops Podcast or Download Show 211-220

Listen To Pronk Pops Podcast or DownloadShow 202-210

Listen To Pronk Pops Podcast or Download Show 194-201

Listen To Pronk Pops Podcast or Download Show 184-193

Listen To Pronk Pops Podcast or Download Show 174-183

Listen To Pronk Pops Podcast or Download Show 165-173

Listen To Pronk Pops Podcast or Download Show 158-164

Listen To Pronk Pops Podcast or Download Show 151-157

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Listen To Pronk Pops Podcast or Download Show 135-142

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 Story 2: Ukraine People vs. Russia — USA Response — Absolutely Nothing! — Videos

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Hagel Urges Russia to Act Cautiously on Ukraine

Russia Readies 140,000 TROOPS for possible INVASION of UKRAINE

Ukraine’s Yanukovich says he’s still president, asks Russia to ensure his safety

Clashes in Ukraine create tension for U.S. and Russia

Obama Criticizes Putin Over Ukraine, Syria

Russia Questions Legitimacy Of New Acting Government In Ukraine – America’s Newsroom

Ukraine: Pro-Russia protesters break police cordon, rally outside Crimean parliament

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Bombshell: CBO’s Impact of Obamacare On Economy Devastating — Time To Repeal Obamacare and Replace It Affordable, Portable, Individual Health Insurance With Health Saving Accounts! — Videos

Posted on February 8, 2014. Filed under: American History, Banking, Blogroll, College, Communications, Constitution, Economics, Education, Federal Government, Federal Government Budget, Fiscal Policy, government spending, history, Language, Law, liberty, Life, Links, Literacy, Macroeconomics, media, Monetary Policy, Money, People, Philosophy, Photos, Politics, Press, Rants, Raves, Regulations, Resources, Tax Policy, Transportation, Unemployment, Video, War, Wealth, Wisdom | Tags: , , , , , , , , , , , , , , , , |

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The Pronk Pops Show Podcasts

Pronk Pops Show 206: February 7, 2014 

Pronk Pops Show 205: February 5, 2014 

Pronk Pops Show 204: February 4, 2014 

Pronk Pops Show 203: February 3, 2014

Pronk Pops Show 202: January 31, 2014

Pronk Pops Show 201: January 30, 2014

Pronk Pops Show 200: January 29, 2014

Pronk Pops Show 199: January 28, 2014

Pronk Pops Show 198: January 27, 2014

Pronk Pops Show 197: January 24, 2014

Pronk Pops Show 196: January 22, 2014

Pronk Pops Show 195: January 21, 2014

Pronk Pops Show 194: January 17, 2014

Pronk Pops Show 193: January 16, 2014

Pronk Pops Show 192: January 14, 2014

Pronk Pops Show 191: January 13, 2014

Pronk Pops Show 190: January 10, 2014

Pronk Pops Show 189: January 9, 2014

Pronk Pops Show 188: January 8, 2014

Pronk Pops Show 187: January 7, 2014

Pronk Pops Show 186: January 6, 2014

Pronk Pops Show 185: January 3, 2014

Pronk Pops Show 184: December 19, 2013

Pronk Pops Show 183: December 17, 2013

Pronk Pops Show 182: December 16, 2013

Pronk Pops Show 181: December 13, 2013

Pronk Pops Show 180: December 12, 2013

Pronk Pops Show 179: December 11, 2013

Pronk Pops Show 178: December 5, 2013

Pronk Pops Show 177: December 2, 2013

Pronk Pops Show 176: November 27, 2013

Pronk Pops Show 175: November 26, 2013

Pronk Pops Show 174: November 25, 2013

Pronk Pops Show 173: November 22, 2013

Pronk Pops Show 172: November 21, 2013

Pronk Pops Show 171: November 20, 2013

Pronk Pops Show 170: November 19, 2013

Pronk Pops Show 169: November 18, 2013

Pronk Pops Show 168: November 15, 2013

Pronk Pops Show 167: November 14, 2013

Pronk Pops Show 166: November 13, 2013

Pronk Pops Show 165: November 12, 2013

Pronk Pops Show 164: November 11, 2013

Pronk Pops Show 163: November 8, 2013

Pronk Pops Show 162: November 7, 2013

Pronk Pops Show 161: November 4, 2013

Pronk Pops Show 160: November 1, 2013

The Pronk Pops Show Podcasts Portfolio

Listen To Pronk Pops Podcast or Download Show 202-206

Listen To Pronk Pops Podcast or Download Show 194-201

Listen To Pronk Pops Podcast or Download Show 184-193

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Listen To Pronk Pops Podcast or Download Show 158-164

Listen To Pronk Pops Podcast or Download Show 151-157

Listen To Pronk Pops Podcast or Download Show 143-150

Listen To Pronk Pops Podcast or Download Show 135-142

Listen To Pronk Pops Podcast or Download Show 131-134

Listen To Pronk Pops Podcast or Download Show 124-130

Listen To Pronk Pops Podcast or Download Shows 121-123

Listen To Pronk Pops Podcast or Download Shows 118-120

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Listen To Pronk Pops Podcast or Download Show 112

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Listen To Pronk Pops Podcast or Download Shows 94-97

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Bombshell: CBO’s Impact of Obamacare On Economy Devastating — Time To Repeal Obamacare and Replace It Affordable, Portable, Individual Health Insurance With Health Saving Accounts! — Videos

job_impactobamacare_impact

Analysis of CBO report on ObamaCare impact

CBO On Obamacare’s Impact 2.5 Million Fewer Full Time Workers Cavuto

CBO: Obamacare Will Reduce Jobs By 2.3 Million Workers – Stuart Varney On The Real Story

CBO Predicts Obamacare Will Reduce The Number Of Full Time Workers Brit Hume The Kelly File

ObamaCare Forcing Companies To Reduce Hours And Not Hire Full-Time Workers

Obamacare Will Cost 2,3 Million Full Time Jobs Obama Admin Says People Don’t Want To Work

Conservatives Push Misreading Of CBO Report To Claim Obamacare Is A Job-Killer

White House Pushing Back Against CBO Report On Obamacare Job Losses – America’s Newsroom

CBO: Actually, ObamaCare is kinda’ like a tax, and it’s going to result in 2 million…

Health Savings Account Breakdown

Health Savings Accounts

Deductibles and Coinsurances

Health Savings Account Safety Net

The CBO’s Obamacare Scorecard

Obamacare by the numbers, according to the Congressional Budget Office — labor lost: equivalent of 2.5 million full-time jobs over the next decade; insurance enrollment: down 1 million from earlier first-year estimate; cost: $1.2 trillion over the next decade; number of Americans uninsured: 30 million.

Which is to say: We are spending $1.2 trillion and taking a blowtorch to the work force in order to fund a semi-public insurance system that still leaves tens of millions uncovered. And that’s assuming that CBO has not taken too rosy a view of Obamacare, which it may well have.

There is more wrong with Obamacare than a bumble-thumbed website.

The White House has tried, with hilarious results, to spin the labor-force data, emphasizing the CBO’s estimate that the so-called Affordable Care Act will cost the economy the equivalent of 2.5 million full-time jobs not because there will be a pink-slip bloodbath at Walmart but because fewer people will choose to work, or will choose to work fewer hours, once their federally subsidized health insurance makes the prospect of quitting their jobs less enticing. In the considered view of the Obama administration, that is good news. We are happy to see that the White House seems finally to have stumbled upon the concept of economic incentives — give people less reason to work and they will work less. But the administration still does not seem to be able to get its collective head around the fact that American workers are not just hungry mouths that have to be filled with paychecks: They are people who provide economically valuable goods and services. Those 2.5 million out of the work force may be happier at their leisure, but the economy as a whole will be substantially worse off without their contributions. We could, in theory, simply have the federal government deliver checks to every household and allow each and every one to follow his bliss as he sees fit, but the shelves of the grocery stores soon would be empty. The depth of the Obamacare crater in the labor force isn’t some abstract unemployment rate, but the lost value of the work those Americans would have done.

The spending largely speaks for itself: $1.2 trillion is a great deal of money. The CBO still holds out the possibility that the expenses associated with the program may yet outweigh the cost of its benefits, meaning merely that that $1.2 trillion in spending will be accompanied by approximately $1.2 trillion in taxes, or slightly more. “Revenue-neutral” is not a synonym for “free.” We are still to spend $1.2 trillion, regardless of the combined ledger impact on our bloated deficit.

Spending $1.2 trillion on what? That is the most galling bit. Obamacare was sold as a response to the alleged emergency presented by 40-odd million Americans’ lacking insurance. That number was hotly disputed at the time, but even if we were to take it at face value, getting the figure down to 30 million at a cost of more than $1 trillion is hardly a bargain.

We are familiar with the phrase “money for nothing,” but had always understood it to denote a positive cash flow rather than a negative one.

We already have begun to experience the effects of Obamacare as they relate to health insurance specifically: canceled policies, chaos in the insurance markets, insecurity for consumers. But the more significant cost may in the long run prove to be its structural hobbling of our economy, reducing the work force and redirecting trillions of dollars away from the productive economy into a system of rewards and subsidies for cronies and political constituencies. The CBO’s increasingly bleak economic forecasts suggest that it has begun to take the measure of the long-term costs of the Obama administration’s economic misgovernance, of which Obamacare is one, but only one, significant part. But detailed as those estimates are, they can only begin to suggest the damage.

http://www.nationalreview.com/article/370367/cbos-obamacare-scorecard-editors

What the CBO report on Obamacare really found

  • BY GREG SARGENT

Republicans erupted in applause today when the Congressional Budget Office released a new report on projected deficits and on the impact of the Affordable Care Act. They widely claimed the CBO report had found that Obamacare will cause the loss of over two million jobs.

That isn’t what the report found at all. And there’s a very simple way to prove it. But more on that in a moment.

Here is a sample of GOP reactions to the report. Mitch McConnell’s spokesman claimedthat CBO had projected “a loss of at least two million jobs.” A spokesman for the NRCCinsisted that “because of Obamacare, there will be 2 million less [sic] jobs in the economy.”

A statement from Senator Chuck Grassley claimed that the CBO had found that the law will “cause the loss of 2.5 million jobs.” Former Romney policy adviser Lanhee Chenclaimed the CBO had estimated that Obamacare “will result in 2.5 million jobs lost.”

That’s not what the report says. Here is the key passage, on page 117:

Although CBO projects that total employment (and compensation) will increase over the coming decade, that increase will be smaller than it would have been in the absence of the aCA. The decline in full-time-equivalent employment stemming from the ACA will consist of some people not being employed at all and other people working fewer hours; however, CBO has not tried to quantify those two components of the overall effect. The estimated reduction stems almost entirely from a net decline in the amount of labor that workers choose to supply, rather than from a net drop in business’ demand for labor, so it will appear almost entirely as a reduction in labor force participation and in hours worked relative to what have occurred otherwise rather than as an increase in unemployment (that is, more workers seeking, but not finding jobs) or underemployment (such as part-time workers who would prefer to work more hours per week).

The CBO report actually says that the impact of the ACA will be “almost entirely” due to a decline in labor that “workers choose to supply.” It says explicitly that the ACA’s impact will not be felt as an “increase in unemployment” or “underemployment.”

Now, a few conservatives on twitter did seize on the report to make an argument about how the CBO report shows that the safety net act as a disincentive to work. Whether or not you agree with that argument, it at least exists within the parameters of what the CBO report actually said. The suggestion that Obamacare will cause over two million jobs to be lost does not. This is not a small distinction. It goes directly to the heart of one of the Republican arguments against the law — that it is a job killer, i.e., that its regulations strangle jobs.

Indeed, the response from many Republicans to the report suggests they are so wedded to their “Obamacare is a job killer” talking point that they will misrepresent what it actually says in order to continue making it. That’s not surprising, in a way. After all, the larger political context here is that claiming the safety net is a disincentive to work — again, whatever you think of the substance of that argument — is politically a hard case to make. Remember how Republicans moved away from arguing that unemployment benefits lull people into a state of dependency — Paul Ryan’s Hammock Theory of Poverty — and began arguing instead that the UI extension needed to be paid for?

As for the CBO report, there is a simple way to settle this argument. CBO director Douglas Elmendorf is set to testify before the House Budget Committee tomorrow. One committee lawmaker can ask him the following question: Is it true that your report found that Obamacare will result in over two million lost jobs?

And so, this doesn’t have to be a partisan argument. Tomorrow we can find out what the CBO’s own director has to say about it. There shouldn’t be any need for this to be represented by neutral news orgs as an unresolvable he-said-she-said standoff.

http://www.washingtonpost.com/blogs/plum-line/wp/2014/02/04/what-the-cbo-report-on-obamacare-really-found/

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Making Sense of Today’s January Jobs Report

February 7th 2014 CNBC Stock Market Squawk Box (January Jobs Report)

gdp_large

sgs-emp

non-farm-payrolls-wide-201312

Employment Level

145,224,000

Series Id:           LNS12000000
Seasonally Adjusted
Series title:        (Seas) Employment Level
Labor force status:  Employed
Type of data:        Number in thousands
Age:                 16 years and over

employment_level
Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual
2000 136559(1) 136598 136701 137270 136630 136940 136531 136662 136893 137088 137322 137614
2001 137778 137612 137783 137299 137092 136873 137071 136241 136846 136392 136238 136047
2002 135701 136438 136177 136126 136539 136415 136413 136705 137302 137008 136521 136426
2003 137417(1) 137482 137434 137633 137544 137790 137474 137549 137609 137984 138424 138411
2004 138472(1) 138542 138453 138680 138852 139174 139556 139573 139487 139732 140231 140125
2005 140245(1) 140385 140654 141254 141609 141714 142026 142434 142401 142548 142499 142752
2006 143150(1) 143457 143741 143761 144089 144353 144202 144625 144815 145314 145534 145970
2007 146028(1) 146057 146320 145586 145903 146063 145905 145682 146244 145946 146595 146273
2008 146378(1) 146156 146086 146132 145908 145737 145532 145203 145076 144802 144100 143369
2009 142152(1) 141640 140707 140656 140248 140009 139901 139492 138818 138432 138659 138013
2010 138451(1) 138599 138752 139309 139247 139148 139179 139427 139393 139111 139030 139266
2011 139287(1) 139422 139655 139622 139653 139409 139524 139904 140154 140335 140747 140836
2012 141677(1) 141943 142079 141963 142257 142432 142272 142204 142947 143369 143233 143212
2013 143384(1) 143464 143393 143676 143919 144075 144285 144179 144270 143485 144443 144586
2014 145224(1)

Civilian Labor Force

155,460,000

Series Id:           LNS11000000
Seasonally Adjusted
Series title:        (Seas) Civilian Labor Force Level
Labor force status:  Civilian labor force
Type of data:        Number in thousands
Age:                 16 years and over

Civilian_Labor_Force_Level

Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual
2000 142267(1) 142456 142434 142751 142388 142591 142278 142514 142518 142622 142962 143248
2001 143800 143701 143924 143569 143318 143357 143654 143284 143989 144086 144240 144305
2002 143883 144653 144481 144725 144938 144808 144803 145009 145552 145314 145041 145066
2003 145937(1) 146100 146022 146474 146500 147056 146485 146445 146530 146716 147000 146729
2004 146842(1) 146709 146944 146850 147065 147460 147692 147564 147415 147793 148162 148059
2005 148029(1) 148364 148391 148926 149261 149238 149432 149779 149954 150001 150065 150030
2006 150214(1) 150641 150813 150881 151069 151354 151377 151716 151662 152041 152406 152732
2007 153144(1) 152983 153051 152435 152670 153041 153054 152749 153414 153183 153835 153918
2008 154063(1) 153653 153908 153769 154303 154313 154469 154641 154570 154876 154639 154655
2009 154210(1) 154538 154133 154509 154747 154716 154502 154307 153827 153784 153878 153111
2010 153404(1) 153720 153964 154642 154106 153631 153706 154087 153971 153631 154127 153639
2011 153198(1) 153280 153403 153566 153526 153379 153309 153724 154059 153940 154072 153927
2012 154328(1) 154826 154811 154565 154946 155134 154970 154669 155018 155507 155279 155485
2013 155699(1) 155511 155099 155359 155609 155822 155693 155435 155473 154625 155284 154937
2014 155460(1)

Labor Force Participation Rate

63.0%

Series Id:           LNS11300000
Seasonally Adjusted
Series title:        (Seas) Labor Force Participation Rate
Labor force status:  Civilian labor force participation rate
Type of data:        Percent or rate
Age:                 16 years and over

labor_participation_rate

Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual
2000 67.3 67.3 67.3 67.3 67.1 67.1 66.9 66.9 66.9 66.8 66.9 67.0
2001 67.2 67.1 67.2 66.9 66.7 66.7 66.8 66.5 66.8 66.7 66.7 66.7
2002 66.5 66.8 66.6 66.7 66.7 66.6 66.5 66.6 66.7 66.6 66.4 66.3
2003 66.4 66.4 66.3 66.4 66.4 66.5 66.2 66.1 66.1 66.1 66.1 65.9
2004 66.1 66.0 66.0 65.9 66.0 66.1 66.1 66.0 65.8 65.9 66.0 65.9
2005 65.8 65.9 65.9 66.1 66.1 66.1 66.1 66.2 66.1 66.1 66.0 66.0
2006 66.0 66.1 66.2 66.1 66.1 66.2 66.1 66.2 66.1 66.2 66.3 66.4
2007 66.4 66.3 66.2 65.9 66.0 66.0 66.0 65.8 66.0 65.8 66.0 66.0
2008 66.2 66.0 66.1 65.9 66.1 66.1 66.1 66.1 66.0 66.0 65.9 65.8
2009 65.7 65.8 65.6 65.7 65.7 65.7 65.5 65.4 65.1 65.0 65.0 64.6
2010 64.8 64.9 64.9 65.2 64.9 64.6 64.6 64.7 64.6 64.4 64.6 64.3
2011 64.2 64.2 64.2 64.2 64.2 64.0 64.0 64.1 64.2 64.1 64.1 64.0
2012 63.7 63.9 63.8 63.7 63.8 63.8 63.7 63.5 63.6 63.7 63.6 63.6
2013 63.6 63.5 63.3 63.4 63.4 63.5 63.4 63.2 63.2 62.8 63.0 62.8
2014 63.0

Unemployment Level

10,236,000

Series Id:           LNS13000000
Seasonally Adjusted
Series title:        (Seas) Unemployment Level
Labor force status:  Unemployed
Type of data:        Number in thousands
Age:                 16 years and over

unemployment_level

Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual
2000 5708 5858 5733 5481 5758 5651 5747 5853 5625 5534 5639 5634
2001 6023 6089 6141 6271 6226 6484 6583 7042 7142 7694 8003 8258
2002 8182 8215 8304 8599 8399 8393 8390 8304 8251 8307 8520 8640
2003 8520 8618 8588 8842 8957 9266 9011 8896 8921 8732 8576 8317
2004 8370 8167 8491 8170 8212 8286 8136 7990 7927 8061 7932 7934
2005 7784 7980 7737 7672 7651 7524 7406 7345 7553 7453 7566 7279
2006 7064 7184 7072 7120 6980 7001 7175 7091 6847 6727 6872 6762
2007 7116 6927 6731 6850 6766 6979 7149 7067 7170 7237 7240 7645
2008 7685 7497 7822 7637 8395 8575 8937 9438 9494 10074 10538 11286
2009 12058 12898 13426 13853 14499 14707 14601 14814 15009 15352 15219 15098
2010 14953 15121 15212 15333 14858 14483 14527 14660 14578 14520 15097 14373
2011 13910 13858 13748 13944 13873 13971 13785 13820 13905 13604 13326 13090
2012 12650 12883 12732 12603 12689 12702 12698 12464 12070 12138 12045 12273
2013 12315 12047 11706 11683 11690 11747 11408 11256 11203 11140 10841 10351
2014 10236

Unemployment Rate

6.6%

Series Id:           LNS14000000
Seasonally Adjusted
Series title:        (Seas) Unemployment Rate
Labor force status:  Unemployment rate
Type of data:        Percent or rate
Age:                 16 years and over

unemployment_rate_U_3
Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual
2000 4.0 4.1 4.0 3.8 4.0 4.0 4.0 4.1 3.9 3.9 3.9 3.9
2001 4.2 4.2 4.3 4.4 4.3 4.5 4.6 4.9 5.0 5.3 5.5 5.7
2002 5.7 5.7 5.7 5.9 5.8 5.8 5.8 5.7 5.7 5.7 5.9 6.0
2003 5.8 5.9 5.9 6.0 6.1 6.3 6.2 6.1 6.1 6.0 5.8 5.7
2004 5.7 5.6 5.8 5.6 5.6 5.6 5.5 5.4 5.4 5.5 5.4 5.4
2005 5.3 5.4 5.2 5.2 5.1 5.0 5.0 4.9 5.0 5.0 5.0 4.9
2006 4.7 4.8 4.7 4.7 4.6 4.6 4.7 4.7 4.5 4.4 4.5 4.4
2007 4.6 4.5 4.4 4.5 4.4 4.6 4.7 4.6 4.7 4.7 4.7 5.0
2008 5.0 4.9 5.1 5.0 5.4 5.6 5.8 6.1 6.1 6.5 6.8 7.3
2009 7.8 8.3 8.7 9.0 9.4 9.5 9.5 9.6 9.8 10.0 9.9 9.9
2010 9.7 9.8 9.9 9.9 9.6 9.4 9.5 9.5 9.5 9.5 9.8 9.4
2011 9.1 9.0 9.0 9.1 9.0 9.1 9.0 9.0 9.0 8.8 8.6 8.5
2012 8.2 8.3 8.2 8.2 8.2 8.2 8.2 8.1 7.8 7.8 7.8 7.9
2013 7.9 7.7 7.5 7.5 7.5 7.5 7.3 7.2 7.2 7.2 7.0 6.7
2014 6.6

Employment-Population Ratio

58.8%

Series Id:           LNS12300000
Seasonally Adjusted
Series title:        (Seas) Employment-Population Ratio
Labor force status:  Employment-population ratio
Type of data:        Percent or rate
Age:                 16 years and over
Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual
2000 64.6 64.6 64.6 64.7 64.4 64.5 64.2 64.2 64.2 64.2 64.3 64.4
2001 64.4 64.3 64.3 64.0 63.8 63.7 63.7 63.2 63.5 63.2 63.0 62.9
2002 62.7 63.0 62.8 62.7 62.9 62.7 62.7 62.7 63.0 62.7 62.5 62.4
2003 62.5 62.5 62.4 62.4 62.3 62.3 62.1 62.1 62.0 62.1 62.3 62.2
2004 62.3 62.3 62.2 62.3 62.3 62.4 62.5 62.4 62.3 62.3 62.5 62.4
2005 62.4 62.4 62.4 62.7 62.8 62.7 62.8 62.9 62.8 62.8 62.7 62.8
2006 62.9 63.0 63.1 63.0 63.1 63.1 63.0 63.1 63.1 63.3 63.3 63.4
2007 63.3 63.3 63.3 63.0 63.0 63.0 62.9 62.7 62.9 62.7 62.9 62.7
2008 62.9 62.8 62.7 62.7 62.5 62.4 62.2 62.0 61.9 61.7 61.4 61.0
2009 60.6 60.3 59.9 59.8 59.6 59.4 59.3 59.1 58.7 58.5 58.6 58.3
2010 58.5 58.5 58.5 58.7 58.6 58.5 58.5 58.6 58.5 58.3 58.2 58.3
2011 58.4 58.4 58.4 58.4 58.4 58.2 58.2 58.3 58.4 58.4 58.5 58.5
2012 58.5 58.5 58.6 58.5 58.6 58.6 58.5 58.4 58.6 58.8 58.7 58.6
2013 58.6 58.6 58.5 58.6 58.7 58.7 58.7 58.6 58.6 58.2 58.6 58.6
2014 58.8

Unemployment Rate – 16-19 Yrs

20.7%

Series Id:           LNS14000012
Seasonally Adjusted
Series title:        (Seas) Unemployment Rate - 16-19 yrs.
Labor force status:  Unemployment rate
Type of data:        Percent or rate
Age:                 16 to 19 years

Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual
2000 12.7 13.8 13.3 12.6 12.8 12.3 13.4 14.0 13.0 12.8 13.0 13.2
2001 13.8 13.7 13.8 13.9 13.4 14.2 14.4 15.6 15.2 16.0 15.9 17.0
2002 16.5 16.0 16.6 16.7 16.6 16.7 16.8 17.0 16.3 15.1 17.1 16.9
2003 17.2 17.2 17.8 17.7 17.9 19.0 18.2 16.6 17.6 17.2 15.7 16.2
2004 17.0 16.5 16.8 16.6 17.1 17.0 17.8 16.7 16.6 17.4 16.4 17.6
2005 16.2 17.5 17.1 17.8 17.8 16.3 16.1 16.1 15.5 16.1 17.0 14.9
2006 15.1 15.3 16.1 14.6 14.0 15.8 15.9 16.0 16.3 15.2 14.8 14.6
2007 14.8 14.9 14.9 15.9 15.9 16.3 15.3 15.9 15.9 15.4 16.2 16.8
2008 17.8 16.6 16.1 15.9 19.0 19.2 20.7 18.6 19.1 20.0 20.3 20.5
2009 20.7 22.3 22.2 22.2 23.4 24.7 24.3 25.0 25.9 27.2 26.9 26.7
2010 26.0 25.6 26.2 25.4 26.5 26.0 25.9 25.6 25.8 27.3 24.8 25.3
2011 25.5 24.1 24.3 24.5 23.9 24.8 24.8 25.1 24.5 24.2 24.1 23.3
2012 23.5 23.8 24.8 24.6 24.2 23.7 23.7 24.4 23.8 23.8 23.9 24.0
2013 23.5 25.2 23.9 23.7 24.1 23.8 23.4 22.6 21.3 22.0 20.8 20.2
2014 20.7

Average Weeks Unemployed

35.4 Weeks

Series Id:           LNS13008275
Seasonally Adjusted
Series title:        (Seas) Average Weeks Unemployed
Labor force status:  Unemployed
Type of data:        Number of weeks
Age:                 16 years and over
average_weeks_unemployed
Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual
2000 13.1 12.6 12.7 12.4 12.6 12.3 13.4 12.9 12.2 12.7 12.4 12.5
2001 12.7 12.8 12.8 12.4 12.1 12.7 12.9 13.3 13.2 13.3 14.3 14.5
2002 14.7 15.0 15.4 16.3 16.8 16.9 16.9 16.5 17.6 17.8 17.6 18.5
2003 18.5 18.5 18.1 19.4 19.0 19.9 19.7 19.2 19.5 19.3 19.9 19.8
2004 19.9 20.1 19.8 19.6 19.8 20.5 18.8 18.8 19.4 19.5 19.7 19.4
2005 19.5 19.1 19.5 19.6 18.6 17.9 17.6 18.4 17.9 17.9 17.5 17.5
2006 16.9 17.8 17.1 16.7 17.1 16.6 17.1 17.1 17.1 16.3 16.2 16.1
2007 16.3 16.7 17.8 16.9 16.6 16.5 17.2 17.0 16.3 17.0 17.3 16.6
2008 17.5 16.9 16.5 16.9 16.6 17.1 17.0 17.7 18.6 19.9 18.9 19.9
2009 19.8 20.2 20.9 21.7 22.4 23.9 25.1 25.3 26.6 27.5 28.9 29.7
2010 30.3 29.9 31.6 33.3 33.9 34.5 33.8 33.6 33.4 34.2 33.9 34.8
2011 37.2 37.5 39.2 38.7 39.5 39.7 40.4 40.2 40.2 39.1 40.3 40.7
2012 40.1 40.0 39.4 39.3 39.6 40.0 38.8 39.1 39.4 40.3 39.2 38.0
2013 35.4 36.9 37.0 36.6 36.9 35.7 36.7 37.0 36.8 36.0 37.1 37.1
2014 35.4

Median Weeks Unemployed

16.0 weeks

Series Id:           LNS13008276
Seasonally Adjusted
Series title:        (Seas) Median Weeks Unemployed
Labor force status:  Unemployed
Type of data:        Number of weeks
Age:                 16 years and over

median_weeks_unemployed

Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual
2000 5.8 6.1 6.0 6.1 5.8 5.7 6.0 6.3 5.2 6.1 6.1 6.0
2001 5.8 6.1 6.6 5.9 6.3 6.0 6.8 6.9 7.2 7.3 7.7 8.2
2002 8.4 8.3 8.4 8.9 9.5 11.0 8.9 9.0 9.5 9.6 9.3 9.6
2003 9.6 9.5 9.7 10.2 9.9 11.5 10.3 10.1 10.2 10.4 10.3 10.4
2004 10.6 10.2 10.2 9.5 9.9 11.0 8.9 9.2 9.6 9.5 9.7 9.5
2005 9.4 9.2 9.3 9.0 9.1 9.0 8.8 9.2 8.4 8.6 8.5 8.7
2006 8.6 9.1 8.7 8.4 8.5 7.3 8.0 8.4 8.0 7.9 8.3 7.5
2007 8.3 8.5 9.1 8.6 8.2 7.7 8.7 8.8 8.7 8.4 8.6 8.4
2008 9.0 8.7 8.7 9.4 7.9 9.0 9.7 9.7 10.2 10.4 9.8 10.5
2009 10.7 11.7 12.3 13.1 14.2 17.2 16.0 16.3 17.8 18.9 19.8 20.1
2010 20.0 19.9 20.5 22.1 22.3 25.0 22.2 20.9 20.2 21.4 21.0 22.0
2011 21.5 21.2 21.7 20.9 21.6 22.1 21.8 22.2 21.9 20.7 20.9 20.6
2012 20.9 20.0 19.6 19.2 19.8 19.8 17.2 18.2 18.7 20.0 18.6 17.8
2013 16.0 17.7 18.1 17.3 16.9 16.2 15.8 16.5 16.4 16.5 17.0 17.1
2014 16.0

Not in Labor Force, Searched for Work and Available

2,592,000

Series Id:                       LNU05026642
Not Seasonally Adjusted
Series title:                    (Unadj) Not in Labor Force, Searched For Work and Available
Labor force status:              Not in labor force
Type of data:                    Number in thousands
Age:                             16 years and over
Job desires/not in labor force:  Want a job now
Reasons not in labor force:      Available to work now
Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual
2000 1207 1281 1219 1216 1113 1142 1172 1097 1166 1044 1100 1125 1157
2001 1295 1337 1109 1131 1157 1170 1232 1364 1335 1398 1331 1330 1266
2002 1532 1423 1358 1397 1467 1380 1507 1456 1501 1416 1401 1432 1439
2003 1598 1590 1577 1399 1428 1468 1566 1665 1544 1586 1473 1483 1531
2004 1670 1691 1643 1526 1533 1492 1557 1587 1561 1647 1517 1463 1574
2005 1804 1673 1588 1511 1428 1583 1516 1583 1438 1414 1415 1589 1545
2006 1644 1471 1468 1310 1388 1584 1522 1592 1299 1478 1366 1252 1448
2007 1577 1451 1385 1391 1406 1454 1376 1365 1268 1364 1363 1344 1395
2008 1729 1585 1352 1414 1416 1558 1573 1640 1604 1637 1947 1908 1614
2009 2130 2051 2106 2089 2210 2176 2282 2270 2219 2373 2323 2486 2226
2010 2539 2527 2255 2432 2223 2591 2622 2370 2548 2602 2531 2609 2487
2011 2800 2730 2434 2466 2206 2680 2785 2575 2511 2555 2591 2540 2573
2012 2809 2608 2352 2363 2423 2483 2529 2561 2517 2433 2505 2614 2516
2013 2443 2588 2326 2347 2164 2582 2414 2342 2302 2283 2096 2427 2360
2014 2592

Total Unemployment Rate U-6

12.7%

Series Id:           LNS13327709
Seasonally Adjusted
Series title:        (seas) Total unemployed, plus all marginally attached workers plus total employed part time for economic reasons, as a percent of all civilian labor force plus all marginally attached workers
Labor force status:  Aggregated totals unemployed
Type of data:        Percent or rate
Age:                 16 years and over
Percent/rates:       Unemployed and mrg attached and pt for econ reas as percent of labor force plus marg attached

Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual
2000 7.1 7.2 7.1 6.9 7.1 7.0 7.0 7.1 7.0 6.8 7.1 6.9
2001 7.3 7.4 7.3 7.4 7.5 7.9 7.8 8.1 8.7 9.3 9.4 9.6
2002 9.5 9.5 9.4 9.7 9.5 9.5 9.6 9.6 9.6 9.6 9.7 9.8
2003 10.0 10.2 10.0 10.2 10.1 10.3 10.3 10.1 10.4 10.2 10.0 9.8
2004 9.9 9.7 10.0 9.6 9.6 9.5 9.5 9.4 9.4 9.7 9.4 9.2
2005 9.3 9.3 9.1 8.9 8.9 9.0 8.8 8.9 9.0 8.7 8.7 8.6
2006 8.4 8.4 8.2 8.1 8.2 8.4 8.5 8.4 8.0 8.2 8.1 7.9
2007 8.4 8.2 8.0 8.2 8.2 8.3 8.4 8.4 8.4 8.4 8.4 8.8
2008 9.2 9.0 9.1 9.2 9.7 10.1 10.5 10.8 11.0 11.8 12.6 13.6
2009 14.2 15.2 15.8 15.9 16.5 16.5 16.4 16.7 16.7 17.1 17.1 17.1
2010 16.7 17.0 17.1 17.2 16.6 16.4 16.4 16.5 16.8 16.6 16.9 16.6
2011 16.1 16.0 15.9 16.1 15.8 16.1 16.0 16.1 16.3 15.9 15.6 15.2
2012 15.1 15.0 14.5 14.6 14.8 14.8 14.9 14.7 14.7 14.4 14.4 14.4
2013 14.4 14.3 13.8 13.9 13.8 14.2 13.9 13.6 13.6 13.7 13.1 13.1
2014 12.7

Employment Situation Summary

Transmission of material in this release is embargoed until                      USDL-14-0168
8:30 a.m. (EST) Friday, February 7, 2014

Technical information:
Household data:        (202) 691-6378  •  cpsinfo@bls.gov  •  www.bls.gov/cps
Establishment data:    (202) 691-6555  •  cesinfo@bls.gov  •  www.bls.gov/ces

Media contact:         (202) 691-5902  •  PressOffice@bls.gov

                                 THE EMPLOYMENT SITUATION -- JANUARY 2014

Total nonfarm payroll employment rose by 113,000 in January, and the unemployment rate
was little changed at 6.6 percent, the U.S. Bureau of Labor Statistics reported today.
Employment grew in construction, manufacturing, wholesale trade, and mining. 

  ------------------------------------------------------------------------------------
 |                        Changes to the Employment Situation Data                    |
 |                                                                                    |
 |Establishment survey data have been revised as a result of the annual benchmarking  |
 |process and the updating of seasonal adjustment factors. Also, household survey data|
 |for January 2014 reflect updated population estimates. See the notes at the end of  |
 |this release for more information about these changes.                              |
 |                                                                                    |
  ------------------------------------------------------------------------------------

Household Survey Data

Both the number of unemployed persons, at 10.2 million, and the unemployment rate, at
6.6 percent, changed little in January. Since October, the jobless rate has decreased by
0.6 percentage point. (See table A-1.)  (See the note and tables B and C for information
about the effect of annual population adjustments to the household survey estimates.) 

Among the major worker groups, the unemployment rates for adult men (6.2 percent), adult
women (5.9 percent), teenagers (20.7 percent), whites (5.7 percent), blacks (12.1 percent),
and Hispanics (8.4 percent) showed little change in January. The jobless rate for Asians
was 4.8 percent (not seasonally adjusted), down by 1.7 percentage points over the year.
(See tables A-1, A-2, and A-3.)

The number of long-term unemployed (those jobless for 27 weeks or more), at 3.6 million,
declined by 232,000 in January. These individuals accounted for 35.8 percent of the
unemployed. The number of long-term unemployed has declined by 1.1 million over the year.
(See table A-12.)

After accounting for the annual adjustment to the population controls, the civilian labor
force rose by 499,000 in January, and the labor force participation rate edged up to 63.0
percent. Total employment, as measured by the household survey, increased by 616,000 over
the month, and the employment-population ratio increased by 0.2 percentage point to 58.8
percent. (See table A-1. For additional information about the effects of the population
adjustments, see table C.)

The number of persons employed part time for economic reasons (sometimes referred to as
involuntary part-time workers) fell by 514,000 to 7.3 million in January. These individuals
were working part time because their hours had been cut back or because they were unable to
find full-time work. (See table A-8.)

In January, 2.6 million persons were marginally attached to the labor force, little changed
from a year earlier. (The data are not seasonally adjusted.) These individuals were not in
the labor force, wanted and were available for work, and had looked for a job sometime in
the prior 12 months. They were not counted as unemployed because they had not searched for
work in the 4 weeks preceding the survey. (See table A-16.)

Among the marginally attached, there were 837,000 discouraged workers in January, about
unchanged from a year earlier. Discouraged workers are persons not currently looking for
work because they believe no jobs are available for them. The remaining 1.8 million persons
marginally attached to the labor force in January had not searched for work for reasons such
as school attendance or family responsibilities. (See table A-16.)

Establishment Survey Data

Total nonfarm payroll employment increased by 113,000 in January. In 2013, employment growth
averaged 194,000 per month. In January, job gains occurred in construction, manufacturing,
wholesale trade, and mining. (See table B-1.)

Construction added 48,000 jobs over the month, more than offsetting a decline of 22,000 in
December. In January, job gains occurred in both residential and nonresidential building
(+13,000 and +8,000, respectively) and in nonresidential specialty trade contractors
(+13,000). Heavy and civil engineering construction also added 10,000 jobs.

Employment in manufacturing increased in January (+21,000). Over the month, job gains
occurred in machinery (+7,000), wood products (+5,000), and motor vehicles and parts
(+5,000). Manufacturing added an average of 7,000 jobs per month in 2013.

In January, wholesale trade added 14,000 jobs, with most of the increase occurring in
nondurable goods (+10,000).

Mining added 7,000 jobs in January, compared with an average monthly gain of 2,000 jobs
in 2013.

Employment in professional and business services continued to trend up in January (+36,000).
The industry added an average of 55,000 jobs per month in 2013. Within the industry,
professional and technical services added 20,000 jobs in January. 

Leisure and hospitality employment continued to trend up over the month (+24,000). Job
growth in the industry averaged 38,000 per month in 2013. 

Employment in health care was essentially unchanged in January for the second consecutive
month.  Health care added an average of 17,000 jobs per month in 2013. 

Employment in retail trade changed little in January (-13,000). Within the industry, sporting
goods, hobby, book, and music stores lost 22,000 jobs, offsetting job gains in the prior 3
months. In January, motor vehicle and parts dealers added 7,000 jobs.

In January, federal government employment decreased by 12,000; the U.S. Postal Service
accounted for most of this decline (-9,000).

Employment in other major industries, including transportation and warehousing, information,
and financial activities, showed little or no change over the month.

In January, the average workweek for all employees on private nonfarm payrolls was unchanged
at 34.4 hours. The manufacturing workweek declined by 0.2 hour to 40.7 hours, and factory
overtime edged down by 0.1 hour to 3.4 hours. The average workweek for production and
nonsupervisory employees on private nonfarm payrolls was unchanged at 33.5 hours. (See
tables B-2 and B-7.)

Average hourly earnings for all employees on private nonfarm payrolls rose by 5 cents to
$24.21. Over the year, average hourly earnings have risen by 46 cents, or 1.9 percent. In
January, average hourly earnings of private-sector production and nonsupervisory employees
increased by 6 cents to $20.39. (See tables B-3 and B-8.)

The change in total nonfarm payroll employment for November was revised from +241,000 to
+274,000, and the change for December was revised from +74,000 to +75,000. With these
revisions, employment gains in November and December were 34,000 higher than previously
reported. Monthly revisions result from additional reports received from businesses since
the last published estimates and the monthly recalculation of seasonal factors. The annual
benchmark process also contributed to the revisions in this news release.

_____________
The Employment Situation for February is scheduled to be released on Friday, March 7, 2014,
at 8:30 a.m. (EST).

                                  Revisions to Establishment Survey Data

In accordance with annual practice, the establishment survey data released today have been
benchmarked to reflect comprehensive counts of payroll jobs for March 2013. These counts
are derived principally from the Quarterly Census of Employment and Wages (QCEW), which
enumerates jobs covered by the UI tax system. The benchmark process results in revisions
to not seasonally adjusted data from April 2012 forward. Seasonally adjusted data from
January 2009 forward are subject to revision. In addition, data for some series prior to
2009, both seasonally adjusted and unadjusted, incorporate revisions.

The total nonfarm employment level for March 2013 was revised upward by 369,000 (+347,000
on a not seasonally adjusted basis, or 0.3 percent). The average benchmark revision over
the past 10 years was plus or minus 0.3 percent. 

This revision incorporates the reclassification of jobs in the QCEW. Private household
employment is out of scope for the establishment survey. The QCEW reclassified some
private household employment into an industry that is in scope for the establishment
survey--services for the elderly and persons with disabilities. This reclassification
accounted for an increase of 466,000 jobs in the establishment survey. This increase of
466,000 associated with reclassification was offset by survey error of -119,000 for a
total net benchmark revision of +347,000 on a not seasonally adjusted basis. Historical
time series have been reconstructed to incorporate these revisions. 

The effect of these revisions on the underlying trend in nonfarm payroll employment was
minor. For example, the over-the-year change in total nonfarm employment for 2013 was
revised from 2,186,000 to 2,322,000 seasonally adjusted. Table A presents revised total
nonfarm employment data on a seasonally adjusted basis for January through December 2013.

All revised historical CES data, as well as an article that discusses the benchmark and
post-benchmark revisions and other technical issues can be accessed through the CES
homepage at www.bls.gov/ces/. Information on the data released today also may be obtained
by calling (202) 691-6555.

Table A. Revisions in total nonfarm employment, January-December 2013, seasonally adjusted
(Numbers in thousands)

------------------------------------------------------------------------------------------
                    |                                    |                                
                    |                Level               |      Over-the-month change     
                    |---------------------------------------------------------------------
    Year and month  |    As     |           |            |    As    |         |           
                    |previously |    As     | Difference |previously|   As    | Difference
                    |published  |  revised  |            |published | revised |           
------------------------------------------------------------------------------------------
                    |           |           |            |          |         |           
          2013      |           |           |            |          |         |           
                    |           |           |            |          |         |           
 January............|  134,839  |  135,261  |     422    |    148   |    197  |      49   
 February...........|  135,171  |  135,541  |     370    |    332   |    280  |     -52   
 March..............|  135,313  |  135,682  |     369    |    142   |    141  |      -1   
 April..............|  135,512  |  135,885  |     373    |    199   |    203  |       4   
 May................|  135,688  |  136,084  |     396    |    176   |    199  |      23   
 June...............|  135,860  |  136,285  |     425    |    172   |    201  |      29   
 July...............|  135,949  |  136,434  |     485    |     89   |    149  |      60   
 August.............|  136,187  |  136,636  |     449    |    238   |    202  |     -36   
 September..........|  136,362  |  136,800  |     438    |    175   |    164  |     -11   
 October............|  136,562  |  137,037  |     475    |    200   |    237  |      37   
 November...........|  136,803  |  137,311  |     508    |    241   |    274  |      33   
 December (p).......|  136,877  |  137,386  |     509    |     74   |     75  |       1   
------------------------------------------------------------------------------------------

   p = preliminary

                Adjustments to Population Estimates for the Household Survey

Effective with data for January 2014, updated population estimates have been used in the
household survey. Population estimates for the household survey are developed by the U.S.
Census Bureau. Each year, the Census Bureau updates the estimates to reflect new information
and assumptions about the growth of the population since the previous decennial census. The
change in population reflected in the new estimates results from adjustments for net
international migration, updated vital statistics and other information, and some
methodological changes in the estimation process. 

In accordance with usual practice, BLS will not revise the official household survey estimates
for December 2013 and earlier months. To show the impact of the population adjustments, however,
differences in selected December 2013 labor force series based on the old and new population
estimates are shown in table B. 

The adjustments increased the estimated size of the civilian noninstitutional population in
December by 2,000, the civilian labor force by 24,000, employment by 22,000, and unemployment
by 2,000. The number of persons not in the labor force was reduced by 22,000. The total
unemployment rate, employment-population ratio, and labor force participation rate were
unaffected. 

Data users are cautioned that these annual population adjustments can affect the comparability
of household data series over time. Table C shows the effect of the introduction of new
population estimates on the comparison of selected labor force measures between December 2013
and January 2014. Additional information on the population adjustments and their effect on
national labor force estimates is available at www.bls.gov/cps/cps14adj.pdf.

Table B. Effect of the updated population controls on December 2013 estimates by sex, race, and
Hispanic or Latino ethnicity, not seasonally adjusted
(Numbers in thousands)

__________________________________________________________________________________________________
                                        |      |     |      |       |        |       |            
                                        |      |     |      |       |  Black |       |            
                                        |      |     |      |       |    or  |       |  Hispanic  
                  Category              | Total| Men | Women| White | African| Asian | or Latino  
                                        |      |     |      |       |American|       | ethnicity  
                                        |      |     |      |       |        |       |            
________________________________________|______|_____|______|_______|________|_______|____________
                                        |      |     |      |       |        |       |            
  Civilian noninstitutional population..|    2 |  29 |  -27 |   -65 |     48 |    33 |     -57    
    Civilian labor force................|   24 |  24 |    0 |   -17 |     34 |    15 |     -38    
      Participation rate................|   .0 |  .0 |   .0 |    .0 |     .0 |    .0 |      .0    
     Employed...........................|   22 |  22 |    0 |   -16 |     31 |    14 |     -34    
      Employment-population ratio.......|   .0 |  .0 |   .0 |    .0 |     .0 |    .0 |      .0    
     Unemployed.........................|    2 |   3 |   -1 |    -1 |      4 |     1 |      -4    
      Unemployment rate.................|   .0 |  .0 |   .0 |    .0 |     .0 |    .0 |      .0    
    Not in labor force..................|  -22 |   4 |  -27 |   -48 |     14 |    18 |     -18    
________________________________________|______|_____|______|_______|________|_______|____________

   NOTE: Detail may not sum to totals because of rounding. Estimates for the above race groups
(white, black or African American, and Asian) do not sum to totals because data are not presented
for all races. Persons whose ethnicity is identified as Hispanic or Latino may be of any race.

Table C. December 2013-January 2014 changes in selected labor force measures,
with adjustments for population control effects
(Numbers in thousands)

______________________________________________________________________________
                                       |           |            |             
                                       |           |            |  Dec.-Jan.  
                                       | Dec.-Jan. |    2014    |   change,   
                                       |  change,  | population |  after re-  
                Category               |    as     |   control  |  moving the 
                                       | published |   effect   |  population 
                                       |           |            |   control   
                                       |           |            |  effect (1) 
_______________________________________|___________|____________|_____________
                                       |           |            |             
  Civilian noninstitutional population.|    170    |       2    |     168     
    Civilian labor force...............|    523    |      24    |     499     
      Participation rate...............|     .2    |      .0    |      .2     
     Employed..........................|    638    |      22    |     616     
      Employment-population ratio......|     .2    |      .0    |      .2     
     Unemployed........................|   -115    |       2    |    -117     
      Unemployment rate................|    -.1    |      .0    |     -.1     
    Not in labor force.................|   -353    |     -22    |    -331     
_______________________________________|___________|____________|_____________

   (1) This Dec.-Jan. change is calculated by subtracting the population 
control effect from the over-the-month change in the published seasonally
adjusted estimates.
   NOTE: Detail may not sum to totals because of rounding.

  ------------------------------------------------------------------------------------
 |                                                                                    |
 |                            Change to the Household Survey Tables                   |
 |                                                                                    |
 |Effective with this release, household survey table A-10 includes two new seasonally|
 |adjusted series for women age 55 and over--the number of unemployed persons and the |
 |unemployment rate. These replace the series that were previously displayed for this |
 |group, which were not seasonally adjusted.                                          |
 |                                                                                    |
  ------------------------------------------------------------------------------------

  ------------------------------------------------------------------------------------
 |                                                                                    |
 |               Updated Veteran Weighting Methodology for Household Survey           |
 |                                                                                    |
 |Beginning with data for January 2014, estimates for veterans in table A-5 of this   |
 |release incorporate updated weighting procedures. The new weighting methodology more|
 |accurately reflects the current demographic composition of the veteran population.  |
 |The primary impact of the change was an increase in the "Gulf War-era I" veteran    |
 |population and a decrease in the number of veterans in the "Other service periods"  |
 |category. The updated methodology had little effect on unemployment rates for       |
 |veterans, regardless of gender or period of service. Additional information on the  |
 |effect of the change on labor force estimates for veterans is available at          |
 |www.bls.gov/cps/vetsweights2014.pdf.                                                |
 |                                                                                    |
  ------------------------------------------------------------------------------------

Employment Situation Summary Table A. Household data, seasonally adjusted

HOUSEHOLD DATA
Summary table A. Household data, seasonally adjusted
[Numbers in thousands]

CategoryJan.
2013Nov.
2013Dec.
2013Jan.
2014Change from:
Dec.
2013-
Jan.
2014Employment status Civilian noninstitutional population244,663246,567246,745246,915-Civilian labor force155,699155,284154,937155,460-Participation rate63.663.062.863.0-Employed143,384144,443144,586145,224-Employment-population ratio58.658.658.658.8-Unemployed12,31510,84110,35110,236-Unemployment rate7.97.06.76.6-Not in labor force88,96391,28391,80891,455- Unemployment rates Total, 16 years and over7.97.06.76.6-Adult men (20 years and over)7.46.76.36.2-Adult women (20 years and over)7.26.26.05.9-Teenagers (16 to 19 years)23.520.820.220.7-White7.16.15.95.7-Black or African American13.812.411.912.1-Asian (not seasonally adjusted)6.55.34.14.8-Hispanic or Latino ethnicity9.78.78.38.4- Total, 25 years and over6.55.85.65.4-Less than a high school diploma12.010.69.89.6-High school graduates, no college8.17.37.16.5-Some college or associate degree7.06.46.16.0-Bachelor’s degree and higher3.83.43.33.2- Reason for unemployment Job losers and persons who completed temporary jobs6,6755,7315,3665,407-Job leavers984890862818-Reentrants3,5203,0653,0362,937-New entrants1,2741,1691,2011,184- Duration of unemployment Less than 5 weeks2,7532,4392,2552,434-5 to 14 weeks3,0772,5852,5062,429-15 to 26 weeks1,8671,7421,6511,689-27 weeks and over4,7074,0443,8783,646- Employed persons at work part time Part time for economic reasons7,9837,7237,7717,257-Slack work or business conditions5,1174,8694,8844,405-Could only find part-time work2,6132,4992,5922,571-Part time for noneconomic reasons18,55618,85818,73119,165- Persons not in the labor force (not seasonally adjusted) Marginally attached to the labor force2,4432,0962,4272,592-Discouraged workers804762917837– December – January changes in household data are not shown due to the introduction of updated population controls.
NOTE: Persons whose ethnicity is identified as Hispanic or Latino may be of any race. Detail for the seasonally adjusted data shown in this table will not necessarily add to totals because of the independent seasonal adjustment of the various series. Updated population controls are introduced annually with the release of January data.

Employment Situation Summary Table B. Establishment data, seasonally adjusted

ESTABLISHMENT DATA
Summary table B. Establishment data, seasonally adjusted
Category Jan.
2013
Nov.
2013
Dec.
2013(p)
Jan.
2014(p)
EMPLOYMENT BY SELECTED INDUSTRY
(Over-the-month change, in thousands)
Total nonfarm 197 274 75 113
Total private 219 272 89 142
Goods-producing 43 68 -13 76
Mining and logging 3 1 1 7
Construction 23 32 -22 48
Manufacturing 17 35 8 21
Durable goods(1) 9 19 2 15
Motor vehicles and parts 3.5 4.7 3.3 4.7
Nondurable goods 8 16 6 6
Private service-providing(1) 176 204 102 66
Wholesale trade 16.9 16.8 10.2 13.9
Retail trade 26.9 22.3 62.7 -12.9
Transportation and warehousing 9.8 32.4 10.6 9.9
Information -1 1 -10 0
Financial activities 8 -4 3 -2
Professional and business services(1) 45 73 4 36
Temporary help services 4.9 36.6 30.1 8.1
Education and health services(1) 17 25 -4 -6
Health care and social assistance 23.5 24.4 1.1 1.5
Leisure and hospitality 47 37 20 24
Other services 7 -1 7 4
Government -22 2 -14 -29
WOMEN AND PRODUCTION AND NONSUPERVISORY EMPLOYEES(2)
AS A PERCENT OF ALL EMPLOYEES
Total nonfarm women employees 49.4 49.5 49.5 49.4
Total private women employees 48.0 48.0 48.0 47.9
Total private production and nonsupervisory employees 82.6 82.6 82.6 82.6
HOURS AND EARNINGS
ALL EMPLOYEES
Total private
Average weekly hours 34.4 34.5 34.4 34.4
Average hourly earnings $23.75 $24.15 $24.16 $24.21
Average weekly earnings $817.00 $833.18 $831.10 $832.82
Index of aggregate weekly hours (2007=100)(3) 97.5 99.6 99.4 99.5
Over-the-month percent change 0.2 0.5 -0.2 0.1
Index of aggregate weekly payrolls (2007=100)(4) 110.5 114.8 114.6 114.9
Over-the-month percent change 0.4 0.8 -0.2 0.3
HOURS AND EARNINGS
PRODUCTION AND NONSUPERVISORY EMPLOYEES
Total private
Average weekly hours 33.6 33.7 33.5 33.5
Average hourly earnings $19.95 $20.30 $20.33 $20.39
Average weekly earnings $670.32 $684.11 $681.06 $683.07
Index of aggregate weekly hours (2002=100)(3) 104.9 107.1 106.6 106.7
Over-the-month percent change -0.2 0.5 -0.5 0.1
Index of aggregate weekly payrolls (2002=100)(4) 139.8 145.3 144.8 145.3
Over-the-month percent change 0.1 0.8 -0.3 0.3
DIFFUSION INDEX(5)
(Over 1-month span)
Total private (264 industries) 64.0 66.9 56.4 61.2
Manufacturing (81 industries) 56.8 65.4 59.9 54.3
Footnotes
(1) Includes other industries, not shown separately.
(2) Data relate to production employees in mining and logging and manufacturing, construction employees in construction, and nonsupervisory employees in the service-providing industries.
(3) The indexes of aggregate weekly hours are calculated by dividing the current month’s estimates of aggregate hours by the corresponding annual average aggregate hours.
(4) The indexes of aggregate weekly payrolls are calculated by dividing the current month’s estimates of aggregate weekly payrolls by the corresponding annual average aggregate weekly payrolls.
(5) Figures are the percent of industries with employment increasing plus one-half of the industries with unchanged employment, where 50 percent indicates an equal balance between industries with increasing and decreasing employment.
(p) Preliminary
NOTE: Data have been revised to reflect March 2013 benchmark levels and updated seasonal adjustment factors.

Weakness Continues as 113,000 Jobs Are Added in January

Employers added jobs at a slower-than-expected pace in January, the second month in a row that hiring has been disappointing and a sign that the labor market remains anemic despite indications of growth elsewhere in the economy.

Payrolls increased by 113,000, the Labor Department reported Friday morning, well below the gain of 180,000 that economists expected. The unemployment rate, based on a separate survey of households that was more encouraging, actually fell by a tenth of a percentage point, to 6.6 percent.

The data for January come after an even more disappointing report on the labor market for December, which was revised upward only slightly Friday, to show a gain of just 75,000 jobs, from 74,000. The level of hiring in January was also substantially below the average monthly gain of 178,000 positions over the last six months, as well as the monthly addition of 187,000 over the last year.

The two weak months in a row will prompt questions about whether the Federal Reserve acted prematurely when policy makers in December voted to begin scaling back the central bank’s expansive stimulus efforts.

The new data is not expected to alter the Fed’s course, economists said, but another poor report on hiring next month might force policy makers to rethink their plan when they next meet in late March.

“In one line: grim,” said Ian Shepherdson, chief economist at Pantheon Macroeconomics, in a note to clients Friday morning.

While seasonal adjustments may have played a role and upward revisions for hiring in October and November were more encouraging, he said, “The payroll rebound clearly is disappointing; none of the ground lost in December was recovered.”

Other economists conceded the picture for January was hardly bright, but cautioned it was too soon to conclude there had been a fundamental loss of momentum in the economy, especially given seasonal fluctuations in the data and the possibility that weather inhibited some hiring.

“We’re not seeing the takeoff that people wanted to see, but it’s not a disaster,” said Julia Coronado, chief economist for North America at BNP Paribas. “The 113,000 figure is definitely way below trend, but we want another month or two of data before we can draw conclusions.”

One mystery economists will be focusing on is why employment gains have not kept up with economic growth as measured by gross domestic product, which picked up substantially in the second half of 2013. The annualized pace of expansion was 3.2 percent in the fourth quarter, and 4.1 percent in the third quarter.

One reason may be that new technologies are allowing employers to make do with fewer workers, for instance the use of automated customer service systems instead of call centers, or Internet retailers’ taking over from brick-and-mortar stores where sales associates prowl the floors.

Another shift is evident from the yawning gap in employment for college graduates versus workers who lack a high school diploma. For people with a college degree or higher, the jobless rate was 3.1 percent, compared with 9.6 percent for Americans who did not finish high school.

Wintry conditions that held back hiring were blamed for the weakness in December, a theory popular among more optimistic economists after those numbers came out in early January.

But despite what seems like an endless series of snowstorms on the East Coast and arctic conditions in the Midwest recently, the reference week for the latest survey was Jan. 12-18, when conditions were fairly normal as Januaries go, limiting some of the impact of the weather in this report.

In the report on January, one sector holding back payrolls was the government, which shrank by 29,000 jobs in January. Excluding that loss, private employers added 142,000 positions, a slightly better showing.

Several other sectors which had been strong in recent months – education and health care as well as retailing – also lost positions, contributing to the overall weakness.

The falloff in hiring in the health care sector was especially notable. In December and January together, just 2,600 health care positions were filled. By contrast, as recently as November, nearly 25,000 health care workers were added to payrolls.

Although this area of the economy is going through a transformation as President Obama’s new health care plan is slowly introduced, that is unlikely to have caused the abrupt slowdown in hiring, said Ethan Harris, a head of global economics at Bank of America Merrill Lynch. If anything, he said, the law should create new jobs in the sector as health care coverage is expanded, even if higher costs for some employers result in job cuts elsewhere in the economy.

As for retail, which lost nearly 13,000 jobs in January, some of that reduction could have essentially been because of excessive hiring in December, Mr. Harris said, when stores added nearly 63,000 positions as the holiday shopping season peaked. The cuts may also have been spurred by weak results at some retailers, with chains like J. C. Penney announcing major job cuts last month, and Loehmann’s, the venerable discounter, now in liquidation.

The employment-population ratio, which has been falling as more workers drop out of the job market, edged up 0.2 percentage points to 58.8 percent. In recent years, the exit of people from the work force has reduced the unemployment rate, but it is a sign that people are giving up hope of finding a job in the face of slack conditions, hardly the way policy makers would like to see joblessness come down.

http://www.nytimes.com/2014/02/08/business/us-economy-adds-113000-jobs-unemployment-rate-at-6-6.html?_r=0

EMBARGOED UNTIL RELEASE AT 8:30 A.M. EST, THURSDAY, JANUARY 30, 2014
BEA 14-03

* See the navigation bar at the right side of the news release text for links to data tables,
contact personnel and their telephone numbers, and supplementary materials.

Lisa S. Mataloni: (202) 606-5304 (GDP) gdpniwd@bea.gov
Recorded message: (202) 606-5306
Jeannine Aversa: (202) 606-2649 (News Media)
National Income and Product Accounts
Gross Domestic Product, 4th quarter and annual 2013 (advance estimate)
      Real gross domestic product -- the output of goods and services produced by labor and property
located in the United States -- increased at an annual rate of 3.2 percent in the fourth quarter of 2013
(that is, from the third quarter to the fourth quarter), according to the "advance" estimate released by the
Bureau of Economic Analysis.  In the third quarter, real GDP increased 4.1 percent.

      The Bureau emphasized that the fourth-quarter advance estimate released today is based on
source data that are incomplete or subject to further revision by the source agency (see the box on page 4
and "Comparisons of Revisions to GDP" on page 5).  The "second" estimate for the fourth quarter, based
on more complete data, will be released on February 28, 2014.

      The increase in real GDP in the fourth quarter primarily reflected positive contributions from
personal consumption expenditures (PCE), exports, nonresidential fixed investment, private inventory
investment, and state and local government spending that were partly offset by negative contributions
from federal government spending and residential fixed investment.  Imports, which are a subtraction in
the calculation of GDP, increased.

      The deceleration in real GDP in the fourth quarter reflected a deceleration in private inventory
investment, a larger decrease in federal government spending, a downturn in residential fixed
investment, and decelerations in state and local government spending and in nonresidential fixed
investment that were partly offset by accelerations in exports and in PCE and a deceleration in imports.

      The price index for gross domestic purchases, which measures prices paid by U.S. residents,
increased 1.2 percent in the fourth quarter, compared with an increase of 1.8 percent in the third.
Excluding food and energy prices, the price index for gross domestic purchases increased 1.7 percent in
the fourth quarter, compared with an increase of 1.5 percent in the third.

_______
FOOTNOTE.  Quarterly estimates are expressed at seasonally adjusted annual rates, unless otherwise
specified.  Quarter-to-quarter dollar changes are differences between these published estimates.  Percent
changes are calculated from unrounded data and are annualized.  "Real" estimates are in chained (2009)
dollars.  Price indexes are chain-type measures.

This news release is available on www.bea.gov along with the Technical Note and Highlights 
related to this release.
_______

      Real personal consumption expenditures increased 3.3 percent in the fourth quarter, compared
with an increase of 2.0 percent in the third. Durable goods increased 5.9 percent, compared with an
increase of 7.9 percent.  Nondurable goods increased 4.4 percent, compared with an increase of 2.9
percent.  Services increased 2.5 percent, compared with an increase of 0.7 percent.

      Real nonresidential fixed investment increased 3.8 percent in the fourth quarter, compared with
an increase of 4.8 percent in the third.  Nonresidential structures decreased 1.2 percent, in contrast to an
increase of 13.4 percent.  Equipment increased 6.9 percent, compared with an increase of 0.2 percent.
Intellectual property products increased 3.2 percent, compared with an increase of 5.8 percent.  Real
residential fixed investment decreased 9.8 percent, in contrast to an increase of 10.3 percent.

      Real exports of goods and services increased 11.4 percent in the fourth quarter, compared with
an increase of 3.9 percent in the third.  Real imports of goods and services increased 0.9 percent,
compared with an increase of 2.4 percent.

      Real federal government consumption expenditures and gross investment decreased 12.6 percent
in the fourth quarter, compared with a decrease of 1.5 percent in the third.  National defense decreased
14.0 percent, compared with a decrease of 0.5 percent.  Nondefense decreased 10.3 percent, compared
with a decrease of 3.1 percent.  Real state and local government consumption expenditures and gross
investment increased 0.5 percent, compared with an increase of 1.7 percent.

      The change in real private inventories added 0.42 percentage point to the fourth-quarter change
in real GDP after adding 1.67 percentage points to the third-quarter change.  Private businesses
increased inventories $127.2 billion in the fourth quarter, following increases of $115.7 billion in the
third quarter and $56.6 billion in the second.

      Real final sales of domestic product -- GDP less change in private inventories -- increased 2.8
percent in the fourth quarter, compared with an increase of 2.5 percent in the third.

Gross domestic purchases

      Real gross domestic purchases -- purchases by U.S. residents of goods and services wherever
produced -- increased 1.8 percent in the fourth quarter, compared with an increase of 3.9 percent in the
third.

Disposition of personal income

      Current-dollar personal income increased $69.4 billion (2.0 percent) in the fourth quarter,
compared with an increase of $140.0 billion (4.0 percent) in the third.  The deceleration in personal
income primarily reflected downturns in personal dividend income and in farm proprietors’ income and
a deceleration in personal current transfer receipts that were partly offset by an acceleration in wages
and salaries.

      Personal current taxes increased $23.7 billion in the fourth quarter, in contrast to a decrease of
$11.0 billion in the third.

      Disposable personal income increased $45.7 billion (1.5 percent) in the fourth quarter, compared
with an increase of $151.0 billion (5.0 percent) in the third.  Real disposable personal income increased
0.8 percent in the fourth quarter, compared with an increase of 3.0 percent in the third.

      Personal outlays increased $118.6 billion (4.0 percent) in the fourth quarter, compared with an
increase of $113.4 billion (3.9 percent) in the third.  Personal saving -- disposable personal income less
personal outlays -- was $545.1 billion in the fourth quarter, compared with $618.0 billion in the third.

      The personal saving rate -- personal saving as a percentage of disposable personal income -- was
4.3 percent in the fourth quarter, compared with 4.9 percent in the third.  For a comparison of personal
saving in BEA’s national income and product accounts with personal saving in the Federal Reserve
Board’s financial accounts of the United States and data on changes in net worth, go to
www.bea.gov/national/nipaweb/Nipa-Frb.asp.

Current-dollar GDP

      Current-dollar GDP -- the market value of the nation's output of goods and services -- increased
4.6 percent, or $189.6 billion, in the fourth quarter to a level of $17,102.5 billion.  In the third quarter,
current-dollar GDP increased 6.2 percent, or $251.9 billion.

2013 GDP

	Real GDP increased 1.9 percent in 2013 (that is, from the 2012 annual level to the 2013 annual
level), compared with an increase of 2.8 percent in 2012.

      The increase in real GDP in 2013 primarily reflected positive contributions from personal
consumption expenditures (PCE), exports, residential fixed investment, nonresidential fixed investment,
and private inventory investment that were partly offset by a negative contribution from federal
government spending.  Imports, which are a subtraction in the calculation of GDP, increased.

      The deceleration in real GDP in 2013 primarily reflected a deceleration in nonresidential fixed
investment, a larger decrease in federal government spending, and decelerations in PCE and in exports
that were partly offset by a deceleration in imports and a smaller decrease in state and local government
spending.

      The price index for gross domestic purchases increased 1.2 percent in 2013, compared with an
increase of 1.7 percent in 2012.

      Current-dollar GDP increased 3.4 percent, or $558.4 billion, in 2013, compared with an increase
of 4.6 percent, or $710.8 billion, in 2012.

      During 2013 (that is, measured from the fourth quarter of 2012 to the fourth quarter of 2013) real
GDP increased 2.7 percent.  Real GDP increased 2.0 percent during 2012.  The price index for gross
domestic purchases increased 1.1 percent during 2013, compared with an increase of 1.5 percent in
2012.

________
BOX.	  Information on the assumptions used for unavailable source data is provided in a technical note
that is posted with the news release on BEA's Web site.  Within a few days after the release, a detailed
"Key Source Data and Assumptions" file is posted on the Web site.  In the middle of each month, an analysis
of the current quarterly estimate of GDP and related series is made available on the Web site; click on
Survey of Current Business, "GDP and the Economy."  For information on revisions, see "Revisions to GDP, GDI,
and Their Major Components."
________

      BEA's national, international, regional, and industry estimates; the Survey of Current Business;
and BEA news releases are available without charge on BEA's Web site at www.bea.gov.  By visiting
the site, you can also subscribe to receive free e-mail summaries of BEA releases and announcements.

                                      *          *          *

                          Next release -- February 28, 2014 at 8:30 A.M. EST for:
                  Gross Domestic Product:  Fourth Quarter and Annual 2013 (Second Estimate)

                                      *          *          *

Release dates in 2014

Gross Domestic Product

           		2013: IV and 2013 annual    	2014: I     	2014: II       	  2014: III

Advance...		January 30            	        April 30	July 30		  October 30
Second....		February 28          	        May 29      	August 28	  November 25
Third..... 		March 27             	        June 25     	September 26	  December 23

Corporate Profits

Preliminary...          ......	                        May 29         August 28         November 25
Revised....... 		March 27             	        June 25        September 26      December 23

                                            Comparisons of Revisions to GDP

     Quarterly estimates of GDP are released on the following schedule:  the "advance" estimate, based on
source data that are incomplete or subject to further revision by the source agency, is released near the end of the
first month after the end of the quarter; as more detailed and more comprehensive data become available,
the "second" and "third" estimates are released near the end of the second and third months, respectively.
The "latest"” estimate reflects the results of both annual and comprehensive revisions.

     Annual revisions, which generally cover the quarters of the 3 most recent calendar years, are usually carried
out each summer and incorporate newly available major annual source data.  Comprehensive (or benchmark)
revisions are carried out at about 5-year intervals and incorporate major periodic source data, as well as
improvements in concepts and methods that update the accounts to portray more accurately the evolving U.S.
economy.

The table below shows comparisons of the revisions between quarterly percent changes of current-dollar
and of real GDP for the different vintages of the estimates.  From the advance estimate to the second estimate (one
month later), the average revision to real GDP without regard to sign is 0.5 percentage point, while from the
advance estimate to the third estimate (two months later), it is 0.6 percentage point.  From the advance estimate to
the latest estimate, the average revision without regard to sign is 1.3 percentage points.  The average revision
(with regard to sign) from the advance estimate to the latest estimate is 0.3 percentage point, which is larger
than the average revisions from the advance estimate to the second or to the third estimates.  The larger average
revisions to the latest estimate reflect the fact that comprehensive revisions include major improvements, such as
the incorporation of BEA’s latest benchmark input-output accounts.  The quarterly estimates correctly indicate the
direction of change of real GDP 97 percent of the time, correctly indicate whether GDP is accelerating or
decelerating 72 percent of the time, and correctly indicate whether real GDP growth is above, near, or below trend
growth more than four-fifths of the time.

                           Revisions Between Quarterly Percent Changes of GDP: Vintage Comparisons
                                                     [Annual rates]

       Vintages                                   Average         Average without     Standard deviation of
       compared                                                    regard to sign      revisions without
                                                                                         regard to sign

____________________________________________________Current-dollar GDP_______________________________________________

Advance to second....................               0.2                 0.5                  0.4
Advance to third.....................                .2                  .7                   .4
Second to third......................                .0                  .3                   .2

Advance to latest....................                .3                 1.3                  1.0

________________________________________________________Real GDP_____________________________________________________

Advance to second....................               0.1                 0.5                  0.4
Advance to third.....................                .1                  .6                   .4
Second to third......................                .0                  .2                   .2

Advance to latest....................                .3                 1.3                  1.0

NOTE.  These comparisons are based on the period from 1983 through 2010.http://bea.gov/newsreleases/national/gdp/gdpnewsrelease.htm
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Confirmed 4 Dead and 63 Injured in New York City Train Derailment — Brakes Failed? — Videos

Posted on December 2, 2013. Filed under: Blogroll, Communications, Federal Government, Law, liberty, Life, Links, People, Philosophy, Photos, Politics, Technology, Trains, Transportation, Video, Wisdom | Tags: , , , , , , , , , , |

NYC Train DerailmentNYC Train Derailmentmta-crash-9mta-crash-12mta-crash-14mta-train-derailment7mta-crash-13

Witness Interviews on New York MTA Metro-North Train Derail, 4 Passengers Dead

Metro-North Poughkeepsie to Grand Central Terminal Passenger Train Derails in Bronx New York

MTA Metro-North Train derails in New York at Spitting Devil’s Curve, Passenger Deaths Confirmed

Metro North Train Derails in Bronx area of New York City[RAW FOOTOGE]

Metro-North train derails in The Bronx

Metro-North Poughkeepsie to Grand Central Terminal Train Derailment Initial Information

Member Weener briefs media on Bronx, N.Y., Metro North train derailment, December 1, 2013

NTSB: Train going too fast at curve before wreck

A commuter train that derailed over the weekend, killing four passengers, was hurtling at 82 mph as it entered a 30 mph curve, a federal investigator said Monday. But whether the wreck was the result of human error or mechanical trouble was unclear, he said.

Safety experts said the tragedy might have been prevented if Metro-North Railroad had installed automated crash-avoidance technology that safety authorities have been urging for decades.

The locomotive’s speed was extracted from the train’s two data recorders after the Sunday morning accident, which happened in the Bronx along a bend so sharp that the speed limit drops from 70 mph to 30 mph.

Asked why the train was going so fast, National Transportation Safety Board member Earl Weener said: “That’s the question we need to answer.”

Weener would not disclose what the engineer operating the train told investigators, and he said results of drug and alcohol tests were not yet available. Investigators are also examining the engineer’s cellphone, apparently to determine whether he was distracted.

“When I heard about the speed, I gulped,” said Sen. Charles Schumer, D-N.Y.

The engineer, William Rockefeller, was injured and “is totally traumatized by everything that has happened,” said Anthony Bottalico, executive director of the rail employees union.

He said Rockefeller, 46, was cooperating fully with investigators.

“He’s a sincere human being with an impeccable record that I know of. He’s diligent and competent,” Bottalico said. Rockefeller has been an engineer for about 11 years and a Metro-North employee for about 20, he said.

Weener sketched a scenario that suggested that the throttle was let up and the brakes were fully applied way too late to stave off disaster.

He said the throttle went to idle six seconds before the derailed train came to a complete stop — “very late in the game” for a train going that fast — and the brakes were fully engaged five seconds before the train stopped.

It takes about a mile for a train going 70 mph to stop, according to Steve Ditmeyer, a former Federal Railroad Administration official who now teaches at Michigan State University.

Asked whether the tragedy was the result of human error or faulty brakes, Weener said: “The answer is, at this point in time, we can’t tell.”

But he said investigators are not aware of any problems with the brakes during the nine stops the train made before the derailment.

The wreck came two years before the federal government’s deadline for Metro-North and other railroads to install automatic-slowdown technology designed to prevent catastrophes caused by human error.

Metro-North’s parent agency and other railroads have pressed the government to extend Congress’ 2015 deadline a few years because of the cost and complexity of the Positive Train Control system, which uses GPS, wireless radio and computers to monitor trains and stop them from colliding, derailing or going the wrong way.

Ditmeyer said the technology would have monitored the brakes and would not have allowed the train in Sunday’s tragedy to exceed the speed limit.

http://www.washingtonpost.com/business/nyc-train-derailment-kills-4-hurts-more-than-60/2013/12/01/fb8e3a0e-5ae8-11e3-801f-1f90bf692c9b_story.html

4 dead, 63 injured in NYC train derail ‘bloodbath’

By Larry Celona, Jamie Schram and Kevin Sheehan

A Metro-North train loaded with holiday travelers derailed as it hurtled around a tight Bronx curve just north of Manhattan on Sunday — leaving at least four dead and 63 injured in a crash the engineer blamed on brake malfunction.

“It was just a bloodbath,” a shaken FDNY worker said of the scene of twisted metal and shattered glass along a bucolic stretch of the Hudson River, where the accident occurred just north of the Spuyten Duyvil station at 7:22 a.m.

Rescue crews were still working early Monday morning to right three of the seven derailed passenger cars to look for more possible bodies.

The train’s operator — 20-year MTA veteran William Rockefeller, 46, of upstate Germantown — was said to have told emergency responders that the brakes didn’t work.

“The guy’s distraught over the accident and the people who were injured,” a source said of Rockefeller, who was among those hurt.

All of those killed were New Yorkers. They included two women — Ahn Kisook, 35, of Queens, and Donna Smith, 54, of Newburgh — as well as married dads James Ferrari, 59, of Montrose and James Lovell, 58, of Cold Spring.

Three of the dead were thrown from the Hudson Line train, which had originated in Poughkeepsie at 5:54 a.m., bound for Grand Central. Their bodies were recovered between the second and third cars.

Passenger Emilie Miyauchi, 28, said she used her yoga mat to cover one of the victims.

“[She] seemed like she had lost most of her head. The side of the car was just covered in her blood,” she recalled.

Injured passengers are removed from the derailed Metro-North train.Photo: William Farrington

It was the first time any passenger had been killed in Metro-North’s 31-year history.

Riders described chaos as the train flew off the tracks.

“I was just holding on . . . and people were flying around,” said Eddie Russell, 48, who was headed to work as a guard at SiriusXM. “I was afraid I was going to fall out the window.”

Joel Zaritsky said he was asleep and woke up as his train car started rolling over.

“Then I saw the gravel coming at me, and I heard people screaming,” he said.

The scene “looked like a toy train set that was mangled by some super-powerful force,” Gov. Cuomo later told CNN.

Gov. Cuomo said Monday that the high speed of the train probably caused the accident.

“I think it’s going to be speed-related,” he said. “It’s not about the turn. I think it’s going to be about the speed…” he said on NBC’s “Today” show.

Cuomo added that investigators are still trying to determine if the excessive speed was caused by “operator error” or a mechanical or other problem.

The governor called the scene of the tragedy horrific.

“It was actually worse than it looks,” he said.

Later, on Fox’s “Good Day New York,” he said it was hard to describe what he saw.

“This was breathtaking,” Cuomo recalled. “One minute everything is fine and the next minute we lost New Yorkers in a really tragic and violent way.

The first train car landed inches from Spuyten Duyvil Creek. NYPD divers searched the water to make sure no victims were thrown in.

The train, pushed by a diesel locomotive from behind, should have been going 70 mph before it slowed to 30 mph to round the curve, officials said.

Passengers told probers that the train seemed to be going much faster than usual.

“I have no idea why. I take this train every morning, and they always slow on this curve,” passenger Frank Tatulli told WABC-TV.

A person is evacuated from the scene of the derailment of a Metro-North passenger train in The Bronx.Photo: AP

Investigators recovered the train’s “black box,” which should reveal how fast it was going when it crashed, said officials with the National Transportation Safety Board, which is leading the probe.

There were 120 passengers aboard — making it about half full — along with four crew.

At least 11 people were critically hurt, including a man in his early 40s who suffered a spinal-cord injury and may be paralyzed, authorities said. A 14-year-old boy also was critical.

Another six people were hospitalized in serious condition.

Firefighters at the scene where a train derailed in The Bronx Sunday morning.Photo: Theodore Parisienne

The train’s conductor was among those injured, as were three city cops. The most seriously hurt officer, Elsie Rodriguez, was on her way to work at her domestic-violence post at the 40th Precinct station in The Bronx, said sources, who added that she broke her collarbone.

Police Commissioner Ray Kelly visited Rodriguez at St. Barnabas Hospital in The Bronx. Mayor Bloomberg — who had been MIA for most of the day, with staffers refusing to say where he was — also dropped in to see Rodriguez on Sunday evening.

“We chitchatted about her job and how I was going to be unemployed, and she thought that was funny,” Bloomberg said.

Asked about why he hadn’t been at the accident scene, the mayor responded, “What can I do? I’m not a professional firefighter or a police officer. There’s nothing I can do! What I can do is make sure the right people from New York . . . are there and have all the resources that they want.”

Two other cops were treated at Montefiore Medical Center, also in The Bronx. They were identified as Richie Hernandez of the NYPD’s Special Victims Unit and Gabriel Rodriguez of the 42nd Precinct. Rodriguez, who was on his way to work, was treated for a leg injury and released, sources said.

An NYPD school-safety officer also was on board, along with a Police Department recruit, but neither was hurt, sources said.

NTSB member Earl Weener said six teams of investigators would be probing everything from the train’s speed and instruments to its maintenance and personnel records and the condition of the tracks.

“Our mission is to understand not just what happened but why it happened,” he said.

Cuomo insisted that the train route’s curve had nothing to do with anything.

“Trains take the curve every day 365 days a year, so it’s not the fact that there’s a curve here,’’ he said. “There has to be another factor.’’

The accident was the second involving a Metro-North train in six months.

http://nypost.com/2013/12/01/metro-north-train-derails-in-the-bronx/

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Anthony Welters Bundler of Campaign Contributions — Corrupt Crony Capitalism Continues With Obama’s Tech Surge to Fix Broken HealthCare.gov — Smiling Faces Sometimes — Videos

Posted on November 1, 2013. Filed under: American History, Blogroll, College, Communications, Computers, Demographics, Diasters, Economics, Education, Employment, Federal Government, Federal Government Budget, Fiscal Policy, government spending, Health Care, history, Investments, IRS, Language, Law, liberty, Life, Links, Macroeconomics, Medicine, People, Philosophy, Rants, Raves, Regulations, Security, Tax Policy, Taxes, Technology, Transportation, Unemployment, Video, Wealth, Wisdom | Tags: , , , , , , , , |

Anthony Welters, Executive Vice President of

United Health Group

?????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????

unitedhealth_group

Optum_QSSI

healthcare_gov

The Undisputed Truth “Smiling Faces Sometimes” (1971)

Smiling faces sometimes pretend to be your friend
Smiling faces show no traces of the evil that lurks within
Smiling faces, smiling faces sometimes
They don’t tell the truth uh
Smiling faces, smiling faces
Tell lies and I got proof

The truth is in the eyes
Cause the eyes don’t lie, amen
Remember a smile is just
A frown turned upside down
My friend let me tell you
Smiling faces, smiling faces sometimes
They don’t tell the truth, uh
Smiling faces, smiling faces
Tell lies and I got proof
Beware, beware of the handshake
That hides the snake
I’m telling you beware
Beware of the pat on the back
It just might hold you back
Jealousy (jealousy)
Misery (misery)
Envy

I tell you, you can’t see behind smiling faces
Smiling faces sometimes they don’t tell the truth
Smiling faces, smiling faces
Tell lies and I got proof

Smiling faces, smiling faces sometimes
They don’t tell the truth
Smiling faces, smiling faces
Tell lies and I got proof
(Smiling faces, smiling faces sometimes)
(Smiling faces, smiling faces sometimes)
I’m telling you beware, beware of the handshake
That hides the snake
Listen to me now, beware
Beware of that pat on the back
It just might hold you back
Smiling faces, smiling faces sometimes
They don’t tell the truth
Smiling faces, smiling faces
Tell lies and I got proof

Your enemy won’t do you no harm
Cause you’ll know where he’s coming from
Don’t let the handshake and the smile fool ya
Take my advice I’m only try’ to school ya

obama_smiling

Obama to AMA keep your doctor and insurance we will build economy

Obama Knew Millions Would Not Keep Their Private Health Insurance, Get Ready To Pay Much More!

President Obama repeatedly assured Americans that after the Affordable Care Act became law, people who liked their health insurance would be able to keep it. But millions of Americans are getting or are about to get cancellation letters for their health insurance under Obama-care, say experts, and the Obama administration has known that for at least three years.

Four sources deeply involved in the Affordable Care Act tell NBC News that 50 to 75 percent of the 14 million consumers who buy their insurance individually can expect to receive a “cancellation” letter or the equivalent over the next year because their existing policies don’t meet the standards mandated by the new health care law. One expert predicts that number could reach as high as 80 percent. And all say that many of those forced to buy pricier new policies will experience “sticker shock.”

Obama knew millions would lose their health insurance

Obama administration knew millions would lose health insurance

How Cronyism is Hurting the Economy

If You Like Your Health Care Plan You Can’t Keep It!

Uploaded on Jun 16, 2010

Fox News report highlighting how empty Obama’s promise “If you like your health care plan you can keep it” really is. A new government report reveals that 51% of employers may have to relinquish their current health care coverage by 2013 due to ObamaCare. That numbers soars to 66% for small-business employers.

With new restrictions on health insurance being issued by the Secretary of Health and Human Services millions of Americans will shortly be forced to accept government insurance. Exempted from these new rules will be labor unions.

Remember that Obama in a September 2009 speech to congress said: “If you misrepresent what’s in the plan, we will call you out.”

O.K. Obama misrepresented what was in his plan. It’s time to CALL HIM OUT. Then THROW him out in 2012!

UnitedHealth Group Overview Video

UnitedHealth Group’s Simon Stevens

United Health Group Pressuring Employees To Campaign Against Health Care Reform (With Audio)

Wealth Strategies: Obamacare to benefit HCA, UnitedHealth

Obamacare Fallout – Critics Ask If White House Was Misleading Americans – Brit Humes – Kelly File

Who’s Fixing healthcare.gov?

Healthcare.gov hearings on Capitol Hill

Healthcare.gov Website Issues Plague Obama Administration

‘This Week’: Healthcare.gov Website Havoc

Software Engineers Blame Poor Design For Obamacare Site

Problems

ObamaCare glitches lead to tech surge with unknown price tag

Obama donor’s firm hired to fix Web mess it created

A tech firm linked to a campaign-donor crony of President Obama not only got the job to help build the federal health-insurance Web site — but also is getting paid to fix it.

Anthony Welters, a top campaign bundler for Obama and frequent White House guest, is the executive vice president of UnitedHealth Group, which owns the software company now at the center of the ObamaCare Web-site fiasco.

UnitedHealth Group subsidiary Quality Software Services Inc. (QSSI), which built the data hub for the ObamaCare system, has been named the new general contractor in charge of repairing the glitch-plagued HealthCare.gov.

Welters and his wife, Beatrice, have shoveled piles of cash into Obama’s campaign coffers and ­apparently reaped the rewards.

Beatrice Welters bundled donations totaling between $200,000 and $500,000 for Obama’s campaign during the 2008 election ­cycle, according to campaign- ­finance data compiled by Center for Responsive Politics.

SICK CALL: Obama bundler Anthony Welters’ firm owns the company picked to repair the health Web site.

The couple then became top donors for Obama’s inauguration festivities, kicking in $100,000 out of their own pockets and bundling another $300,000 from friends and business associates, according to the center.

The investments quickly paid off for Beatrice Welters. The Obama administration tapped her in 2009 for the plum job of US ambassador to Trinidad and Tobago, which she held through last November.

The couple have been frequent guests at the White House.

Visitors logs show at least a dozen visits between the two by the end of 2012, the most recent information available.

The entire Welters family has gotten into the donation game.

The Welters, along with their sons, Andrew and Bryant, have contributed more than $258,000 to mostly Democratic candidates and committees since 2007.

What’s more, UnitedHealth Group is one of the largest health-insurance companies in the country and spent millions lobbying for ObamaCare.

The insurance giant’s purchase of QSSI in 2012 raised eyebrows on Capitol Hill, but the tech firm nevertheless kept the job of building the data hub for the ObamaCare Web site where consumers buy the new mandatory health- ­insurance plans.

QSSI has been paid an estimated $150 million so far, but officials couldn’t say how much more the company might collect on the ­repair contract.

By all accounts, the data hub has run smoothly while many other components of the Web site have failed.

Meanwhile, tempers flared among Obama’s Democratic allies over the disastrous rollout of the president’s signature initiative.

“I’m extraordinarily frustrated,” said Sen. Jeff Merkley (D-Ore.) ­after top Obama-administration officials gave Senate Democrats a private briefing on the state of the Web-site repairs.

He said they were losing confidence the site could be quickly fixed.

“I don’t think there’s confidence by anyone in the room. This is more of a show-me moment,” said Merkley.

http://nypost.com/2013/11/01/obama-donors-firm-hired-to-fix-web-mess-it-helped-make/

Berges Lecture Series: Anthony Welters

Anthony Welters is the Executive Vice President of United Health Group, which serves more than 70 million Americans through its health and well-being companies. In January 2011, Mr. Welters was appointed a Member of the Office of the CEO.

Anthony Welters

Mr. Anthony Welters served as an Executive Vice President at Unitedhealth Group Inc. since December, 2006. Mr. Welters served as the President of Public and Senior Markets Group at UnitedHealth Group Inc. since September 2007. He served as the Chief Executive Officer of AmeriChoice Health Services, Inc. He served as Head of Public & Social Markets Group of UnitedHealth Group since August 2007. He co-founded AmeriChoice Corporation (AmeriChoice) in 1989 and served as its Chief Executive Officer and President from 1989 to December 2006. He served a number of senior positions in the federal government and in private industry. He served as an Attorney for the securities and exchange commission and an Executive Assistant of U.S. Senator Jacob Javits. He served as Director of Federal Affairs and as Assistant Vice President of corporate development of AMTRAK. He served as an Associate Deputy Secretary of the U.S. Department of Transportation. He serves as the Chairman of the Board of Morehouse School of Medicine Inc. He served as Chairman of AmeriChoice Corporation from 1989 to September 2002. He serves as Vice Chairman of New York University, Morehouse School of Medicine the NYU Hospitals Center and the Library of Congress. He serves as Vice Chairman at the Board of Trustees of the Morehouse School of Medicine in Atlanta. He serves as a Trustee of Morehouse School Of Medicine Inc., The. He has been an Independent Director of Qwest Communications International Inc. since July 25, 2006, CR Bard Inc. (formerly known as Bard C R Inc.) since February 1999, West Pharmaceutical Services, Inc. since March 1997 and AmeriChoice Corporation since 1989. He has been a Director of Loews Corporation since October 8, 2013. He serves as a Director of Horatio Alger Association, The Congressional Black Caucus foundation Inc., The An-bryce Foundation and the Wolf Trap Foundation for the Performing Arts. He serves as Council Member of the National Museum of African American History and Culture. He serves as Trustee of The John F. Kennedy Center for the Performing Arts. He serves as Trustee of the Healthcare leadership Council, New York University Law School and Medical Center and the National board of the Smithsonian Institution and is a Member of the Young President’ organization. He is a recipient of the Horatio Alger Award in recognition of his achievements and contributions to society and serves on the board of that charitable organization. Mr. Welters holds a JD from New York University of Law and a BA from Manhattanville College. He is admitted to the bars of New York and DC.

Profile

On August 13, 2013, the registrants Board of Directors elect Anthony Welters as a director of the registrant, with both such actions to become effective on October 8, 2013. Mr. Welters is Executive Vice President and a member of the Office of the CEO of UnitedHealth Group Incorporated. He is also Chairman of the Boards of the Morehouse School of Medicine and of New York University School of Law.

UnitedHealth Group Inc
Compensation for 2011
Salary $744,231
Restricted stock awards $4,500,060
All other compensation $112,118
Non-equity incentive plan compensation $2,514,600
Total Compensation $7,871,009
Options Exercised for 2011
Number of securities underlying options exercisable 19,006
Number of securities underlying options unexercisable 57,018
Shares acquired on exercise 96,562
Stock Ownership for 2012
Number of shares owned 119,908
West Pharmaceutical Services, Inc.
Director Compensation for 2011
Fees earned or paid in cash $54,000
Stock awards $110,000
All other compensation $24,261
Total Compensation $188,261
Stock Ownership for 2013
Number of shares owned 18,762
C.R. Bard, Inc.
Director Compensation for 2011
Fees earned or paid in cash $89,350
Stock awards $64,531
All other compensation $79,800
Total Compensation $233,681
Stock Ownership for 2013
Number of shares owned 2,147
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Pleasure Way — Videos

Posted on October 9, 2013. Filed under: Blogroll, Class B Camper Van, Communications, Computers, Homes, Transportation, Water, Wealth, Wisdom | Tags: , , , , |

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The Problem Is Too Much Federal Spending — Balance The Budget — Zero Growth In Government Spending For Next 10 Years! — Balanced Budget = $2.5 Trillion In Tax Revenues = $2.5 Trillion in Government Spending — Just Do It! — Videos

Posted on September 29, 2013. Filed under: American History, Banking, Blogroll, College, Communications, Constitution, Diasters, Economics, Education, Employment, Federal Government, Federal Government Budget, Fiscal Policy, Foreign Policy, government, government spending, history, History of Economic Thought, Illegal, Immigration, Inflation, Investments, IRS, Language, Law, liberty, Life, Links, Literacy, Macroeconomics, media, Monetary Policy, Money, People, Philosophy, Photos, Politics, Psychology, Public Sector, Radio, Rants, Raves, Regulations, Resources, Security, Talk Radio, Tax Policy, Taxes, Terrorism, Transportation, Unemployment, Unions, Video, War, Wealth, Wisdom | Tags: , , , |

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BUREAU OF THE FISCAL SERVICE
STAR – TREASURY FINANCIAL DATABASE
TABLE 1.  SUMMARY OF RECEIPTS, OUTLAYS AND THE DEFICIT/SURPLUS BY MONTH OF THE U.S. GOVERNMENT (IN MILLIONS)

ACCOUNTING DATE:  08/13

PERIOD                                                                     RECEIPTS                OUTLAYS    DEFICIT/SURPLUS (-)
+  ____________________________________________________________  _____________________  _____________________  _____________________
PRIOR YEAR

OCTOBER                                                                   163,072                261,539                 98,466
NOVEMBER                                                                  152,402                289,704                137,302
DECEMBER                                                                  239,963                325,930                 85,967
JANUARY                                                                   234,319                261,726                 27,407
FEBRUARY                                                                  103,413                335,090                231,677
MARCH                                                                     171,215                369,372                198,157
APRIL                                                                     318,807                259,690                -59,117
MAY                                                                       180,713                305,348                124,636
JUNE                                                                      260,177                319,919                 59,741
JULY                                                                      184,585                254,190                 69,604
AUGUST                                                                    178,860                369,393                190,533
SEPTEMBER                                                                 261,566                186,386                -75,180

YEAR-TO-DATE                                                          2,449,093              3,538,286              1,089,193

CURRENT YEAR

OCTOBER                                                                   184,316                304,311                119,995
NOVEMBER                                                                  161,730                333,841                172,112
DECEMBER                                                                  269,508                270,699                  1,191
JANUARY                                                                   272,225                269,342                 -2,883
FEBRUARY                                                                  122,815                326,354                203,539
MARCH                                                                     186,018                292,548                106,530
APRIL                                                                     406,723                293,834               -112,889
MAY                                                                       197,182                335,914                138,732
JUNE                                                                      286,627                170,126               -116,501
JULY                                                                      200,030                297,627                 97,597
AUGUST                                                                    185,370                333,293                147,923

YEAR-TO-DATE                                                          2,472,542              3,227,888                755,345
-
-
-
-
-
0REPORT ID: STM0P081
USER ID  :
DATE: 2013-09-10 TIME: 22.20.05                                                                                         PAGE   1(1)

Dan Mitchell Testifying to the Joint Economic Committee about the Debt Ceiling

It’s Simple to Balance The Budget Without Higher Taxes

Federal workers face new furloughs if government shuts down

Conservative Mark Levin on a possible government shutdown

Govt Shutdown Showdown – House Bill Would Delay Obamacare By One Year – Louie Gohmert (R)

Funding Government by the Minute

Will Taxing the Rich Fix the Deficit?

Why Not Print More Money?

Milton Friedman – Why Tax Reform Is Impossible

United States Government Shutdown Over Health Debate

29 09 2013  Syria News , The Government Shutdown to Come    WSJ Opinion

Ted Cruz: Killing Obamacare for one year is ‘the essence of a compromise’

House sends stopgap back to Senate 48 hours before shutdown

By Mike Lillis

House Republicans approved a stopgap spending bill that delays ObamaCare in  an early-morning Sunday vote that increases the chances of a government  shutdown.

The high-stakes GOP move intensifies a game of chicken with Senate Democrats  with just 48 hours to go before the lights could go out on the federal  government.

The White House threatened to veto the measure, while Senate Majority Leader  Harry Reid (D-Nev.) proclaimed it dead in the upper chamber.

The imminent deadline, combined with the prolonged impasse, has led some  lawmakers to predict a shutdown is all but inevitable.

“In candor … when the clock strikes midnight on Monday, the place is shutting  down,” Rep. Robert Andrews (N.J.), head of the Democrats’ Steering and Policy  Committee, said Saturday night.

The House added language delaying implementation of the healthcare law by a  year in a 231-192 vote, with Democratic Reps. Jim Matheson (Utah) and Mike  McIntyre (N.C.)  joining Republicans. Two Republicans voted against the  delay, Reps. Chris Gibson (N.Y.) and Richard Hanna (N.Y.).

The House also voted to eliminate a tax on medical devices in a 248-174 vote,  with 17 Democrats joining the GOP. The tax is intended to pay for some of the  law’s costs. Gibson switched his vote from no to yes toward the end of the  vote.

Under the rule adopted earlier in the day, the underlying spending bill was  deemed passed with the approval of the two amendments.

Unveiled by GOP leaders just hours earlier, the continuing resolution (CR)  would fund the government through Dec. 15. It would delay the individual  coverage mandate and the insurance exchanges which are set to launch on Tuesday  – and eliminate a 2.3 percent tax on medical devices.

Republican supporters said the ObamaCare delay is necessary to prepare a wary  public for sweeping changes that lack the underlying infrastructure to make them  work. They framed their postponement proposal as a compromise, relative to the  defunding measure they had pushed earlier in the month.

“This bill is not about whether ObamaCare is going to come in or not,” said  Rep. Dana Rohrabacher (R-Calif.). “What we’re voting on is whether or not you’ll  accept the compromise which we have reached out to offer.”

The argument didn’t sit well with Democrats, who were quick to note that the  sequester-level spending contained in the Senate-passed bill – a level anathema  to many Democrats – is the same as that of the initial House CR.

“You’ve won,” said Minority Whip Steny Hoyer (D-Md), “but you can’t take yes  for an answer.”

A separate bill, designed to ensure that military personnel are paid even if  a shutdown is not averted, was also approved in a unanimous vote.

Republicans characterized the bill as a safety net in the event Congress  can’t reach a deal. Democrats countered with charges that the proposal is  evidence that the GOP’s CR strategy is designed to shutter the government.

The CR package was designed to cater to conservative Republicans, who have  insisted that any spending package must scale back ObamaCare. Those  conservatives had revolted earlier in the month when Speaker John Boehner  (R-Ohio) tried to move a funding bill without that direct link.

The resistance forced GOP leaders to approve a CR last week that would have  defunded the healthcare law – language that was stripped by Senate Democrats  Friday, putting the ball back in Boehner’s court.

At a closely watched meeting of the GOP conference Saturday afternoon in the  Capitol basement, Boehner outlined his hard-line strategy, leading to cheers  from a conference that’s often been wary of his conservative credentials.

“This is exactly what we hoped for so we’re all getting behind leadership,”  said Rep. Michele Bachmann (R-Minn.), a Tea Party favorite. “We’re excited [and]  we’re united.”

The bill now moves back to the Senate, where Reid is expected to scrap the  two healthcare amendments with a single vote on Monday, when the Senate returns,  and return the “clean” CR, yet again, to Boehner and House Republicans.

“To be absolutely clear, the Senate will reject both the one-year delay of  the Affordable Care Act and the repeal of the medical device tax,” Reid said in  a statement. “After weeks of futile political games from Republicans, we are  still at square one: Republicans must decide whether to pass the Senate’s clean  CR, or force a Republican government shutdown.”

That move could potentially come just hours before the Tuesday shutdown.

“ObamaCare is based on limitless government, bureaucratic arrogance, and a  disregard of the will of the people,” said Rep. Marlin Stutzman (R-Ind.).

The 17 Democrats who voted to eliminate the medical device tax were McIntyre,  Matheson, Ron Barber (Ariz.), Tammy Duckworth (Ill.), John Barrow (Ga.), Dan  Maffei (N.Y.), Patrick Murphy (Fla.), Cheri Bustos (Ill.), John Delaney (Md.),  William Enyart (Ill.), Sean Maloney (N.Y.), Jerry McNerney (Calif.), Bill Owens  (N.Y.), Scott Peters (Calif.), Nick Rahall (W.Va.), Bradley Schneider (Ill.) and  Kyrsten Sinema (Ariz.).

Rep. Elijah Cummings (Md.), the top Democrat on the House Oversight  Committee, said in a statement early Sunday that Republicans “failed the  American people.”

“They voted to shut down the government, all because of their obsession with  taking away health insurance for millions of people and giving back to insurance  companies the power to decide who gets what care. In their blind pursuit of  ideology over our nation’s best interests, Republicans are hurting our economy,  threatening job creation, and leaving families with less security and  stability,” Cummings said.

Read more: http://thehill.com/homenews/house/325331-house-sends-stopgap-back-before-senate-48-hours-to-shutdown#ixzz2gJOLOkn2 Follow us: @thehill on Twitter | TheHill on Facebook

U.S. government shutdowns have long history

OK, gridlocked politicians we’re used to. But why padlock the Statue of Liberty? You don’t see other democracies shuttering landmarks and sending civil servants home just because their political parties can’t get along. Belgian civil servants, for example, carried on nicely for a year and a half while their politicians bickered over forming a new government.

The potential for a partial shutdown Tuesday is a quirk of American history. So if you’re bored with blaming House Republicans or President Barack Obama, you can lay some responsibility on the Founding Fathers.

Or blame President Jimmy Carter for his rectitude. Or ex-House Speaker Newt Gingrich for his hissy fit over how he got off Air Force One.

A history of government shutdowns, American-style:

1789: Balance of powers.

The framers of the Constitution gave Congress control over spending as a way to limit the power of the presidency. The government can only spend money “in consequence of appropriations made by law,” or in other words, after Congress says so and with the president’s signature.

1800s: Power struggles.

Turns out it’s not easy to shoo federal bureaucrats away from the piggy bank.

When they wanted to spend more than Congress gave, the War Department and other agencies ordered stuff on credit. Then they would go to Congress seeking an appropriation to pay the bills. Lawmakers felt obliged to cover the government’s debts, but they weren’t happy about it. The executive branch was undermining Congress’s power of the purse.

Congress responded with a series of laws that eventually got one of those dreadful Washington monikers: the Anti-Deficiency Act.

Because of the act, officials who mistakenly spend money Congress hasn’t OK’d face disciplinary action, ranging from firing to hours stuck in mind-numbing budget training. There are exceptions for spending to protect lives or property.

But willful overspending is a crime that carries the threat of fines and two years in prison.

1900s: A delicate balance.

The Anti-Deficiency Act seems clear. But as usual, Congress sent mixed messages. Lawmakers routinely failed to pass most of each year’s dozen or so appropriations bills on time. Sometimes agencies went a full year without a budget. Usually lawmakers would smooth that over with a short-term money approval, called a “continuing resolution” in Washington-speak.

Sometimes Congress couldn’t even agree on those: Stopgap resolutions got tangled up for days or a couple of weeks in political fights over matters such as abortion, foreign aid or congressional pay raises. Sort of like the current fight over health care.

But government agencies didn’t shut down and Cabinet secretaries weren’t led away in handcuffs. Agency chiefs might delay workers’ pay and put items such as travel and new contracts on hold. But they assumed Congress didn’t want them to turn off the lights and go home. Eventually lawmakers would cough up a spending bill to retroactively paper over the funding gap.

1980: An inconvenient truth.

This look-the-other-way system worked for decades. Until the Carter administration.

A stickler for the rules, Carter asked his attorney general to look into the Anti-Deficiency Act. In April 1980, Attorney General Benjamin Civiletti issued a startling opinion. “The legal authority for continued operations either exists or it does not,” he wrote.

When it does not, government must send employees home. They can’t work for free or with the expectation that they will be paid someday. What’s more, Civiletti declared, any agency chief who broke that law would be prosecuted.

Five days later, funding for the Federal Trade Commission expired amid a congressional disagreement over limiting the agency’s powers. The FTC halted operations, canceled court dates and meetings, and sent 1,600 workers packing, apparently the first agency ever closed by a budget dispute.

Embarrassed lawmakers made a quick fix. The FTC reopened the next day. The estimated cost of the brouhaha: $700,000.

Carter, a Democratic president forever stymied by his own party in Congress, ordered the whole government to be ready to shut down when the budget year ended on Oct. 1, 1980, in case lawmakers missed their deadline for appropriations bills.

A report by what’s now the Government Accountability Office captured federal officials’ dismay: “That the federal government would shut its doors was, they said, incomprehensible, inconceivable, unthinkable.”

It almost happened. Funding for many agencies did expire, but just for a few hours, and nobody was sent home.

Near the end of his term, Civiletti further clarified the law’s meaning. In a government-wide shutdown, the military, air traffic control, prisons and other work that protects human safety or property would continue. So would things such as Social Security benefits, which Congress has financed indefinitely.

1981-1990: Playing chicken.

With the threat of shutdown as a weapon, budget fights would never be the same, and a big one was brewing.

Republican Ronald Reagan moved into the White House in January 1981 with a promise to cut taxes and shrink government, setting up a showdown with Democrats who ran the House.

High noon came early on Monday, Nov. 23, 1981.

The government had technically been without money all weekend, but Congress approved emergency spending to keep it running. That morning, Reagan wielded his first veto. He was making a stand against “budget-busting policies,” the president declared, sending confused federal workers streaming out of offices in Washington and across the nation.

It was the first government shutdown. But it lasted only hours. By that afternoon, Congress approved a three-week spending extension more to Reagan’s liking. Workers returned Tuesday morning. The estimated cost: more than $80 million.

The pattern was set. Over his two terms, Reagan and congressional Democrats would regularly argue to the brink of shutdown, and twice more they sent workers home for a half-day.

President George H.W. Bush used the tactic only once, during the budget wrangling that punctured his “no new taxes” pledge.

That partial shutdown over the 1990 Columbus Day weekend mostly served to miff tourists who found national park visitor centers locked and Smithsonian museums closed.

Shutdown threats were becoming ho-hum, just more Washington games. After all, what politician would relish a full body plunge into the “unthinkable”?

1995-96: The real thing.

Cue President Bill Clinton and Gingrich.

Two big men with big ideas and big-time egos, the Democratic president and the Republican House speaker charged into a cage match and ended up wrestling the U.S. government to the ground. Twice.

These two shutdowns, for six days and 21 days, were the longest ever. Until now they were assumed to have taught politicians the folly of ever again powering down the world’s most powerful government. Maybe not.

Serious issues were at stake in 1995 — the future of Medicare, tax cuts, aid for the poor, the budget deficit. But they got lost in the absurdities:

The shutdowns didn’t save money; they cost millions.

Despite all the buildup, most of government didn’t close, because of complexities of the federal budget and exemptions for essential workers.

Still, the first shutdown resulted in 800,000 workers eventually getting paid for staying home.

Despite public disgust, Clinton and the Republicans failed to settle all their disputes and soon idled 280,000 employees for another three weeks, through Christmas and into the New Year.

The effects rippled through the economy, harming federal contractors and businesses that serve visitors to national parks and industries that must work with federal inspectors.

The tone of the whole exercise was set when a huffy Gingrich suggested he had steered the government to a standstill because Clinton relegated him to the back door of Air Force One on an overseas trip. The public tantrum delighted Democrats and cartoonists alike.

The president was judged to have “won” the tussle. Republicans took a drubbing in the polls and ended up accepting most of Clinton’s conditions in a compromise that seemed more like crying uncle.

But faith in government may have been the biggest loser.

A footnote: On the January day that missing workers were scheduled to finally return to their posts, the Northeast was just starting to dig out from an extreme blizzard.

After weeks of insisting it was vital to get government back to work quickly, Clinton decided to keep Washington closed another four days.

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Russia’s Main Concern in Syria — Tartus Naval Base

Posted on September 10, 2013. Filed under: American History, Ammunition, Blogroll, Communications, Constitution, Crime, Economics, European History, Federal Government, Foreign Policy, government, government spending, history, Investments, Islam, Islam, Law, liberty, Life, Links, People, Philosophy, Photos, Pistols, Politics, Rants, Raves, Regulations, Religion, Rifles, Talk Radio, Terrorism, Transportation, Video, War, Wealth, Weapons, Wisdom | Tags: , , , , , , , |

 

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Cyprus Base

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Russia sends Warships to Syria WW3 looming Syria Russia Ships ‘Bound For Mediterranean’

 

September 2013 Russia said very concerned USA may respond militarily

 

Russia Builds Up Naval Presence Off Syria

Russia expands its naval presence near a key base in Syria in a build-up that U.S. and European officials say appears aimed at deterring intervention in the country’s increasingly bloody civil war.

 

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Be Careful: Russia is Back to Stay in the Middle East – Guest Post

Be Careful: Russia is Back to Stay in the Middle East

Russia is back. President Vladimir Putin wants the world to acknowledge that Russia remains a global power. He is making his stand in Syria.

The Soviet Union acquired the Tardus Naval Port in Syria in 1971 without any real purpose for it. With their ships welcomed in Algeria, Cuba or Vietnam, Tardus was too insignificant to be developed. After the collapse of the Soviet Union, Russia lacked the funds to spend on the base and no reason to invest in it.

The Russian return to the Middle East brought them first to where the Soviet Union had its closest ties. Libya had been a major buyer of arms and many of the military officers had studied in the Soviet Union. Russia was no longer a global power, but it could be used by the Libyans as a counter force to block domination by the United States and Europeans.

When Gaddafi fell, Tardus became Russia’s only presence in the region. That and the discovery of vast gas deposits just offshore have transformed the once insignificant port into a strategic necessity.

Earlier at the United Nations, Russia had failed to realize that Security Council Resolution 1973 that was to implement a new policy of “responsibility to protect” cloaked a hidden agenda. It was to be turned from a no-fly zone into a free-fire zone for NATO. That strategic blunder of not vetoing the resolution led to the destruction of Gaddafi’s regime and cost Russia construction contracts and its investments in Libyan gas and oil to the tune of 10 billion dollars.

That was one more in a series of humiliating defeats; and something that Putin will not allow to happen again while he is president. Since his time as an officer in the KGB, he has seen the Soviet Empire lose half of its population, a quarter of its land mass, and most of its global influence. He has described the collapse of the Soviet Union as a “geopolitical catastrophe.”

In spite of all of the pressure from Washington and elsewhere to have him persuade Bashar Al-Assad to relinquish power, Putin is staying loyal to the isolated regime. He is calculating that Russia can afford to lose among the Arabs what little prestige that it has remaining and gain a major political and economic advantage in Southern Europe and in the Eastern Mediterranean.

What Russia lost through the anti-Al-Assad alliance was the possibility to control the natural gas market across Europe and the means to shape events on the continent. In July 2011, Iran, Iraq, and Syria agreed to build a gas pipeline from the South Pars gas field in Iran to Lebanon and across the Mediterranean to Europe. The pipeline that would have been managed by Gazprom would have carried 110 million cubic meters of gas. About a quarter of the gas would be consumed by the transit countries, leaving seventy or so million cubic meters to be sold to Europe.

Violence in Iraq and the Syrian civil war has ended any hope that the pipeline will be built, but not all hope is lost. One possibility is for Al-Assad to withdraw to the traditional Aliwite coastal enclave to begin the partitioning of Syria into three or more separate zones, Aliwite, Kurdish, and Sunni. Al-Assad’s grandfather in 1936 had asked the French administrators of the Syrian mandate to create a separate Aliwite territory in order to avoid just this type of ethnic violence.

What the French would not do circumstance may force the grandson to accept as his only choice to survive. His one hundred thousand heavily armed troops would be able to defend the enclave.

The four or five million Aliwites, Christians, and Druze would have agricultural land, water, a deep water port and an international airport. Very importantly, they would have the still undeveloped natural gas offshore fields that extend from Israel, Lebanon, and Cyprus. The Aliwite Republic could be energy self-sufficient and even an exporter. Of course, Russia’s Gazprom in which Putin has a vital interest would get a privileged position in the development of the resource.

In an last effort to bring the nearly two year long civil war to an end, Russia’s foreign minister Sergei Lavrov urged Syrian president Bashar al-Assad at the end of December to start talks with the Syrian opposition in line with the agreements for a cease fire that was reached in Geneva on 30 June. The Russians have also extended the invitation to the Syrian opposition National Coalition head, Ahmed Moaz al-Khatib. The National Coalition refuses to negotiate with Al-Assad and Al-Assad will not relinquish power voluntarily.

The hardened positions of both sides leaves little hope for a negotiated settlement; and foreign minister Sergei Lavrov has made it clear that only by an agreement among the Syrians will Russia accept the removal of Al-Assad. Neither do they see a settlement through a battlefield victory which leaves only a partitioning that will allow the civil war to just wind down as all sides are exhausted.

The Russians are troubled by what they see as a growing trend among the Western Powers to remove disapproved administrations in other sovereign countries and a program to isolate Russia. They saw the U.S involvement in the Ukraine and Georgia. There was the separation of Kosovo from Serbia over Russian objections. There was the extending of NATO to the Baltic States after pledging not to expand the organization to Russia’s frontier.

Again, Russia is seeing Washington’s hand in Syria in the conflict with Iran. The United States is directing military operations in Syria with Turkey, Qatar, and Saudi Arabia at a control center in Adana about 60 miles from the Syrian border, which is also home to the American air base in Incirlik. The Program by President Obama to have the CIA acquire heavy weapons at a facility in Benghazi to be sent to Turkey and onward to Syria is the newest challenge that Putin cannot allow to go unanswered. It was the involvement of Ambassador Chris Stevens in the arms trade that may have contributed to his murder; and the Russians are not hesitating to remind the United States and Europeans that their dealings with the various Moslem extremists is a very dangerous game.

The Russians are backing their determination to block another regime change by positioning and manning an advanced air defense system in what is becoming the Middle East casino. Putin is betting that NATO will not risk in Syria the cost that an air operation similar to what was employed over Libya will impose. Just in case Russia’s determination is disregarded and Putin’s bluff is called, Surface to surface Iskander missiles have been positioned along the Jordanian and Turkish frontiers. They are aimed at a base in Jordan operated by the United States to train rebels and at Patriot Missile sites and other military facilities in Turkey.

Putin is certain that he is holding the winning hand in this very high stakes poker game. An offshore naval task force, the presence of Russian air defense forces, an electronic intelligence center in latakia, and the port facilities at Tardus will guarantee the independence of the enclave. As the supplier of sixty percent of Turkey’s natural gas, Moscow does have leverage that Ankara will not be able to ignore; and Ankara well knows that gas is one of Putin’s diplomatic weapons.

When the Turks and U.S see that there is little chance of removing Al-Assad, they will have no option other than to negotiate a settlement with him; and that would involve Russia as the protector and the mediator. That would establish Russia’s revived standing as a Mediterranean power; and Putin could declare confidently that “Russia is back.” After that, the Russians will be free to focus upon their real interests in the region.

And what is Russia’s real interest? Of course, it is oil and gas and the power that control of them can bring.

Source: http://oilprice.com/Geopolitics/International/Be-Careful-Russia-is-Back-to-Stay-in-the-Middle-East.html

 

Tartus

Tartus is the second largest port city on the Syrian coast (after Latakia) and the largest city in Tartus Governorate with an estimated population of 118,000 inhabitants as of 2004.[1] The majority of the population is ethnic Levantine Arab. However, there are about 3,000 people of Greek origin who reside mainly in the town of Al Hamidiyah just south of Tartus.[2] Since the start of the Iraqi War, a few thousands Iraqi nationals now reside in Tartus.

tartus The History of Tartus goes back to the 2nd millennium BC when it was founded as a Phoenician colony of Aradus.[5] The colony was known as Antaradus (from Greek Anti-Arados → Antarados , Anti-Aradus, meaning The town facing Arwad ). Not much remains of the Phoenician Antaradus, the mainland settlement that was linked to the more important and larger settlements of Aradus, off the shore of Tartus, and the nearby site of Amrit.[6]

tartus On September 22, 2008, Russian Navy spokesman Igor Dygalo said the nuclear-powered battlecruiser Peter The Great, accompanied by three other ships, sailed from the Northern Fleet’s base of Severomorsk. The ships will cover about 15,000n nautical miles (28,000 km) to conduct joint maneuvers with the Venezuelan navy. Dygalo refused to comment on Monday’s report in the daily Izvestia claiming that the ships were to make a stopover in the Syrian port of Tartus on their way to Venezuela. Russian officials said the Soviet-era base there was being renovated to serve as a foothold for a permanent Russian navy presence in the Mediterranean.[14]

tartus The historic centre of Tartus consists of more recent buildings built on and inside the walls of the Crusader-era Templar fortress, whose moat still separates this old town from the modern city on its northern and eastern sides. Outside the fortress few historic remains can be seen, with the exception of the former cathedral of Notre-Dame of Tartus (Our Lady of Tortosa), from the 12th century. The church is now the site of a museum. Former President Hafez Assad and his predominantly Islamic administration had promised to return the site to the Christians as a symbol of deep Christianity in Syria, however he died before this promise was executed. Assad’s son, President Bashar Assad, has claimed to honor his father’s promise.

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People Peace Doves vs. Politician War Hawks– Bye Bye Birdie — Obama’s Secret Sincere Syria Weapon? — War, Eve of Destruction, Where Have All The Flowers Gone? — Videos

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Obama’s Syria War Is Really About Iran and Israel

Bob Dreyfuss

The dirty little not-so-secret behind President Obama’s much-lobbied-for, illegal and strategically incompetent war against Syria is that it’s not about Syria at all. It’s about Iran—and Israel. And it has been from the start.

By “the start,” I mean 2011, when the Obama administration gradually became convinced that it could deal Iran a mortal blow by toppling President Bashar al-Assad of Syria, a secular, Baathist strongman who is, despite all, an ally of Iran’s. Since then, taking Iran down a peg has been the driving force behind Obama’s Syria policy.

Not coincidentally, the White House plans to scare members of Congress into supporting the ill-conceived war plan by waving the Iranian flag in their faces. Even liberal Democrats, some of whom are opposing or questioning war with Syria, blanch at the prospect of opposing Obama and the Israel lobby over Iran.

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Item for consideration: a new column by the Syria analyst at the Washington Institute for Near East Policy, the chief think tank of the Israel lobby. Andrew Tabler headlines his piece: “Attacking Syria Is the Best Way to Deal with Iran.” In it, he says:

At first glance, the festering Syria crisis seems bad news for diplomatic efforts to keep Iran from developing nuclear capabilities. In actuality, however, achieving U.S. objectives in the Syria crisis is an opportunity to pressure Iran into making hard choices not only in Syria, but regarding its nuclear program as well. More U.S. involvement to achieve its objectives in Syria will inevitably run counter to Tehran’s interests, be it to punish the Assad regime for chemical weapons use or to show support for the Syrian opposition in changing Assad’s calculus and forcing him to “step aside” at the negotiating table or on the battlefield.

Many in U.S. policymaking circles have viewed containing swelling Iranian influence in Syria and preventing Iran from going nuclear as two distinct policy discussions, as the Obama Administration only has so much “bandwidth” to deal with Middle East threats. But the recent deepening of cooperation between Tehran, Hezbollah and the Assad regime, combined with their public acknowledgement of these activities, indicates that they themselves see these activities as furthering the efficacy of the “resistance axis.”

Like every alliance, its members will only make hard policy choices if the costs of its current policies far outweigh the benefits. U.S. strikes on the Assad regime, if properly calibrated as part of an overall plan to degrade the regime, would force Tehran to become more involved in Syria in order to rescue its stalwart ally. This would be costly for Iran financially, militarily and politically. Those costs would make the Iranian regime and its people reassess aspirations to go nuclear.

Needless to say, such a strategy is bound to be counterproductive, since—by slamming Syria, never mind toppling Assad—Washington is likely to undermine doves and bolster hawks in Tehran and undermine the chances for successful negotiations with Iran’s new president, Hassan Rouhani, who’ll be speaking at the UN General Assembly later this month.

In fact, both Russia and Iran have signaled recently, in the wake of Syria’s obvious deployment and use of sarin gas and other deadly weapons that they might be getting ready to join the rest of the world in condemning Syria’s chemical warfare, and that makes it far more likely that the much-postponed US-Russia “Geneva II” peace conference on Syria might work. The hawkish Washington Post today notes Rouhani’s new administration in Tehran is softening its tone on Syria, and it reports that the new Iranian foreign minister, Javad Zarif, has acknowledged the Syria has erred, saying: “We believe that the government in Syria has made grave mistakes that have, unfortunately, paved the way for the situation in the country to be abused.”

Meanwhile, Russia’s President Vladimir Putin, while issuing scathing denunciations of the coming U.S. attack on Syria, has dropped broad hints that he might be willing to join with other nations if and when the United Nations weapons team concludes that Assad used nerve gas, suggesting that Russia might not block a UN Security Council resolution against Syria. In his much-reported interview with the Associated Press, Putin insisted on waiting for the UN report:

“If there is evidence that chemical weapons have been used, and used specifically by the regular army, this evidence should be submitted to the U.N. Security Council. And it ought to be convincing. It shouldn’t be based on some rumors and information obtained by intelligence agencies through some kind of eavesdropping, some conversations and things like that.”

Then, according to the Washington Post, Putin declared that he might join a UN-sponsored coalition on Syria:

He said he “doesn’t exclude” backing the use of force against Syria at the United Nations if there is objective evidence proving that Assad’s regime used chemical weapons against its people. But he strongly warned Washington against launching military action without U.N. approval, saying it would represent an aggression. Russia can veto resolutions at the U.N. Security Council and has protected Syria from punitive actions there before.

But a change in tone on the part of Russia and Iran—the latter of whom the Obama administration still refuses to invite to Geneva II if and when it occurs—won’t mean a thing if the object of war with Syria is to send a message to Iran. As Jeffrey Goldberg, writing for Bloomberg, says, for Israel it’s all about Iran:

Prime Minister Benjamin Netanyahu of Israel would prefer that Obama enforce his red line on chemical weapons use, because he would like to see proof that Obama believes in the red lines he draws. From Netanyahu’s perspective, Israel isn’t unduly threatened by Assad. Syria constitutes a dangerous, but ultimately manageable, threat.

Netanyahu believes, of course, that Iran, Syria’s primary sponsor, poses an existential threat to his country, and so would like the Iranians to understand very clearly that Obama’s red lines are, in fact, very red. As Robert Satloff, the executive director of the Washington Institute for Near East Policy, told me last night, the formula is simple: “If the Iranians do not fear Obama, then the Israelis will lose confidence in Obama.”

In his round-robin television appearances on Sunday, Secretary of State John Kerry—now the administration’s über-hawk—repeatedly said that bombing Syria would send a message to Iran. As he told Fox News on Sunday:

“The fact is that if we act and if we act in concert, then Iran will know that this nation is capable of speaking with one voice on something like this, and that has serious, profound implications, I think, with respect to the potential of a confrontation over their nuclear program. That is one of the things that is at stake here.”

http://www.thenation.com/blog/176040/obamas-syria-war-really-about-iran-and-israel#

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Posted on September 3, 2013. Filed under: American History, Blogroll, Bomb, College, Communications, Diasters, Economics, Education, Employment, Federal Government, Foreign Policy, Genocide, government, government spending, history, Islam, Islam, Law, liberty, Life, Links, media, People, Philosophy, Politics, Rants, Raves, Religion, Science, Security, Shite, Sunni, Talk Radio, Terrorism, Transportation, Video, War, Wealth, Weapons, Weapons of Mass Destruction, Wisdom | Tags: , , , , , |

Syrian-Rebels-Canister

Syrian “rebels” are firing chemical weapons.

Published on Aug 26, 2013

FSA or SAA?
FSA or SAA?
FSA or SAA?
Syrian “rebels” are firing chemical weapons.
Syrian “rebels” are firing chemical weapons.
Syrian “rebels” are firing chemical weapons.

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Syria Rebels testing Tekkim chemicals to use as chem weapons

Published on Dec 5, 2012

This video appeared on YouTube yesterday showing what appears to be a rebel group in Syria testing a chemical combination to be used as a chemical weapon (most likely nerve agents as judged by the reaction of lab rabbits in the video) and threatening to use this chem weapon against civilians in Syria on a sectarian basis.

Non-Arabic speakers: Please click the captions button.

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CHEMICAL WEAPONS: US Armed FSA Syrian Rebels Use SARIN NERVE GAS!

Published on May 11, 2013

CHEMICAL WEAPONS: US Armed FSA Syrian Rebels Use SARIN NERVE GAS!

The US Defense Secretary says the old order in the Middle East is disappearing, although it’s still not clear what will replace it. Chuck Hagel stressed the conflict in Syria is becoming increasingly more sectarian and extremist, with the country’s collapse now more real than ever. But, while some US lawmakers make fresh calls for military intervention, Washington’s taken a backseat.

GENEVA — U.N. human rights investigators have gathered testimony from casualties of Syria’s civil war and medical staff indicating that rebel forces have used the nerve agent sarin, one of the lead investigators said on Sunday.

The United Nations independent commission of inquiry on Syria has not yet seen evidence of government forces having used chemical weapons, which are banned under international law, said commission member Carla Del Ponte.

“Our investigators have been in neighboring countries interviewing victims, doctors and field hospitals and, according to their report of last week which I have seen, there are strong, concrete suspicions but not yet incontrovertible proof of the use of sarin gas, from the way the victims were treated,” Del Ponte said in an interview with Swiss-Italian television.

“This was use on the part of the opposition, the rebels, not by the government authorities,” she added.

Del Ponte, a former Swiss attorney-general who also served as prosecutor of the International Criminal Tribunal for the former Yugoslavia, gave no details as to when or where sarin may have been used.

The Geneva-based inquiry into war crimes and other human rights violations is separate from an investigation of the alleged use of chemical weapons in Syria instigated by U.N. Secretary-General Ban Ki-moon, which has since stalled.

President Bashar al-Assad’s government and the rebels accuse each another of carrying out three chemical weapon attacks, one near Aleppo and another near Damascus, both in March, and another in Homs in December.

The civil war began with anti-government protests in March 2011. The conflict has now claimed an estimated 70,000 lives and forced 1.2 million Syrian refugees to flee.

The United States has said it has “varying degrees of confidence” that sarin has been used by Syria’s government on its people.

President Barack Obama last year declared that the use or deployment of chemical weapons by Assad would cross a “red line”.

UN has testimony showing Syrian rebels used sarin gas

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Yes, the Syrian Rebels DO Have Access to Chemical Weapons

Washington’s Blog
Sept 2, 2013

One of the U.S. government’s main justifications for its claim that the Syrian government carried out a chemical weapons attack is that the rebels don’t have chemical weapons.

However, multiple lines of evidence show that the rebels do have chemical weapons.

Potential Looting of Syrian Weapons

The Washington Post noted last December:

U.S. officials are increasingly worried that Syria’s weapons of mass destruction could fall into the hands of Islamist extremists, rogue generals or other uncontrollable factions.

Last week, fighters from a group that the Obama administration has branded aterrorist organization were among rebels who seized the Sheik Suleiman military base near Aleppo, where research on chemical weapons had been conducted. Rebels are also closing in on another base near Aleppo, known as Safirah, which has served as a major production center for such munitions, according to U.S. officials and analysts.

***

A former Syrian general who once led the army’s chemical weapons training program said that the main storage sites for mustard gas and nerve agents are supposed to be guarded by thousands of Syrian troops but that they would be easily overrun.

The sites are not secure, retired Maj. Gen. Adnan Silou, who defected to the opposition in June, said in an interview near Turkey’s border with Syria. “Probablyanyone from the Free Syrian Army or any Islamic extremist group could take them over,” he said.

***

As the Syrian opposition steadily makes territorial gains, U.S. officials and analysts said the odds are increasing that insurgents will seize control of a chemical weapons site or that Syrian troops guarding the installations will simply abandon their posts.

It’s almost inevitable,” [Michael Eisenstadt, a retired Army officer who directs the military and security studies program at the Washington Institute for Near East Policy] said. “It may have already happened, for what we know.”

***

Last week, the Syrian Foreign Ministry said the al-Nusra Front — an anti-Assad group that has been labeled a terrorist organization by the United States and is also known as Jabhat al-Nusra — had seized a chlorine factory near the town of Safirah, east of Aleppo. “Terrorist groups may resort to using chemical weapons against the Syrian people,” the ministry cautioned.

AP reports:

Questions remaining about who actually controls some of Syria’s chemical weapons stores ….

A report by the Office of the Director for National Intelligence outlining that evidence against Syria includes a few key caveats — including acknowledging that the U.S. intelligence community no longer has the certainty it did six months ago of where the regime’s chemical weapons are stored ….

U.S. and allied spies have lost track of who controls some of the country’s chemical weapons supplies, according to the two intelligence officials and two other U.S. officials.

***

U.S. analysts … are also not certain that when they saw what looked like Assad’s forces moving chemical supplies, those forces were able to remove everything before rebels took over an area where weapons had been stored.

AP hit the nail on the head when it wrote:

U.S. intelligence officials are not so certain that the suspected chemical attack was carried out on Assad’s orders, or even completely sure it was carried out by government forces, the officials said.

***

Another possibility that officials would hope to rule out: that stocks had fallen out of the government’s control and were deployed by rebels in a callous and calculated attempt to draw the West into the war.

Looting of Libyan Chemical Weapons

Fox News reported in 2011:

In August, Fox News interviewed Rep. Mike Rogers, R.-Mich., who said he saw a chemical weapon stockpile in the country during a 2004 trip. At the time, he said the U.S. was concerned about “thousands of pounds of very active mustard gas.”

He also said there is some sarin gas that is unaccounted for.

The Wall Street Journal noted in 2011:

Spread across the desert here off the Sirte-Waddan road sits one of the biggest threats to Western hopes for Libya: a massive, unguarded weapons depot that is being pillaged daily by anti-Gadhafi military units, hired work crews and any enterprising individual who has the right vehicle and chooses to make the trip.

In one of dozens of warehouses the size of a single-family home, Soviet-era guided missiles remain wrapped inside crates stacked to the 15-foot ceiling. In another, dusted with sand, are dozens of sealed cases labeled “warhead.” Artillery rounds designed to carry chemical weapons are stashed in the back of another. Rockets, antitank grenades and projectiles of all calibers are piled so high they defy counting….

Convoys of armed groups from all over Libya have made the trek here and piled looted weapons into trailer trucks, dump trucks, buses and even empty meat trucks….

The highly-regarded NTI reported the same year:

In the desert near Sirte, there was no security for dozens of small armories at the complex, where weapons are removed every day by opposition fighters, paid contractors and others. In one structure, the word “warhead” was stamped on dozens of sealed containers. At another depot, empty chemical agent munitions were found.

There is at present no viable Libyan government-sanctioned force with the capacity to keep freelancer fighters from taking what they please from the warehouses, according to the Journal.

***

U.S. Senator John McCain (R-Ariz.) visited the Libyan capital, where he said gaining control over the country’s armories was a “very big topic.”

“We have a game plan to secure the weapon caches, particularly biological and chemical weapons,” McCain said.

The Telegraph reported last year:

Al Qaeda terrorists in North Africa could be in possession of chemical weapons, a leading Spanish intelligence officer said on Monday.

The head of National Police counter-terrorist intelligence, Commissioner-General Enrique Baron, told a strategic security conference in Barcelona that it was believed that the self-styled Al Qaeda of the Islamic Maghreb – AQMI – could have acquired such arms in Libya or elsewhere during the Arab Spring last year.

***

Commissioner Baron told his audience: “The Al Qaeda of the Islamic Maghreb has acquired and used very powerful conventional arms and probably also has non-conventional arms, basically chemical, as a result of the loss of control of arsenals.”

The most likely place where this could have happened was in Libya during the uprising which overthrew the Gaddafi regime, said Commissioner Baron.

In his position as the head of Spanish National Police intelligence the Commissioner-General works closely with MI6, the CIA and other Western European intelligence services.

Remember, the head of the Libyan rebels admitted that the rebels were largely Al Qaeda.  CNN, theTelegraph,  the Washington Times, and many other mainstream sources confirm that Al Qaeda terrorists from Libya have since flooded into Syria to fight the Assad regime … bringing their arms with them.  And the post-Gaddafi Libyan government is also itself a top funder and arms supplier of the Syrian opposition.  (CNN notes that the CIA may have had a hand in this operation.)

Other Countries

A reporter who has written extensively for Associated PressBBC and National Public Radio reports thatlocals in the area hit by chemical weapons allege that Saudi Arabia supplied the chemicals. And see this.

Bush administration official Colonel Lawrence Wilkerson and British MP George Galloway speculate that Israel or another country may have given chemical weapons to the Syrian rebels.

We don’t know which countries did or didn’t give chemical weapons to the rebels. The point is that there are quite a few opportunities or possibilities.

Evidence of Possession and Use

The above, of course, is simply speculation.  More important is actual evidence of possession and use.

Turkish state newspaper Zaman reported earlier this year (Google translation):

The Turkish General Directorate of Security … seized 2 kg of sarin gas in the city of Adana in the early hours of yesterday morning. The chemical weapons were in the possession of Al Nusra terrorists believed to have been heading for Syria.

Haaretz reported on March 24th, “Jihadists, not Assad, apparently behind reported chemical attack in Syria“.

UN investigator Carla Del Ponte said that there is strong evidence that the rebels used chemical weapons, but that there is not evidence that the government used such weapons.

http://www.infowars.com/yes-the-syrian-rebels-do-have-access-to-chemical-weapons/

Russia Claims Syrian Rebels Used Chemical Weapons

By PETER JAMES SPIELMANN and EDITH M. LEDERER

UNITED NATIONS — Russia’s U.N. ambassador said Tuesday that Russian experts determined that Syrian rebels made sarin nerve gas and used it in a deadly chemical weapon attack outside Aleppo in March.

Ambassador Vitaly Churkin blamed opposition fighters for the March 19 attack in the government-controlled Aleppo suburb of Khan al-Assal, which he said killed 26 people, including 16 military personnel, and injured 86 others.

The rebels have blamed the government for the attack. The U.S. Britain and France have said they have seen no evidence to indicate that the opposition has acquired or used chemical weapons.

In Washington, White House spokesman Jay Carney said “We have yet to see any evidence that backs up the assertion that anybody besides the Syrian government has had the ability to use chemical weapons or has used chemical weapons.”

Churkin told reporters after delivering an 80-page report to Secretary-General Ban Ki-moon that the Assad regime asked Russia, its closest ally, to investigate the attack after a U.N. team of chemical weapons experts was unable to enter the country in a dispute over the probe’s scope.

Acting U.S. Ambassador Rosemary DiCarlo said Syrian President Bashar Assad should now allow U.N. chemical weapons experts into the country to conduct an investigation of the Khan al-Assal incident as well as other allegations of chemical weapons use by the U.S., U.K., and France.

The samples taken from the impact site of the gas-laden projectile were analyzed at a Russian laboratory certified by the Organization for the Prohibition of Chemical Weapons, Churkin said.

He said the analysis showed that the unguided Basha’ir-3 rocket that hit Khan al-Assal was not a military-standard chemical weapon.

Churkin said the results indicate it “was not industrially manufactured and was filled with sarin.” He said the samples indicated the sarin and the projectile were produced in makeshift “cottage industry” conditions, and the projectile “is not a standard one for chemical use.”

The absence of chemical stabilizers, which are needed for long-term storage and later use, indicated its “possibly recent production,” Churkin said.

“Therefore, there is every reason to believe that it was the armed opposition fighters who used the chemical weapons in Khan al-Assal,” Churkin said.

“According to information at our disposal,” he added, “the production of `Basha’ir 3′ unguided projectiles was started in February 2013 by the so-called `Basha’ir al-Nasr’ brigade affiliated with the Free Syrian Army.”

On Monday, Syria invited Ake Sellstrom, head of the U.N. fact-finding mission on allegations of chemical weapons use in Syria, and U.N. disarmament chief Angela Kane to visit Damascus for foreign-minister level talks on conducting a probe of just the Khan al-Assal attack.

The Russian ambassador strongly backed the idea, calling it “a promising process” that hopefully will lead to an investigation.

Britain, France and the United States have provided the secretary-general with information on other alleged chemical weapons attacks in Syria. Ban has repeatedly said he wants a broader investigation than just Khan al-Assal.

“We support a thorough investigation of all credible allegations,” Churkin said, but added that Russian experts “were not impressed at all” by the material provided to them by the U.K., U.S. and France.

At the White House, Carney said that Syria’s President “Bashar al-Assad called for a U.N. investigation into the use of chemical weapons and then he blocked the ability of the United Nations to conduct that investigation. The way to answer this question is to allow the United Nations to investigate.”

President Barack Obama’s administration says it has “high confidence” that Syrian President Bashar Assad’s forces have killed up to 150 people with sarin gas.

In a letter to the secretary-general on June 14, then-U.S. Ambassador Susan Rice said the U.S. had determined that sarin was used in the March 19 attack on Khan al-Assal and also in an April 13 attack on the Aleppo neighborhood of Shaykh Maqsud. She said unspecified chemicals, possibly including chemical warfare agents, were used May 14 in an attack on Qasr Abu Samrah and in a May 23 attack on Adra.

The use of a chemical weapon crossed Obama’s “red line” for escalating U.S. involvement in the conflict and prompted the decision to send arms and ammunition to the opposition, not just humanitarian aid and non-lethal material like armored vests and night goggles.

Churkin said Russia plans to provide the 80-page report to the U.S., U.K. and France, and “I hope they find it persuasive.” But he said it will not be made public.

U.N. spokesman Martin Nesirky had no immediate comment on the issue, noting that the Russian ambassador had delivered the “weighty and quite technical” report only minutes earlier. He said the Department of Disarmament Affairs would study it and provide guidance to the secretary-general.

http://www.huffingtonpost.com/2013/07/09/russia-syria-chemical-weapons_n_3568731.html

Is It Possible The Syrian Rebels (Not Assad) Used Chemical Weapons?

by EYDER PERALTA

August 27, 2013

As it lays the groundwork for a potential military strike against Syria, the Obama administration says it is all but certain that President Bashar Assad used chemical weapons against his own people last week.

Secretary of State John Kerry made the case Monday. “We know that the Syrian regime maintains custody of these chemical weapons,” Kerry said. “We know that the Syrian regime has the capacity to do this with rockets. We know that the regime has been determined to clear the opposition from those very places where the attacks took place. And with our own eyes, we have all of us become witnesses.” On Tuesday, White House spokesman Jay Carney reiterated the point, saying that “anyone who approaches this logically” would conclude that Assad is responsible.

As you might expect, Russia, which has been an unyielding Assad ally and holds veto power on the U.N. Security Council, rejected those conclusions, and the Assad regime blamed the rebels.

So, is it possible the United States and its allies are wrong? Is it possible that it was the rebels, or another group within Syria, that launched the attack near Damascus that reportedly left hundreds dead and thousands more injured?

“I have been asking myself the same question ever since it happened, because it was difficult to find a rationale [for an Assad-led attack],” says Gwyn Winfield, the editorial director of CBRNe World, a magazine that covers biological and chemical weapons for the industry.

“[A rebel attack] is feasible, but not particularly likely,” said Winfield.

What Winfield means is that this seems like a lose-lose situation for Assad. A chemical attack by the regime would seem to bolster the opposition, because it could mean an international intervention. As for the rebels, there are huge questions about whether they could have pulled off such an attack.

Back in 2002, research conducted by George Lopez, a professor of peace studies at the University of Notre Dame, cast doubt on the presence of weapons of mass destruction in Iraq. In this situation, Lopez rejects the notion that it was the Syrian rebels who used chemical weapons.

Lopez and Winfield agree that the rebels may have the motivation to use chemical weapons.

“This anarchic, killing stalemate” could motivate anyone, Winfield says, but such a scenario just doesn’t make sense.

For one thing, the alleged chemical attack happened in the Ghouta region of Damascus. It is controlled by the rebels, and civilians in the area sympathize with the rebels.

“The smart thing [for the rebels] would be for you to aim for barracks and maime/kill a significant few hundred soldiers as the best chance for reverberations that played to your advantage,” said Lopez. “This was not done.”

It seems clear, Lopez says,”that some armed unit foot soldiers were sent in by Assad some time after the attack in limited numbers. That achieved the desired effect of making the case that since Assad soldiers were hit, the weapons came from the ‘terrorists;’ but these were exemplars, too few to make a strategic difference for the rebels.”

In making the case against Assad, the U.S. has said it is his forces who have the capabilities to launch such an attack and that the rebels do not.

An August 20 report by the Congressional Research Service (pdf) says that Syria has had a vast stockpile of chemical weapons since the early 1980s and perhaps as far back as 1973. Not only that, but the military was trained by the Soviets and possesses the delivery methods — scud missiles and batteries of rocket launchers — that could be used to “rapidly achieve lethal doses of non-persistent agents in a concentrated area.”

The report goes on to explain that U.S. officials “have unanimously stated that the weapons stockpiles are secure.”

Winfield maintains that the Free Syrian Army has the experience and perhaps even the launching systems to perpetrate such an attack. But that would mean that U.S. officials, and Assad himself, were wrong when they said the chemical stockpiles were secure.

“If [the rebels] have overrun an arms dump which had some of the agent, if a defector brought a limited amount with him, then it would explain why some of the signs and symptoms showed less toxicity than we expected,” Winfield said. “That is a lot of ‘ifs,’ though.”

Lopez concurs: “Western intelligence has been standing on its head to monitor all intel about those groups hostile to the West and what they have in their weapons access and supply. The amount of gas agents seemingly used was way beyond what a clandestine group could mix and develop without detection. And it is unclear they would have the expertise to mix the agents.

“Is it possible that a rebel group overran a storage facility of the government and captured some shells that were ready to be activated and then did so?” Lopez says. “Yes, but it would have had to have been a very large seizure preceded by a big battle between Assad top teams and rebels. It could not have happened without inside/outside knowledge.”

All of that said, note that the U.S. has qualified every statement it has made about the situation.Kerry said it is “undeniable” that chemical weapons had been used in Syria and he set out a case against Assad without directly blaming the regime for the attack.

During his daily press briefing Tuesday, Carney said: “There is also very little doubt, and should be no doubt for anyone who approaches this logically, that the Syrian regime is responsible for the use of chemical weapons on August 21st outside of Damascus.”

Jean Pascal Zanders, who worked for the European Union Institute for Security Studies from 2008 to 2013 and concentrated on the non-proliferation of chemical weapons says until the U.N. investigative team presents its report, “we need to keep our minds open that the events of last Wednesday could in whole or partially have alternative explanations.”

“In fact, we – the public – know very little beyond the observation of outward symptoms of asphyxiation and possible exposure to neurotoxicants, despite the mass of images and film footage,” Zanders added. “For the West’s credibility, I think that governments should await the results of the U.N. investigation.”

http://www.npr.org/blogs/thetwo-way/2013/08/27/216172145/is-it-possible-the-syrian-rebels-not-assad-used-chemical-weapons

Evidence: Syrian Rebels used Chemical Weapons (not Assad)

by  on August 27, 2013 in BlogGeneral
By Walid Shoebat and Ben Barrack

Recent news of a chemical weapons attack in Syria smacks of desperation. The question comes down to who is most desperate right now, the Assad regime or the Muslim Brotherhood rebels? Consider that since June, Assad’s forces have been winning. According to a CBS News report from last month, victories for the rebels had become “increasingly rare” and that the Muslim Brotherhood-backed opposition fighters were sustaining “some of their heaviest losses” near Damascus.

Saudi Chemicals in hands of Syrian Rebels

Saudi Chemicals in hands of Syrian Rebels

The New York Times echoed this sentiment, even saying that before gaining the upper hand, concerns were that Assad would use chemical weapons; he did not.

In fact, even before Assad’s forces gained the momentum, a UN official reportedly found evidence of rebels using chemical weapons but no evidence Assad’s regime did. This, from a Washington Times article by Shaun Waterman dated May 6, 2013:

Testimony from victims strongly suggests it was the rebels, not the Syrian government, that used Sarin nerve gas during a recent incident in the revolution-wracked nation, a senior U.N. diplomat said Monday.

Carla del Ponte, a member of the U.N. Independent International Commission of Inquiry on Syria, told Swiss TV there were “strong, concrete suspicions but not yet incontrovertible proof,” that rebels seeking to oust Syrian strongman Bashar al-Assad had used the nerve agent.

But she said her panel had not yet seen any evidence of Syrian government forces using chemical weapons, according to the BBC, but she added that more investigation was needed. {emphasis ours}

Today, while the rebels are more desperate than they were at the time of that article, evidence of rebels using chemical weapons is available; evidence Assad’s regime has used them is not.

Waterman wrote…

Rebel Free Syrian Army spokesman Louay Almokdad denied that rebels had use chemical weapons.

That doesn’t square with a video uploaded on August 23, 2013, in which Free Syrian operatives threatened to launch chemical weapons:

A day later, on August 24th, a video was uploaded and featured on facebook that purports to show Syrian rebels loading what very well may be a rocket armed with some sort of chemical agent. The tip of the rocket is armed with a light blue tank or canister that very well contains a nerve agent. At the end of this video, two separate launches of these rockets can be seen:

This video from a Syrian TV news report claims to show chemicals (some of labels on these chemicals are in English) and weapons seized by the Syrian government in the rebel stronghold of Jobar. Note at the :10 mark a label that reads:

“Saudi Factory for Chlorine and Alkalies”

In this video, two Syrian rebels (Muslim Brotherhood gang) can be heard coordinating an attack on a nearby building. As smoke billows a short distance from the building, a rebel on the ground can be heard directing someone – presumably at the source of the launch – to change his direction. At that point, the rebel from the launch point can be heard talking about using sarin gas next:

In this video of a Russia Today news report originally broadcast on or before June 16, 2013, testimony from a United Nations panel is reported to demonstrate that rebel groups – not the Assad regime – was responsible for the use of chemical weapons in general, Sarin gas in particular, which backs up the claims in the previous video. Those who attempt to discredit the report below because it is from Russia Today should have difficulty doing so when factoring in rebels above talking about using sarin gas:

UN Panel implicates Syrian Rebels in Chemical weapons attacks

It’s significant to consider that the rebels were reportedly using chemical weapons at a time when Assad was more desperate than he is now. Again, why would Assad use chemical weapons now and not then? Who is more desperate at this point in the conflict?

The answer is, the Muslim Brotherhood rebels, who have no problem killing themselves (or their own) if the cause of Islam is moved forward.

Even CNN International, which has typically been quick to report favorably for the Muslim Brotherhood rebels, is hedging its bets lately, when it comes to who is responsible for the attack. Here is a video report from Frederik Pleitgen in which he leaves the possibility open that the rebels may have perpetrated or staged the attack:

Back in March, we chronicled evidence of chemical weapons being used by the Syrian rebels. Unfortunately, since google terminated Theodore’s YouTube account, most of the videos in that post have been deleted and have been more than a little difficult to find.

Running concurrent with the tide that turned in Assad’s favor a few months ago was another defeat for the Muslim Brotherhood – in Egypt. That defeat has been taking place ever since Mohammed Mursi was ousted on July 3rd. So why would Assad use chemical weapons now and not months ago, when his situation was much more precarious?

As the Associated Press was reporting that the U.S. is moving ships closer to Syria in response to the alleged chemical weapons attack, Reuters reported that Assad’s army found chemical weapons in tunnels that had been used by the rebels, according to Syrian state television.

Oxford University historian Mark Almond granted Russia Today an interview and explained both why western nations are so willing to blame Assad and why rebels would have a motive to murder their own people. In response to a question about why the U.S., the U.K., and France appear so eager to blame Assad, Almond said:

“Western governments… want to say ‘Gotcha’. They have been demanding the fall of Assad for more than two-and-a-half years now and it has become increasingly frustrating that his regime has shown much more resilience than they had expected, despite the resources that they and the Gulf Kingdoms have thrown into the war on the other side.

It is also like a distraction from the embarrassment of Egypt, where we see the European and the US governments basically using weasel words to avoid any kind of condemnation of a massacre in the streets of Cairo. So there are both the specifics of Syria and the context of what is going on elsewhere in the Arab world, especially in Egypt.”

Almond gives a very interesting answer to the question about why the rebels would intentionally gas their own people:

“We do have some very radical groups who would no doubt say, as they have when they have been challenged about using suicide bombers, killing innocent people, that God will recognize his own when the dead die, that he will save for heaven the justified victims and just send to hell the wicked supporters of Assad. So it is not impossible that somebody has staged this.

Consider that a man many of the Syrian rebels show the utmost of reverence for is the Muslim Brotherhood’s spiritual leader, Yusuf Al-Qaradawi. When writing about a Muslim tactic known asMuruna, Qaradawi expressed when it is acceptable for Muslims to kill fellow Muslims:

“…killing Muslims whom the unbelievers use as shields… leaving these unbelievers is a danger to the Muslims, so it is permissible to kill these unbelievers even if Muslims are killed with them in the process.” – The Case FOR Islamophobia, p. 56

Of course, if the rebels are desperate enough, Muruna could sanction the murder of their own people if it meant bearing false witness and a blood libel that would engage external forces that want Assad removed. As things stand today, the rebels are more desperate than is the Assad regime.

Specific examples include the staged death of twelve year-old Muhammad Al-Dura by Palestinians. Whether the child was used as a prop in a Palestinian blood-libel or was actually killed, he was clearly put in danger by Palestinians who shot at him as the news cameras rolled for a false report that aired on France 2. They wanted to blame the Israelis.

Earlier this month in Egypt, Muslim Brotherhood supporters were caught behaving as victims of oppression at the hands of the military. They might have gotten away with it if nothing but still shots were taken. Unfortunately for these miscreants, video was recorded that revealed a staged, mass display of despicable behavior.

Syria’s Muslim Brotherhood rebels would never get away with launching chemical weapons and taking credit for it. They’d have to do so while blaming Assad. It’s straight out of the Nazi playbook and a violation of two major commandments – Thou shalt not murder and thou shalt not bear false witness. However, the Muslim Brotherhood, as usual, provides more evil spin. It bears false witness while committing murder in order to push an agenda.

Lying, bearing false witness, blood libel, and murder.

Yeah, that smells like the Brotherhood.

**UPDATE at 8:40am EST on August 31, 2013**
Associated Press reporter Dale Gavlak reports in MintPress news that firsthand accounts indicate that the Chemical weapons attack was the result of the rebels’ mishandling of them. According to Gavlak, the weapons came from Saudi Arabia’s Prince Bandar bin Sultan and were given to rebels who did not know what the weapons were or how to store them, nor were they trained how to use them. If these accounts are correct, the Obama administration – along with more than a handful of Republican congressmen – may be complicit in a blood libel.

http://shoebat.com/2013/08/27/evidence-syrian-rebels-used-chemical-weapons-not-assad/]

First Syria rebels armed and trained by CIA ‘on way to battlefield’

The first cell of Syrian rebels trained and armed by the CIA is making its way to the battlefield, President Barack Obama has reportedly told senators.

The US announced in June that it would send light arms to the rebels but refused to provide anti-aircraft missiles and other heavy weapons.<br /><br /><br /><br /><br /><br /><br /><br /><br /><br /><br /><br /><br />
” src=”<a href=http://i.telegraph.co.uk/multimedia/archive/02660/obama1_2660362b.jpg&#8221; width=”620″ height=”387″ />

The US announced in June that it would send light arms to the rebels but refused to provide anti-aircraft missiles and other heavy weapons.  Photo: JIM WATSON/AFP

Raf Sanchez in Washington

3:15PM BST 03 Sep 2013

During a meeting at the White House, the president assured Senator John McCain that after months of delay the US was meeting its commitment to back moderate elements of the opposition.

Mr Obama said that a 50-man cell, believed to have been trained by US special forces in Jordan, was making its way across the border into Syria, according to the New York Times.

The deployment of the rebel unit seems to be the first tangible measure of support since Mr Obama announced in June that the US would begin providing the opposition with small arms.

Congressional opposition delayed the plan for several weeks and rebel commanders publicly complained the US was still doing nothing to match the Russian-made firepower of the Assad regime.

Mr McCain has been a chief critic of the White House’s reluctance to become involved in Syria and has long demanded that Mr Obama provide the rebels with arms needed to overthrow the regime.

He and Senator Lindsey Graham, a fellow Republican foreign policy hawk, emerged from the Oval Office meeting on Monday cautiously optimistic that Mr Obama would step up support for the rebels.

“There seems to be emerging from this administration a pretty solid plan to upgrade the opposition,” Mr Graham said.

He added that he hoped the opposition would be given “a chance to speak directly to the American people” to counter US fears that they were dominated by al-Qaeda sympathisers.

“They’re not trying to replace one dictator, Assad, who has been brutal… to only have al-Qaeda run Syria,” Mr Graham said.

The US announced in June, following the first allegations the Assad regime had used chemical weapons, that it would send light arms to the rebels but refused to provide anti-aircraft missiles and other heavy weapons.

American concerns were born partly out of the experience of Afghanistan in the 1980s, when CIA weapons given to the anti-Russian mujahideen were later used by the Taliban.

Related Posts On Pronk Palisades

Obama’s Red Lines — Videos

Who used chemical weapons in Syria? Syrian Rebels (FSA) or Syrian Regime (SAA) — American People Do Not Want To Take Sides in Syrian Civil War — Videos

Big Interventionist Government Statist (BIGS) Obama Sending Military Support To Syrian Rebels Including Jabhat al-Nusra (Al Qaeda connected) — Neocon Warmonger McCain Approves — All In For World War 3 — Videos

Launching World War 3 with The Missiles of September — Videos

Who Wants World War 3 To Start in Syria? The Warmongers Obama and McCain — Not The American People! — Videos

Muslim Brotherhood Massive Attack on Coptic Christians in Egypt — Silence From President Obama Who Supports Muslim Brotherhood — Muslim Ethnic Cleansing of Coptic Christians — Videos

Obama’s Siding With Muslim Brotherhood Not Popular in Egypt or in The United States — Videos

Muslim Brotherhood in America — Videos

Big Interventionist Government Statist (BIGS) Obama Sending Military Support To Syrian Rebels Including Jabhat al-Nusra (Al Qaeda connected) — Neocon Warmonger McCain Approves — All In For World War 3 — Videos

Launching World War 3 with The Missiles of September — Videos

Who Wants World War 3 To Start in Syria? The Warmongers Obama and McCain — Not The American People! — Videos

Muslim Brotherhood Massive Attack on Coptic Christians in Egypt — Silence From President Obama Who Supports Muslim Brotherhood — Muslim Ethnic Cleansing of Coptic Christians — Videos

Obama’s Siding With Muslim Brotherhood Not Popular in Egypt or in The United States — Videos

Muslim Brotherhood in America — Videos

Read Full Post | Make a Comment ( None so far )

Only 162,000 Nonfarm Payroll Jobs Created in July 2013 — 300,000 New Jobs Needed To Reduce Unemployment by .1%– Unemployment Rate Declines .2% to 7.4% — Labor Participation Rate Declines .1% to 63.5% As Number of Discourage Workers Increases By 136,000 — Obama’s Jobs Gap 10 Million Jobs Widens — Videos

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Obama-Unemployment

obama-unemployed-college-grad-empty-nest-syndrome-cartoon

ITS-THE-ECONOMY-OBAMA-WHITE-HOUSE-ATTIC-CAI-012610-COLOR

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Unemployment Rate Drops to Near Five-Year Low

US jobs numbers disappoint but ‘underlying tone is bullish’

Data extracted on: August 2, 2013 (2:01:21 PM)

Labor Force Statistics from the Current Population Survey

Employment Level

144,285,000

Series Id:           LNS12000000
Seasonally Adjusted
Series title:        (Seas) Employment Level
Labor force status:  Employed
Type of data:        Number in thousands
Age:                 16 years and over

employment_level
Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual
2000 136559(1) 136598 136701 137270 136630 136940 136531 136662 136893 137088 137322 137614
2001 137778 137612 137783 137299 137092 136873 137071 136241 136846 136392 136238 136047
2002 135701 136438 136177 136126 136539 136415 136413 136705 137302 137008 136521 136426
2003 137417(1) 137482 137434 137633 137544 137790 137474 137549 137609 137984 138424 138411
2004 138472(1) 138542 138453 138680 138852 139174 139556 139573 139487 139732 140231 140125
2005 140245(1) 140385 140654 141254 141609 141714 142026 142434 142401 142548 142499 142752
2006 143150(1) 143457 143741 143761 144089 144353 144202 144625 144815 145314 145534 145970
2007 146028(1) 146057 146320 145586 145903 146063 145905 145682 146244 145946 146595 146273
2008 146378(1) 146156 146086 146132 145908 145737 145532 145203 145076 144802 144100 143369
2009 142153(1) 141644 140721 140652 140250 140005 139898 139481 138810 138421 138665 138025
2010 138439(1) 138624 138767 139296 139255 139148 139167 139405 139388 139097 139046 139295
2011 139253(1) 139471 139643 139606 139681 139405 139509 139870 140164 140314 140771 140896
2012 141608(1) 142019 142020 141934 142302 142448 142250 142164 142974 143328 143277 143305
2013 143322(1) 143492 143286 143579 143898 144058 144285
1 : Data affected by changes in population controls.

Civilian Labor Force

155,798,000

Series Id:           LNS11000000
Seasonally Adjusted
Series title:        (Seas) Civilian Labor Force Level
Labor force status:  Civilian labor force
Type of data:        Number in thousands
Age:                 16 years and over

civilian_labor_force_level
Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual
2000 142267(1) 142456 142434 142751 142388 142591 142278 142514 142518 142622 142962 143248
2001 143800 143701 143924 143569 143318 143357 143654 143284 143989 144086 144240 144305
2002 143883 144653 144481 144725 144938 144808 144803 145009 145552 145314 145041 145066
2003 145937(1) 146100 146022 146474 146500 147056 146485 146445 146530 146716 147000 146729
2004 146842(1) 146709 146944 146850 147065 147460 147692 147564 147415 147793 148162 148059
2005 148029(1) 148364 148391 148926 149261 149238 149432 149779 149954 150001 150065 150030
2006 150214(1) 150641 150813 150881 151069 151354 151377 151716 151662 152041 152406 152732
2007 153144(1) 152983 153051 152435 152670 153041 153054 152749 153414 153183 153835 153918
2008 154063(1) 153653 153908 153769 154303 154313 154469 154641 154570 154876 154639 154655
2009 154232(1) 154526 154142 154479 154742 154710 154505 154300 153815 153804 153887 153120
2010 153455(1) 153702 153960 154577 154110 153623 153709 154078 153966 153681 154140 153649
2011 153244(1) 153269 153358 153478 153552 153369 153325 153707 154074 154010 154096 153945
2012 154356(1) 154825 154707 154451 154998 155149 154995 154647 155056 155576 155319 155511
2013 155654(1) 155524 155028 155238 155658 155835 155798

Labor Force Participation Rate

63.4%

Series Id:           LNS11300000
Seasonally Adjusted
Series title:        (Seas) Labor Force Participation Rate
Labor force status:  Civilian labor force participation rate
Type of data:        Percent or rate
Age:                 16 years and over

civilian_labor_force_participation_rate
Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual
2000 67.3 67.3 67.3 67.3 67.1 67.1 66.9 66.9 66.9 66.8 66.9 67.0
2001 67.2 67.1 67.2 66.9 66.7 66.7 66.8 66.5 66.8 66.7 66.7 66.7
2002 66.5 66.8 66.6 66.7 66.7 66.6 66.5 66.6 66.7 66.6 66.4 66.3
2003 66.4 66.4 66.3 66.4 66.4 66.5 66.2 66.1 66.1 66.1 66.1 65.9
2004 66.1 66.0 66.0 65.9 66.0 66.1 66.1 66.0 65.8 65.9 66.0 65.9
2005 65.8 65.9 65.9 66.1 66.1 66.1 66.1 66.2 66.1 66.1 66.0 66.0
2006 66.0 66.1 66.2 66.1 66.1 66.2 66.1 66.2 66.1 66.2 66.3 66.4
2007 66.4 66.3 66.2 65.9 66.0 66.0 66.0 65.8 66.0 65.8 66.0 66.0
2008 66.2 66.0 66.1 65.9 66.1 66.1 66.1 66.1 66.0 66.0 65.9 65.8
2009 65.7 65.8 65.6 65.7 65.7 65.7 65.5 65.4 65.1 65.0 65.0 64.6
2010 64.8 64.9 64.9 65.1 64.9 64.6 64.6 64.7 64.6 64.4 64.6 64.3
2011 64.2 64.2 64.2 64.2 64.2 64.0 64.0 64.1 64.2 64.1 64.1 64.0
2012 63.7 63.9 63.8 63.6 63.8 63.8 63.7 63.5 63.6 63.8 63.6 63.6
2013 63.6 63.5 63.3 63.3 63.4 63.5 63.4

Unemployment Level

11,514,000

Series Id:           LNS13000000
Seasonally Adjusted
Series title:        (Seas) Unemployment Level
Labor force status:  Unemployed
Type of data:        Number in thousands
Age:                 16 years and over

unemployment_level

Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual
2000 5708 5858 5733 5481 5758 5651 5747 5853 5625 5534 5639 5634
2001 6023 6089 6141 6271 6226 6484 6583 7042 7142 7694 8003 8258
2002 8182 8215 8304 8599 8399 8393 8390 8304 8251 8307 8520 8640
2003 8520 8618 8588 8842 8957 9266 9011 8896 8921 8732 8576 8317
2004 8370 8167 8491 8170 8212 8286 8136 7990 7927 8061 7932 7934
2005 7784 7980 7737 7672 7651 7524 7406 7345 7553 7453 7566 7279
2006 7064 7184 7072 7120 6980 7001 7175 7091 6847 6727 6872 6762
2007 7116 6927 6731 6850 6766 6979 7149 7067 7170 7237 7240 7645
2008 7685 7497 7822 7637 8395 8575 8937 9438 9494 10074 10538 11286
2009 12079 12881 13421 13826 14492 14705 14607 14819 15005 15382 15223 15095
2010 15016 15078 15192 15281 14856 14475 14542 14673 14577 14584 15094 14354
2011 13992 13798 13716 13872 13871 13964 13817 13837 13910 13696 13325 13049
2012 12748 12806 12686 12518 12695 12701 12745 12483 12082 12248 12042 12206
2013 12332 12032 11742 11659 11760 11777 11514

Unemployment Rate U-3

7.4%

Series Id:           LNS14000000
Seasonally Adjusted
Series title:        (Seas) Unemployment Rate
Labor force status:  Unemployment rate
Type of data:        Percent or rate
Age:                 16 years and over

unemployment_rate_u3

Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual
2000 4.0 4.1 4.0 3.8 4.0 4.0 4.0 4.1 3.9 3.9 3.9 3.9
2001 4.2 4.2 4.3 4.4 4.3 4.5 4.6 4.9 5.0 5.3 5.5 5.7
2002 5.7 5.7 5.7 5.9 5.8 5.8 5.8 5.7 5.7 5.7 5.9 6.0
2003 5.8 5.9 5.9 6.0 6.1 6.3 6.2 6.1 6.1 6.0 5.8 5.7
2004 5.7 5.6 5.8 5.6 5.6 5.6 5.5 5.4 5.4 5.5 5.4 5.4
2005 5.3 5.4 5.2 5.2 5.1 5.0 5.0 4.9 5.0 5.0 5.0 4.9
2006 4.7 4.8 4.7 4.7 4.6 4.6 4.7 4.7 4.5 4.4 4.5 4.4
2007 4.6 4.5 4.4 4.5 4.4 4.6 4.7 4.6 4.7 4.7 4.7 5.0
2008 5.0 4.9 5.1 5.0 5.4 5.6 5.8 6.1 6.1 6.5 6.8 7.3
2009 7.8 8.3 8.7 9.0 9.4 9.5 9.5 9.6 9.8 10.0 9.9 9.9
2010 9.8 9.8 9.9 9.9 9.6 9.4 9.5 9.5 9.5 9.5 9.8 9.3
2011 9.1 9.0 8.9 9.0 9.0 9.1 9.0 9.0 9.0 8.9 8.6 8.5
2012 8.3 8.3 8.2 8.1 8.2 8.2 8.2 8.1 7.8 7.9 7.8 7.8
2013 7.9 7.7 7.6 7.5 7.6 7.6 7.4

Employment-Population Ratio

58.7%

Series Id:           LNS12300000
Seasonally Adjusted
Series title:        (Seas) Employment-Population Ratio
Labor force status:  Employment-population ratio
Type of data:        Percent or rate
Age:                 16 years and over

Employment-Population Ratio

Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual
2000 64.6 64.6 64.6 64.7 64.4 64.5 64.2 64.2 64.2 64.2 64.3 64.4
2001 64.4 64.3 64.3 64.0 63.8 63.7 63.7 63.2 63.5 63.2 63.0 62.9
2002 62.7 63.0 62.8 62.7 62.9 62.7 62.7 62.7 63.0 62.7 62.5 62.4
2003 62.5 62.5 62.4 62.4 62.3 62.3 62.1 62.1 62.0 62.1 62.3 62.2
2004 62.3 62.3 62.2 62.3 62.3 62.4 62.5 62.4 62.3 62.3 62.5 62.4
2005 62.4 62.4 62.4 62.7 62.8 62.7 62.8 62.9 62.8 62.8 62.7 62.8
2006 62.9 63.0 63.1 63.0 63.1 63.1 63.0 63.1 63.1 63.3 63.3 63.4
2007 63.3 63.3 63.3 63.0 63.0 63.0 62.9 62.7 62.9 62.7 62.9 62.7
2008 62.9 62.8 62.7 62.7 62.5 62.4 62.2 62.0 61.9 61.7 61.4 61.0
2009 60.6 60.3 59.9 59.8 59.6 59.4 59.3 59.1 58.7 58.5 58.6 58.3
2010 58.5 58.5 58.5 58.7 58.6 58.5 58.5 58.5 58.5 58.3 58.2 58.3
2011 58.3 58.4 58.4 58.4 58.4 58.2 58.2 58.3 58.4 58.4 58.5 58.6
2012 58.5 58.6 58.5 58.5 58.6 58.6 58.5 58.4 58.7 58.7 58.7 58.6
2013 58.6 58.6 58.5 58.6 58.6 58.7 58.7

Unemployment Rate 16-19 Years Old

 

23.7%


Series Id:           LNS14000012
Seasonally Adjusted
Series title:        (Seas) Unemployment Rate - 16-19 yrs.
Labor force status:  Unemployment rate
Type of data:        Percent or rate
Age:                 16 to 19 years


unemployment_rate_teenagers

Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual
2000 12.7 13.8 13.3 12.6 12.8 12.3 13.4 14.0 13.0 12.8 13.0 13.2
2001 13.8 13.7 13.8 13.9 13.4 14.2 14.4 15.6 15.2 16.0 15.9 17.0
2002 16.5 16.0 16.6 16.7 16.6 16.7 16.8 17.0 16.3 15.1 17.1 16.9
2003 17.2 17.2 17.8 17.7 17.9 19.0 18.2 16.6 17.6 17.2 15.7 16.2
2004 17.0 16.5 16.8 16.6 17.1 17.0 17.8 16.7 16.6 17.4 16.4 17.6
2005 16.2 17.5 17.1 17.8 17.8 16.3 16.1 16.1 15.5 16.1 17.0 14.9
2006 15.1 15.3 16.1 14.6 14.0 15.8 15.9 16.0 16.3 15.2 14.8 14.6
2007 14.8 14.9 14.9 15.9 15.9 16.3 15.3 15.9 15.9 15.4 16.2 16.8
2008 17.8 16.6 16.1 15.9 19.0 19.2 20.7 18.6 19.1 20.0 20.3 20.5
2009 20.7 22.2 22.2 22.2 23.4 24.7 24.3 25.0 25.9 27.1 26.9 26.6
2010 26.0 25.4 26.2 25.5 26.6 26.0 26.0 25.7 25.8 27.2 24.6 25.1
2011 25.5 24.0 24.4 24.7 24.0 24.7 24.9 25.2 24.4 24.1 23.9 22.9
2012 23.4 23.7 25.0 24.9 24.4 23.7 23.9 24.5 23.7 23.7 23.6 23.5
2013 23.4 25.1 24.2 24.1 24.5 24.0 23.7

White Unemployment Rate

 

6.6%

 

Series Id:           LNS14000003
Seasonally Adjusted
Series title:        (Seas) Unemployment Rate - White
Labor force status:  Unemployment rate
Type of data:        Percent or rate
Age:                 16 years and over
Race:                White

white_unemployment_rate

Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual
2000 3.4 3.6 3.5 3.4 3.5 3.4 3.5 3.6 3.5 3.4 3.5 3.5
2001 3.6 3.7 3.7 3.9 3.8 4.0 4.0 4.3 4.3 4.7 4.9 5.1
2002 5.1 5.0 5.0 5.2 5.1 5.1 5.2 5.1 5.1 5.1 5.1 5.1
2003 5.2 5.1 5.1 5.3 5.4 5.5 5.4 5.4 5.3 5.1 5.2 5.0
2004 5.0 4.9 5.1 5.0 4.9 5.0 4.7 4.7 4.6 4.6 4.6 4.5
2005 4.5 4.6 4.5 4.4 4.4 4.3 4.2 4.2 4.4 4.4 4.3 4.2
2006 4.1 4.1 4.0 4.1 4.1 4.1 4.1 4.1 3.9 3.9 4.0 3.9
2007 4.2 4.1 3.8 4.0 3.9 4.1 4.2 4.2 4.2 4.1 4.2 4.4
2008 4.4 4.4 4.5 4.4 4.8 5.0 5.2 5.4 5.4 5.9 6.2 6.7
2009 7.1 7.6 8.0 8.1 8.6 8.7 8.7 8.9 9.0 9.2 9.2 9.0
2010 8.8 8.9 8.9 9.0 8.7 8.6 8.5 8.6 8.6 8.6 8.9 8.5
2011 8.1 8.1 8.0 8.1 8.0 8.1 8.0 7.9 7.9 8.0 7.7 7.5
2012 7.4 7.4 7.3 7.4 7.4 7.3 7.4 7.2 7.0 6.9 6.8 6.9
2013 7.0 6.8 6.7 6.7 6.7 6.6 6.6

Black Unemployment Rate

 

Series Id:           LNS14000006
Seasonally Adjusted
Series title:        (Seas) Unemployment Rate - Black or African American
Labor force status:  Unemployment rate
Type of data:        Percent or rate
Age:                 16 years and over
Race:                Black or African American

Employment Situation News Release

Transmission of material in this release is embargoed                                  USDL-13-1527
until 8:30 a.m. (EDT) Friday, August 2, 2013

Technical information:
 Household data:       (202) 691-6378  *  cpsinfo@bls.gov  *  www.bls.gov/cps
 Establishment data:   (202) 691-6555  *  cesinfo@bls.gov  *  www.bls.gov/ces

Media contact:         (202) 691-5902  *  PressOffice@bls.gov

                         THE EMPLOYMENT SITUATION -- JULY 2013

Total nonfarm payroll employment increased by 162,000 in July, and the unemployment rate edged
down to 7.4 percent, the U.S. Bureau of Labor Statistics reported today. Employment rose in
retail trade, food services and drinking places, financial activities, and wholesale trade.

Household Survey Data

Both the number of unemployed persons, at 11.5 million, and the unemployment rate, at 7.4 percent,
edged down in July. Over the year, these measures were down by 1.2 million and 0.8 percentage
point, respectively. (See table A-1.)

Among the major worker groups, the unemployment rates for adult women (6.5 percent) and blacks
(12.6 percent) declined in July. The rates for adult men (7.0 percent), teenagers (23.7 percent),
whites (6.6 percent), and Hispanics (9.4 percent) showed little or no change. The jobless rate
for Asians was 5.7 percent (not seasonally adjusted), little changed from a year earlier. (See
tables A-1, A-2, and A-3.)

In July, the number of long-term unemployed (those jobless for 27 weeks or more) was little
changed at 4.2 million. These individuals accounted for 37.0 percent of the unemployed. The
number of long-term unemployed has declined by 921,000 over the past year. (See table A-12.)

The civilian labor force participation rate was 63.4 percent in July, little changed over the
month. The employment-population ratio was unchanged at 58.7 percent. (See table A-1.)

The number of persons employed part time for economic reasons (sometimes referred to as involuntary
part-time workers) was essentially unchanged at 8.2 million in July. These individuals were working
part time because their hours had been cut back or because they were unable to find a full-time
job. (See table A-8.)

In July, 2.4 million persons were marginally attached to the labor force, little changed from a
year earlier. (The data are not seasonally adjusted.) These individuals were not in the labor
force, wanted and were available for work, and had looked for a job sometime in the prior 12
months. They were not counted as unemployed because they had not searched for work in the 4 weeks
preceding the survey. (See table A-16.)

Among the marginally attached, there were 988,000 discouraged workers in July, up by 136,000 from
a year earlier. (The data are not seasonally adjusted.) Discouraged workers are persons not
currently looking for work because they believe no jobs are available for them. The remaining
1.4 million persons marginally attached to the labor force in July had not searched for work for
reasons such as school attendance or family responsibilities. (See table A-16.)

Establishment Survey Data

Total nonfarm payroll employment increased by 162,000 in July, with gains in retail trade, food
services and drinking places, financial activities, and wholesale trade. Over the prior 12 months,
nonfarm employment growth averaged 189,000 per month. (See table B-1.)

Retail trade added 47,000 jobs in July and has added 352,000 over the past 12 months. In July, job
growth occurred in general merchandise stores (+9,000), motor vehicle and parts dealers (+6,000),
building material and garden supply stores (+6,000), and health and personal care stores (+5,000).

Within leisure and hospitality, employment in food services and drinking places increased by 38,000
in July and by 381,000 over the year.

Financial activities employment increased by 15,000 in July, with a gain of 6,000 in securities,
commodity contracts, and investments. Over the year, financial activities has added 120,000 jobs.

Employment increased in wholesale trade (+14,000) in July. Over the past 12 months, this industry
has added 83,000 jobs.

Employment in professional and business services continued to trend up in July (+36,000). Within
the industry, job growth continued in management of companies and enterprises (+7,000) and in
management and technical consulting services (+7,000). Employment in temporary help services
changed little over the month.

Manufacturing employment was essentially unchanged in July and has changed little, on net, over
the past 12 months. Within the industry, employment in motor vehicles and parts rose by 9,000
in July.

Employment in health care was essentially unchanged over the month. Thus far in 2013, health
care has added an average of 16,000 jobs per month, compared with an average monthly increase
of 27,000 in 2012.

Employment in other major industries, including mining and logging, construction, transportation
and warehousing, and government, showed little change in July.

The average workweek for all employees on private nonfarm payrolls decreased by 0.1 hour in July
to 34.4 hours. In manufacturing, the workweek decreased by 0.2 hour to 40.6 hours, and overtime
declined by 0.2 hour to 3.2 hours. The average workweek for production and nonsupervisory employees
on private nonfarm payrolls decreased by 0.1 hour to 33.6 hours. (See tables B-2 and B-7.)

In July, average hourly earnings for all employees on private nonfarm payrolls edged down by 2 cents
to $23.98, following a 10-cent increase in June. Over the year, average hourly earnings have risen
by 44 cents, or 1.9 percent. In July, average hourly earnings of private-sector production and
nonsupervisory employees were unchanged at $20.14. (See tables B-3 and B-8.)

The change in total nonfarm payroll employment for May was revised from +195,000 to +176,000, and
the change for June was revised from +195,000 to +188,000. With these revisions, employment gains
in May and June combined were 26,000 less than previously reported.

_____________
The Employment Situation for August is scheduled to be released on Friday, September 6, 2013, at
8:30 a.m. (EDT).
HOUSEHOLD DATA
Summary table A. Household data, seasonally adjusted

[Numbers in thousands]
Category July
2012
May
2013
June
2013
July
2013
Change from:
June
2013-
July
2013
Employment status
Civilian noninstitutional population 243,354 245,363 245,552 245,756 204
Civilian labor force 154,995 155,658 155,835 155,798 -37
Participation rate 63.7 63.4 63.5 63.4 -0.1
Employed 142,250 143,898 144,058 144,285 227
Employment-population ratio 58.5 58.6 58.7 58.7 0.0
Unemployed 12,745 11,760 11,777 11,514 -263
Unemployment rate 8.2 7.6 7.6 7.4 -0.2
Not in labor force 88,359 89,705 89,717 89,957 240
Unemployment rates
Total, 16 years and over 8.2 7.6 7.6 7.4 -0.2
Adult men (20 years and over) 7.7 7.2 7.0 7.0 0.0
Adult women (20 years and over) 7.5 6.5 6.8 6.5 -0.3
Teenagers (16 to 19 years) 23.9 24.5 24.0 23.7 -0.3
White 7.4 6.7 6.6 6.6 0.0
Black or African American 14.1 13.5 13.7 12.6 -1.1
Asian (not seasonally adjusted) 6.2 4.3 5.0 5.7 -
Hispanic or Latino ethnicity 10.3 9.1 9.1 9.4 0.3
Total, 25 years and over 6.9 6.1 6.2 6.1 -0.1
Less than a high school diploma 12.7 11.1 10.7 11.0 0.3
High school graduates, no college 8.6 7.4 7.6 7.6 0.0
Some college or associate degree 7.1 6.5 6.4 6.0 -0.4
Bachelor’s degree and higher 4.1 3.8 3.9 3.8 -0.1
Reason for unemployment
Job losers and persons who completed temporary jobs 7,106 6,147 6,119 5,921 -198
Job leavers 879 944 1,030 979 -51
Reentrants 3,374 3,333 3,291 3,258 -33
New entrants 1,299 1,268 1,259 1,254 -5
Duration of unemployment
Less than 5 weeks 2,697 2,706 2,692 2,563 -129
5 to 14 weeks 3,102 2,669 2,864 2,869 5
15 to 26 weeks 1,756 1,950 1,896 1,788 -108
27 weeks and over 5,167 4,357 4,328 4,246 -82
Employed persons at work part time
Part time for economic reasons 8,245 7,904 8,226 8,245 19
Slack work or business conditions 5,319 4,841 5,193 5,177 -16
Could only find part-time work 2,568 2,721 2,652 2,665 13
Part time for noneconomic reasons 18,846 18,934 19,044 19,128 84
Persons not in the labor force (not seasonally adjusted)
Marginally attached to the labor force 2,529 2,164 2,582 2,414 -
Discouraged workers 852 780 1,027 988 -
- Over-the-month changes are not displayed for not seasonally adjusted data.
NOTE: Persons whose ethnicity is identified as Hispanic or Latino may be of any race. Detail for the seasonally adjusted data shown in this table will not necessarily add to totals because of the independent seasonal adjustment of the various series. Updated population controls are introduced annually with the release of January data.
ESTABLISHMENT DATA
Summary table B. Establishment data, seasonally adjusted
Category July
2012
May
2013
June
2013(p)
July
2013(p)
EMPLOYMENT BY SELECTED INDUSTRY
(Over-the-month change, in thousands)
Total nonfarm 153 176 188 162
Total private 177 187 196 161
Goods-producing 26 -4 8 4
Mining and logging -1 2 3 4
Construction 5 -1 8 -6
Manufacturing 22 -5 -3 6
Durable goods(1) 20 1 0 8
Motor vehicles and parts 12.0 6.0 6.4 9.1
Nondurable goods 2 -6 -3 -2
Private service-providing(1) 151 191 188 157
Wholesale trade 10.1 7.3 7.0 13.7
Retail trade 3.1 32.6 39.7 46.8
Transportation and warehousing 11.3 -5.7 0.7 4.6
Information 9 3 -4 9
Financial activities 0 7 13 15
Professional and business services(1) 52 70 61 36
Temporary help services 15.3 26.8 16.2 7.7
Education and health services(1) 35 20 16 13
Health care and social assistance 25.5 9.7 18.4 8.3
Leisure and hospitality 27 43 57 23
Other services 10 13 -3 -2
Government -24 -11 -8 1
WOMEN AND PRODUCTION AND NONSUPERVISORY EMPLOYEES(2)
AS A PERCENT OF ALL EMPLOYEES
Total nonfarm women employees 49.4 49.4 49.4 49.4
Total private women employees 47.9 47.9 47.9 47.9
Total private production and nonsupervisory employees 82.6 82.6 82.6 82.6
HOURS AND EARNINGS
ALL EMPLOYEES
Total private
Average weekly hours 34.4 34.5 34.5 34.4
Average hourly earnings $23.54 $23.90 $24.00 $23.98
Average weekly earnings $809.78 $824.55 $828.00 $824.91
Index of aggregate weekly hours (2007=100)(3) 96.4 98.4 98.5 98.4
Over-the-month percent change 0.2 0.2 0.1 -0.1
Index of aggregate weekly payrolls (2007=100)(4) 108.2 112.1 112.8 112.5
Over-the-month percent change 0.3 0.2 0.6 -0.3
HOURS AND EARNINGS
PRODUCTION AND NONSUPERVISORY EMPLOYEES
Total private
Average weekly hours 33.7 33.7 33.7 33.6
Average hourly earnings $19.77 $20.08 $20.14 $20.14
Average weekly earnings $666.25 $676.70 $678.72 $676.70
Index of aggregate weekly hours (2002=100)(3) 104.0 105.7 105.9 105.8
Over-the-month percent change 0.2 0.2 0.2 -0.1
Index of aggregate weekly payrolls (2002=100)(4) 137.2 141.8 142.4 142.2
Over-the-month percent change 0.2 0.2 0.4 -0.1
DIFFUSION INDEX(5)
(Over 1-month span)
Total private (266 industries) 56.0 58.1 57.3 54.5
Manufacturing (81 industries) 51.2 45.1 45.7 50.0
Footnotes
(1) Includes other industries, not shown separately.
(2) Data relate to production employees in mining and logging and manufacturing, construction employees in construction, and nonsupervisory employees in the service-providing industries.
(3) The indexes of aggregate weekly hours are calculated by dividing the current month’s estimates of aggregate hours by the corresponding annual average aggregate hours.
(4) The indexes of aggregate weekly payrolls are calculated by dividing the current month’s estimates of aggregate weekly payrolls by the corresponding annual average aggregate weekly payrolls.
(5) Figures are the percent of industries with employment increasing plus one-half of the industries with unchanged employment, where 50 percent indicates an equal balance between industries with increasing and decreasing employment.
(p) Preliminary
Frequently Asked Questions about Employment and Unemployment Estimates

1. Why are there two monthly measures of employment?

   The household survey and establishment survey both produce sample-based estimates
   of   employment, and both have strengths and limitations. The establishment survey
   employment series has a   smaller margin of error on the measurement of month-to-
   month change   than the household survey because of its much larger sample size. An
   over-the-month employment change of about 100,000 is statistically significant in
   the establishment survey, while the threshold for a statistically significant change
   in the household survey is about 400,000. However, the household survey has a more
   expansive scope than the establishment survey because it includes self-employed
   workers whose businesses are unincorporated, unpaid family workers, agricultural
   workers, and private household workers, who are excluded by the establishment survey.
   The household survey also provides estimates of employment for demographic groups.
   For more information on the differences between the two surveys, please visit
   www.bls.gov/web/empsit/ces_cps_trends.pdf.

2. Are undocumented immigrants counted in the surveys?

   It is likely that both surveys include at least some undocumented immigrants. However,
   neither the establishment nor the household survey is designed to identify the legal
   status of workers. Therefore, it is not possible to determine how many are counted in
   either survey. The establishment survey does not collect data on the legal status of
   workers. The household survey does include questions which identify the foreign and
   native born, but it does not include questions about the legal status of the foreign
   born. Data on the foreign and native born are published each month in table A-7 of
   The Employment Situation news release.

3. Why does the establishment survey have revisions?

   The establishment survey revises published estimates to improve its data series by
   incorporating additional information that was not available at the time of the
   initial publication of the estimates. The establishment survey revises its initial
   monthly estimates twice, in the immediately succeeding 2 months, to incorporate
   additional sample receipts from respondents in the survey and recalculated seasonal
   adjustment factors. For more information on the monthly revisions, please visit
   www.bls.gov/ces/cesrevinfo.htm.

   On an annual basis, the establishment survey incorporates a benchmark revision that
   re-anchors estimates to nearly complete employment counts available from unemployment
   insurance tax records. The benchmark helps to control for sampling and modeling errors
   in the estimates. For more information on the annual benchmark revision, please visit
   www.bls.gov/web/empsit/cesbmart.htm.

4. Does the establishment survey sample include small firms?

   Yes; about 40 percent of the establishment survey sample is comprised of business
   establishments with fewer than 20 employees. The establishment survey sample is
   designed to maximize the reliability of the statewide total nonfarm employment
   estimate; firms from all states, size classes, and industries are appropriately
   sampled to achieve that goal.

5. Does the establishment survey account for employment from new businesses?

   Yes; monthly establishment survey estimates include an adjustment to account for
   the net employment change generated by business births and deaths. The adjustment
   comes from an econometric model that forecasts the monthly net jobs impact of
   business births and deaths based on the actual past values of the net impact that
   can be observed with a lag from the Quarterly Census of Employment and Wages. The
   establishment survey uses modeling rather than sampling for this purpose because
   the survey is not immediately able to bring new businesses into the sample. There
   is an unavoidable lag between the birth of a new firm and its appearance on the
   sampling frame and availability for selection. BLS adds new businesses to the survey
   twice a year.

6. Is the count of unemployed persons limited to just those people receiving unemployment
   insurance benefits?

   No; the estimate of unemployment is based on a monthly sample survey of households.
   All persons who are without jobs and are actively seeking and available to work are
   included among the unemployed. (People on temporary layoff are included even if
   they do not actively seek work.) There is no requirement or question relating to
   unemployment insurance benefits in the monthly survey.

7. Does the official unemployment rate exclude people who want a job but are not currently
   looking for work?

   Yes; however, there are separate estimates of persons outside the labor force who
   want a job, including those who are not currently looking because they believe no
   jobs are available (discouraged workers). In addition, alternative measures of labor
   underutilization (some of which include discouraged workers and other groups not
   officially counted as unemployed) are published each month in table A-15 of The
   Employment Situation news release. For more information about these alternative
   measures, please visit www.bls.gov/cps/lfcharacteristics.htm#altmeasures.

8. How can unusually severe weather affect employment and hours estimates?

   In the establishment survey, the reference period is the pay period that includes
   the 12th of the month. Unusually severe weather is more likely to have an impact on
   average weekly hours than on employment. Average weekly hours are estimated for paid
   time during the pay period, including pay for holidays, sick leave, or other time off.
   The impact of severe weather on hours estimates typically, but not always, results in
   a reduction in average weekly hours. For example, some employees may be off work for
   part of the pay period and not receive pay for the time missed, while some workers,
   such as those dealing with cleanup or repair, may work extra hours.

   In order for severe weather conditions to reduce the estimate of payroll employment,
   employees have to be off work without pay for the entire pay period. Slightly more
   than 20 percent of all employees in the payroll survey sample have a weekly pay
   period. Employees who receive pay for any part of the pay period, even 1 hour, are
   counted in the payroll employment figures. It is not possible to quantify the effect
   of extreme weather on estimates of over-the-month change in employment.

   In the household survey, the reference period is generally the calendar week that
   includes the 12th of the month. Persons who miss the entire week's work for weather-
   related events are counted as employed whether or not they are paid for the time
   off. The household survey collects data on the number of persons who had a job but
   were not at work due to bad weather. It also provides a measure of the number of
   persons who usually work full time but had reduced hours. Current and historical
   data are available on the  household survey's most requested statistics page at

http://data.bls.gov/cgi-bin/surveymost?ln.

Technical Note

   This news release presents statistics from two major surveys, the Current
Population Survey (CPS; household survey) and the Current Employment Statistics
survey (CES; establishment survey). The household survey provides information
on the labor force, employment, and unemployment that appears in the "A" tables,
marked HOUSEHOLD DATA. It is a sample survey of about 60,000 eligible households
conducted by the U.S. Census Bureau for the U.S. Bureau of Labor Statistics (BLS).

   The establishment survey provides information on employment, hours, and
earnings of employees on nonfarm payrolls; the data appear in the "B" tables,
marked ESTABLISHMENT DATA. BLS collects these data each month from the payroll
records of a sample of nonagricultural business establishments. Each month
the CES program surveys about 145,000 businesses and government agencies,
representing approximately 557,000 individual worksites, in order to provide
detailed industry data on employment, hours, and earnings of workers on nonfarm
payrolls. The active sample includes approximately one-third of all nonfarm
payroll employees.

   For both surveys, the data for a given month relate to a particular week or
pay period. In the household survey, the reference period is generally the
calendar week that contains the 12th day of the month. In the establishment
survey, the reference period is the pay period including the 12th, which may or
may not correspond directly to the calendar week.

Coverage, definitions, and differences between surveys

   Household survey. The sample is selected to reflect the entire civilian 
noninstitutional population. Based on responses to a series of questions on 
work and job search activities, each person 16 years and over in a sample
household is classified as employed, unemployed, or not in the labor force.

   People are classified as employed if they did any work at all as paid employees
during the reference week; worked in their own business, profession, or on their
own farm; or worked without pay at least 15 hours in a family business or farm.
People are also counted as employed if they were temporarily absent from their jobs
because of illness, bad weather, vacation, labor-management disputes, or personal
reasons.

   People are classified as unemployed if they meet all of the following criteria:
they had no employment during the reference week; they were available for work at
that time; and they made specific efforts to find employment sometime during the
4-week period ending with the reference week. Persons laid off from a job and
expecting recall need not be looking for work to be counted as unemployed. The
unemployment data derived from the household survey in no way depend upon the
eligibility for or receipt of unemployment insurance benefits.

   The civilian labor force is the sum of employed and unemployed persons.
Those persons not classified as employed or unemployed are not in the labor 
force. The unemployment rate is the number unemployed as a percent of the 
labor force. The labor force participation rate is the labor force as a 
percent of the population, and the employment-population ratio is the 
employed as a percent of the population. Additional information about the 
household survey can be found at www.bls.gov/cps/documentation.htm.

   Establishment survey. The sample establishments are drawn from private
nonfarm businesses such as factories, offices, and stores, as well as
from federal, state, and local government entities. Employees on nonfarm
payrolls are those who received pay for any part of the reference pay
period, including persons on paid leave. Persons are counted in each job
they hold. Hours and earnings data are produced for the private sector for
all employees and for production and nonsupervisory employees. Production
and nonsupervisory employees are defined as production and related employees
in manufacturing and mining and logging, construction workers in construction,
and nonsupervisory employees in private service-providing industries.

   Industries are classified on the basis of an establishment’s principal
activity in accordance with the 2012 version of the North American Industry
Classification System. Additional information about the establishment survey
can be found at www.bls.gov/ces/.

   Differences in employment estimates. The numerous conceptual and methodological
differences between the household and establishment  surveys result in important
distinctions in the employment estimates derived from the surveys. Among these are:

   --The household survey includes agricultural workers, self-employed workers
     whose businesses are unincorporated, unpaid family workers, and private
     household workers among the employed. These groups are excluded from the
     establishment survey.

   --The household survey includes people on unpaid leave among the employed.
     The establishment survey does not.

   --The household survey is limited to workers 16 years of age and older.
     The establishment survey is not limited by age.

   --The household survey has no duplication of individuals, because
     individuals are counted only once, even if they hold more than one
     job. In the establishment survey, employees working at more than one
     job and thus appearing on more than one payroll are counted separately
     for each appearance.

Seasonal adjustment

   Over the course of a year, the size of the nation's labor force and the levels
of employment and unemployment undergo regularly occurring fluctuations. These 
events may result from seasonal changes in weather, major holidays, and the opening
and closing of schools. The effect of such seasonal variation can be very large.

   Because these seasonal events follow a more or less regular pattern each year,
their influence on the level of a series can be tempered by adjusting for regular
seasonal variation. These adjustments make nonseasonal developments, such as
declines in employment or increases in the participation of women in the labor
force, easier to spot. For example, in the household survey, the large number of
youth entering the labor force each June is likely to obscure any other changes
that have taken place relative to May, making it difficult to determine if the 
level of economic activity has risen or declined. Similarly, in the establishment
survey, payroll employment in education declines by about 20 percent at the end
of the spring term and later rises with the start of the fall term, obscuring the
underlying employment trends in the industry. Because seasonal employment changes
at the end and beginning of the school year can be estimated, the statistics can be
adjusted to make underlying employment patterns more discernable.  The seasonally
adjusted figures provide a more useful tool with which to analyze changes in
month-to-month economic activity.

   Many seasonally adjusted series are independently adjusted in both the household
and establishment surveys. However, the adjusted series for many major estimates,
such as total payroll employment, employment in most major sectors, total employment,
and unemployment are computed by aggregating independently adjusted component series.
For example, total unemployment is derived by summing the adjusted series for four
major age-sex components; this differs from the unemployment estimate that would be
obtained by directly adjusting the total or by combining
the duration, reasons, or more detailed age categories.

   For both the household and establishment surveys, a concurrent seasonal adjustment
methodology is used in which new seasonal factors are calculated each month using all
relevant data, up to and including the data for the current month. In the household
survey, new seasonal factors are used to adjust only the current month's data. In the
establishment survey, however, new seasonal factors are used each month to adjust the
three most recent monthly estimates. The prior 2 months are routinely revised to
incorporate additional sample reports and recalculated seasonal adjustment factors.
In both surveys, 5-year revisions to historical data are made once a year.

Reliability of the estimates

   Statistics based on the household and establishment surveys are subject to both
sampling and nonsampling error. When a sample, rather than the entire population,
is surveyed, there is a chance that the sample estimates may differ from the true
population values they represent. The component of this difference that occurs
because samples differ by chance is known as sampling error, and its variability
is measured by the standard error of the estimate. There is about a 90-percent
chance, or level of confidence, that an estimate based on a sample will differ by
no more than 1.6 standard errors from the true population value because of sampling
error. BLS analyses are generally conducted at the 90-percent level of confidence.

   For example, the confidence interval for the monthly change in total nonfarm
employment from the establishment survey is on the order of plus or minus 90,000.
Suppose the estimate of nonfarm employment increases by 50,000 from one month to
the next. The 90-percent confidence interval on the monthly change would range from
-40,000 to +140,000 (50,000 +/- 90,000). These figures do not mean that the sample
results are off by these magnitudes, but rather that there is about a 90-percent
chance that the true over-the-month change lies within this interval. Since this
range includes values of less than zero, we could not say with confidence that
nonfarm employment had, in fact, increased that month. If, however, the reported
nonfarm employment rise was 250,000, then all of the values within the 90- percent
confidence interval would be greater than zero. In this case, it is likely (at
least a 90-percent chance) that nonfarm employment had, in fact, risen that month.
At an unemployment rate of around 6.0 percent, the 90-percent confidence interval
for the monthly change in unemployment as measured by the household survey is
about +/- 300,000, and for the monthly change in the unemployment rate it is about
+/- 0.2 percentage point.

   In general, estimates involving many individuals or establishments have lower
standard errors (relative to the size of the estimate) than estimates which are based
on a small number of observations. The precision of estimates also is improved when
the data are cumulated over time, such as for quarterly and annual averages.

   The household and establishment surveys are also affected by nonsampling error,
which can occur for many reasons, including the failure to sample a segment of the
population, inability to obtain information for all respondents in the sample,
inability or unwillingness of respondents to provide correct information on a
timely basis, mistakes made by respondents, and errors made in the collection or
processing of the data.

   For example, in the establishment survey, estimates for the most recent 2 months
are based on incomplete returns; for this reason, these estimates are labeled
preliminary in the tables. It is only after two successive revisions to a monthly
estimate, when nearly all sample reports have been received, that the estimate is
considered final.

   Another major source of nonsampling error in the establishment survey is the
inability to capture, on a timely basis, employment generated by new firms. To
correct for this systematic underestimation of employment growth, an estimation
procedure with two components is used to account for business births. The first
component excludes employment losses from business deaths from sample-based
estimation in order to offset the missing employment gains from business births.
This is incorporated into the sample-based estimation procedure by simply not
reflecting sample units going out of business, but imputing to them the same
employment trend as the other firms in the sample. This procedure accounts for
most of the net birth/death employment.

   The second component is an ARIMA time series model designed to estimate the
residual net birth/death employment not accounted for by the imputation. The
historical time series used to create and test the ARIMA model was derived from
the unemployment insurance universe micro- level database, and reflects the actual
residual net of births and deaths over the past 5 years.

   The sample-based estimates from the establishment survey are adjusted once a
year (on a lagged basis) to universe counts of payroll employment obtained from
administrative records of the unemployment insurance program. The difference 
between the March sample-based employment estimates and the March universe counts
is known as a benchmark revision, and serves as a rough proxy for total survey
error. The new benchmarks also incorporate changes in the classification of
industries. Over the past decade, absolute benchmark revisions for total nonfarm
employment have averaged 0.3 percent, with a range from -0.7 to 0.6 percent.

Other information

   Information in this release will be made available to sensory impaired
individuals upon request. Voice phone: (202) 691-5200; Federal Relay
Service: (800) 877-8339.
HOUSEHOLD DATA
Table A-1. Employment status of the civilian population by sex and age

[Numbers in thousands]
Employment status, sex, and age Not seasonally adjusted Seasonally adjusted(1)
July
2012
June
2013
July
2013
July
2012
Mar.
2013
Apr.
2013
May
2013
June
2013
July
2013
TOTAL
Civilian noninstitutional population 243,354 245,552 245,756 243,354 244,995 245,175 245,363 245,552 245,756
Civilian labor force 156,526 157,089 157,196 154,995 155,028 155,238 155,658 155,835 155,798
Participation rate 64.3 64.0 64.0 63.7 63.3 63.3 63.4 63.5 63.4
Employed 143,126 144,841 145,113 142,250 143,286 143,579 143,898 144,058 144,285
Employment-population ratio 58.8 59.0 59.0 58.5 58.5 58.6 58.6 58.7 58.7
Unemployed 13,400 12,248 12,083 12,745 11,742 11,659 11,760 11,777 11,514
Unemployment rate 8.6 7.8 7.7 8.2 7.6 7.5 7.6 7.6 7.4
Not in labor force 86,828 88,463 88,560 88,359 89,967 89,936 89,705 89,717 89,957
Persons who currently want a job 6,837 7,152 6,862 6,587 6,722 6,413 6,712 6,580 6,619
Men, 16 years and over
Civilian noninstitutional population 117,381 118,490 118,595 117,381 118,204 118,296 118,393 118,490 118,595
Civilian labor force 83,554 83,837 83,965 82,407 82,584 82,621 82,862 82,898 82,852
Participation rate 71.2 70.8 70.8 70.2 69.9 69.8 70.0 70.0 69.9
Employed 76,691 77,277 77,569 75,512 76,329 76,239 76,299 76,447 76,466
Employment-population ratio 65.3 65.2 65.4 64.3 64.6 64.4 64.4 64.5 64.5
Unemployed 6,863 6,560 6,396 6,895 6,255 6,382 6,564 6,451 6,387
Unemployment rate 8.2 7.8 7.6 8.4 7.6 7.7 7.9 7.8 7.7
Not in labor force 33,828 34,654 34,630 34,975 35,619 35,675 35,531 35,592 35,743
Men, 20 years and over
Civilian noninstitutional population 108,727 109,943 110,054 108,727 109,635 109,736 109,839 109,943 110,054
Civilian labor force 79,758 80,186 80,275 79,376 79,747 79,803 79,878 79,883 79,909
Participation rate 73.4 72.9 72.9 73.0 72.7 72.7 72.7 72.7 72.6
Employed 73,863 74,717 74,854 73,288 74,228 74,159 74,124 74,276 74,328
Employment-population ratio 67.9 68.0 68.0 67.4 67.7 67.6 67.5 67.6 67.5
Unemployed 5,894 5,469 5,421 6,089 5,519 5,644 5,754 5,607 5,581
Unemployment rate 7.4 6.8 6.8 7.7 6.9 7.1 7.2 7.0 7.0
Not in labor force 28,969 29,757 29,778 29,351 29,888 29,933 29,961 30,060 30,145
Women, 16 years and over
Civilian noninstitutional population 125,972 127,062 127,161 125,972 126,791 126,878 126,970 127,062 127,161
Civilian labor force 72,972 73,253 73,231 72,588 72,443 72,617 72,796 72,938 72,946
Participation rate 57.9 57.7 57.6 57.6 57.1 57.2 57.3 57.4 57.4
Employed 66,435 67,565 67,543 66,738 66,956 67,340 67,599 67,612 67,819
Employment-population ratio 52.7 53.2 53.1 53.0 52.8 53.1 53.2 53.2 53.3
Unemployed 6,537 5,688 5,688 5,850 5,487 5,277 5,197 5,326 5,127
Unemployment rate 9.0 7.8 7.8 8.1 7.6 7.3 7.1 7.3 7.0
Not in labor force 53,000 53,809 53,930 53,384 54,348 54,261 54,174 54,124 54,215
Women, 20 years and over
Civilian noninstitutional population 117,648 118,804 118,907 117,648 118,520 118,612 118,708 118,804 118,907
Civilian labor force 69,402 69,899 69,656 69,673 69,544 69,744 69,895 70,075 70,033
Participation rate 59.0 58.8 58.6 59.2 58.7 58.8 58.9 59.0 58.9
Employed 63,703 64,981 64,754 64,437 64,707 65,101 65,329 65,314 65,489
Employment-population ratio 54.1 54.7 54.5 54.8 54.6 54.9 55.0 55.0 55.1
Unemployed 5,700 4,918 4,902 5,236 4,837 4,642 4,566 4,761 4,544
Unemployment rate 8.2 7.0 7.0 7.5 7.0 6.7 6.5 6.8 6.5
Not in labor force 48,246 48,905 49,251 47,975 48,976 48,868 48,813 48,730 48,875
Both sexes, 16 to 19 years
Civilian noninstitutional population 16,979 16,805 16,795 16,979 16,840 16,827 16,816 16,805 16,795
Civilian labor force 7,366 7,004 7,264 5,945 5,737 5,692 5,886 5,878 5,857
Participation rate 43.4 41.7 43.3 35.0 34.1 33.8 35.0 35.0 34.9
Employed 5,560 5,143 5,504 4,525 4,351 4,320 4,445 4,469 4,469
Employment-population ratio 32.7 30.6 32.8 26.7 25.8 25.7 26.4 26.6 26.6
Unemployed 1,806 1,860 1,760 1,420 1,386 1,372 1,441 1,409 1,388
Unemployment rate 24.5 26.6 24.2 23.9 24.2 24.1 24.5 24.0 23.7
Not in labor force 9,613 9,801 9,530 11,033 11,103 11,135 10,930 10,927 10,938
Footnotes
(1) The population figures are not adjusted for seasonal variation; therefore, identical numbers appear in the unadjusted and seasonally adjusted columns.
NOTE: Updated population controls are introduced annually with the release of January data.
HOUSEHOLD DATA
Table A-2. Employment status of the civilian population by race, sex, and age

[Numbers in thousands]
Employment status, race, sex, and age Not seasonally adjusted Seasonally adjusted(1)
July
2012
June
2013
July
2013
July
2012
Mar.
2013
Apr.
2013
May
2013
June
2013
July
2013
WHITE
Civilian noninstitutional population 193,245 194,254 194,373 193,245 193,946 194,041 194,147 194,254 194,373
Civilian labor force 124,749 124,627 124,807 123,578 123,382 123,504 123,844 123,766 123,719
Participation rate 64.6 64.2 64.2 63.9 63.6 63.6 63.8 63.7 63.7
Employed 115,255 116,132 116,321 114,428 115,080 115,266 115,557 115,563 115,552
Employment-population ratio 59.6 59.8 59.8 59.2 59.3 59.4 59.5 59.5 59.4
Unemployed 9,493 8,495 8,486 9,151 8,302 8,238 8,287 8,204 8,167
Unemployment rate 7.6 6.8 6.8 7.4 6.7 6.7 6.7 6.6 6.6
Not in labor force 68,496 69,628 69,565 69,667 70,565 70,537 70,303 70,488 70,654
Men, 20 years and over
Civilian labor force 64,795 64,843 64,906 64,485 64,549 64,674 64,680 64,625 64,595
Participation rate 73.8 73.3 73.3 73.4 73.1 73.2 73.2 73.1 73.0
Employed 60,588 60,951 60,995 60,073 60,594 60,540 60,545 60,620 60,528
Employment-population ratio 69.0 68.9 68.9 68.4 68.7 68.6 68.5 68.6 68.4
Unemployed 4,208 3,892 3,911 4,413 3,955 4,135 4,135 4,005 4,067
Unemployment rate 6.5 6.0 6.0 6.8 6.1 6.4 6.4 6.2 6.3
Women, 20 years and over
Civilian labor force 54,141 54,239 54,204 54,380 54,255 54,221 54,447 54,469 54,501
Participation rate 58.4 58.1 58.0 58.6 58.2 58.2 58.4 58.4 58.4
Employed 50,115 50,893 50,794 50,653 50,940 51,123 51,311 51,222 51,339
Employment-population ratio 54.0 54.5 54.4 54.6 54.7 54.8 55.0 54.9 55.0
Unemployed 4,026 3,346 3,410 3,727 3,315 3,098 3,136 3,247 3,162
Unemployment rate 7.4 6.2 6.3 6.9 6.1 5.7 5.8 6.0 5.8
Both sexes, 16 to 19 years
Civilian labor force 5,812 5,545 5,698 4,713 4,578 4,608 4,717 4,672 4,623
Participation rate 45.9 44.3 45.6 37.2 36.5 36.8 37.7 37.3 37.0
Employed 4,553 4,289 4,532 3,702 3,546 3,603 3,700 3,721 3,685
Employment-population ratio 36.0 34.3 36.2 29.3 28.3 28.8 29.6 29.7 29.5
Unemployed 1,259 1,256 1,165 1,010 1,032 1,005 1,017 951 938
Unemployment rate 21.7 22.7 20.5 21.4 22.5 21.8 21.6 20.4 20.3
BLACK OR AFRICAN AMERICAN
Civilian noninstitutional population 29,918 30,355 30,390 29,918 30,255 30,290 30,322 30,355 30,390
Civilian labor force 18,643 18,852 18,825 18,424 18,524 18,617 18,723 18,636 18,671
Participation rate 62.3 62.1 61.9 61.6 61.2 61.5 61.7 61.4 61.4
Employed 15,845 16,154 16,311 15,833 16,068 16,167 16,202 16,090 16,318
Employment-population ratio 53.0 53.2 53.7 52.9 53.1 53.4 53.4 53.0 53.7
Unemployed 2,799 2,698 2,513 2,590 2,456 2,450 2,521 2,546 2,353
Unemployment rate 15.0 14.3 13.4 14.1 13.3 13.2 13.5 13.7 12.6
Not in labor force 11,274 11,502 11,565 11,494 11,731 11,673 11,599 11,719 11,719
Men, 20 years and over
Civilian labor force 8,307 8,411 8,450 8,277 8,447 8,377 8,441 8,358 8,434
Participation rate 68.1 67.5 67.7 67.9 68.1 67.4 67.9 67.1 67.6
Employed 7,071 7,331 7,398 7,049 7,370 7,319 7,301 7,270 7,382
Employment-population ratio 58.0 58.9 59.3 57.8 59.4 58.9 58.7 58.4 59.2
Unemployed 1,236 1,079 1,052 1,228 1,077 1,058 1,140 1,088 1,052
Unemployment rate 14.9 12.8 12.4 14.8 12.7 12.6 13.5 13.0 12.5
Women, 20 years and over
Civilian labor force 9,361 9,551 9,444 9,371 9,365 9,529 9,562 9,556 9,508
Participation rate 62.1 62.3 61.5 62.1 61.3 62.3 62.5 62.3 62.0
Employed 8,170 8,365 8,382 8,290 8,226 8,425 8,487 8,413 8,510
Employment-population ratio 54.2 54.6 54.6 55.0 53.9 55.1 55.4 54.9 55.5
Unemployed 1,190 1,186 1,063 1,080 1,139 1,105 1,074 1,143 998
Unemployment rate 12.7 12.4 11.3 11.5 12.2 11.6 11.2 12.0 10.5
Both sexes, 16 to 19 years
Civilian labor force 976 891 930 776 713 711 720 722 729
Participation rate 37.0 34.7 36.3 29.4 27.6 27.5 28.0 28.1 28.4
Employed 604 458 531 494 472 423 413 407 426
Employment-population ratio 22.9 17.8 20.7 18.7 18.2 16.4 16.1 15.8 16.6
Unemployed 372 433 399 282 241 287 307 315 303
Unemployment rate 38.1 48.6 42.9 36.3 33.8 40.5 42.6 43.6 41.6
ASIAN
Civilian noninstitutional population 12,812 13,291 13,298 - - - - - -
Civilian labor force 8,346 8,737 8,641 - - - - - -
Participation rate 65.1 65.7 65.0 - - - - - -
Employed 7,830 8,302 8,153 - - - - - -
Employment-population ratio 61.1 62.5 61.3 - - - - - -
Unemployed 516 435 488 - - - - - -
Unemployment rate 6.2 5.0 5.7 - - - - - -
Not in labor force 4,466 4,554 4,657 - - - - - -
Footnotes
(1) The population figures are not adjusted for seasonal variation; therefore, identical numbers appear in the unadjusted and seasonally adjusted columns.
- Data not available.
NOTE: Estimates for the above race groups will not sum to totals shown in table A-1 because data are not presented for all races. Updated population controls are introduced annually with the release of January data.
HOUSEHOLD DATA
Table A-3. Employment status of the Hispanic or Latino population by sex and age

[Numbers in thousands]
Employment status, sex, and age Not seasonally adjusted Seasonally adjusted(1)
July
2012
June
2013
July
2013
July
2012
Mar.
2013
Apr.
2013
May
2013
June
2013
July
2013
HISPANIC OR LATINO ETHNICITY
Civilian noninstitutional population 36,792 37,471 37,548 36,792 37,242 37,320 37,395 37,471 37,548
Civilian labor force 24,627 24,975 25,220 24,467 24,354 24,512 24,848 24,869 25,040
Participation rate 66.9 66.7 67.2 66.5 65.4 65.7 66.4 66.4 66.7
Employed 22,092 22,698 22,822 21,950 22,122 22,310 22,583 22,601 22,675
Employment-population ratio 60.0 60.6 60.8 59.7 59.4 59.8 60.4 60.3 60.4
Unemployed 2,536 2,277 2,398 2,517 2,232 2,202 2,265 2,267 2,366
Unemployment rate 10.3 9.1 9.5 10.3 9.2 9.0 9.1 9.1 9.4
Not in labor force 12,164 12,495 12,328 12,325 12,888 12,808 12,547 12,602 12,508
Men, 20 years and over
Civilian labor force 13,426 13,768 13,847 - - - - - -
Participation rate 81.0 81.4 81.7 - - - - - -
Employed 12,325 12,731 12,784 - - - - - -
Employment-population ratio 74.4 75.3 75.5 - - - - - -
Unemployed 1,102 1,036 1,063 - - - - - -
Unemployment rate 8.2 7.5 7.7 - - - - - -
Women, 20 years and over
Civilian labor force 9,814 9,914 9,930 - - - - - -
Participation rate 59.3 58.6 58.6 - - - - - -
Employed 8,788 9,057 9,041 - - - - - -
Employment-population ratio 53.1 53.5 53.3 - - - - - -
Unemployed 1,027 857 889 - - - - - -
Unemployment rate 10.5 8.6 9.0 - - - - - -
Both sexes, 16 to 19 years
Civilian labor force 1,386 1,293 1,443 - - - - - -
Participation rate 37.9 35.4 39.5 - - - - - -
Employed 979 910 997 - - - - - -
Employment-population ratio 26.8 24.9 27.3 - - - - - -
Unemployed 407 383 446 - - - - - -
Unemployment rate 29.4 29.6 30.9 - - - - - -
Footnotes
(1) The population figures are not adjusted for seasonal variation; therefore, identical numbers appear in the unadjusted and seasonally adjusted columns.
- Data not available.
NOTE: Persons whose ethnicity is identified as Hispanic or Latino may be of any race. Updated population controls are introduced annually with the release of January data.
HOUSEHOLD DATA
Table A-4. Employment status of the civilian population 25 years and over by educational attainment

[Numbers in thousands]
Educational attainment Not seasonally adjusted Seasonally adjusted
July
2012
June
2013
July
2013
July
2012
Mar.
2013
Apr.
2013
May
2013
June
2013
July
2013
Less than a high school diploma
Civilian labor force 11,457 11,414 10,886 11,446 11,264 10,999 11,237 11,161 10,889
Participation rate 46.2 45.5 45.4 46.2 46.0 44.8 45.0 44.5 45.4
Employed 10,062 10,312 9,723 9,997 10,012 9,725 9,993 9,969 9,692
Employment-population ratio 40.6 41.1 40.5 40.3 40.9 39.6 40.0 39.8 40.4
Unemployed 1,395 1,102 1,163 1,449 1,252 1,274 1,243 1,192 1,197
Unemployment rate 12.2 9.7 10.7 12.7 11.1 11.6 11.1 10.7 11.0
High school graduates, no college(1)
Civilian labor force 36,782 36,324 36,722 37,014 36,121 36,200 36,236 36,320 36,741
Participation rate 59.2 59.1 59.0 59.6 58.6 58.7 58.9 59.1 59.0
Employed 33,676 33,681 33,995 33,823 33,359 33,510 33,572 33,562 33,950
Employment-population ratio 54.2 54.8 54.6 54.5 54.1 54.3 54.6 54.6 54.5
Unemployed 3,105 2,643 2,727 3,191 2,762 2,689 2,664 2,757 2,791
Unemployment rate 8.4 7.3 7.4 8.6 7.6 7.4 7.4 7.6 7.6
Some college or associate degree
Civilian labor force 37,299 36,943 37,252 37,414 37,232 37,371 37,470 37,297 37,341
Participation rate 68.1 67.4 67.1 68.3 68.1 68.4 68.5 68.1 67.3
Employed 34,546 34,561 34,931 34,772 34,845 34,992 35,036 34,925 35,105
Employment-population ratio 63.1 63.1 62.9 63.5 63.8 64.1 64.0 63.7 63.2
Unemployed 2,752 2,382 2,320 2,642 2,387 2,379 2,435 2,372 2,237
Unemployment rate 7.4 6.4 6.2 7.1 6.4 6.4 6.5 6.4 6.0
Bachelor’s degree and higher(2)
Civilian labor force 47,517 49,086 48,831 47,675 49,236 49,492 49,473 49,466 49,173
Participation rate 75.5 75.1 75.0 75.8 75.3 75.6 75.8 75.6 75.5
Employed 45,381 47,163 46,779 45,711 47,371 47,563 47,581 47,537 47,281
Employment-population ratio 72.1 72.1 71.8 72.6 72.5 72.7 72.9 72.7 72.6
Unemployed 2,136 1,923 2,051 1,964 1,865 1,929 1,892 1,929 1,891
Unemployment rate 4.5 3.9 4.2 4.1 3.8 3.9 3.8 3.9 3.8
Footnotes
(1) Includes persons with a high school diploma or equivalent.
(2) Includes persons with bachelor’s, master’s, professional, and doctoral degrees.
NOTE: Updated population controls are introduced annually with the release of January data.
HOUSEHOLD DATA
Table A-5. Employment status of the civilian population 18 years and over by veteran status, period of service, and sex, not seasonally adjusted

[Numbers in thousands]
Employment status, veteran status, and period of service Total Men Women
July
2012
July
2013
July
2012
July
2013
July
2012
July
2013
VETERANS, 18 years and over
Civilian noninstitutional population 21,163 21,384 19,349 19,159 1,814 2,225
Civilian labor force 10,925 10,923 9,845 9,529 1,080 1,395
Participation rate 51.6 51.1 50.9 49.7 59.5 62.7
Employed 10,173 10,221 9,171 8,918 1,002 1,303
Employment-population ratio 48.1 47.8 47.4 46.5 55.2 58.6
Unemployed 752 702 674 610 79 92
Unemployment rate 6.9 6.4 6.8 6.4 7.3 6.6
Not in labor force 10,238 10,461 9,504 9,630 734 830
Gulf War-era II veterans
Civilian noninstitutional population 2,453 2,728 2,056 2,197 397 530
Civilian labor force 1,945 2,155 1,683 1,800 263 355
Participation rate 79.3 79.0 81.9 81.9 66.1 67.0
Employed 1,771 1,989 1,524 1,661 247 328
Employment-population ratio 72.2 72.9 74.2 75.6 62.2 61.8
Unemployed 174 166 159 138 15 27
Unemployment rate 8.9 7.7 9.4 7.7 5.9 7.7
Not in labor force 507 573 373 397 135 175
Gulf War-era I veterans
Civilian noninstitutional population 3,158 3,291 2,668 2,664 489 627
Civilian labor force 2,599 2,713 2,237 2,208 361 504
Participation rate 82.3 82.4 83.8 82.9 73.8 80.5
Employed 2,428 2,572 2,098 2,093 330 479
Employment-population ratio 76.9 78.1 78.6 78.6 67.5 76.4
Unemployed 170 141 139 115 31 26
Unemployment rate 6.5 5.2 6.2 5.2 8.5 5.1
Not in labor force 559 578 431 456 128 122
World War II, Korean War, and Vietnam-era veterans
Civilian noninstitutional population 9,868 9,789 9,551 9,421 318 368
Civilian labor force 3,217 2,922 3,125 2,835 92 87
Participation rate 32.6 29.9 32.7 30.1 29.1 23.7
Employed 3,020 2,727 2,932 2,644 88 84
Employment-population ratio 30.6 27.9 30.7 28.1 27.7 22.7
Unemployed 197 195 193 192 4 4
Unemployment rate 6.1 6.7 6.2 6.8 4.6 4.0
Not in labor force 6,652 6,867 6,426 6,586 225 281
Veterans of other service periods
Civilian noninstitutional population 5,684 5,576 5,074 4,876 610 700
Civilian labor force 3,164 3,133 2,800 2,685 364 448
Participation rate 55.7 56.2 55.2 55.1 59.7 64.0
Employed 2,953 2,933 2,617 2,520 336 413
Employment-population ratio 52.0 52.6 51.6 51.7 55.1 58.9
Unemployed 211 200 183 165 28 36
Unemployment rate 6.7 6.4 6.5 6.1 7.7 7.9
Not in labor force 2,520 2,443 2,274 2,191 246 252
NONVETERANS, 18 years and over
Civilian noninstitutional population 213,366 215,592 93,604 94,951 119,762 120,641
Civilian labor force 142,848 143,519 72,405 73,049 70,443 70,470
Participation rate 66.9 66.6 77.4 76.9 58.8 58.4
Employed 130,997 133,021 66,608 67,722 64,389 65,299
Employment-population ratio 61.4 61.7 71.2 71.3 53.8 54.1
Unemployed 11,850 10,498 5,797 5,327 6,054 5,171
Unemployment rate 8.3 7.3 8.0 7.3 8.6 7.3
Not in labor force 70,518 72,072 21,199 21,902 49,319 50,171
NOTE: Veterans served on active duty in the U.S. Armed Forces and were not on active duty at the time of the survey. Nonveterans never served on active duty in the U.S. Armed Forces. Veterans could have served anywhere in the world during these periods of service: Gulf War era II (September 2001-present), Gulf War era I (August 1990-August 2001), Vietnam era (August 1964-April 1975), Korean War (July 1950-January 1955), World War II (December 1941-December 1946), and other service periods (all other time periods). Veterans who served in more than one wartime period are classified only in the most recent one. Veterans who served during one of the selected wartime periods and another period are classified only in the wartime period. Beginning with data for January 2013, estimates for veterans incorporate population controls derived from the updated Department of Veterans Affairs’ population model.
HOUSEHOLD DATA
Table A-6. Employment status of the civilian population by sex, age, and disability status, not seasonally adjusted

[Numbers in thousands]
Employment status, sex, and age Persons with a disability Persons with no disability
July
2012
July
2013
July
2012
July
2013
TOTAL, 16 years and over
Civilian noninstitutional population 28,007 28,406 215,346 217,349
Civilian labor force 5,791 5,778 150,735 151,418
Participation rate 20.7 20.3 70.0 69.7
Employed 5,004 4,926 138,122 140,186
Employment-population ratio 17.9 17.3 64.1 64.5
Unemployed 787 852 12,613 11,231
Unemployment rate 13.6 14.7 8.4 7.4
Not in labor force 22,216 22,628 64,611 65,932
Men, 16 to 64 years
Civilian labor force 2,612 2,638 76,636 76,858
Participation rate 34.4 35.3 83.9 83.6
Employed 2,289 2,240 70,401 71,084
Employment-population ratio 30.2 30.0 77.0 77.3
Unemployed 323 398 6,235 5,774
Unemployment rate 12.4 15.1 8.1 7.5
Not in labor force 4,971 4,841 14,742 15,073
Women, 16 to 64 years
Civilian labor force 2,207 2,188 67,470 67,576
Participation rate 28.7 28.3 71.2 71.0
Employed 1,817 1,778 61,567 62,468
Employment-population ratio 23.6 23.0 64.9 65.7
Unemployed 390 410 5,903 5,108
Unemployment rate 17.7 18.7 8.7 7.6
Not in labor force 5,487 5,556 27,352 27,574
Both sexes, 65 years and over
Civilian labor force 973 953 6,629 6,984
Participation rate 7.6 7.2 22.7 23.1
Employed 898 908 6,155 6,634
Employment-population ratio 7.1 6.9 21.1 21.9
Unemployed 74 44 474 350
Unemployment rate 7.6 4.7 7.2 5.0
Not in labor force 11,758 12,232 22,517 23,285
NOTE: A person with a disability has at least one of the following conditions: is deaf or has serious difficulty hearing; is blind or has serious difficulty seeing even when wearing glasses; has serious difficulty concentrating, remembering, or making decisions because of a physical, mental, or emotional condition; has serious difficulty walking or climbing stairs; has difficulty dressing or bathing; or has difficulty doing errands alone such as visiting a doctor’s office or shopping because of a physical, mental, or emotional condition. Updated population controls are introduced annually with the release of January data.
HOUSEHOLD DATA
Table A-7. Employment status of the civilian population by nativity and sex, not seasonally adjusted

[Numbers in thousands]
Employment status and nativity Total Men Women
July
2012
July
2013
July
2012
July
2013
July
2012
July
2013
Foreign born, 16 years and over
Civilian noninstitutional population 37,627 37,941 18,428 18,391 19,199 19,550
Civilian labor force 25,180 25,382 14,575 14,634 10,606 10,748
Participation rate 66.9 66.9 79.1 79.6 55.2 55.0
Employed 23,211 23,689 13,553 13,767 9,657 9,922
Employment-population ratio 61.7 62.4 73.5 74.9 50.3 50.8
Unemployed 1,970 1,693 1,021 867 948 825
Unemployment rate 7.8 6.7 7.0 5.9 8.9 7.7
Not in labor force 12,446 12,559 3,853 3,757 8,593 8,802
Native born, 16 years and over
Civilian noninstitutional population 205,727 207,815 98,954 100,204 106,774 107,611
Civilian labor force 131,346 131,814 68,979 69,331 62,367 62,483
Participation rate 63.8 63.4 69.7 69.2 58.4 58.1
Employed 119,916 121,424 63,137 63,803 56,778 57,621
Employment-population ratio 58.3 58.4 63.8 63.7 53.2 53.5
Unemployed 11,430 10,390 5,842 5,528 5,589 4,862
Unemployment rate 8.7 7.9 8.5 8.0 9.0 7.8
Not in labor force 74,381 76,001 29,975 30,873 44,407 45,128
NOTE: The foreign born are those residing in the United States who were not U.S. citizens at birth. That is, they were born outside the United States or one of its outlying areas such as Puerto Rico or Guam, to parents neither of whom was a U.S. citizen. The native born are persons who were born in the United States or one of its outlying areas such as Puerto Rico or Guam or who were born abroad of at least one parent who was a U.S. citizen. Updated population controls are introduced annually with the release of January data.
HOUSEHOLD DATA
Table A-8. Employed persons by class of worker and part-time status

[In thousands]
Category Not seasonally adjusted Seasonally adjusted
July
2012
June
2013
July
2013
July
2012
Mar.
2013
Apr.
2013
May
2013
June
2013
July
2013
CLASS OF WORKER
Agriculture and related industries 2,477 2,234 2,435 2,224 2,001 2,017 2,059 2,067 2,159
Wage and salary workers(1) 1,584 1,380 1,494 1,397 1,250 1,227 1,263 1,268 1,303
Self-employed workers, unincorporated 843 836 915 786 710 772 793 790 842
Unpaid family workers 49 18 25 - - - - - -
Nonagricultural industries 140,649 142,607 142,678 140,013 141,317 141,592 141,890 142,004 142,165
Wage and salary workers(1) 131,619 133,652 133,606 131,154 132,761 132,847 133,201 133,273 133,224
Government 19,332 19,719 19,151 20,100 20,633 20,269 20,361 20,157 20,041
Private industries 112,287 113,932 114,455 110,990 112,147 112,558 112,865 113,167 113,164
Private households 818 702 704 - - - - - -
Other industries 111,469 113,230 113,752 110,255 111,462 111,932 112,274 112,552 112,535
Self-employed workers, unincorporated 8,957 8,885 9,010 8,845 8,407 8,651 8,597 8,643 8,831
Unpaid family workers 74 71 62 - - - - - -
PERSONS AT WORK PART TIME(2)
All industries
Part time for economic reasons(3) 8,316 8,440 8,324 8,245 7,638 7,916 7,904 8,226 8,245
Slack work or business conditions 5,235 5,222 5,140 5,319 4,906 5,129 4,841 5,193 5,177
Could only find part-time work 2,637 2,748 2,757 2,568 2,576 2,527 2,721 2,652 2,665
Part time for noneconomic reasons(4) 17,200 17,931 17,503 18,846 18,745 18,908 18,934 19,044 19,128
Nonagricultural industries
Part time for economic reasons(3) 8,218 8,328 8,207 8,104 7,544 7,793 7,797 8,111 8,101
Slack work or business conditions 5,175 5,150 5,068 5,258 4,832 5,058 4,778 5,120 5,106
Could only find part-time work 2,607 2,717 2,732 2,558 2,510 2,454 2,686 2,632 2,665
Part time for noneconomic reasons(4) 16,863 17,644 17,201 18,519 18,435 18,542 18,511 18,696 18,779
Footnotes
(1) Includes self-employed workers whose businesses are incorporated.
(2) Refers to those who worked 1 to 34 hours during the survey reference week and excludes employed persons who were absent from their jobs for the entire week.
(3) Refers to those who worked 1 to 34 hours during the reference week for an economic reason such as slack work or unfavorable business conditions, inability to find full-time work, or seasonal declines in demand.
(4) Refers to persons who usually work part time for noneconomic reasons such as childcare problems, family or personal obligations, school or training, retirement or Social Security limits on earnings, and other reasons. This excludes persons who usually work full time but worked only 1 to 34 hours during the reference week for reasons such as vacations, holidays, illness, and bad weather.
- Data not available.
NOTE: Detail for the seasonally adjusted data shown in this table will not necessarily add to totals because of the independent seasonal adjustment of the various series. Updated population controls are introduced annually with the release of January data.
HOUSEHOLD DATA
Table A-9. Selected employment indicators

[Numbers in thousands]
Characteristic Not seasonally adjusted Seasonally adjusted
July
2012
June
2013
July
2013
July
2012
Mar.
2013
Apr.
2013
May
2013
June
2013
July
2013
AGE AND SEX
Total, 16 years and over 143,126 144,841 145,113 142,250 143,286 143,579 143,898 144,058 144,285
16 to 19 years 5,560 5,143 5,504 4,525 4,351 4,320 4,445 4,469 4,469
16 to 17 years 1,956 1,676 1,870 1,538 1,482 1,490 1,505 1,451 1,460
18 to 19 years 3,604 3,467 3,634 3,007 2,868 2,834 2,937 3,027 3,034
20 years and over 137,566 139,698 139,608 137,725 138,935 139,260 139,453 139,589 139,816
20 to 24 years 13,901 13,981 14,180 13,380 13,382 13,569 13,412 13,605 13,654
25 years and over 123,665 125,717 125,428 124,279 125,615 125,678 126,057 125,978 126,087
25 to 54 years 93,769 94,390 94,247 94,000 94,409 94,393 94,569 94,461 94,476
25 to 34 years 30,601 31,206 31,168 30,554 31,180 31,133 31,292 31,217 31,176
35 to 44 years 30,389 30,523 30,582 30,523 30,620 30,637 30,691 30,570 30,686
45 to 54 years 32,779 32,661 32,497 32,924 32,610 32,623 32,586 32,675 32,613
55 years and over 29,896 31,326 31,181 30,279 31,206 31,285 31,488 31,517 31,612
Men, 16 years and over 76,691 77,277 77,569 75,512 76,329 76,239 76,299 76,447 76,466
16 to 19 years 2,827 2,560 2,715 2,224 2,101 2,080 2,175 2,171 2,138
16 to 17 years 912 832 929 666 645 653 686 696 679
18 to 19 years 1,916 1,728 1,786 1,560 1,444 1,426 1,485 1,495 1,457
20 years and over 73,863 74,717 74,854 73,288 74,228 74,159 74,124 74,276 74,328
20 to 24 years 7,313 7,193 7,412 6,936 7,006 6,990 6,917 6,952 7,037
25 years and over 66,550 67,524 67,442 66,323 67,205 67,095 67,192 67,331 67,270
25 to 54 years 50,581 50,878 50,882 50,263 50,669 50,565 50,613 50,672 50,592
25 to 34 years 16,726 16,987 16,971 16,561 16,980 16,887 16,961 16,944 16,849
35 to 44 years 16,583 16,607 16,680 16,500 16,655 16,673 16,660 16,602 16,597
45 to 54 years 17,272 17,284 17,231 17,202 17,034 17,005 16,992 17,125 17,146
55 years and over 15,969 16,646 16,560 16,060 16,536 16,530 16,578 16,659 16,678
Women, 16 years and over 66,435 67,565 67,543 66,738 66,956 67,340 67,599 67,612 67,819
16 to 19 years 2,733 2,584 2,789 2,301 2,250 2,239 2,271 2,298 2,330
16 to 17 years 1,045 844 941 871 837 837 819 755 781
18 to 19 years 1,688 1,739 1,848 1,447 1,424 1,408 1,452 1,532 1,577
20 years and over 63,703 64,981 64,754 64,437 64,707 65,101 65,329 65,314 65,489
20 to 24 years 6,588 6,789 6,768 6,443 6,376 6,578 6,495 6,653 6,617
25 years and over 57,115 58,192 57,986 57,956 58,411 58,583 58,866 58,647 58,817
25 to 54 years 43,188 43,512 43,365 43,737 43,740 43,828 43,955 43,790 43,884
25 to 34 years 13,875 14,220 14,197 13,992 14,200 14,246 14,330 14,272 14,327
35 to 44 years 13,805 13,915 13,902 14,023 13,965 13,964 14,030 13,968 14,089
45 to 54 years 15,507 15,377 15,265 15,722 15,575 15,619 15,595 15,550 15,467
55 years and over 13,927 14,680 14,621 14,219 14,670 14,755 14,910 14,857 14,934
MARITAL STATUS
Married men, spouse present 43,743 43,923 43,873 43,764 44,007 44,024 44,176 43,963 43,914
Married women, spouse present 33,734 34,276 33,950 34,365 34,319 34,346 34,716 34,672 34,622
Women who maintain families 9,354 9,348 9,291 - - - - - -
FULL- OR PART-TIME STATUS
Full-time workers(1) 116,131 117,400 117,688 114,478 115,903 116,053 116,238 115,998 116,090
Part-time workers(2) 26,995 27,442 27,425 27,890 27,442 27,549 27,699 28,059 28,233
MULTIPLE JOBHOLDERS
Total multiple jobholders 6,741 6,990 6,897 6,871 7,102 6,983 6,918 7,065 7,036
Percent of total employed 4.7 4.8 4.8 4.8 5.0 4.9 4.8 4.9 4.9
SELF-EMPLOYMENT
Self-employed workers, incorporated 5,256 5,170 5,187 - - - - - -
Self-employed workers, unincorporated 9,800 9,720 9,925 9,630 9,117 9,423 9,390 9,432 9,673
Footnotes
(1) Employed full-time workers are persons who usually work 35 hours or more per week.
(2) Employed part-time workers are persons who usually work less than 35 hours per week.
- Data not available.
NOTE: Detail for the seasonally adjusted data shown in this table will not necessarily add to totals because of the independent seasonal adjustment of the various series. Updated population controls are introduced annually with the release of January data.
HOUSEHOLD DATA
Table A-10. Selected unemployment indicators, seasonally adjusted
Characteristic Number of
unemployed persons
(in thousands)
Unemployment rates
July
2012
June
2013
July
2013
July
2012
Mar.
2013
Apr.
2013
May
2013
June
2013
July
2013
AGE AND SEX
Total, 16 years and over 12,745 11,777 11,514 8.2 7.6 7.5 7.6 7.6 7.4
16 to 19 years 1,420 1,409 1,388 23.9 24.2 24.1 24.5 24.0 23.7
16 to 17 years 564 522 599 26.8 27.1 27.3 27.5 26.5 29.1
18 to 19 years 859 882 755 22.2 22.1 22.6 22.4 22.6 19.9
20 years and over 11,325 10,368 10,125 7.6 6.9 6.9 6.9 6.9 6.8
20 to 24 years 2,082 2,123 1,962 13.5 13.3 13.1 13.2 13.5 12.6
25 years and over 9,266 8,274 8,163 6.9 6.2 6.1 6.1 6.2 6.1
25 to 54 years 7,248 6,491 6,463 7.2 6.4 6.4 6.4 6.4 6.4
25 to 34 years 2,735 2,579 2,544 8.2 7.4 7.4 7.2 7.6 7.5
35 to 44 years 2,213 1,932 1,952 6.8 6.0 5.8 6.2 5.9 6.0
45 to 54 years 2,299 1,981 1,967 6.5 5.7 5.9 5.9 5.7 5.7
55 years and over 1,973 1,777 1,657 6.1 5.5 5.5 5.3 5.3 5.0
Men, 16 years and over 6,895 6,451 6,387 8.4 7.6 7.7 7.9 7.8 7.7
16 to 19 years 806 844 805 26.6 25.9 26.2 27.1 28.0 27.4
16 to 17 years 286 309 327 30.0 30.7 31.2 31.6 30.8 32.5
18 to 19 years 512 521 460 24.7 23.4 23.9 24.0 25.8 24.0
20 years and over 6,089 5,607 5,581 7.7 6.9 7.1 7.2 7.0 7.0
20 to 24 years 1,224 1,228 1,158 15.0 14.4 14.0 14.6 15.0 14.1
25 years and over 4,865 4,406 4,415 6.8 6.0 6.3 6.3 6.1 6.2
25 to 54 years 3,752 3,436 3,431 6.9 6.1 6.5 6.5 6.4 6.4
25 to 34 years 1,420 1,362 1,404 7.9 7.1 7.6 7.3 7.4 7.7
35 to 44 years 1,150 1,015 1,028 6.5 5.6 5.7 6.1 5.8 5.8
45 to 54 years 1,181 1,059 999 6.4 5.6 6.2 6.2 5.8 5.5
55 years and over 1,113 970 984 6.5 5.7 5.7 5.8 5.5 5.6
Women, 16 years and over 5,850 5,326 5,127 8.1 7.6 7.3 7.1 7.3 7.0
16 to 19 years 614 565 583 21.1 22.4 22.1 21.7 19.7 20.0
16 to 17 years 278 214 272 24.2 24.0 23.8 23.6 22.0 25.8
18 to 19 years 347 361 295 19.3 20.7 21.2 20.6 19.1 15.8
20 years and over 5,236 4,761 4,544 7.5 7.0 6.7 6.5 6.8 6.5
20 to 24 years 858 895 804 11.8 12.0 12.3 11.8 11.9 10.8
25 years and over 4,401 3,868 3,748 7.1 6.3 5.9 5.9 6.2 6.0
25 to 54 years 3,496 3,055 3,032 7.4 6.6 6.2 6.3 6.5 6.5
25 to 34 years 1,315 1,217 1,140 8.6 7.7 7.3 7.1 7.9 7.4
35 to 44 years 1,063 916 924 7.0 6.5 6.0 6.4 6.2 6.2
45 to 54 years 1,118 921 968 6.6 5.7 5.5 5.7 5.6 5.9
55 years and over(1) 979 836 750 6.6 5.2 4.8 4.3 5.4 4.9
MARITAL STATUS
Married men, spouse present 2,276 1,975 1,967 4.9 4.3 4.4 4.4 4.3 4.3
Married women, spouse present 2,074 1,677 1,678 5.7 4.7 4.4 4.4 4.6 4.6
Women who maintain families(1) 1,239 1,123 1,095 11.7 10.7 10.3 9.9 10.7 10.5
FULL- OR PART-TIME STATUS
Full-time workers(2) 10,787 9,956 9,604 8.6 7.9 7.9 7.9 7.9 7.6
Part-time workers(3) 1,953 1,834 1,882 6.5 5.9 6.0 5.9 6.1 6.2
Footnotes
(1) Not seasonally adjusted.
(2) Full-time workers are unemployed persons who have expressed a desire to work full time (35 hours or more per week) or are on layoff from full-time jobs.
(3) Part-time workers are unemployed persons who have expressed a desire to work part time (less than 35 hours per week) or are on layoff from part-time jobs.
NOTE: Detail for the seasonally adjusted data shown in this table will not necessarily add to totals because of the independent seasonal adjustment of the various series. Updated population controls are introduced annually with the release of January data.
HOUSEHOLD DATA
Table A-11. Unemployed persons by reason for unemployment

[Numbers in thousands]
Reason Not seasonally adjusted Seasonally adjusted
July
2012
June
2013
July
2013
July
2012
Mar.
2013
Apr.
2013
May
2013
June
2013
July
2013
NUMBER OF UNEMPLOYED
Job losers and persons who completed temporary jobs 7,151 5,939 5,934 7,106 6,329 6,410 6,147 6,119 5,921
On temporary layoff 1,525 1,139 1,337 1,429 1,107 1,170 997 1,199 1,221
Not on temporary layoff 5,626 4,800 4,597 5,677 5,223 5,240 5,151 4,920 4,700
Permanent job losers 4,377 3,639 3,548 4,368 3,959 3,976 3,822 3,700 3,589
Persons who completed temporary jobs 1,248 1,161 1,049 1,308 1,264 1,264 1,329 1,220 1,111
Job leavers 897 981 996 879 986 864 944 1,030 979
Reentrants 3,579 3,600 3,450 3,374 3,176 3,151 3,333 3,291 3,258
New entrants 1,773 1,728 1,703 1,299 1,316 1,280 1,268 1,259 1,254
PERCENT DISTRIBUTION
Job losers and persons who completed temporary jobs 53.4 48.5 49.1 56.1 53.6 54.8 52.6 52.3 51.9
On temporary layoff 11.4 9.3 11.1 11.3 9.4 10.0 8.5 10.2 10.7
Not on temporary layoff 42.0 39.2 38.0 44.8 44.2 44.8 44.1 42.1 41.2
Job leavers 6.7 8.0 8.2 6.9 8.4 7.4 8.1 8.8 8.6
Reentrants 26.7 29.4 28.6 26.7 26.9 26.9 28.5 28.1 28.5
New entrants 13.2 14.1 14.1 10.3 11.1 10.9 10.8 10.8 11.0
UNEMPLOYED AS A PERCENT OF THE
CIVILIAN LABOR FORCE
Job losers and persons who completed temporary jobs 4.6 3.8 3.8 4.6 4.1 4.1 3.9 3.9 3.8
Job leavers 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.7 0.6
Reentrants 2.3 2.3 2.2 2.2 2.0 2.0 2.1 2.1 2.1
New entrants 1.1 1.1 1.1 0.8 0.8 0.8 0.8 0.8 0.8
NOTE: Updated population controls are introduced annually with the release of January data.
HOUSEHOLD DATA
Table A-12. Unemployed persons by duration of unemployment

[Numbers in thousands]
Duration Not seasonally adjusted Seasonally adjusted
July
2012
June
2013
July
2013
July
2012
Mar.
2013
Apr.
2013
May
2013
June
2013
July
2013
NUMBER OF UNEMPLOYED
Less than 5 weeks 3,021 3,569 2,842 2,697 2,464 2,474 2,706 2,692 2,563
5 to 14 weeks 3,585 2,592 3,348 3,102 2,838 2,848 2,669 2,864 2,869
15 weeks and over 6,794 6,086 5,892 6,923 6,348 6,320 6,306 6,225 6,034
15 to 26 weeks 1,547 1,841 1,570 1,756 1,737 1,967 1,950 1,896 1,788
27 weeks and over 5,247 4,245 4,322 5,167 4,611 4,353 4,357 4,328 4,246
Average (mean) duration, in weeks 37.4 34.1 35.3 38.8 37.1 36.5 36.9 35.6 36.6
Median duration, in weeks 15.2 14.3 13.8 16.8 18.1 17.5 17.3 16.3 15.7
PERCENT DISTRIBUTION
Less than 5 weeks 22.5 29.1 23.5 21.2 21.1 21.3 23.2 22.9 22.4
5 to 14 weeks 26.8 21.2 27.7 24.4 24.4 24.5 22.8 24.3 25.0
15 weeks and over 50.7 49.7 48.8 54.4 54.5 54.3 54.0 52.8 52.6
15 to 26 weeks 11.5 15.0 13.0 13.8 14.9 16.9 16.7 16.1 15.6
27 weeks and over 39.2 34.7 35.8 40.6 39.6 37.4 37.3 36.7 37.0
NOTE: Updated population controls are introduced annually with the release of January data.
HOUSEHOLD DATA
Table A-13. Employed and unemployed persons by occupation, not seasonally adjusted

[Numbers in thousands]
Occupation Employed Unemployed Unemployment
rates
July
2012
July
2013
July
2012
July
2013
July
2012
July
2013
Total, 16 years and over(1) 143,126 145,113 13,400 12,083 8.6 7.7
Management, professional, and related occupations 53,165 54,064 2,666 2,286 4.8 4.1
Management, business, and financial operations occupations 22,943 22,754 912 737 3.8 3.1
Professional and related occupations 30,222 31,309 1,753 1,549 5.5 4.7
Service occupations 26,565 26,768 2,666 2,573 9.1 8.8
Sales and office occupations 32,835 33,142 2,836 2,450 8.0 6.9
Sales and related occupations 15,536 15,840 1,400 1,170 8.3 6.9
Office and administrative support occupations 17,299 17,301 1,436 1,280 7.7 6.9
Natural resources, construction, and maintenance occupations 13,174 13,973 1,529 1,288 10.4 8.4
Farming, fishing, and forestry occupations 1,216 1,157 138 78 10.2 6.3
Construction and extraction occupations 7,157 7,665 1,056 930 12.9 10.8
Installation, maintenance, and repair occupations 4,801 5,151 335 280 6.5 5.2
Production, transportation, and material moving
occupations
17,388 17,167 1,900 1,735 9.8 9.2
Production occupations 8,545 8,337 903 857 9.6 9.3
Transportation and material moving occupations 8,843 8,830 997 878 10.1 9.0
Footnotes
(1) Persons with no previous work experience and persons whose last job was in the U.S. Armed Forces are included in the unemployed total.
NOTE: Updated population controls are introduced annually with the release of January data.
HOUSEHOLD DATA
Table A-14. Unemployed persons by industry and class of worker, not seasonally adjusted
Industry and class of worker Number of
unemployed
persons
(in thousands)
Unemployment
rates
July
2012
July
2013
July
2012
July
2013
Total, 16 years and over(1) 13,400 12,083 8.6 7.7
Nonagricultural private wage and salary workers 9,692 8,683 7.9 7.1
Mining, quarrying, and oil and gas extraction 83 57 7.6 5.1
Construction 994 767 12.3 9.1
Manufacturing 1,128 1,082 7.2 6.9
Durable goods 703 619 7.2 6.3
Nondurable goods 426 463 7.3 7.8
Wholesale and retail trade 1,780 1,389 8.6 6.8
Transportation and utilities 392 388 6.5 6.4
Information 190 172 6.7 5.8
Financial activities 458 412 5.1 4.5
Professional and business services 1,378 1,265 9.1 8.1
Education and health services 1,436 1,283 6.5 5.7
Leisure and hospitality 1,420 1,470 9.7 10.0
Other services 433 396 6.7 6.0
Agriculture and related private wage and salary workers 131 97 7.9 6.5
Government workers 1,182 1,073 5.7 5.3
Self-employed workers, unincorporated, and unpaid family workers 623 528 5.9 5.0
Footnotes
(1) Persons with no previous work experience and persons whose last job was in the U.S. Armed Forces are included in the unemployed total.
NOTE: Updated population controls are introduced annually with the release of January data.
HOUSEHOLD DATA
Table A-15. Alternative measures of labor underutilization

[Percent]
Measure Not seasonally adjusted Seasonally adjusted
July
2012
June
2013
July
2013
July
2012
Mar.
2013
Apr.
2013
May
2013
June
2013
July
2013
U-1 Persons unemployed 15 weeks or longer, as a percent of the civilian labor force 4.3 3.9 3.7 4.5 4.1 4.1 4.1 4.0 3.9
U-2 Job losers and persons who completed temporary jobs, as a percent of the civilian labor force 4.6 3.8 3.8 4.6 4.1 4.1 3.9 3.9 3.8
U-3 Total unemployed, as a percent of the civilian labor force (official unemployment rate) 8.6 7.8 7.7 8.2 7.6 7.5 7.6 7.6 7.4
U-4 Total unemployed plus discouraged workers, as a percent of the civilian labor force plus discouraged workers 9.1 8.4 8.3 8.7 8.1 8.0 8.0 8.2 8.0
U-5 Total unemployed, plus discouraged workers, plus all other persons marginally attached to the labor force, as a percent of the civilian labor force plus all persons marginally attached to the labor force 10.0 9.3 9.1 9.7 8.9 8.9 8.8 9.1 8.8
U-6 Total unemployed, plus all persons marginally attached to the labor force, plus total employed part time for economic reasons, as a percent of the civilian labor force plus all persons marginally attached to the labor force 15.2 14.6 14.3 14.9 13.8 13.9 13.8 14.3 14.0
NOTE: Persons marginally attached to the labor force are those who currently are neither working nor looking for work but indicate that they want and are available for a job and have looked for work sometime in the past 12 months. Discouraged workers, a subset of the marginally attached, have given a job-market related reason for not currently looking for work. Persons employed part time for economic reasons are those who want and are available for full-time work but have had to settle for a part-time schedule. Updated population controls are introduced annually with the release of January data.
HOUSEHOLD DATA
Table A-16. Persons not in the labor force and multiple jobholders by sex, not seasonally adjusted

[Numbers in thousands]
Category Total Men Women
July
2012
July
2013
July
2012
July
2013
July
2012
July
2013
NOT IN THE LABOR FORCE
Total not in the labor force 86,828 88,560 33,828 34,630 53,000 53,930
Persons who currently want a job 6,837 6,862 3,062 3,113 3,775 3,749
Marginally attached to the labor force(1) 2,529 2,414 1,328 1,260 1,200 1,154
Discouraged workers(2) 852 988 514 572 338 416
Other persons marginally attached to the labor force(3) 1,676 1,426 815 688 862 738
MULTIPLE JOBHOLDERS
Total multiple jobholders(4) 6,741 6,897 3,409 3,568 3,333 3,329
Percent of total employed 4.7 4.8 4.4 4.6 5.0 4.9
Primary job full time, secondary job part time 3,459 3,689 1,939 2,061 1,520 1,627
Primary and secondary jobs both part time 1,871 1,810 670 715 1,201 1,094
Primary and secondary jobs both full time 271 289 191 174 80 115
Hours vary on primary or secondary job 1,065 1,038 567 584 498 454
Footnotes
(1) Data refer to persons who want a job, have searched for work during the prior 12 months, and were available to take a job during the reference week, but had not looked for work in the past 4 weeks.
(2) Includes those who did not actively look for work in the prior 4 weeks for reasons such as thinks no work available, could not find work, lacks schooling or training, employer thinks too young or old, and other types of discrimination.
(3) Includes those who did not actively look for work in the prior 4 weeks for such reasons as school or family responsibilities, ill health, and transportation problems, as well as a number for whom reason for nonparticipation was not determined.
(4) Includes a small number of persons who work part time on their primary job and full time on their secondary job(s), not shown separately.
NOTE: Updated population controls are introduced annually with the release of January data.
ESTABLISHMENT DATA
Table B-1. Employees on nonfarm payrolls by industry sector and selected industry detail

[In thousands]
Industry Not seasonally adjusted Seasonally adjusted
July
2012
May
2013
June
2013(p)
July
2013(p)
July
2012
May
2013
June
2013(p)
July
2013(p)
Change from:
June2013 – July2013(p)
Total nonfarm 133,368 136,383 136,777 135,664 133,762 135,688 135,876 136,038 162
Total private 112,746 114,141 114,975 115,081 111,871 113,829 114,025 114,186 161
Goods-producing 18,785 18,663 18,923 18,988 18,436 18,631 18,639 18,643 4
Mining and logging 868 868 881 889 852 868 871 875 4
Logging 52.6 49.6 51.5 52.0 50.8 51.2 51.1 50.2 -0.9
Mining 815.0 818.4 829.7 837.2 800.7 816.3 819.8 824.7 4.9
Oil and gas extraction 190.2 193.1 194.6 196.4 187.6 193.1 192.6 193.9 1.3
Mining, except oil and gas(1) 229.1 226.3 229.8 229.7 221.8 222.3 223.3 223.2 -0.1
Coal mining 86.8 85.6 86.6 86.6 86.4 85.0 85.8 86.1 0.3
Support activities for mining 395.7 399.0 405.3 411.1 391.3 400.9 403.9 407.6 3.7
Construction 5,888 5,834 5,992 6,054 5,627 5,791 5,799 5,793 -6
Construction of buildings 1,274.9 1,259.1 1,290.3 1,301.0 1,236.0 1,261.1 1,261.7 1,262.1 0.4
Residential building 598.7 585.9 602.2 606.8 576.3 584.3 583.6 583.7 0.1
Nonresidential building 676.2 673.2 688.1 694.2 659.7 676.8 678.1 678.4 0.3
Heavy and civil engineering construction 930.2 910.9 940.5 950.4 872.0 888.6 893.2 891.2 -2.0
Specialty trade contractors 3,682.7 3,663.5 3,761.1 3,802.4 3,519.0 3,641.1 3,643.7 3,640.1 -3.6
Residential specialty trade contractors 1,542.7 1,556.0 1,608.7 1,628.8 1,468.7 1,541.9 1,547.2 1,553.4 6.2
Nonresidential specialty trade contractors 2,140.0 2,107.5 2,152.4 2,173.6 2,050.3 2,099.2 2,096.5 2,086.7 -9.8
Manufacturing 12,029 11,961 12,050 12,045 11,957 11,972 11,969 11,975 6
Durable goods 7,525 7,516 7,565 7,548 7,496 7,512 7,512 7,520 8
Wood products 342.6 346.3 349.8 352.9 335.9 345.6 344.8 346.4 1.6
Nonmetallic mineral products 371.8 371.9 375.6 378.4 362.0 367.9 367.2 368.9 1.7
Primary metals 406.7 397.0 395.6 393.0 406.7 395.6 393.9 392.5 -1.4
Fabricated metal products 1,426.3 1,435.2 1,445.2 1,443.8 1,418.5 1,434.3 1,435.3 1,436.8 1.5
Machinery 1,106.1 1,101.7 1,103.7 1,104.3 1,100.9 1,101.1 1,098.3 1,100.0 1.7
Computer and electronic products(1) 1,101.4 1,081.9 1,089.0 1,086.5 1,097.0 1,083.9 1,084.7 1,081.5 -3.2
Computer and peripheral equipment 160.7 161.1 163.3 163.0 159.7 161.6 162.3 161.8 -0.5
Communications equipment 110.0 107.2 107.3 106.6 110.1 107.3 106.9 106.6 -0.3
Semiconductors and electronic components 387.9 378.3 381.0 380.1 386.2 378.9 379.9 378.2 -1.7
Electronic instruments 402.6 396.0 398.2 397.4 400.9 396.5 396.5 395.7 -0.8
Electrical equipment and appliances 373.0 364.3 364.2 366.0 370.6 365.3 362.7 364.1 1.4
Transportation equipment(1) 1,461.6 1,487.6 1,503.2 1,486.7 1,472.0 1,488.0 1,494.2 1,496.2 2.0
Motor vehicles and parts(2) 774.9 802.3 813.2 807.0 788.1 802.5 808.9 818.0 9.1
Furniture and related products 352.5 353.8 358.9 357.9 349.2 352.7 353.8 354.6 0.8
Miscellaneous durable goods manufacturing 582.9 576.1 579.8 578.2 583.1 577.6 577.1 578.5 1.4
Nondurable goods 4,504 4,445 4,485 4,497 4,461 4,460 4,457 4,455 -2
Food manufacturing 1,498.6 1,454.2 1,477.6 1,490.2 1,473.0 1,471.3 1,470.6 1,465.1 -5.5
Textile mills 118.1 114.3 115.9 115.0 118.0 114.3 114.7 114.9 0.2
Textile product mills 116.8 113.7 115.3 114.1 116.1 113.9 113.8 113.6 -0.2
Apparel 147.2 143.7 143.0 139.6 147.6 142.4 141.5 140.7 -0.8
Paper and paper products 380.7 376.1 379.5 379.4 378.9 377.1 377.1 377.4 0.3
Printing and related support activities 464.6 450.0 450.4 449.1 463.5 450.1 448.8 448.0 -0.8
Petroleum and coal products 114.9 115.3 117.0 117.5 111.9 114.0 114.5 114.8 0.3
Chemicals 786.2 795.3 798.9 801.7 782.8 795.6 795.5 797.2 1.7
Plastics and rubber products 649.7 658.7 660.7 662.1 647.4 657.9 657.1 659.7 2.6
Miscellaneous nondurable goods manufacturing 226.9 223.2 226.8 228.7 222.0 223.2 222.9 223.6 0.7
Private service-providing 93,961 95,478 96,052 96,093 93,435 95,198 95,386 95,543 157
Trade, transportation, and utilities 25,485 25,816 25,966 25,978 25,485 25,873 25,921 25,984 63
Wholesale trade 5,721.2 5,758.4 5,791.2 5,803.9 5,685.7 5,748.2 5,755.2 5,768.9 13.7
Durable goods 2,857.4 2,859.0 2,878.3 2,887.1 2,838.2 2,859.5 2,863.1 2,868.8 5.7
Nondurable goods 1,987.2 2,010.7 2,016.8 2,016.8 1,974.3 1,999.4 2,001.2 2,004.3 3.1
Electronic markets and agents and brokers 876.6 888.7 896.1 900.0 873.2 889.3 890.9 895.8 4.9
Retail trade 14,838.5 15,029.7 15,143.8 15,191.7 14,838.9 15,104.5 15,144.2 15,191.0 46.8
Motor vehicle and parts dealers(1) 1,743.4 1,773.1 1,786.2 1,796.9 1,725.1 1,763.5 1,771.5 1,777.7 6.2
Automobile dealers 1,095.3 1,116.1 1,126.3 1,131.0 1,088.5 1,114.2 1,120.4 1,123.9 3.5
Furniture and home furnishings stores 433.7 445.8 444.7 445.8 440.2 452.8 451.3 452.8 1.5
Electronics and appliance stores 502.2 496.3 496.0 498.7 508.2 505.0 505.4 505.9 0.5
Building material and garden supply stores 1,205.2 1,254.1 1,248.2 1,230.4 1,172.7 1,181.7 1,189.9 1,195.6 5.7
Food and beverage stores 2,880.4 2,906.5 2,938.1 2,946.9 2,858.8 2,908.0 2,915.9 2,924.0 8.1
Health and personal care stores 999.1 1,024.6 1,025.1 1,028.0 1,001.3 1,028.7 1,025.4 1,030.5 5.1
Gasoline stations 852.5 856.1 868.4 874.5 839.5 855.6 856.8 860.0 3.2
Clothing and clothing accessories stores 1,380.8 1,388.2 1,412.6 1,429.5 1,396.6 1,440.3 1,449.4 1,453.7 4.3
Sporting goods, hobby, book, and music stores 571.7 564.2 568.8 569.3 583.6 579.0 580.4 580.3 -0.1
General merchandise stores(1) 3,036.3 3,076.3 3,095.1 3,109.1 3,069.1 3,129.6 3,131.0 3,140.1 9.1
Department stores 1,455.4 1,453.2 1,458.5 1,466.1 1,485.9 1,494.8 1,495.1 1,495.3 0.2
Miscellaneous store retailers 799.6 810.4 822.5 825.4 798.1 813.5 818.9 822.0 3.1
Nonstore retailers 433.6 434.1 438.1 437.2 445.7 446.8 448.3 448.4 0.1
Transportation and warehousing 4,372.4 4,469.3 4,469.2 4,422.1 4,411.5 4,463.0 4,463.7 4,468.3 4.6
Air transportation 464.4 447.5 449.6 448.5 460.0 446.3 445.3 444.1 -1.2
Rail transportation 230.3 231.5 231.5 231.5 229.9 230.7 230.8 231.1 0.3
Water transportation 65.5 62.9 63.7 64.9 63.6 62.7 62.4 62.8 0.4
Truck transportation 1,375.3 1,385.8 1,396.2 1,407.2 1,356.2 1,384.5 1,381.5 1,387.8 6.3
Transit and ground passenger transportation 381.8 486.7 462.4 394.8 442.8 467.8 466.6 458.0 -8.6
Pipeline transportation 44.0 45.3 45.4 45.6 43.7 45.3 45.1 45.3 0.2
Scenic and sightseeing transportation 34.8 28.2 33.6 33.7 26.0 26.1 26.5 25.6 -0.9
Support activities for transportation 577.4 583.8 586.3 589.8 577.6 583.8 586.2 590.3 4.1
Couriers and messengers 516.4 518.2 517.5 517.7 528.5 530.9 530.6 532.9 2.3
Warehousing and storage 682.5 679.4 683.0 688.4 683.2 684.9 688.7 690.4 1.7
Utilities 552.8 558.4 562.2 560.0 549.0 557.2 557.7 556.1 -1.6
Information 2,691 2,706 2,697 2,710 2,684 2,695 2,691 2,700 9
Publishing industries, except Internet 740.9 725.7 727.7 731.3 738.2 729.3 728.3 728.1 -0.2
Motion picture and sound recording industries 384.0 407.4 389.5 394.6 377.2 390.6 383.9 388.0 4.1
Broadcasting, except Internet 284.4 284.0 286.5 284.3 284.8 284.9 286.1 284.8 -1.3
Telecommunications 856.7 854.5 856.6 859.7 859.2 857.1 857.5 861.1 3.6
Data processing, hosting and related services 249.8 253.4 254.5 257.4 250.6 251.7 254.2 257.8 3.6
Other information services 175.3 180.6 182.4 182.2 173.5 181.2 180.8 180.5 -0.3
Financial activities 7,847 7,875 7,941 7,971 7,788 7,880 7,893 7,908 15
Finance and insurance 5,851.0 5,882.6 5,913.6 5,932.5 5,833.9 5,894.4 5,903.3 5,915.3 12.0
Monetary authorities – central bank 17.4 16.7 16.9 17.0 17.2 16.8 16.9 16.8 -0.1
Credit intermediation and related
activities(1)
2,582.8 2,605.6 2,616.0 2,624.0 2,575.9 2,610.8 2,614.0 2,617.6 3.6
Depository credit intermediation(1) 1,742.7 1,731.8 1,737.2 1,740.1 1,734.8 1,734.7 1,733.8 1,733.2 -0.6
Commercial banking 1,320.5 1,302.4 1,304.3 1,306.7 1,315.1 1,305.0 1,302.8 1,302.2 -0.6
Securities, commodity contracts, investments 819.7 827.0 833.4 838.8 816.2 830.9 829.5 835.1 5.6
Insurance carriers and related activities 2,343.5 2,347.3 2,360.6 2,365.0 2,337.7 2,349.5 2,356.2 2,358.9 2.7
Funds, trusts, and other financial vehicles 87.6 86.0 86.7 87.7 86.9 86.4 86.7 86.9 0.2
Real estate and rental and leasing 1,996.3 1,992.5 2,027.0 2,038.5 1,954.4 1,985.3 1,989.6 1,992.8 3.2
Real estate 1,442.4 1,443.9 1,465.9 1,475.1 1,417.8 1,440.9 1,445.0 1,448.0 3.0
Rental and leasing services 529.6 525.7 537.7 540.1 512.5 521.3 521.3 521.7 0.4
Lessors of nonfinancial intangible assets 24.3 22.9 23.4 23.3 24.1 23.1 23.3 23.1 -0.2
Professional and business services 18,053 18,492 18,657 18,691 17,965 18,489 18,550 18,586 36
Professional and technical services(1) 7,881.4 8,051.2 8,087.4 8,121.1 7,904.1 8,104.1 8,118.5 8,139.6 21.1
Legal services 1,135.1 1,125.1 1,134.5 1,138.8 1,123.2 1,126.9 1,124.2 1,127.0 2.8
Accounting and bookkeeping services 839.6 896.7 879.5 874.7 912.6 940.4 942.6 945.1 2.5
Architectural and engineering services 1,341.1 1,352.2 1,368.5 1,372.3 1,322.1 1,351.9 1,355.5 1,352.8 -2.7
Computer systems design and related services 1,633.9 1,683.1 1,690.6 1,704.8 1,627.3 1,686.6 1,694.5 1,698.8 4.3
Management and technical consulting services 1,128.4 1,177.4 1,187.5 1,197.3 1,124.6 1,178.5 1,185.4 1,192.3 6.9
Management of companies and enterprises 2,024.0 2,038.0 2,057.6 2,067.2 2,012.6 2,042.1 2,046.9 2,054.2 7.3
Administrative and waste services 8,147.9 8,402.6 8,512.2 8,502.6 8,048.2 8,342.6 8,384.4 8,392.0 7.6
Administrative and support services(1) 7,764.7 8,023.8 8,126.3 8,113.2 7,674.6 7,964.3 8,003.9 8,012.2 8.3
Employment services(1) 3,149.3 3,331.9 3,381.1 3,358.3 3,166.4 3,345.4 3,367.6 3,367.9 0.3
Temporary help services 2,508.1 2,664.8 2,703.9 2,679.0 2,529.6 2,675.4 2,691.6 2,699.3 7.7
Business support services 813.9 838.5 839.1 843.2 829.4 848.3 851.9 855.4 3.5
Services to buildings and dwellings 1,938.9 1,949.4 1,993.4 2,003.9 1,825.7 1,871.4 1,882.3 1,889.2 6.9
Waste management and remediation services 383.2 378.8 385.9 389.4 373.6 378.3 380.5 379.8 -0.7
Education and health services 19,991 20,714 20,460 20,330 20,331 20,646 20,662 20,675 13
Educational services 3,058.4 3,411.3 3,163.4 3,074.8 3,358.0 3,369.5 3,366.9 3,371.9 5.0
Health care and social assistance 16,933.0 17,302.6 17,296.1 17,255.2 16,973.3 17,276.6 17,295.0 17,303.3 8.3
Health care(3) 14,328.2 14,541.2 14,579.1 14,580.6 14,303.5 14,546.5 14,561.3 14,563.8 2.5
Ambulatory health care services(1) 6,319.7 6,502.3 6,521.1 6,517.0 6,319.2 6,500.7 6,513.4 6,520.0 6.6
Offices of physicians 2,393.6 2,427.7 2,433.7 2,432.4 2,393.7 2,433.1 2,434.5 2,433.8 -0.7
Outpatient care centers 653.7 686.7 689.1 690.9 654.4 685.4 688.5 691.3 2.8
Home health care services 1,195.5 1,277.5 1,282.5 1,281.1 1,197.7 1,274.2 1,280.4 1,284.3 3.9
Hospitals 4,801.9 4,822.3 4,831.4 4,835.1 4,788.7 4,829.1 4,829.5 4,825.1 -4.4
Nursing and residential care facilities(1) 3,206.6 3,216.6 3,226.6 3,228.5 3,195.6 3,216.7 3,218.4 3,218.7 0.3
Nursing care facilities 1,670.4 1,660.6 1,663.8 1,660.9 1,665.5 1,660.3 1,659.6 1,657.2 -2.4
Social assistance(1) 2,604.8 2,761.4 2,717.0 2,674.6 2,669.8 2,730.1 2,733.7 2,739.5 5.8
Child day care services 790.0 880.6 830.0 780.2 855.5 852.3 850.6 847.4 -3.2
Leisure and hospitality 14,387 14,368 14,782 14,864 13,743 14,129 14,186 14,209 23
Arts, entertainment, and recreation 2,267.6 2,095.7 2,301.1 2,343.2 1,960.3 2,025.1 2,043.1 2,032.9 -10.2
Performing arts and spectator sports 426.0 447.6 449.2 447.8 399.5 425.9 426.0 421.9 -4.1
Museums, historical sites, and similar institutions 148.4 141.8 147.3 147.7 133.5 136.5 135.3 134.0 -1.3
Amusements, gambling, and recreation 1,693.2 1,506.3 1,704.6 1,747.7 1,427.3 1,462.7 1,481.8 1,477.0 -4.8
Accommodation and food services 12,119.3 12,272.3 12,480.8 12,521.2 11,782.3 12,103.9 12,142.5 12,175.6 33.1
Accommodation 1,965.7 1,835.8 1,932.7 1,979.8 1,815.7 1,829.9 1,833.5 1,828.2 -5.3
Food services and drinking places 10,153.6 10,436.5 10,548.1 10,541.4 9,966.6 10,274.0 10,309.0 10,347.4 38.4
Other services 5,507 5,507 5,549 5,549 5,439 5,486 5,483 5,481 -2
Repair and maintenance 1,199.6 1,207.1 1,203.6 1,201.7 1,192.8 1,201.3 1,195.7 1,195.0 -0.7
Personal and laundry services 1,322.7 1,346.7 1,350.7 1,343.5 1,313.2 1,332.4 1,334.1 1,334.5 0.4
Membership associations and organizations 2,985.1 2,953.2 2,994.4 3,003.6 2,933.1 2,952.2 2,952.7 2,951.1 -1.6
Government 20,622 22,242 21,802 20,583 21,891 21,859 21,851 21,852 1
Federal 2,826.0 2,757.0 2,761.0 2,761.0 2,805.0 2,758.0 2,748.0 2,746.0 -2.0
Federal, except U.S. Postal Service 2,213.2 2,168.2 2,171.9 2,170.0 2,194.6 2,166.1 2,156.4 2,157.2 0.8
U.S. Postal Service 612.9 589.0 589.1 591.0 610.0 592.0 591.6 588.6 -3.0
State government 4,740.0 5,070.0 4,802.0 4,716.0 5,042.0 5,037.0 5,028.0 5,025.0 -3.0
State government education 2,058.1 2,408.7 2,126.0 2,046.4 2,377.8 2,383.1 2,376.2 2,372.8 -3.4
State government, excluding education 2,682.3 2,661.7 2,676.1 2,669.6 2,664.4 2,653.7 2,651.9 2,652.3 0.4
Local government 13,056.0 14,415.0 14,239.0 13,106.0 14,044.0 14,064.0 14,075.0 14,081.0 6.0
Local government education 6,550.7 8,139.0 7,766.0 6,573.1 7,765.7 7,776.0 7,774.1 7,784.2 10.1
Local government, excluding education 6,505.3 6,275.5 6,473.3 6,533.1 6,278.3 6,287.9 6,301.0 6,297.0 -4.0
Footnotes
(1) Includes other industries, not shown separately.
(2) Includes motor vehicles, motor vehicle bodies and trailers, and motor vehicle parts.
(3) Includes ambulatory health care services, hospitals, and nursing and residential care facilities.
(p) Preliminary
ESTABLISHMENT DATA
Table B-2. Average weekly hours and overtime of all employees on private nonfarm payrolls by industry sector, seasonally adjusted
Industry July
2012
May
2013
June
2013(p)
July
2013(p)
AVERAGE WEEKLY HOURS
Total private 34.4 34.5 34.5 34.4
Goods-producing 40.2 40.4 40.4 40.2
Mining and logging 44.1 43.8 44.2 43.9
Construction 38.5 39.1 39.0 38.7
Manufacturing 40.7 40.7 40.8 40.6
Durable goods 41.0 41.1 41.1 40.9
Nondurable goods 40.2 40.2 40.3 40.1
Private service-providing 33.3 33.3 33.3 33.2
Trade, transportation, and utilities 34.5 34.6 34.5 34.5
Wholesale trade 38.6 38.7 38.8 38.7
Retail trade 31.5 31.5 31.4 31.4
Transportation and warehousing 38.3 38.6 38.5 38.5
Utilities 42.0 42.3 42.5 41.9
Information 36.5 36.7 36.9 36.7
Financial activities 37.1 37.3 37.3 37.2
Professional and business services 36.0 36.1 36.0 35.9
Education and health services 32.9 32.8 32.9 32.8
Leisure and hospitality 26.0 26.0 26.0 25.9
Other services 31.7 31.7 31.6 31.7
AVERAGE OVERTIME HOURS
Manufacturing 3.2 3.3 3.4 3.2
Durable goods 3.2 3.3 3.4 3.2
Nondurable goods 3.3 3.4 3.4 3.3
Footnotes
(p) Preliminary
ESTABLISHMENT DATA
Table B-3. Average hourly and weekly earnings of all employees on private nonfarm payrolls by industry sector, seasonally adjusted
Industry Average hourly earnings Average weekly earnings
July
2012
May
2013
June
2013(p)
July
2013(p)
July
2012
May
2013
June
2013(p)
July
2013(p)
Total private $23.54 $23.90 $24.00 $23.98 $809.78 $824.55 $828.00 $824.91
Goods-producing 24.72 25.08 25.21 25.18 993.74 1,013.23 1,018.48 1,012.24
Mining and logging 28.73 29.36 29.71 29.32 1,266.99 1,285.97 1,313.18 1,287.15
Construction 25.78 26.10 26.18 26.21 992.53 1,020.51 1,021.02 1,014.33
Manufacturing 23.94 24.28 24.41 24.37 974.36 988.20 995.93 989.42
Durable goods 25.32 25.70 25.83 25.80 1,038.12 1,056.27 1,061.61 1,055.22
Nondurable goods 21.57 21.83 21.95 21.92 867.11 877.57 884.59 878.99
Private service-providing 23.25 23.62 23.71 23.69 774.23 786.55 789.54 786.51
Trade, transportation, and utilities 20.53 20.89 20.97 20.95 708.29 722.79 723.47 722.78
Wholesale trade 26.84 27.62 27.77 27.77 1,036.02 1,068.89 1,077.48 1,074.70
Retail trade 16.33 16.56 16.61 16.58 514.40 521.64 521.55 520.61
Transportation and warehousing 22.02 22.18 22.24 22.31 843.37 856.15 856.24 858.94
Utilities 34.59 35.22 35.12 35.09 1,452.78 1,489.81 1,492.60 1,470.27
Information 31.82 32.58 32.85 32.68 1,161.43 1,195.69 1,212.17 1,199.36
Financial activities 29.22 30.08 30.27 30.26 1,084.06 1,121.98 1,129.07 1,125.67
Professional and business services 28.09 28.43 28.49 28.47 1,011.24 1,026.32 1,025.64 1,022.07
Education and health services 24.22 24.52 24.63 24.61 796.84 804.26 810.33 807.21
Leisure and hospitality 13.40 13.45 13.46 13.48 348.40 349.70 349.96 349.13
Other services 20.83 21.21 21.26 21.28 660.31 672.36 671.82 674.58
Footnotes
(p) Preliminary
ESTABLISHMENT DATA
Table B-4. Indexes of aggregate weekly hours and payrolls for all employees on private nonfarm payrolls by industry sector, seasonally adjusted

[2007=100]
Industry Index of aggregate weekly hours(1) Index of aggregate weekly payrolls(2)
July
2012
May
2013
June
2013(p)
July
2013(p)
Percent change from:
June
2013 – July
2013(p)
July
2012
May
2013
June
2013(p)
July
2013(p)
Percent change from:
June
2013 – July
2013(p)
Total private 96.4 98.4 98.5 98.4 -0.1 108.2 112.1 112.8 112.5 -0.3
Goods-producing 84.4 85.8 85.8 85.4 -0.5 94.3 97.2 97.8 97.2 -0.6
Mining and logging 118.1 119.5 121.0 120.7 -0.2 136.2 140.8 144.3 142.1 -1.5
Construction 74.7 78.1 78.0 77.3 -0.9 83.7 88.5 88.7 88.0 -0.8
Manufacturing 87.6 87.7 87.9 87.5 -0.5 97.5 99.0 99.7 99.1 -0.6
Durable goods 86.5 86.9 86.9 86.6 -0.3 97.3 99.2 99.7 99.2 -0.5
Nondurable goods 89.5 89.5 89.6 89.2 -0.4 98.0 99.1 99.8 99.2 -0.6
Private service-providing 99.9 101.8 102.0 101.8 -0.2 112.5 116.4 117.1 116.8 -0.3
Trade, transportation, and utilities 95.6 97.4 97.3 97.5 0.2 105.7 109.5 109.8 109.9 0.1
Wholesale trade 95.8 97.1 97.4 97.4 0.0 107.3 111.9 112.9 112.9 0.0
Retail trade 94.9 96.6 96.6 96.9 0.3 102.5 105.8 106.1 106.2 0.1
Transportation and warehousing 96.7 98.6 98.4 98.5 0.1 108.1 111.0 111.0 111.5 0.5
Utilities 99.8 102.0 102.5 100.8 -1.7 114.0 118.7 119.0 116.9 -1.8
Information 89.5 90.3 90.7 90.5 -0.2 101.4 104.8 106.1 105.3 -0.8
Financial activities 94.6 96.3 96.4 96.3 -0.1 107.9 112.9 113.8 113.7 -0.1
Professional and business services 101.7 105.0 105.0 104.9 -0.1 115.8 120.9 121.2 121.0 -0.2
Education and health services 108.9 110.2 110.7 110.4 -0.3 123.6 126.6 127.7 127.3 -0.3
Leisure and hospitality 102.0 104.8 105.2 105.0 -0.2 110.2 113.7 114.3 114.2 -0.1
Other services 95.5 96.4 96.0 96.3 0.3 112.9 116.0 115.8 116.3 0.4
Footnotes
(1) The indexes of aggregate weekly hours are calculated by dividing the current month’s estimates of aggregate hours by the corresponding 2007 annual average aggregate hours. Aggregate hours estimates are the product of estimates of average weekly hours and employment.
(2) The indexes of aggregate weekly payrolls are calculated by dividing the current month’s estimates of aggregate weekly payrolls by the corresponding 2007 annual average aggregate weekly payrolls. Aggregate payrolls estimates are the product of estimates of average hourly earnings, average weekly hours, and employment.
(p) Preliminary
ESTABLISHMENT DATA
Table B-5. Employment of women on nonfarm payrolls by industry sector, seasonally adjusted
Industry Women employees (in thousands) Percent of all employees
July
2012
May
2013
June
2013(p)
July
2013(p)
July
2012
May
2013
June
2013(p)
July
2013(p)
Total nonfarm 66,017 66,981 67,083 67,200 49.4 49.4 49.4 49.4
Total private 53,559 54,513 54,628 54,744 47.9 47.9 47.9 47.9
Goods-producing 4,103 4,107 4,104 4,101 22.3 22.0 22.0 22.0
Mining and logging 114 118 116 116 13.4 13.6 13.3 13.3
Construction 726 741 741 740 12.9 12.8 12.8 12.8
Manufacturing 3,263 3,248 3,247 3,245 27.3 27.1 27.1 27.1
Durable goods 1,735 1,734 1,734 1,735 23.1 23.1 23.1 23.1
Nondurable goods 1,528 1,514 1,513 1,510 34.3 33.9 33.9 33.9
Private service-providing 49,456 50,406 50,524 50,643 52.9 52.9 53.0 53.0
Trade, transportation, and utilities 10,281 10,507 10,535 10,569 40.3 40.6 40.6 40.7
Wholesale trade 1,708.0 1,704.9 1,705.5 1,709.1 30.0 29.7 29.6 29.6
Retail trade 7,412.2 7,615.7 7,641.6 7,671.1 50.0 50.4 50.5 50.5
Transportation and warehousing 1,024.1 1,048.1 1,050.0 1,049.7 23.2 23.5 23.5 23.5
Utilities 137.0 138.3 138.0 138.7 25.0 24.8 24.7 24.9
Information 1,079 1,071 1,069 1,075 40.2 39.7 39.7 39.8
Financial activities 4,518 4,543 4,542 4,548 58.0 57.7 57.5 57.5
Professional and business services 7,950 8,224 8,266 8,310 44.3 44.5 44.6 44.7
Education and health services 15,597 15,837 15,853 15,860 76.7 76.7 76.7 76.7
Leisure and hospitality 7,175 7,344 7,376 7,392 52.2 52.0 52.0 52.0
Other services 2,856 2,880 2,883 2,889 52.5 52.5 52.6 52.7
Government 12,458 12,468 12,455 12,456 56.9 57.0 57.0 57.0
Footnotes
(p) Preliminary
ESTABLISHMENT DATA
Table B-6. Employment of production and nonsupervisory employees on private nonfarm payrolls by industry sector, seasonally adjusted(1)

[In thousands]
Industry July
2012
May
2013
June
2013(p)
July
2013(p)
Total private 92,421 93,995 94,158 94,309
Goods-producing 13,295 13,395 13,385 13,393
Mining and logging 643 639 640 645
Construction 4,217 4,375 4,377 4,371
Manufacturing 8,435 8,381 8,368 8,377
Durable goods 5,182 5,155 5,148 5,162
Nondurable goods 3,253 3,226 3,220 3,215
Private service-providing 79,126 80,600 80,773 80,916
Trade, transportation, and utilities 21,620 21,890 21,933 21,992
Wholesale trade 4,578.1 4,631.6 4,638.8 4,651.7
Retail trade 12,784.5 12,954.3 12,990.5 13,033.5
Transportation and warehousing 3,819.8 3,854.7 3,853.5 3,857.3
Utilities 437.4 449.8 450.0 449.7
Information 2,172 2,187 2,181 2,189
Financial activities 5,995 6,063 6,075 6,090
Professional and business services 14,845 15,301 15,351 15,390
Education and health services 17,833 18,099 18,117 18,129
Leisure and hospitality 12,114 12,485 12,541 12,556
Other services 4,547 4,575 4,575 4,570
Footnotes
(1) Data relate to production employees in mining and logging and manufacturing, construction employees in construction, and nonsupervisory employees in the service-providing industries. These groups account for approximately four-fifths of the total employment on private nonfarm payrolls.
(p) Preliminary
ESTABLISHMENT DATA
Table B-7. Average weekly hours and overtime of production and nonsupervisory employees on private nonfarm payrolls by industry sector, seasonally adjusted(1)
Industry July
2012
May
2013
June
2013(p)
July
2013(p)
AVERAGE WEEKLY HOURS
Total private 33.7 33.7 33.7 33.6
Goods-producing 41.1 41.3 41.3 41.1
Mining and logging 46.8 45.9 45.7 45.7
Construction 39.1 39.7 39.5 39.4
Manufacturing 41.7 41.8 41.8 41.7
Durable goods 42.1 42.1 42.2 42.0
Nondurable goods 41.0 41.2 41.3 41.3
Private service-providing 32.4 32.5 32.4 32.3
Trade, transportation, and utilities 33.7 33.8 33.6 33.5
Wholesale trade 38.6 38.8 38.7 38.6
Retail trade 30.4 30.3 30.1 30.0
Transportation and warehousing 37.9 38.5 38.3 38.3
Utilities 41.3 41.9 41.9 40.9
Information 35.8 35.7 35.9 35.7
Financial activities 36.6 36.7 36.8 36.5
Professional and business services 35.3 35.3 35.2 35.2
Education and health services 32.2 32.2 32.3 32.1
Leisure and hospitality 24.9 25.0 25.0 24.9
Other services 30.7 30.7 30.8 30.6
AVERAGE OVERTIME HOURS
Manufacturing 4.2 4.3 4.3 4.2
Durable goods 4.3 4.3 4.3 4.3
Nondurable goods 4.0 4.2 4.3 4.1
Footnotes
(1) Data relate to production employees in mining and logging and manufacturing, construction employees in construction, and nonsupervisory employees in the service-providing industries. These groups account for approximately four-fifths of the total employment on private nonfarm payrolls.
(p) Preliminary
ESTABLISHMENT DATA
Table B-8. Average hourly and weekly earnings of production and nonsupervisory employees on private nonfarm payrolls by industry sector, seasonally adjusted(1)
Industry Average hourly earnings Average weekly earnings
July
2012
May
2013
June
2013(p)
July
2013(p)
July
2012
May
2013
June
2013(p)
July
2013(p)
Total private $19.77 $20.08 $20.14 $20.14 $666.25 $676.70 $678.72 $676.70
Goods-producing 20.97 21.26 21.27 21.25 861.87 878.04 878.45 873.38
Mining and logging 25.99 27.13 27.07 26.80 1,216.33 1,245.27 1,237.10 1,224.76
Construction 24.02 24.28 24.29 24.28 939.18 963.92 959.46 956.63
Manufacturing 19.11 19.27 19.29 19.28 796.89 805.49 806.32 803.98
Durable goods 20.19 20.32 20.37 20.40 850.00 855.47 859.61 856.80
Nondurable goods 17.34 17.55 17.53 17.47 710.94 723.06 723.99 721.51
Private service-providing 19.52 19.83 19.90 19.91 632.45 644.48 644.76 643.09
Trade, transportation, and utilities 17.46 17.62 17.69 17.67 588.40 595.56 594.38 591.95
Wholesale trade 22.22 22.59 22.64 22.64 857.69 876.49 876.17 873.90
Retail trade 13.83 13.89 13.97 13.97 420.43 420.87 420.50 419.10
Transportation and warehousing 19.58 19.62 19.67 19.65 742.08 755.37 753.36 752.60
Utilities 32.01 31.97 32.10 32.10 1,322.01 1,339.54 1,344.99 1,312.89
Information 27.04 27.61 27.95 27.61 968.03 985.68 1,003.41 985.68
Financial activities 22.82 23.88 23.98 24.04 835.21 876.40 882.46 877.46
Professional and business services 23.21 23.59 23.66 23.67 819.31 832.73 832.83 833.18
Education and health services 21.08 21.38 21.45 21.47 678.78 688.44 692.84 689.19
Leisure and hospitality 11.64 11.74 11.75 11.76 289.84 293.50 293.75 292.82
Other services 17.60 17.83 17.87 17.90 540.32 547.38 550.40 547.74
Footnotes
(1) Data relate to production employees in mining and logging and manufacturing, construction employees in construction, and nonsupervisory employees in the service-providing industries. These groups account for approximately four-fifths of the total employment on private nonfarm payrolls.
(p) Preliminary
ESTABLISHMENT DATA
Table B-9. Indexes of aggregate weekly hours and payrolls for production and nonsupervisory employees on private nonfarm payrolls by industry sector, seasonally adjusted(1)

[2002=100]
Industry Index of aggregate weekly hours(2) Index of aggregate weekly payrolls(3)
July
2012
May
2013
June
2013(p)
July
2013(p)
Percent change from:
June
2013 – July
2013(p)
July
2012
May
2013
June
2013(p)
July
2013(p)
Percent change from:
June
2013 – July
2013(p)
Total private 104.0 105.7 105.9 105.8 -0.1 137.2 141.8 142.4 142.2 -0.1
Goods-producing 83.5 84.5 84.5 84.1 -0.5 107.2 110.1 110.0 109.5 -0.5
Mining and logging 159.9 155.9 155.4 156.6 0.8 241.7 245.9 244.7 244.2 -0.2
Construction 82.6 87.0 86.6 86.2 -0.5 107.1 114.0 113.5 113.1 -0.4
Manufacturing 80.7 80.4 80.3 80.2 -0.1 100.9 101.3 101.3 101.1 -0.2
Durable goods 82.0 81.5 81.6 81.5 -0.1 103.3 103.4 103.8 103.8 0.0
Nondurable goods 78.6 78.3 78.4 78.2 -0.3 96.3 97.1 97.1 96.6 -0.5
Private service-providing 109.4 111.8 111.7 111.6 -0.1 146.4 151.9 152.3 152.2 -0.1
Trade, transportation, and utilities 101.6 103.1 102.7 102.7 0.0 126.5 129.6 129.6 129.5 -0.1
Wholesale trade 104.1 105.8 105.7 105.7 0.0 136.2 140.8 141.0 141.0 0.0
Retail trade 98.4 99.4 99.0 99.0 0.0 116.6 118.3 118.5 118.5 0.0
Transportation and warehousing 109.0 111.7 111.1 111.2 0.1 135.4 139.0 138.6 138.6 0.0
Utilities 92.4 96.4 96.4 94.1 -2.4 123.4 128.6 129.2 126.0 -2.5
Information 88.7 89.1 89.4 89.2 -0.2 118.8 121.8 123.7 121.9 -1.5
Financial activities 103.3 104.7 105.2 104.6 -0.6 145.0 153.9 155.3 154.8 -0.3
Professional and business services 117.4 121.1 121.1 121.4 0.2 162.2 169.9 170.5 171.0 0.3
Education and health services 123.9 125.7 126.2 125.5 -0.6 171.7 176.7 178.0 177.2 -0.4
Leisure and hospitality 110.5 114.3 114.8 114.5 -0.3 146.1 152.4 153.2 152.9 -0.2
Other services 97.9 98.5 98.8 98.1 -0.7 125.5 128.0 128.7 127.9 -0.6
Footnotes
(1) Data relate to production employees in mining and logging and manufacturing, construction employees in construction, and nonsupervisory employees in the service-providing industries. These groups account for approximately four-fifths of the total employment on private nonfarm payrolls.
(2) The indexes of aggregate weekly hours are calculated by dividing the current month’s estimates of aggregate hours by the corresponding 2002 annual average aggregate hours. Aggregate hours estimates are the product of estimates of average weekly hours and employment.
(3) The indexes of aggregate weekly payrolls are calculated by dividing the current month’s estimates of aggregate weekly payrolls by the corresponding 2002 annual average aggregate weekly payrolls. Aggregate payrolls estimates are the product of estimates of average hourly earnings, average weekly hours, and employment.
(p) Preliminary

 

Series Id:           LNS14000006
Seasonally Adjusted
Series title:        (Seas) Unemployment Rate - Black or African American
Labor force status:  Unemployment rate
Type of data:        Percent or rate
Age:                 16 years and over
Race:                Black or African American
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Train Derailment and Crash in Spain Near Santiago De Compostela Kills 80 and Injures 178 Passengers — Photos and Videos

Posted on July 25, 2013. Filed under: Blogroll, Communications, Diasters, Economics, Education, government spending, Law, Life, Links, media, People, Photos, Radio, Regulations, Trains, Transportation, Video | Tags: , , , , , , , , , |

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CCTV Video Shows Spain Train Crash  

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High-speed-train-derails-in-Spain

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Spain Train Crash CAUGHT ON CAMERA! | Moment High Speed Train Derails in Santiago, Spain

BBC News  Spain train crash  Video shows moment of derailment

Derailment Disaster: High-speed train crash in Spain kills dozens

Spain Train Crash: Santiago Train Derailment Killed 78 | Santiago Tren Accidente

Raw: Train Derails in Spain, Dozens Feared Dead  

Spain Train CRASH Near Santiago De Compostela | Accidente Tren en España  

Spain train crash: Dozens killed as high-speed train derails in Santiago de Compostela

Train Crash In Spain: At Least 80 Killed near Santiago de Compostela  

Driver in custody after 80 killed in Spain train crash

By Teresa Medrano and Tracy Rucinski

The driver of a Spanish train that derailed, killing at least 80 people, was under police guard in hospital on Thursday after the dramatic accident which an official source said was caused by excessive speed.

The eight-carriage train came off the tracks, hit a wall and caught fire just outside the pilgrimage destination Santiago de Compostela in northwestern Spain on Wednesday night. It was one of Europe’s worst rail disasters.

The source had knowledge of the official investigation into a crash which brought misery to Santiago on Thursday, the day when it should have celebrated one of Europe’s biggest Christian festivals. Authorities canceled festivities as the city went into mourning.

The Galicia regional supreme court said in a statement the judge investigating the accident had ordered police to take a statement from the driver.

He was being formally investigated and under police guard but not under arrest, the court said. He was in hospital but it was not clear what kind of injuries he had suffered.

Video footage from a security camera showed the train, with 247 people on board, hurtling into a concrete wall at the side of the track as carriages jack-knifed and the engine overturned.

One local official described the aftermath of the crash as like a scene from hell, with bodies strewn next to the tracks.

The impact was so huge one carriage flew several meters into the air and landed on the other side of a high concrete barrier.

Around 94 people were injured, 35 of them, including four children, in a serious condition, the deputy head of the regional government said.

“We heard a massive noise and we went down the tracks. I helped get a few injured and bodies out of the train. I went into one of the cars but I’d rather not tell you what I saw there,” Ricardo Martinez, a 47-year old baker from Santiago de Compostela, told Reuters.

Newspaper accounts cited witnesses as saying the driver, Francisco Jose Garzon, who had helped rescue victims, shouted into a phone: “I’ve derailed! What do I do?”.

The 52-year-old had been a train driver for 30 years, said a spokeswoman for Renfe, the state train company.

A court source told Reuters there was one driver on the train. Previously, a Galicia government source had said there were two.

TRAIN HIT BEND AT SPEED

El Pais newspaper said the driver told the railway station by radio after being trapped in his cabin that the train entered the bend at 190 kilometers per hour (120 mph). An official source said the speed limit on that stretch of twin track, laid in 2011, was 80 kph.

“We’re only human! We’re only human!” the driver told the station, the newspaper said, citing sources close to the investigation. “I hope there are no dead, because this will weigh on my conscience.”

Investigators were trying to find out why the train was going so fast and why security devices to keep speed within permitted limits had not slowed the train.

Operated by state-owned company Renfe, the train was built by Bombardier and Talgo and was around five years old. It had almost the maximum number of passengers.

Spain’s rail safety record is better than the European average, ranking 18th out of 27 countries in terms of railway deaths per kilometers traveled, the European Railway Agency said. There were 218 train accidents in Spain between 2008-2011, well below the EU average of 426 for the same period.

Firefighters called off a strike to help with the disaster, while hospital staff, many operating on reduced salaries because of spending cuts in recession-hit Spain, worked overtime to tend the injured.

The disaster happened at 8.41 p.m. (2:41 p.m. ET) on the eve of a festival dedicated to St. James, one of Jesus’s 12 disciples, whose remains are said to rest in Santiago’s centuries-old cathedral.

The apostle’s shrine is the destination of the famous El Camino de Santiago pilgrimage across the Pyrenees, which has been followed by Christians since the Middle Ages.

“The main mass (in the cathedral) was transformed from a mass of joy into a mass of mourning,” said Italian pilgrim Irene Valsangiacomo.

KING, PM VISIT

One U.S. citizen died in the crash and five were injured, the State Department said in Washington. Mexico said one of its nationals was among the dead.

At least one British citizen was injured, a British embassy spokesman said. People from several other countries were believed to be among the passengers.

People living nearby ran to the site to help emergency workers tend to the wounded. Ana Taboada, a 29-year-old hospital worker, was one of the first on the scene.

“When the dust lifted I saw corpses. I didn’t make it down to the track, because I was helping the passengers that were coming up the embankment,” she told Reuters. “I saw a man trying to break a window with a stone to help those inside get out.”

Prime Minister Mariano Rajoy, who was born in Santiago de Compostela, the capital of Galicia region, visited the site and the main hospital on Thursday. He declared three days of official national mourning for the victims of the disaster.

King Juan Carlos and Queen Sofia also went to Santiago and visited the injured in hospital.

“All of Spain is united in grief with the bereaved families,” the king said.

Both Renfe and state-owned Adif, which is in charge of the tracks, opened an investigation into the derailment.

Passenger Ricardo Montesco told Cadena Ser radio station the train approached the curve at high speed, twisted and the carriages piled up one on top of the other.

“A lot of people were squashed on the bottom. We tried to squeeze out of the bottom of the wagons to get out and we realized the train was burning. … I was in the second carriage and there was fire. … I saw corpses,” he said.

Clinics in Santiago de Compostela were overwhelmed with people flocking to give blood, while hotels organized free rooms for relatives. Madrid sent forensic scientists and hospital staff to the scene on special flights.

Allianz Seguros, owned by Germany’s Allianz, owns the insurance contract for loss suffered by Renfe passengers, a company spokeswoman told Reuters. The contract does not cover Renfe’s trains. The company had sent experts to the scene.

The disaster stirred memories of a train bombing in Madrid in 2004, carried out by Islamist militants, that killed 191 people, although officials do not suspect an attack this time.

Spain is struggling to emerge from a long-running recession marked by government-driven austerity to bring its deeply indebted finances into order.

But Adif, the state railways infrastructure company, told Reuters no budget cuts had been implemented on maintenance of the line, which connects La Coruna, Santiago de Compostela and Ourense and was inaugurated in 2011.

It said more than 100 million euros a year were being spent on track maintenance in Spain.

(Additional reporting by Inmaculada Sanz, Sonya Dowsett, Sarah White, Andres Gonzalez, Blanca Rodriguez, Julien Toyer, Emma Pinedo, Raquel Castillo, Robert Hetz; Writing by Sonya Dowsett and Julien Toyer and Elisabeth O’Leary,; editing by Barry Moody and Andrew Heavens)

http://www.reuters.com/article/2013/07/25/us-spain-train-idUSBRE96N17R20130725

80 dead in Spain crash; video catches train’s final moments

By Al Goodman. Laura Smith-Spark and Laura Perez Maestro, CNN

The train races into view, and in the space of a heartbeat, the cars derail and crash into a wall of concrete, flipping onto their sides and skidding along the track with terrifying speed and force.

Security footage shows the horror of the moment an express train derailed as it hurtled around a curve in northwestern Spain on Wednesday. A spokeswoman for the Spanish government in the Galicia region, speaking on routine condition of anonymity, confirmed 80 people have died in the crash.

One U.S. citizen is among the dead, according to Deputy State Department spokeswoman Marie Harf. At least five U.S. citizens were also injured, she added.

Flames burst out of one train car as another car was snapped in half after the crash. Rescue crews and fellow passengers pulled bodies through broken windows and pried open doors as stunned survivors looked on.

Investigations into the cause of the crash continue, but suggestions that the train was traveling too fast appear to be gaining weight.

The train driver is being questioned by police and is under formal investigation, said Maria Pardo Rios, a spokeswoman for the Galicia regional supreme court. “He is not being charged by a judge at the moment — it is all at a police level,” she said.

Ninety-five of the 178 injured are still hospitalized, the local government’s official Twitter account said. Thirty-two adults and four children are in critical condition.

Most of the deaths happened at the scene, Rios said. In Spain, judges typically record deaths that take place outside of hospitals.

Judicial teams are still at the crash site and expect to find more bodies, she told CNN on Thursday morning.

Interim charge d’affaires Luis G. Moreno at the embassy said it was in touch “with families of some injured American citizens.”

“We are deeply shocked by the news of last night’s train crash in Galicia. Our hearts and prayers are with the friends and families of the victims,” he said Thursday.

UK Foreign Secretary William Hague said one British citizen was injured.

The crash came on the eve of a public holiday held to mark the region’s saint’s day. Local officials canceled festivities planned for Wednesday night and Thursday across Galicia.

Train’s speed questioned

The state railway, Renfe, said the train crashed on a curve several kilometers from the train station in the city of Santiago de Compostela, a popular tourist destination.

The train was nearing the end of a six-hour trip from Madrid to the town of Ferrol in northwest Spain when it derailed at 8:41 p.m. Wednesday, the railway said.

It was unclear how fast the train was traveling when it crashed. It was capable of going up to 250 kilometers per hour (155 mph), said Julio Hermida, a spokesman for the state railway.

The driver, who suffered minor injuries, told police the train had entered the bend too fast, TVE reported.

The driver has worked for the company for the last 30 years, a spokesman for the railway confirmed to CNN. In 2000, the driver started working as a train driver assistant, and in 2003 began working as a train driver, a job the driver has held since.

Rafael Catala, secretary of state for transport and housing, told Spanish radio network Cadena SER that the “tragedy appears to be linked to the train going too fast,” but that the reasons for that are not yet known.

Spanish news agency Efe and national daily El Pais cited sources within the investigation as saying that the driver had said the train was going at about 190 kilometers per hour, and that the limit on that curve was 80 kilometers per hour (50 mph.)

The president of Renfe, Julio Gomez-Pomar, told radio station COPE on Thursday that the train had undergone a routine inspection that same morning.

“The train did not have an operating problem,” he said. “The maintenance and control record of the train was perfect.”

Mourning declared

Spain’s King Juan Carlos visited a hospital in Santiago de Compostela where victims injured in Wednesday’s train accident are recovering.

“All Spaniards, we are united at this time. … Really all Spaniards join in the pain of the families of the dead,” he said. “We hope that the wounded will recover, little by little.”

The royal family canceled all events scheduled for the day out of respect for the day of mourning, the royal household told CNN.

Alberto Nunez Feijoo, head of the regional government in Galicia, declared seven days of mourning in the region for victims of the tragedy.

In a speech, he said “all of the community cries about the tragedy that we are living, we cry for the victims, we cry for the unease and sadness of the families.”

Spanish Prime Minister Mariano Rajoy viewed the scene of devastation Thursday morning and visited some of the hospitalized crash victims.

Rajoy, who is from the area, told a news conference there was a “huge challenge” ahead, not least in identifying all those killed and informing their families, and he praised the response of everyone who has helped after the crash.

Two investigations are under way, he said, adding, “We want to establish what happened.”

Rajoy declared three days of national mourning to honor the victims of the crash.

The prime minister came under fire in Spanish media after a condolences message for the train crash victims posted by his office late Wednesday included a paragraph apparently “copied and pasted” from a statement previously sent to victims of an earthquake in Gansu, China.

”I would like to express my deepest condolences for the loss of human lives and the material damage from the earthquake that has occurred in Gansu has caused,” the note said.

Victim: ‘Everything went dark’

One victim, speaking from a hospital bed with his arm in a sling, told CNN affiliate Atlas that it seemed like train was going fast.

“But we didn’t know what was the maximum speed, so I thought it was normal,” he said, “And suddenly there was a curve, the suitcases fell, and everything went dark. And I hit my head a ton of times, and 10 seconds later I was wedged between seats, and I had people’s legs on top of me.”

As he waited for rescuers to pull him from the wreckage, he heard other passengers yelling.

“I heard little children screaming. … I also heard two girls that yelled out, one supporting the other,” he said.

A passenger who got off at the last stop before the train derailed told the broadcaster it was packed with people at the time.

Residents who lived near the tracks told the Voz de Galicia newspaper that they heard a thunderous bang when the train crashed. Many of them rushed to the area with blankets and bottled water for the injured, the newspaper reported.

“The train had broken in half. Some pieces were on top, some pieces were on the bottom,” said Ivette Rubiera Cabrera of Florida, who caught a glimpse of the wreckage while on a family vacation in Spain and sent photos to CNN’s iReport.

“It was quite shocking,” she said. “We had never seen anything like that. We had just been on the train last week.”

Oscar Mateos told the El Pais newspaper that he saw fellow passengers thrown to the floor, then tossed from one side of the train to the other.

“Help came in five minutes, but that time became an eternity,” he said. “I helped people get out with broken legs and many bruises.”

Crash investigation

Investigators are looking at all possible causes of the crash, a senior aide to the prime minister said Wednesday.

Are you there and safe? Tell us what’s happening

Renfe’s spokesman said he did not know how many crew members were aboard the train when it crashed. Normally, there would be at least five crew members on a train like that, he said.

Officials appealed for blood donations just after the crash but on Thursday said the short-term needs were met.

Herman Van Rompuy, president of the European Council, expressed condolences from the European Union.

Pope Francis, who is on a visit to Brazil for World Youth Day, sent a telegram to the bishop of Santiago de Compostela, Julian Barrio Barrio, offering his support and prayers for all those affected by the tragedy.