Story 1: Trump Rattles The American Okie Doke Obama Into Stuttering Empty Suit –The Great Pretender — The Truth Hurts — Get Out of Our Lives — Roll It Back To A Full Employment Growing Booming Economy with 67% Labor Participation Rate and Less Than 3% Unemployment Rate — Make America Great Again — Catch Me If You Can — Videos
-A joke played on someone. Someone getting played for a fool.
-Also, someone who is fake or is a joke.
“I felt like a dumbass when that nigga hit me with the okie doke.”
“I keep it real homeboy. I ain’t no okie doke.”
Psychological projection is a theory in psychology in which humans defend themselves against their own unpleasant impulses by denying their existence while attributing them to others. For example, a person who is habitually rude may constantly accuse other people of being rude. It incorporates blame shifting.
Immigration moderation. Before any new green cards are issued to foreign workers abroad, there will be a pause where employers will have to hire from the domestic pool of unemployed immigrant and native workers. This will help reverse women’s plummeting workplace participation rate, grow wages, and allow record immigration levels to subside to more moderate historical averages.
U.S. Labor Participation Rate – Graph of Reagan vs obama
Obama Tries to Trash Donald Trump and Turns into a Stuttering Mess
Obama attacks Trump in Indiana speech but won’t use his name
Obama Busts GOP Economic Myths
Obama takes a victory lap over Elkhart, Indiana’s resurgence
Why doesn’t Obama say Donald Trump’s name?
The Great Pretender Obama Says Don’t Fall For The Okie-Doke
No Help Wanted – Labor Participation Rate Lowest Since 1977 – Fox & Friends.
Labor participation has hit a 38-year low, and that’s a problem
Labor participation rate is down to unprecedented levels
Unemployment and the Unemployment Rate
Types of Unemployment
Top 10 Greatest Con Artists in Movies
Catch me if you can best scenes
Catch Me If You Can Movie- Check Fraud
Catch Me If You Can Trailer
To Tell the Truth: Frank William Abagnale Jr. (1977)
The Real Frank Abagnale, “Catch me if you can” man – CNN Red Chair
Catch Me If You Can: Frank Abagnale’s Story
Frank Abagnale, who evolved from being a brilliant young mastermind of international deception and fraud into one of the world’s most respected authorities on forgery and embezzlement, tells his life story. His intercontinental saga prompted Steven Spielberg to turn Abagnale’s life into the movie Catch Me If You Can starring Leonardo DiCaprio.
The Platters – The Great Pretender – HD (1955)
Data extracted on: June 2, 2016 (4:31:21 PM)
Labor Force Statistics from the Current Population Survey
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
Download:
Year
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Annual
1980
64.0
64.0
63.7
63.8
63.9
63.7
63.8
63.7
63.6
63.7
63.8
63.6
1981
63.9
63.9
64.1
64.2
64.3
63.7
63.8
63.8
63.5
63.8
63.9
63.6
1982
63.7
63.8
63.8
63.9
64.2
63.9
64.0
64.1
64.1
64.1
64.2
64.1
1983
63.9
63.8
63.7
63.8
63.7
64.3
64.1
64.3
64.3
64.0
64.1
64.1
1984
63.9
64.1
64.1
64.3
64.5
64.6
64.6
64.4
64.4
64.4
64.5
64.6
1985
64.7
64.7
64.9
64.9
64.8
64.6
64.7
64.6
64.9
65.0
64.9
65.0
1986
64.9
65.0
65.1
65.1
65.2
65.4
65.4
65.3
65.4
65.4
65.4
65.3
1987
65.4
65.5
65.5
65.4
65.7
65.5
65.6
65.7
65.5
65.7
65.7
65.7
1988
65.8
65.9
65.7
65.8
65.7
65.8
65.9
66.1
65.9
66.0
66.2
66.1
1989
66.5
66.3
66.3
66.4
66.3
66.5
66.5
66.5
66.4
66.5
66.6
66.5
1990
66.8
66.7
66.7
66.6
66.6
66.4
66.5
66.5
66.4
66.4
66.4
66.4
1991
66.2
66.2
66.3
66.4
66.2
66.2
66.1
66.0
66.2
66.1
66.1
66.0
1992
66.3
66.2
66.4
66.5
66.6
66.7
66.7
66.6
66.5
66.2
66.3
66.3
1993
66.2
66.2
66.2
66.1
66.4
66.5
66.4
66.4
66.2
66.3
66.3
66.4
1994
66.6
66.6
66.5
66.5
66.6
66.4
66.4
66.6
66.6
66.7
66.7
66.7
1995
66.8
66.8
66.7
66.9
66.5
66.5
66.6
66.6
66.6
66.6
66.5
66.4
1996
66.4
66.6
66.6
66.7
66.7
66.7
66.9
66.7
66.9
67.0
67.0
67.0
1997
67.0
66.9
67.1
67.1
67.1
67.1
67.2
67.2
67.1
67.1
67.2
67.2
1998
67.1
67.1
67.1
67.0
67.0
67.0
67.0
67.0
67.2
67.2
67.1
67.2
1999
67.2
67.2
67.0
67.1
67.1
67.1
67.1
67.0
67.0
67.0
67.1
67.1
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
64.1
64.2
64.2
64.1
64.0
64.0
64.1
64.2
64.1
64.1
64.0
2012
63.7
63.8
63.8
63.7
63.7
63.8
63.7
63.5
63.7
63.8
63.6
63.7
2013
63.6
63.4
63.3
63.4
63.4
63.4
63.3
63.2
63.3
62.8
63.0
62.9
2014
62.9
63.0
63.2
62.8
62.8
62.8
62.9
62.9
62.8
62.9
62.9
62.7
2015
62.9
62.8
62.7
62.7
62.8
62.6
62.6
62.6
62.4
62.5
62.5
62.6
2016
62.7
62.9
63.0
62.8
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
Download:
Year
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Annual
1980
6.3
6.3
6.3
6.9
7.5
7.6
7.8
7.7
7.5
7.5
7.5
7.2
1981
7.5
7.4
7.4
7.2
7.5
7.5
7.2
7.4
7.6
7.9
8.3
8.5
1982
8.6
8.9
9.0
9.3
9.4
9.6
9.8
9.8
10.1
10.4
10.8
10.8
1983
10.4
10.4
10.3
10.2
10.1
10.1
9.4
9.5
9.2
8.8
8.5
8.3
1984
8.0
7.8
7.8
7.7
7.4
7.2
7.5
7.5
7.3
7.4
7.2
7.3
1985
7.3
7.2
7.2
7.3
7.2
7.4
7.4
7.1
7.1
7.1
7.0
7.0
1986
6.7
7.2
7.2
7.1
7.2
7.2
7.0
6.9
7.0
7.0
6.9
6.6
1987
6.6
6.6
6.6
6.3
6.3
6.2
6.1
6.0
5.9
6.0
5.8
5.7
1988
5.7
5.7
5.7
5.4
5.6
5.4
5.4
5.6
5.4
5.4
5.3
5.3
1989
5.4
5.2
5.0
5.2
5.2
5.3
5.2
5.2
5.3
5.3
5.4
5.4
1990
5.4
5.3
5.2
5.4
5.4
5.2
5.5
5.7
5.9
5.9
6.2
6.3
1991
6.4
6.6
6.8
6.7
6.9
6.9
6.8
6.9
6.9
7.0
7.0
7.3
1992
7.3
7.4
7.4
7.4
7.6
7.8
7.7
7.6
7.6
7.3
7.4
7.4
1993
7.3
7.1
7.0
7.1
7.1
7.0
6.9
6.8
6.7
6.8
6.6
6.5
1994
6.6
6.6
6.5
6.4
6.1
6.1
6.1
6.0
5.9
5.8
5.6
5.5
1995
5.6
5.4
5.4
5.8
5.6
5.6
5.7
5.7
5.6
5.5
5.6
5.6
1996
5.6
5.5
5.5
5.6
5.6
5.3
5.5
5.1
5.2
5.2
5.4
5.4
1997
5.3
5.2
5.2
5.1
4.9
5.0
4.9
4.8
4.9
4.7
4.6
4.7
1998
4.6
4.6
4.7
4.3
4.4
4.5
4.5
4.5
4.6
4.5
4.4
4.4
1999
4.3
4.4
4.2
4.3
4.2
4.3
4.3
4.2
4.2
4.1
4.1
4.0
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
9.4
9.5
9.5
9.4
9.8
9.3
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
8.3
8.3
8.2
8.2
8.2
8.2
8.2
8.1
7.8
7.8
7.7
7.9
2013
8.0
7.7
7.5
7.6
7.5
7.5
7.3
7.3
7.3
7.2
6.9
6.7
2014
6.6
6.7
6.7
6.2
6.2
6.1
6.2
6.2
6.0
5.7
5.8
5.6
2015
5.7
5.5
5.5
5.4
5.5
5.3
5.3
5.1
5.1
5.0
5.0
5.0
2016
4.9
4.9
5.0
5.0
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
Download:
Year
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Annual
1994
11.8
11.4
11.4
11.2
10.8
10.9
10.7
10.5
10.4
10.3
10.1
10.0
1995
10.2
9.9
9.9
10.0
10.0
10.1
10.1
10.0
10.1
9.9
10.0
10.0
1996
9.8
10.0
9.8
9.9
9.7
9.6
9.7
9.3
9.4
9.4
9.3
9.5
1997
9.4
9.4
9.1
9.2
8.8
8.8
8.6
8.6
8.7
8.4
8.3
8.4
1998
8.4
8.4
8.4
7.9
7.9
8.0
8.1
7.9
7.9
7.8
7.6
7.6
1999
7.7
7.7
7.6
7.6
7.4
7.5
7.5
7.3
7.4
7.2
7.1
7.1
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
17.1
16.6
16.4
16.4
16.5
16.8
16.6
16.9
16.6
2011
16.2
16.0
15.9
16.1
15.8
16.1
15.9
16.1
16.4
15.8
15.5
15.2
2012
15.2
15.0
14.6
14.6
14.8
14.8
14.8
14.6
14.8
14.4
14.4
14.4
2013
14.5
14.3
13.8
14.0
13.8
14.2
13.8
13.6
13.7
13.7
13.1
13.1
2014
12.7
12.6
12.6
12.3
12.1
12.0
12.2
12.0
11.8
11.5
11.4
11.2
2015
11.3
11.0
10.9
10.8
10.7
10.5
10.4
10.3
10.0
9.8
9.9
9.9
2016
9.9
9.7
9.8
9.7
Obama in Elkhart: Voters should beware of politicians ‘preying’ on economic fears
President Barack Obama says people should beware of politicians who are “preying” on Americans’ anxieties about the economy in a bid to win headlines and votes.
Obama isn’t naming names. But he says some politicians are running on anti-trade, anti-immigrant policies in an effort to play to people’s fears.
Obama made the remarks during a visit to Elkhart, Indiana. He’s holding up the manufacturing community as a symbol of the nation’s climb from recession to recovery.
Obama says his administration’s “smart” decisions played a part in helping Elkhart come back. He says he wants to bust “myths” that Democratic policies are bad for the economy.
Indiana’s Republican governor, Mike Pence, says Elkhart had rebounded “in spite of Obama’s policies” and that those policies inflicted onerous federal burdens on Indiana.
To Obama, lingering challenges aren’t enough to forestall a planned victory lap. Arguing that his controversial $840 billion stimulus package was ultimately vindicated, Obama will call on the next president to be willing to spend big to enable further economic growth.
The president is making his eighth visit to the state since taking office in January 2009. Here are details on the visits:
Feb. 2, 2009: Travels to Elkhart for his first event outside the Washington area since taking office 13 days earlier and speaks about his economic stimulus plan at Concord High School as Elkhart County’s unemployment rate was about 15 percent.
May 17, 2009: Delivers commencement address at the University of Notre Dame in South Bend, an appearance that drew weeks of criticism from many Catholic bishops and abortion opponents. Then travels to Indianapolis for two Democratic Party fundraisers.
Aug. 5, 2009: Visits Monaco RV factory in Wakarusa and announces $2.4 billion in grants for electric car production.
Nov. 23, 2010: Obama and Vice President Joe Biden both fly into Grissom Air Reserve Base then travel to a Chrysler transmission factory in Kokomo, where Obama promotes the U.S. auto industry revival.
May 6, 2011: Travels to an Allison Transmission factory in Indianapolis and speaks about how the hybrid transmissions made there can help reduce the country’s need for imported oil.
Oct. 3, 2014: Travels to Millennium Steel Services, a minority-owned steel processor near Princeton, and speaks about the nation’s manufacturing gains and the improving U.S. economy.
Feb. 6, 2015: Visits an Ivy Tech Community College campus in Indianapolis to tout his proposal for offering two years of college free.
June 1, 2016: Scheduled to speak about the economy at Concord Community High School in Elkhart and then take part in a PBS town hall at Elkhart’s Lerner Theatre.
Psychological projection is a theory in psychology in which humans defend themselves against their own unpleasant impulses by denying their existence while attributing them to others.[1] For example, a person who is habitually rudemay constantly accuse other people of being rude. It incorporates blame shifting.
According to some research, the projection of one’s negative qualities onto others is a common process in everyday life.[2]
Historical precursors
A prominent precursor in the formulation of the projection principle was Giambattista Vico,[3][4] and an early formulation of it is found in ancient Greek writer Xenophanes, which observed that “the gods of Ethiopians were inevitably black with flat noses while those of the Thracians were blond with blue eyes.”[citation needed] In 1841, Ludwig Feuerbach was the first to employ this concept as the basis for a systematic critique of religion.[5][6][7]
Psychoanalytic developments
Projection (German: Projektion) was conceptualised by Freud in his letters to Wilhelm Fliess,[8] and further refined by Karl Abraham and Anna Freud. Freud considered that in projection thoughts, motivations, desires, and feelings that cannot be accepted as one’s own are dealt with by being placed in the outside world and attributed to someone else.[9] What the ego repudiates is split off and placed in another.[10]
Freud would later come to believe that projection did not take place arbitrarily, but rather seized on and exaggerated an element that already existed on a small scale in the other person.[11] (The related defence of projective identification differs from projection in that there the other person is expected to become identified with the impulse or desire projected outside,[12] so that the self maintains a connection with what is projected, in contrast to the total repudiation of projection proper.)[13]
Melanie Klein saw the projection of good parts of the self as leading potentially to over-idealisation of the object.[14] Equally, it may be one’s conscience that is projected, in an attempt to escape its control: a more benign version of this allows one to come to terms with outside authority.[15]
Carl Jung considered that the unacceptable parts of the personality represented by the Shadow archetype were particularly likely to give rise to projection, both small-scale and on a national/international basis.[19]Marie-Louise Von Franz extended her view of projection, stating that “wherever known reality stops, where we touch the unknown, there we project an archetypal image”.[20]
Psychological projection is one of the medical explanations of bewitchment used to explain the behavior of the afflicted children at Salem in 1692. The historian John Demos asserts that the symptoms of bewitchment experienced by the afflicted girls were due to the girls undergoing psychological projection of repressed aggression.[21]
Practical examples
Victim blaming: The victim of someone else’s accident or bad luck may be offered criticism, the theory being that the victim may be at fault for having attracted the other person’s hostility.[22]
Projection of marital guilt: Thoughts of infidelity to a partner may be unconsciously projected in self-defence on to the partner in question, so that the guiltattached to the thoughts can be repudiated or turned to blame instead, in a process linked to denial.[23]
Bullying: A bully may project his/her own feelings of vulnerability onto the target(s) of the bullying activity. Despite the fact that a bully’s typically denigrating activities are aimed at the bully’s targets, the true source of such negativity is ultimately almost always found in the bully’s own sense of personal insecurityand/or vulnerability.[24] Such aggressive projections of displaced negative emotions can occur anywhere from the micro-level of interpersonal relationships, all the way up through to the macro-level of international politics, or even international armed conflict.[19]
Projection of general guilt: Projection of a severe conscience[25] is another form of defence, one which may be linked to the making of false accusations, personal or political.[19]
Projection of hope: Also, in a more positive light, a patient may sometimes project his or her feelings of hope onto the therapist.[26]
Counter-projection
Jung wrote, “All projections provoke counter-projection when the object is unconscious of the quality projected upon it by the subject.”[27] Thus, what is unconscious in the recipient will be projected back onto the projector, precipitating a form of mutual acting out.[28]
In a rather different usage, Harry Stack Sullivan saw counter-projection in the therapeutic context as a way of warding off the compulsive re-enactment of apsychological trauma, by emphasising the difference between the current situation and the projected obsession with the perceived perpetrator of the original trauma.[29]
Clinical approaches
Drawing on Gordon Allport‘s idea of the expression of self onto activities and objects, projective techniques have been devised to aid personality assessment, including the Rorschach ink-blots and the Thematic Apperception Test (TAT).[30]
Projection may help a fragile ego reduce anxiety, but at the cost of a certain dissociation, as in dissociative identity disorder.[31] In extreme cases, an individual’s personality may end up becoming critically depleted.[32] In such cases, therapy may be required which would include the slow rebuilding of the personality through the “taking back” of such projections.[33]
Criticism
Some studies were critical of Freud’s theory. Research supports the existence of a false-consensus effect whereby humans have a broad tendency to believe that others are similar to themselves, and thus “project” their personal traits onto others. This applies to good traits as well as bad traits and is not a defense mechanism for denying the existence of the trait within the self.[34]
Instead, Newman, Duff, and Baumeister (1997) proposed a new model of defensive projection. In this view, people try to suppress thoughts of their undesirable traits, and these efforts make those trait categories highly accessible—so that they are then used all the more often when forming impressions of others. The projection is then only a by-product of the real defensive mechanism.[35]
Story 1: US Economy Stagnating With Lowest Labor Participation in 38 Years of 62.4% With 94.6 Million Americans Not In Labor Force and 7.9 Unemployed and Only 142,000 Jobs Created In September — Recession in 2016? — Videos
U.S. economy gains 142,000 jobs in September
Does the weak jobs report take a Fed rate hike off the table?
The weak September jobs report and the markets
RETAIL APOCALYPSE CONTINUES SALES WORSE SINCE 2009
The last time September Retail Sales growth was this weak was 2009, limping aimlessly out of the ‘Great Recession’. With a mere 0.9% year-over-year growth, Johnson-Redbook data seems to confirm what Reuters reports is looming – the weakest U.S. holiday sales season for retailers since the recession. Consultancy firm AlixPartners expects sales to grow 2.8-3.4% during the November-December shopping period compared with 4.4% in 2014, based on analyzing consumer spending trends so far this year, noting (myth-busting for permabulls) dollars saved at the pump are being directed to personal savings or on non-retail activities.
Bursting Oil Bubble Could Put US Back in Recession
Commodities Report: October 2, 2015
Keep U.S. Jobs Numbers Volatility in Perspective: Krueger
Bad Jobs Report Prediction Understandable Says ‘Superforecasting’ Author
October 2, 2015 Financial News – Business News – Stock Exchange – NYSE – Market News
Gold Webcast – Gold climbs on weak US jobs report
Before the Asia Bell: October 2, 2015
Peter Schiff: Minimum Wage Will Result In Mass Unemployment & Self Service
MARC FABER – World Economy Grinding to a Halt. Don’t Trade With Leverage
Thom Hartmann “The Crash of 2016”
Keiser Report: Market Wasteland (E817)
The September Jobs Report in 11 Charts
By JOSH ZUMBRUN , NICK TIMIRAOS and ERIC MORATH
The U.S. economy added 142,000 jobs in September, but there’s more to the monthly jobs report than the number of jobs added. The report provides a wealth of information about the demographics of unemployment—about who is unemployed and why—summarized in the following 11 charts.
Over the past three months the economy has added jobs at the slowest pace since February 2014. Employers were adding an average of more than 200,000 jobs each month since the spring of last year, but now that pace has slowed.
Similarly, the annual pace of job creation has eased in recent months after peaking above three million late last year.
As a result of the weaker gains in August and September, job creation in 2015 has fallen well off last year’s pace. However, the economy is still on track to post the second-best year for employment growth in the past decade.
Every measure of unemployment is declining this year. The broadest gauge, which includes part-timers who would prefer full-time employment and Americans too discouraged to look for a job, fell to 10% last month. That’s the lowest rate since May 2008.
The median unemployed worker has been without a job for 11.4 weeks. That’s substantially shorter than during the first few years of this economic recovery, but still high by historical standards.
The number of Americans working full-time has finally returned to its prerecession levels, though this doesn’t account for an increase in the overall population.
The labor-force participation rate—that is, the share of the population either working or looking for work—declined to the lowest rate since 1977. The employment-to-population ratio, that is, the share of the population with a job, fell to 59.2% from 59.4%.
Much of the reason for the decline in the labor force is simply that a growing number of baby boomers are choosing to retire. Among workers ages 25 to 54, labor-force participation and employment rates are higher. Among this group of workers, dubbed prime-age by labor market economists, labor-force participation fell to 80.6% from 80.7% last month.
People can be unemployed for a range of reasons—whether it’s entering the job market for the first time; re-entering after going to school, starting a family or caring for a relative; quitting an old job with no new one lined up; or losing a job, either on a temporary layoff or permanently. As the recovery has progressed, the share of the unemployed who lost their previous job has declined. A growing share of the unemployed are new entrant or re-entrants to the work force.
College graduates have a significantly lower unemployment rate, which was unchanged at 2.5% this month. High-school dropouts have significantly higher unemployment, which climbed to 7.9% this month from 7.7%.
The unemployment rate has continued to come down for men, women, whites, blacks and Hispanics. The gaps in the unemployment rate between men and women have mostly closed, but significant gaps remain between racial groups.
Corrections & Amplifications
Monthly employment gains in 2015 have averaged 198,000. An earlier version of the chart “Slower, But Still Solid,” incorrectly showed an average gain of 221,000 jobs. Also, the number of Americans working full-time increased in September using a three-month moving average. An earlier version of the chart “Working Longer” included data for July, August and September that didn’t use the three-month average, while the post incorrectly suggested the number of full-time workers according to that measure had declined in September. (Oct. 2, 2015).
U.S. job growth stumbles, raising doubts on economy
BY JASON LANGE
U.S. employers slammed the brakes on hiring over the last two months, raising new doubts the economy is strong enough for the Federal Reserve to raise interest rates by the end of this year.
Payrolls outside of farming rose by 142,000 last month and August figures were revised sharply lower to show only 136,000 jobs added that month, the Labor Department said on Friday.
That marked the smallest two-month gain in employment in over a year and could fuel fears that the China-led global economic slowdown is sapping America’s strength.
“You can’t throw lipstick on this pig of a report,” said Brian Jacobsen, a portfolio strategist at Wells Fargo Funds Management in Menomonee Falls, Wisconsin.
The weak job growth took Wall Street by surprise and U.S. stocks sold off while the dollar also weakened and yields for government bonds fell.
Bets on interest rate futures showed investors only saw a 30 percent chance of a Fed rate hike in December, down from just under 50 percent before the job report’s release.
“(With) a weak report here, in combination with some of the other weakness that we are seeing across the globe, the odds get dinged for December,” said Tom Porcelli, an economist at RBC Capital Markets.
Investors saw virtually no chance the Fed would end its near-zero interest rate policy at its only other scheduled meeting this year, to be held later in October. Futures prices indicated investors were betting the Fed would probably hike in March.
U.S. factories are feeling the global chill and shed 9,000 jobs in September after losing 18,000 in August, according to the Labor Department’s survey of employers.
“We saw events in China lead to some global financial turmoil and you’re seeing that in the data here,” White House chief economist Jason Furman told Reuters.
New orders received by U.S. factories fell 1.7 percent in August, the Commerce Department said in a separate report..
Paul Ryan, a top Republican lawmaker in the House of Representatives, said the weak turn in the economy should be a wake-up call for Washington to reform the national economy with new tax laws, free trade agreements and policies to get people off welfare. “This recovery continues to disappoint, but we can’t accept it as the new normal,” Ryan said.
The recent pace of job growth should have been enough to push the unemployment rate lower because only around 100,000 new jobs are needed a month to keep up with population growth.
But the jobless rate held steady at 5.1 percent. The unemployment rate is derived from a separate survey of households that showed 350,000 workers dropping out of the labor force last month, as well as a lower level of employment.
The share of the population in the work force, which includes people who have jobs or are looking for one, fell to 62.4 percent, the lowest level since 1977.
Average hourly wages fell by a cent to $25.09 during the month and were up only 2.2 percent from the same month in 2014, holding around the same levels seen all year and pointing to marginal inflationary pressures.
The report did have a few bright spots that might be welcomed by Fed chief Janet Yellen, who said last week the economy was doing well enough to warrant higher rates this year.
The number of workers with part-time jobs but who want more hours fell by 447,000 in September to 6.0 million.
Yellen has signaled that the elevated number of these workers points to hidden slack in the labor market that isn’t captured by the jobless rate. A measure of joblessness that includes these workers and is closely followed by the Fed fell to 10 percent, its lowest level since May 2008.
Economists polled by Reuters had expected job growth of 203,000 in September.
All told, revised estimates meant 59,000 fewer jobs were created in July and August than previously believed.
In another grim sign, the number of hours worked in the country fell 0.2 percent, raising the specter that some broader softness might have gripped the economy last month.
Some of the strongest headwinds on the U.S. economy come from the commodity sector, which has slowed in part because of weaker demand from China.
The price of oil has fallen nearly 50 percent over the last year, and U.S. mining payrolls, which include energy sector jobs, fell by 10,000 in September, the ninth straight month of declines.
Transmission of material in this release is embargoed until USDL-15-1912
8:30 a.m. (EDT) Friday, October 2, 2015
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 -- SEPTEMBER 2015
Total nonfarm payroll employment increased by 142,000 in September, and the
unemployment rate was unchanged at 5.1 percent, the U.S. Bureau of Labor
Statistics reported today. Job gains occurred in health care and information,
while mining employment fell.
Household Survey Data
In September, the unemployment rate held at 5.1 percent, and the number of
unemployed persons (7.9 million) changed little. Over the year, the unemployment
rate and the number of unemployed persons were down by 0.8 percentage point and
1.3 million, respectively. (See table A-1.)
Among the major worker groups, the unemployment rates for adult men (4.7 percent),
adult women (4.6 percent), teenagers (16.3 percent), whites (4.4 percent), blacks
(9.2 percent), Asians (3.6 percent), and Hispanics (6.4 percent) showed little
or no change in September. (See tables A-1, A-2, and A-3.)
The number of persons unemployed for less than 5 weeks increased by 268,000 to
2.4 million in September, partially offsetting a decline in August. The number
of long-term unemployed (those jobless for 27 weeks or more) was little changed
at 2.1 million in September and accounted for 26.6 percent of the unemployed.
(See table A-12.)
The civilian labor force participation rate declined to 62.4 percent in September;
the rate had been 62.6 percent for the prior 3 months. The employment-population
ratio edged down to 59.2 percent in September, after showing little movement for
the first 8 months of the year. (See table A-1.)
The number of persons employed part time for economic reasons (sometimes referred to
as involuntary part-time workers) declined by 447,000 to 6.0 million in September.
These individuals, who would have preferred full-time employment, were working part
time because their hours had been cut back or because they were unable to find a
full-time job. Over the past 12 months, the number of persons employed part time
for economic reasons declined by 1.0 million. (See table A-8.)
In September, 1.9 million persons were marginally attached to the labor force, down
by 305,000 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 635,000 discouraged workers in September,
little changed 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 1.3 million persons marginally
attached to the labor force in September 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 142,000 in September. Thus far in
2015, job growth has averaged 198,000 per month, compared with an average monthly
gain of 260,000 in 2014. In September, job gains occurred in health care and
information, while employment in mining continued to decline. (See table B-1.)
Health care added 34,000 jobs in September, in line with the average increase of
38,000 jobs per month over the prior 12 months. Hospitals accounted for 16,000 of
the jobs gained in September, and employment in ambulatory health care services
continued to trend up (+13,000).
Employment in information increased by 12,000 in September and has increased by
44,000 over the year.
Employment in professional and business services continued to trend up in September
(+31,000). Job growth has averaged 45,000 per month thus far in 2015, compared
with an average monthly gain of 59,000 in 2014. In September, job gains occurred
in computer systems design and related services (+7,000) and in legal services
(+5,000).
Retail trade employment trended up in September (+24,000), in line with its average
monthly gain over the prior 12 months (+27,000). In September, employment rose in
general merchandise stores (+10,000) and automobile dealers (+5,000).
Employment in food services and drinking places continued on an upward trend in
September (+21,000). Over the year, this industry has added 349,000 jobs.
Employment in mining continued to decline in September (-10,000), with losses
concentrated in support activities for mining (-7,000). Mining employment has
declined by 102,000 since reaching a peak in December 2014.
Employment in other major industries, including construction, manufacturing,
wholesale trade, transportation and warehousing, financial activities, and
government, showed little or no change over the month.
The average workweek for all employees on private nonfarm payrolls declined by
0.1 hour to 34.5 hours in September. The manufacturing workweek decreased by
0.2 hour to 40.6 hours, and factory overtime declined by 0.2 hour to 3.1 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 September, average hourly earnings for all employees on private nonfarm
payrolls, at $25.09, changed little (-1 cent), following a 9-cent gain in August.
Hourly earnings have risen by 2.2 percent over the year. Average hourly earnings
of private-sector production and nonsupervisory employees were unchanged at
$21.08 in September. (See tables B-3 and B-8.)
The change in total nonfarm payroll employment for July was revised from +245,000
to +223,000, and the change for August was revised from +173,000 to +136,000. With
these revisions, employment gains in July and August combined were 59,000 less
than previously reported. Over the past 3 months, job gains have averaged 167,000
per month.
_____________
The Employment Situation for October is scheduled to be released on Friday,
November 6, 2015, at 8:30 a.m. (EST).
Employment Situation Summary Table A. Household data, seasonally adjusted
HOUSEHOLD DATA
Summary table A. Household data, seasonally adjusted
[Numbers in thousands]
Category
Sept.
2014
July
2015
Aug.
2015
Sept.
2015
Change from:
Aug.
2015-
Sept.
2015
Employment status
Civilian noninstitutional population
248,446
250,876
251,096
251,325
229
Civilian labor force
155,845
157,106
157,065
156,715
-350
Participation rate
62.7
62.6
62.6
62.4
-0.2
Employed
146,607
148,840
149,036
148,800
-236
Employment-population ratio
59.0
59.3
59.4
59.2
-0.2
Unemployed
9,237
8,266
8,029
7,915
-114
Unemployment rate
5.9
5.3
5.1
5.1
0.0
Not in labor force
92,601
93,770
94,031
94,610
579
Unemployment rates
Total, 16 years and over
5.9
5.3
5.1
5.1
0.0
Adult men (20 years and over)
5.3
4.8
4.7
4.7
0.0
Adult women (20 years and over)
5.5
4.9
4.7
4.6
-0.1
Teenagers (16 to 19 years)
19.8
16.2
16.9
16.3
-0.6
White
5.1
4.6
4.4
4.4
0.0
Black or African American
11.0
9.1
9.5
9.2
-0.3
Asian
4.5
4.0
3.5
3.6
0.1
Hispanic or Latino ethnicity
7.0
6.8
6.6
6.4
-0.2
Total, 25 years and over
4.7
4.3
4.2
4.1
-0.1
Less than a high school diploma
8.3
8.3
7.7
7.9
0.2
High school graduates, no college
5.3
5.5
5.5
5.2
-0.3
Some college or associate degree
5.4
4.4
4.4
4.3
-0.1
Bachelor’s degree and higher
2.9
2.6
2.5
2.5
0.0
Reason for unemployment
Job losers and persons who completed temporary jobs
4,521
4,143
4,070
3,908
-162
Job leavers
816
843
790
780
-10
Reentrants
2,805
2,447
2,349
2,436
87
New entrants
1,094
826
850
831
-19
Duration of unemployment
Less than 5 weeks
2,372
2,488
2,095
2,363
268
5 to 14 weeks
2,495
2,257
2,374
2,218
-156
15 to 26 weeks
1,423
1,188
1,250
1,214
-36
27 weeks and over
2,951
2,180
2,187
2,104
-83
Employed persons at work part time
Part time for economic reasons
7,058
6,325
6,483
6,036
-447
Slack work or business conditions
4,165
3,828
3,841
3,569
-272
Could only find part-time work
2,528
2,213
2,242
2,134
-108
Part time for noneconomic reasons
19,579
19,891
19,760
19,971
211
Persons not in the labor force (not seasonally adjusted)
Marginally attached to the labor force
2,226
1,927
1,812
1,921
–
Discouraged workers
698
668
624
635
–
– 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.
Employment Situation Summary Table B. Establishment data, seasonally adjusted
ESTABLISHMENT DATA
Summary table B. Establishment data, seasonally adjusted
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 2014 benchmark levels and updated seasonal adjustment factors.
National Income and Product Accounts
Gross Domestic Product: Second Quarter 2015 (Third Estimate)
Corporate Profits: Second Quarter 2015 (Revised Estimate)
Real gross domestic product -- the value of the goods and services produced by the nation’s
economy less the value of the goods and services used up in production, adjusted for price
changes -- increased at an annual rate of 3.9 percent in the second quarter of 2015, according to the
"third" estimate released by the Bureau of Economic Analysis. In the first quarter, real GDP increased
0.6 percent.
The GDP estimate released today is based on more complete source data than were available for
the "second" estimate issued last month. In the second estimate, the increase in real GDP was 3.7
percent. With the third estimate for the second quarter, the general picture of economic growth remains
the same; personal consumption expenditures (PCE) and nonresidential fixed investment increased more
than previously estimated (see “Revisions” on page 2).
The increase in real GDP in the second quarter primarily reflected positive contributions from
PCE, exports, nonresidential fixed investment, state and local government spending, and residential
fixed investment. Imports, which are a subtraction in the calculation of GDP, increased.
Real GDP increased 3.9 percent in the second quarter, after increasing 0.6 percent in the first.
The acceleration in real GDP in the second quarter reflected an upturn in exports, an acceleration in
PCE, a deceleration in imports, an upturn in state and local government spending, and an acceleration in
nonresidential fixed investment that were partly offset by decelerations in private inventory investment
and in federal government spending.
Real gross domestic income (GDI) -- the value of the costs incurred and the incomes earned in
the production of goods and services in the nation’s economy -- increased 0.7 percent in the second
quarter, compared with an increase of 0.4 percent in the first. The average of real GDP and real GDI, a
supplemental measure of U.S. economic activity that equally weights GDP and GDI, increased 2.3
percent in the second quarter, compared with an increase of 0.5 percent in the first.
_______
FOOTNOTE. Quarterly estimates are expressed at seasonally adjusted annual rates, unless otherwise
specified. 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 BEA's Web site.
_______
Real gross domestic purchases -- purchases by U.S. residents of goods and services wherever
produced -- increased 3.6 percent in the second quarter, compared with an increase of 2.5 percent in
the first.
The price index for gross domestic purchases, which measures prices paid by U.S. residents,
increased 1.5 percent in the second quarter, in contrast to a decrease of 1.6 percent in the first. Excluding
food and energy prices, the price index for gross domestic purchases increased 1.2 percent, compared
with an increase of 0.2 percent.
Current-dollar GDP -- the market value of the goods and services produced by the nation’s
economy less the value of the goods and services used up in production -- increased 6.1 percent, or
$264.4 billion, in the second quarter to a level of $17,913.7 billion. In the first quarter, current-dollar
GDP increased 0.8 percent, or $33.3 billion.
Revisions
The upward revision to the percent change in real GDP primarily reflected upward revisions to
PCE, to nonresidential fixed investment, and to residential fixed investment that were partly offset by a
downward revision to private inventory investment. For information on revisions, see "The Revisions to
GDP, GDI, and Their Major Components."
Advance Estimate Second Estimate Third Estimate
(Percent change from preceding quarter)
Real GDP............................... 2.3 3.7 3.9
Current-dollar GDP..................... 4.4 5.9 6.1
Real GDI............................... ... 0.6 0.7
Average of Real GDP and Real GDI....... ... 2.1 2.3
Gross domestic purchases price index... 1.4 1.5 1.5
Corporate Profits
Profits from current production
Profits from current production (corporate profits with inventory valuation adjustment (IVA) and
capital consumption adjustment (CCAdj)) increased $70.4 billion in the second quarter, in contrast to a
decrease of $123.0 billion in the first.
Profits of domestic financial corporations increased $34.6 billion in the second quarter, in
contrast to a decrease of $23.4 billion in the first. Profits of domestic nonfinancial corporations
increased $24.3 billion, in contrast to a decrease of $70.5 billion. The rest-of-the-world component of
profits increased $11.4 billion, in contrast to a decrease of $29.0 billion. This measure is calculated as
the difference between receipts from the rest of the world and payments to the rest of the world. In the
second quarter, receipts increased $24.9 billion, and payments increased $13.4 billion.
Taxes on corporate income increased $31.3 billion in the second quarter, compared with an
increase of $5.5 billion in the first. Profits after tax with IVA and CCAdj increased $39.2 billion, in
contrast to a decrease of $128.4 billion.
Dividends increased $1.2 billion in the second quarter, compared with an increase of $6.3 billion
in the first. Undistributed profits increased $38.0 billion, in contrast to a decrease of $134.7 billion. Net
cash flow with IVA -- the internal funds available to corporations for investment -- increased $48.1
billion, in contrast to a decrease of $135.5 billion.
The IVA and CCAdj are adjustments that convert inventory withdrawals and depreciation of
fixed assets reported on a tax-return, historical-cost basis to the current-cost economic measures used in
the national income and product accounts. The IVA decreased $78.7 billion in the second quarter, in
contrast to an increase of $45.7 billion in the first. The CCAdj increased $7.7 billion, in contrast to a
decrease of $208.1 billion.
Corporate profits with IVA
Profits of domestic financial corporations increased $34.3 billion in the second quarter, in
contrast to a decrease of $3.1 billion in the first. Profits of domestic nonfinancial corporations increased
$17.0 billion, compared with an increase of $117.3 billion. The second-quarter increase in profits of
nonfinancial corporations primarily reflected an increase in “other” nonfinancial industries that was
partly offset by a decrease in retail trade industries. A small increase in manufacturing industries
reflected an increase in durable goods that was mostly offset by a decrease in nondurable goods.
Gross value added of nonfinancial domestic corporate business
Real gross value added of nonfinancial corporations decreased slightly in the second quarter.
Profits per unit of real value added increased, reflecting an increase in unit prices and a decrease in unit
nonlabor costs that were partly offset by an increase in unit labor costs.
* * *
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 -- October 29, 2015 at 8:30 A.M. EDT for:
Gross Domestic Product: Third Quarter 2015 (Advance Estimate)
http://bea.gov/newsreleases/national/GDP/GDPnewsrelease.htm
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Weekly Market Wrap Up – June 5th, 21015
Nonfarm payrolls total 280,000; unemployment rate at 5.5%
Jeff Cox | @JeffCoxCNBCcom
The U.S. economy created 280,000 jobs in May, better than expected and likely confirming hopes that growth is back on track after a slow start to the year.
The headline unemployment rate increased slightly to 5.5 percent as the labor force participation rate ticked higher to 62.9 percent. (Tweet This) A separate measure that counts those working part time for economic reasons and the unemployed who have not looked for work in the past month held steady at 10.8 percent.
Wages also showed growth, rising 8 cents an hour, equating to an annualized increase of 2.3 percent.
Economists had been expecting a gain of 225,000 positions and the unemployment rate holding steady at 5.4 percent.
“Today’s report showed the U.S. labor market has tremendous momentum. All those factors that parked a weak jobs number in March were short-term,” said Andrew Chamberlain, chief economist at job search site Glassdoor. “All those factors are looking more like a late-winter sniffle than a lingering illness.”
The jobs numbers are critical in that they will go a long way toward determining policy from the Federal Reserve. The hot jobs report sent U.S. government bond yields surging as the wage increase indicates inflation is pushing toward the Fed’s target. Stock futures also indicated a lower open for Wall Street, though the move in the equity market was far less pronounced than in bonds.
After keeping short-term interest rates near zero for 6½ years, the U.S. central bank is looking for a liftoff point that would be confirmed not only by job creation but also by wage growth, which would indicate inflation is on a positive trajectory.
“I think (the jobs number) puts September more firmly on track” for a rate hike, said Jim Caron, portfolio manager of global fixed income at Morgan Stanley Investment Management. “As of yesterday it was probably closer to a 50-50 bet. Today, I think it’s more in lines of a 75 percent probability. It moves the needle in terms of expectations and gives air cover to the Fed.”
Trader bets on the date for a rate hike pushed it forward this week, with the latest trends showing a 33 percent chance of a September hike (up from 26 percent earlier in the week), a 52 percent chance in October (from 44 percent) and a 70 percent likelihood for December (from 61 percent).
While many market participants expect a rate increase this year, the Fed got a stunning jolt Thursday from the International Monetary Fund chief Christine Lagarde, who took the unprecedented step of advising the Fed to wait until 2016 until the inflation picture is clearer.
“This number effectively flies in the face of what the IMF recommended yesterday that the Fed take a pause,” Caron said.
Service industries led the way for May, adding 63,000 positions, while leisure and hospitality grew by 57,000. Health care increased by 47,000, retail added 31,000 and construction moved higher by 17,000. Mining was a dark spot on the report, contracting by 17,000, bringing the decline to 68,000 in 2015.
The average work week was unchanged at 34.5 hours.
The number of full-time workers grew by 630,000, while the part-time rolls fell by 232,000.
Previous months showed minor changes, with March’s disappointing count getting pushed higher to 119,000 from 85,000 and April edging lower from 223,000 to 221,000.
“Overall, at this stage this evident strength in the labor market probably isn’t enough to persuade the Fed to hike rates by July, but it definitely makes a rate cut by September probable,” said Paul Ashworth, chief U.S. economist at Capital Economics. “Only 24 hours later, the IMF’s suggestion that the Fed should wait until 2016 looks very dated.”
Transmission of material in this release is embargoed until USDL-15-1057
8:30 a.m. (EDT) Friday, June 5, 2015
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 2015
Total nonfarm payroll employment increased by 280,000 in May, and the
unemployment rate was essentially unchanged at 5.5 percent, the U.S.
Bureau of Labor Statistics reported today. Job gains occurred in
professional and business services, leisure and hospitality, and health
care. Mining employment continued to decline.
Household Survey Data
In May, both the unemployment rate (5.5 percent) and the number of
unemployed persons (8.7 million) were essentially unchanged. Both
measures have shown little movement since February. (See table A-1.)
Among the major worker groups, the unemployment rates for adult men
(5.0 percent), adult women (5.0 percent), teenagers (17.9 percent),
whites (4.7 percent), blacks (10.2 percent), Asians (4.1 percent),
and Hispanics (6.7 percent) showed little or no change in May. (See
tables A-1, A-2, and A-3.)
The number of unemployed new entrants edged up by 103,000 in May but
is about unchanged over the year. Unemployed new entrants are those
who never previously worked. (See table A-11.)
The number of persons unemployed for less than 5 weeks decreased by
311,000 to 2.4 million in May, following an increase in April. The
number of long-term unemployed (those jobless for 27 weeks or more)
held at 2.5 million in May and accounted for 28.6 percent of the
unemployed. Over the past 12 months, the number of long-term
unemployed is down by 849,000. (See table A-12.)
In May, the civilian labor force rose by 397,000, and the labor force
participation rate was little changed at 62.9 percent. Since April
2014, the participation rate has remained within a narrow range of
62.7 percent to 62.9 percent. The employment-population ratio, at
59.4 percent, was essentially unchanged in May. (See table A-1.)
The number of persons employed part time for economic reasons (sometimes
referred to as involuntary part-time workers) was about unchanged at
6.7 million in May and has shown little movement in recent months.
These individuals, who would have preferred full-time employment, 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, 1.9 million persons were marginally attached to the labor force,
down by 268,000 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 563,000 discouraged workers
in May, down by 134,000 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 1.3
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 rose by 280,000 in May, compared with
an average monthly gain of 251,000 over the prior 12 months. In May,
job gains occurred in professional and business services, leisure
and hospitality, and health care. Employment in mining continued to
decline. (See table B-1.)
Professional and business services added 63,000 jobs in May and
671,000 jobs over the year. In May, employment increased in computer
systems design and related services (+10,000). Employment continued
to trend up in temporary help services (+20,000), in management and
technical consulting services (+7,000), and in architectural and
engineering services (+5,000).
Employment in leisure and hospitality increased by 57,000 in May,
following little change in the prior 2 months. In May, employment
edged up in arts, entertainment, and recreation (+29,000). Employment
in food services and drinking places has shown little net change over
the past 3 months.
Health care added 47,000 jobs in May. Within the industry, employment
in ambulatory care services (which includes home health care services
and outpatient care centers) rose by 28,000. Hospitals added 16,000
jobs over the month. Over the past year, health care has added 408,000
jobs.
Employment in retail trade edged up in May (+31,000). Over the prior
12 months, the industry had added an average of 24,000 jobs per month.
Within retail trade, automobile dealers added 8,000 jobs in May.
Construction employment continued to trend up over the month (+17,000)
and has increased by 273,000 over the past year.
In May, employment continued on an upward trend in transportation and
warehousing (+13,000). Truck transportation added 9,000 jobs over the
month.
In May, employment continued to trend up in financial activities (+13,000).
Over the past 12 months, the industry has added 160,000 jobs, with
about half of the gain in insurance carriers and related activities.
Employment in mining fell for the fifth month in a row, with a decline
of 17,000 in May. The loss was in support activities for mining.
Employment in mining has decreased by 68,000 thus far this year, after
increasing by 41,000 in 2014.
Employment in other major industries, including manufacturing, wholesale
trade, information, and government, showed little change over the month.
The average workweek for all employees on private nonfarm payrolls
remained at 34.5 hours in May. The manufacturing workweek was unchanged
at 40.7 hours, and factory overtime remained at 3.3 hours. The average
workweek for production and nonsupervisory employees on private nonfarm
payrolls edged up by 0.1 hour to 33.7 hours. (See tables B-2 and B-7.)
In May, average hourly earnings for all employees on private nonfarm
payrolls rose by 8 cents to $24.96. Over the year, average hourly
earnings have risen by 2.3 percent. Average hourly earnings of private-
sector production and nonsupervisory employees rose by 6 cents to $20.97
in May. (See tables B-3 and B-8.)
The change in total nonfarm payroll employment for March was revised
from +85,000 to +119,000, and the change for April was revised from
+223,000 to +221,000. With these revisions, employment gains in March
and April combined were 32,000 more than previously reported. Over the
past 3 months, job gains have averaged 207,000 per month.
_____________
The Employment Situation for June is scheduled to be released on
Thursday, July 2, 2015, at 8:30 a.m. (EDT).
Employment Situation Summary Table A. Household data, seasonally adjusted
HOUSEHOLD DATA
Summary table A. Household data, seasonally adjusted
[Numbers in thousands]
Category
May
2014
Mar.
2015
Apr.
2015
May
2015
Change from:
Apr.
2015-
May
2015
Employment status
Civilian noninstitutional population
247,622
250,080
250,266
250,455
189
Civilian labor force
155,629
156,906
157,072
157,469
397
Participation rate
62.8
62.7
62.8
62.9
0.1
Employed
145,868
148,331
148,523
148,795
272
Employment-population ratio
58.9
59.3
59.3
59.4
0.1
Unemployed
9,761
8,575
8,549
8,674
125
Unemployment rate
6.3
5.5
5.4
5.5
0.1
Not in labor force
91,993
93,175
93,194
92,986
-208
Unemployment rates
Total, 16 years and over
6.3
5.5
5.4
5.5
0.1
Adult men (20 years and over)
5.9
5.1
5.0
5.0
0.0
Adult women (20 years and over)
5.7
4.9
4.9
5.0
0.1
Teenagers (16 to 19 years)
19.2
17.5
17.1
17.9
0.8
White
5.4
4.7
4.7
4.7
0.0
Black or African American
11.4
10.1
9.6
10.2
0.6
Asian
5.6
3.2
4.4
4.1
-0.3
Hispanic or Latino ethnicity
7.7
6.8
6.9
6.7
-0.2
Total, 25 years and over
5.2
4.4
4.5
4.5
0.0
Less than a high school diploma
9.2
8.6
8.6
8.6
0.0
High school graduates, no college
6.5
5.3
5.4
5.8
0.4
Some college or associate degree
5.5
4.8
4.7
4.4
-0.3
Bachelor’s degree and higher
3.2
2.5
2.7
2.7
0.0
Reason for unemployment
Job losers and persons who completed temporary jobs
4,959
4,189
4,136
4,267
131
Job leavers
872
875
828
829
1
Reentrants
2,869
2,689
2,685
2,615
-70
New entrants
1,063
815
868
971
103
Duration of unemployment
Less than 5 weeks
2,553
2,488
2,729
2,418
-311
5 to 14 weeks
2,401
2,312
2,307
2,532
225
15 to 26 weeks
1,451
1,253
1,139
1,293
154
27 weeks and over
3,351
2,563
2,525
2,502
-23
Employed persons at work part time
Part time for economic reasons
7,268
6,705
6,580
6,652
72
Slack work or business conditions
4,404
4,069
3,885
3,891
6
Could only find part-time work
2,558
2,337
2,374
2,390
16
Part time for noneconomic reasons
19,149
19,733
20,056
19,961
-95
Persons not in the labor force (not seasonally adjusted)
Marginally attached to the labor force
2,130
2,055
2,115
1,862
–
Discouraged workers
697
738
756
563
–
– 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.
Employment Situation Summary Table B. Establishment data, seasonally adjusted
ESTABLISHMENT DATA
Summary table B. Establishment data, seasonally adjusted
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 2014 benchmark levels and updated seasonal adjustment factors.
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Labor Force Participation Rate
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WSJ Markets Wrap: May 8, 2015
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Closing Bell Happy Hour: May 8, 2015
April Produces Encouraging Jobs Report
Civilian Labor Force Level
157,072,00
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
Year
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
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
153484(1)
153694
153954
154622
154091
153616
153691
154086
153975
153635
154125
153650
2011
153314(1)
153227
153377
153566
153492
153350
153276
153746
154085
153935
154089
153961
2012
154445(1)
154739
154765
154589
154899
155088
154927
154726
155060
155491
155305
155553
2013
155825(1)
155396
155026
155401
155562
155761
155632
155529
155548
154615
155304
155047
2014
155486(1)
155688
156180
155420
155629
155700
156048
156018
155845
156243
156402
156129
2015
157180(1)
157002
156906
157072
1 : Data affected by changes in population controls.
Labor Force Participation Rate
62.8%
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
Year
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
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
64.1
64.0
64.0
64.1
64.2
64.1
64.1
64.0
2012
63.7
63.8
63.8
63.7
63.8
63.8
63.7
63.5
63.6
63.7
63.6
63.7
2013
63.7
63.5
63.3
63.4
63.4
63.4
63.3
63.2
63.2
62.8
63.0
62.8
2014
63.0
63.0
63.2
62.8
62.8
62.8
62.9
62.9
62.7
62.8
62.9
62.7
2015
62.9
62.8
62.7
62.8
Employment Level
148, 523, 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
Year
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
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
138438(1)
138581
138751
139297
139241
139141
139179
139438
139396
139119
139044
139301
2011
139267(1)
139400
139649
139610
139639
139392
139520
139940
140156
140336
140780
140890
2012
141633(1)
141911
142069
141953
142231
142400
142270
142277
142953
143350
143279
143280
2013
143328(1)
143429
143374
143665
143890
144025
144275
144288
144297
143453
144490
144671
2014
145206(1)
145301
145796
145724
145868
146247
146401
146451
146607
147260
147331
147442
2015
148201(1)
148297
148331
148523
1 : Data affected by changes in population controls.
Unemployment Level 8,549,000
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
Year
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
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
15046
15113
15202
15325
14849
14474
14512
14648
14579
14516
15081
14348
2011
14046
13828
13728
13956
13853
13958
13756
13806
13929
13599
13309
13071
2012
12812
12828
12696
12636
12668
12688
12657
12449
12106
12141
12026
12272
2013
12497
11967
11653
11735
11671
11736
11357
11241
11251
11161
10814
10376
2014
10280
10387
10384
9696
9761
9453
9648
9568
9237
8983
9071
8688
2015
8979
8705
8575
8549
U- 3 Unemployment Rate
5.4%
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
Year
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
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
9.4
9.5
9.5
9.4
9.8
9.3
2011
9.2
9.0
9.0
9.1
9.0
9.1
9.0
9.0
9.0
8.8
8.6
8.5
2012
8.3
8.3
8.2
8.2
8.2
8.2
8.2
8.0
7.8
7.8
7.7
7.9
2013
8.0
7.7
7.5
7.6
7.5
7.5
7.3
7.2
7.2
7.2
7.0
6.7
2014
6.6
6.7
6.6
6.2
6.3
6.1
6.2
6.1
5.9
5.7
5.8
5.6
2015
5.7
5.5
5.5
5.4
Not In Labor Force
93,194,000
Series Id: LNS15000000
Seasonally Adjusted
Series title: (Seas) Not in Labor Force
Labor force status: Not in labor force
Type of data: Number in thousands
Age: 16 years and over
Year
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2000
69142
69120
69338
69267
69853
69876
70398
70401
70645
70782
70579
70488
2001
70088
70409
70381
70956
71414
71592
71526
72136
71676
71817
71876
72010
2002
72623
72010
72343
72281
72260
72600
72827
72856
72554
73026
73508
73675
2003
73960
74015
74295
74066
74268
73958
74767
75062
75249
75324
75280
75780
2004
75319
75648
75606
75907
75903
75735
75730
76113
76526
76399
76259
76581
2005
76808
76677
76846
76514
76409
76673
76721
76642
76739
76958
77138
77394
2006
77339
77122
77161
77318
77359
77317
77535
77451
77757
77634
77499
77376
2007
77506
77851
77982
78818
78810
78671
78904
79461
79047
79532
79105
79238
2008
78554
79156
79087
79429
79102
79314
79395
79466
79790
79736
80189
80380
2009
80529
80374
80953
80762
80705
80938
81367
81780
82495
82766
82865
83813
2010
83349
83304
83206
82707
83409
84075
84199
84014
84347
84895
84590
85240
2011
85390
85624
85623
85580
85821
86140
86395
86125
85986
86335
86351
86624
2012
87824
87696
87839
88195
88066
88068
88427
88840
88713
88491
88870
88797
2013
88838
89432
89969
89774
89801
89791
90124
90430
90620
91766
91263
91698
2014
91429
91398
91077
92019
91993
92114
91975
92210
92601
92414
92442
92898
2015
92544
92898
93175
93194
Total Unemployment Rate U-6
10.8%
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
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
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
17.1
16.6
16.4
16.4
16.5
16.8
16.6
16.9
16.6
2011
16.2
16.0
15.9
16.1
15.8
16.1
15.9
16.1
16.3
15.8
15.5
15.2
2012
15.2
15.0
14.5
14.6
14.8
14.8
14.8
14.6
14.7
14.4
14.4
14.4
2013
14.5
14.3
13.8
14.0
13.8
14.2
13.8
13.6
13.6
13.7
13.1
13.1
2014
12.7
12.6
12.6
12.3
12.1
12.0
12.2
12.0
11.7
11.5
11.4
11.2
2015
11.3
11.0
10.9
10.8
Employment Situation Summary
Transmission of material in this release is embargoed until USDL-15-0838
8:30 a.m. (EDT) Friday, May 8, 2015
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 -- APRIL 2015
Total nonfarm payroll employment increased by 223,000 in April, and the
unemployment rate was essentially unchanged at 5.4 percent, the U.S. Bureau
of Labor Statistics reported today. Job gains occurred in professional and
business services, health care, and construction. Mining employment
continued to decline.
Household Survey Data
In April, both the unemployment rate (5.4 percent) and the number of
unemployed persons (8.5 million) were essentially unchanged. Over the
year, the unemployment rate and the number of unemployed persons were down
by 0.8 percentage point and 1.1 million, respectively. (See table A-1.)
Among the major worker groups, the unemployment rate for Asians increased
to 4.4 percent. The rates for adult men (5.0 percent), adult women (4.9
percent), teenagers (17.1 percent), whites (4.7 percent), blacks (9.6
percent), and Hispanics (6.9 percent) showed little or no change in April.
(See tables A-1, A-2, and A-3.)
The number of persons unemployed for less than 5 weeks increased by 241,000
to 2.7 million in April. The number of long-term unemployed (those
jobless for 27 weeks or more) changed little at 2.5 million, accounting
for 29.0 percent of the unemployed. Over the past 12 months, the number
of long-term unemployed has decreased by 888,000. (See table A-12.)
In April, the civilian labor force participation rate (62.8 percent)
changed little. Since April 2014, the participation rate has remained
within a narrow range of 62.7 percent to 62.9 percent. The employment-
population ratio held at 59.3 percent in April and has been at this level
since January. (See table A-1.)
The number of persons employed part time for economic reasons (sometimes
referred to as involuntary part-time workers) was little changed at 6.6
million in April, but is down by 880,000 from a year earlier. These
individuals, who would have preferred full-time employment, 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 April, 2.1 million persons were marginally attached to the labor
force, little changed over the year. (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 756,000 discouraged workers
in April, 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 April 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 rose by 223,000 in April, after
edging up in March (+85,000). In April, employment increased in
professional and business services, health care, and construction,
while employment in mining continued to decline. (See table B-1.)
Professional and business services added 62,000 jobs in April.
Over the prior 3 months, job gains averaged 35,000 per month. In
April, services to buildings and dwellings added 16,000 jobs,
following little change in March. Employment continued to trend up
in April in computer systems design and related services (+9,000),
in business support services (+7,000), and in management and
technical consulting services (+6,000).
Health care employment increased by 45,000 in April. Job growth was
distributed among the three major components--ambulatory health care
services (+25,000), hospitals (+12,000), and nursing and residential
care facilities (+8,000). Over the past year, health care has added
390,000 jobs.
Employment in construction rose by 45,000 in April, after changing
little in March. Over the past 12 months, construction has added
280,000 jobs. In April, job growth was concentrated in specialty
trade contractors (+41,000), with employment gains about evenly
split between the residential and nonresidential components.
Employment declined over the month in nonresidential building
construction (-8,000).
In April, employment continued to trend up in transportation and
warehousing (+15,000).
Employment in mining fell by 15,000 in April, with most of the job
loss in support activities for mining (-10,000) and in oil and gas
extraction (-3,000). Since the beginning of the year, employment
in mining has declined by 49,000, with losses concentrated in
support activities for mining.
Employment in other major industries, including manufacturing,
wholesale trade, retail trade, information, financial activities,
leisure and hospitality, and government, showed little change
over the month.
The average workweek for all employees on private nonfarm payrolls
remained at 34.5 hours in April. The manufacturing workweek for
all employees edged down by 0.1 hour to 40.8 hours, and factory
overtime edged down by 0.1 hour to 3.2 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 April, average hourly earnings for all employees on private
nonfarm payrolls rose by 3 cents to $24.87. Over the past 12
months, average hourly earnings have increased by 2.2 percent.
Average hourly earnings of private-sector production and
nonsupervisory employees edged up by 2 cents to $20.90 in April.
(See tables B-3 and B-8.)
The change in total nonfarm payroll employment for February was
revised from +264,000 to +266,000, and the change for March was
revised from +126,000 to +85,000. With these revisions,
employment gains in February and March combined were 39,000
lower than previously reported. Over the past 3 months, job
gains have averaged 191,000 per month.
_____________
The Employment Situation for May is scheduled to be released
on Friday, June 5, 2015, at 8:30 a.m. (EDT).
http://www.bls.gov/news.release/empsit.nr0.htm
Civilian noninstitutional population247,439249,899250,080250,266186Civilian labor force155,420157,002156,906157,072166Participation rate62.862.862.762.80.1Employed145,724148,297148,331148,523192Employment-population ratio58.959.359.359.30.0Unemployed9,6968,7058,5758,549-26Unemployment rate6.25.55.55.4-0.1Not in labor force92,01992,89893,17593,19419Unemployment rates
Total, 16 years and over6.25.55.55.4-0.1Adult men (20 years and over)5.95.25.15.0-0.1Adult women (20 years and over)5.74.94.94.90.0Teenagers (16 to 19 years)19.117.117.517.1-0.4White5.34.74.74.70.0Black or African American11.410.410.19.6-0.5Asian5.94.03.24.41.2Hispanic or Latino ethnicity7.56.66.86.90.1Total, 25 years and over5.24.54.44.50.1Less than a high school diploma8.88.48.68.60.0High school graduates, no college6.35.45.35.40.1Some college or associate degree5.65.14.84.7-0.1Bachelor’s degree and higher3.32.72.52.70.2Reason for unemployment
Job losers and persons who completed temporary jobs5,1534,1804,1894,136-53Job leavers786884875828-47Reentrants2,6312,6552,6892,685-4New entrants1,05297281586853Duration of unemployment
Less than 5 weeks2,4512,4312,4882,7292415 to 14 weeks2,3462,2232,3122,307-515 to 26 weeks1,5091,3351,2531,139-11427 weeks and over3,4132,7092,5632,525-38Employed persons at work part time
Part time for economic reasons7,4606,6356,7056,580-125Slack work or business conditions4,5173,8474,0693,885-184Could only find part-time work2,6242,4262,3372,37437Part time for noneconomic reasons18,91519,83719,73320,056323Persons not in the labor force (not seasonally adjusted)
Marginally attached to the labor force2,1602,1592,0552,115–Discouraged workers783732738756–– 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. http://www.bls.gov/news.release/empsit.a.htmEmployment Situation Summary Table B. Establishment data, seasonally adjustedhttp://www.bls.gov/news.release/empsit.b.htm2015 April Job Cut Report: Cuts Surge to 61,582, 3-Year High
Falling oil prices contributed to a 68 percent surge in job cuts last month, as US-based employers announced workforce reductions totaling 61,582 in April, up from 36,594 in March, according to the latest report on monthly layoffs released Thursday by global outplacement consultancy Challenger, Gray & Christmas, Inc.
The April total was 53 percent higher than the same month a year ago, when 40,298 planned job cuts were recorded. It represents the highest monthly total since May 2012 (61,887) and the highest April total since 2009 (132,590).
Year to date, employers have announced 201,796 planned job cuts, which marks a 25 percent increase from the 161,639 layoffs tracked in the first four months of 2014. This is the largest four-month total since 2010.
Driving the increased pace of job cutting in April and for the year is the dramatic decline in oil prices, which is forcing producers and suppliers to cut production. Of the 61,582 job cut announced last month, 20,675 or 34 percent were directly attributed to oil prices.
For the year, oil prices were blamed for 68,285 job cuts, or about 34 percent of the 201,796 planned layoffs announced between January 1 and April 30.
“Schlumberger, Baker Hughes and Halliburton have all announced multiple rounds of job cuts in recent months, including April. The largest job cut of the month came from Schlumberger, which announced that it will shed 11,000 workers, in addition to the 9,000 laid off in January,” said John A. Challenger, chief executive officer of Challenger, Gray & Christmas.
“The jobs that are most vulnerable are those in the field – engineers, oil rig operators, drill operators, refinery operators, etc. Managers and executives in the corporate offices are more secure, but the drop in oil prices is leading to increased merger activity, which could put more executives at risk of job loss,” said Challenger.
Most of the oil-related layoffs have occurred in the energy sector, which is the top job-cutting industry to date, with 57,556 planned cuts. That is more than double the second-ranked retail sector, which has announced 26,096 job cuts this year.
The pace of retail sector job cuts is slightly higher than a year ago, when these employers announced 25,224 job cuts through the first four months.
“Low oil prices should be helping retailers. However, the extra money in Americans’ wallets do not appear to be making it into the nation’s cash registers. Retail sales have been lackluster, at best. Furthermore, consumer products giant Procter & Gamble announced in April that it would reduce its headcount by as many as 6,000 workers over the next two years, following a poor earnings report,” noted Challenger.
“We could be witnessing the after-effect of the severe and protracted recession. Much like the generation that lived through the Great Depression, those who scraped by during the recession are being extra careful with their money. Another factor is that not everyone’s boat is rising with the tide. Many Americans are still struggling to find work and those that do are not earning as much they once did,” he said.
HOUSEHOLD DATA
Summary table A. Household data, seasonally adjusted
[Numbers in thousands]
CategoryApr.
2014Feb.
2015Mar.
2015Apr.
2015Change from:
Mar.
2015-
Apr.
2015
Employment status
Civilian noninstitutional population
247,439249,899250,080250,266186
Civilian labor force
155,420157,002156,906157,072166
Participation rate
62.862.862.762.80.1
Employed
145,724148,297148,331148,523192
Employment-population ratio
58.959.359.359.30.0
Unemployed
9,6968,7058,5758,549-26
Unemployment rate
6.25.55.55.4-0.1
Not in labor force
92,01992,89893,17593,19419
Unemployment rates
Total, 16 years and over
6.25.55.55.4-0.1
Adult men (20 years and over)
5.95.25.15.0-0.1
Adult women (20 years and over)
5.74.94.94.90.0
Teenagers (16 to 19 years)
19.117.117.517.1-0.4
White
5.34.74.74.70.0
Black or African American
11.410.410.19.6-0.5
Asian
5.94.03.24.41.2
Hispanic or Latino ethnicity
7.56.66.86.90.1
Total, 25 years and over
5.24.54.44.50.1
Less than a high school diploma
8.88.48.68.60.0
High school graduates, no college
6.35.45.35.40.1
Some college or associate degree
5.65.14.84.7-0.1
Bachelor’s degree and higher
3.32.72.52.70.2
Reason for unemployment
Job losers and persons who completed temporary jobs
5,1534,1804,1894,136-53
Job leavers
786884875828-47
Reentrants
2,6312,6552,6892,685-4
New entrants
1,05297281586853
Duration of unemployment
Less than 5 weeks
2,4512,4312,4882,729241
5 to 14 weeks
2,3462,2232,3122,307-5
15 to 26 weeks
1,5091,3351,2531,139-114
27 weeks and over
3,4132,7092,5632,525-38
Employed persons at work part time
Part time for economic reasons
7,4606,6356,7056,580-125
Slack work or business conditions
4,5173,8474,0693,885-184
Could only find part-time work
2,6242,4262,3372,37437
Part time for noneconomic reasons
18,91519,83719,73320,056323
Persons not in the labor force (not seasonally adjusted)
Marginally attached to the labor force
2,1602,1592,0552,115–
Discouraged workers
783732738756–
– 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 CategoryApr.
2014Feb.
2015Mar.
2015(p)Apr.
2015(p)
EMPLOYMENT BY SELECTED INDUSTRY
(Over-the-month change, in thousands)
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 2014 benchmark levels and updated seasonal adjustment factors.
Transmission of material in this release is embargoed until USDL-15-0325
8:30 a.m. (EST) Friday, March 6, 2015
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 -- FEBRUARY 2015
Total nonfarm payroll employment increased by 295,000 in February, and the
unemployment rate edged down to 5.5 percent, the U.S. Bureau of Labor Statistics
reported today. Job gains occurred in food services and drinking places,
professional and business services, construction, health care, and in
transportation and warehousing. Employment in mining was down over the month.
Household Survey Data
Both the unemployment rate (5.5 percent) and the number of unemployed persons (8.7
million) edged down in February. Over the year, the unemployment rate and the number
of unemployed persons were down by 1.2 percentage points and 1.7 million, respectively.
(See table A-1.)
Among the major worker groups, the unemployment rate for teenagers decreased by 1.7
percentage points to 17.1 percent in February. The jobless rates for adult men (5.2
percent), adult women (4.9 percent), whites (4.7 percent), blacks (10.4 percent),
Asians (4.0 percent), and Hispanics (6.6 percent) showed little or no change. (See
tables A-1, A-2, and A-3.)
The number of long-term unemployed (those jobless for 27 weeks or more) was little
changed at 2.7 million in February. These individuals accounted for 31.1 percent
of the unemployed. Over the past 12 months, the number of long-term unemployed
is down by 1.1 million. (See table A-12.)
The civilian labor force participation rate, at 62.8 percent, changed little in
February and has remained within a narrow range of 62.7 to 62.9 percent since
April 2014. The employment-population ratio was unchanged at 59.3 percent in
February but is up by 0.5 percentage point 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) was little changed in February at 6.6 million.
These individuals, who would have preferred full-time employment, 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 February, 2.2 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 732,000 discouraged workers in
February, 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 February 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 rose by 295,000 in February, compared with
an average monthly gain of 266,000 over the prior 12 months. Job gains occurred
in food services and drinking places, professional and business services,
construction, health care, and in transportation and warehousing. Employment
in mining declined over the month. (See table B-1.)
In February, food services and drinking places added 59,000 jobs. The industry
had added an average of 35,000 jobs per month over the prior 12 months.
Employment in professional and business services increased by 51,000 in February
and has risen by 660,000 over the year. In February, employment continued to
trend up in management and technical consulting services (+7,000), computer
systems design and related services (+5,000), and architectural and engineering
services (+5,000).
Construction added 29,000 jobs in February. Employment in specialty trade
contractors rose by 27,000, mostly in the residential component. Over the past
12 months, construction has added 321,000 jobs.
In February, employment in health care rose by 24,000, with gains in ambulatory
care services (+20,000) and hospitals (+9,000). Health care had added an average
of 29,000 jobs per month over the prior 12 months.
Transportation and warehousing added 19,000 jobs in February, with most of the
gain occurring in couriers and messengers (+12,000). Employment in transportation
and warehousing grew by an average of 14,000 per month over the prior 12 months.
Employment in retail trade continued to trend up in February (+32,000) and has
grown by 319,000 over the year.
Manufacturing employment continued to trend up in February (+8,000). Within the
industry, petroleum and coal products lost 6,000 jobs, largely due to a strike.
Employment in mining decreased by 9,000 in February, with most of the decline in
support activities for mining (-7,000).
Employment in other major industries, including wholesale trade, information,
financial activities, and government, showed little change over the month.
In February, the average workweek for all employees on private nonfarm payrolls
was 34.6 hours for the fifth month in a row. The manufacturing workweek was
unchanged at 41.0 hours in February, 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 33.8 hours. (See tables B-2 and B-7.)
In February, average hourly earnings for all employees on private nonfarm payrolls
rose by 3 cents to $24.78. Over the year, average hourly earnings have risen by 2.0
percent. In February, average hourly earnings of private-sector production and
nonsupervisory employees were unchanged at $20.80. (See tables B-3 and B-8.)
After revision, the change in total nonfarm payroll employment for December
remained at +329,000, and the change for January was revised from +257,000 to
+239,000. With these revisions, employment gains in December and January were
18,000 lower than previously reported. Over the past 3 months, job gains have
averaged 288,000 per month.
_____________
The Employment Situation for March is scheduled to be released on Friday,
April 3, 2015, at 8:30 a.m. (EDT).
HOUSEHOLD DATA
Summary table A. Household data, seasonally adjusted
[Numbers in thousands]
Category
Feb.
2014
Dec.
2014
Jan.
2015
Feb.
2015
Change from:
Jan.
2015-
Feb.
2015
Employment status
Civilian noninstitutional population
247,085
249,027
249,723
249,899
176
Civilian labor force
155,688
156,129
157,180
157,002
-178
Participation rate
63.0
62.7
62.9
62.8
-0.1
Employed
145,301
147,442
148,201
148,297
96
Employment-population ratio
58.8
59.2
59.3
59.3
0.0
Unemployed
10,387
8,688
8,979
8,705
-274
Unemployment rate
6.7
5.6
5.7
5.5
-0.2
Not in labor force
91,398
92,898
92,544
92,898
354
Unemployment rates
Total, 16 years and over
6.7
5.6
5.7
5.5
-0.2
Adult men (20 years and over)
6.3
5.3
5.3
5.2
-0.1
Adult women (20 years and over)
5.9
5.0
5.1
4.9
-0.2
Teenagers (16 to 19 years)
21.3
16.8
18.8
17.1
-1.7
White
5.8
4.8
4.9
4.7
-0.2
Black or African American
12.0
10.4
10.3
10.4
0.1
Asian
5.9
4.2
4.0
4.0
0.0
Hispanic or Latino ethnicity
8.1
6.5
6.7
6.6
-0.1
Total, 25 years and over
5.4
4.5
4.6
4.5
-0.1
Less than a high school diploma
9.8
8.6
8.5
8.4
-0.1
High school graduates, no college
6.4
5.3
5.4
5.4
0.0
Some college or associate degree
6.0
4.9
5.2
5.1
-0.1
Bachelor’s degree and higher
3.4
2.9
2.8
2.7
-0.1
Reason for unemployment
Job losers and persons who completed temporary jobs
5,403
4,325
4,242
4,180
-62
Job leavers
816
798
851
884
33
Reentrants
2,972
2,701
2,829
2,655
-174
New entrants
1,232
971
1,033
972
-61
Duration of unemployment
Less than 5 weeks
2,388
2,375
2,383
2,431
48
5 to 14 weeks
2,558
2,293
2,318
2,223
-95
15 to 26 weeks
1,597
1,274
1,380
1,335
-45
27 weeks and over
3,804
2,785
2,800
2,709
-91
Employed persons at work part time
Part time for economic reasons
7,204
6,790
6,810
6,635
-175
Slack work or business conditions
4,259
4,061
4,012
3,847
-165
Could only find part-time work
2,674
2,432
2,460
2,426
-34
Part time for noneconomic reasons
19,085
19,730
19,822
19,837
15
Persons not in the labor force (not seasonally adjusted)
Marginally attached to the labor force
2,303
2,260
2,234
2,159
–
Discouraged workers
755
740
682
732
–
– 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
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 2014 benchmark levels and updated seasonal adjustment factors.
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.
Typically, it is not possible to precisely quantify the effect of extreme weather on
payroll employment estimates. In order for severe weather conditions to reduce
employment estimates, employees have to be off work without pay for the entire pay
period. Employees who receive pay for any part of the pay period, even 1 hour, are
counted in the payroll employment figures. For more information on how often employees
are paid, please visit www.bls.gov/opub/btn/volume-3/how-frequently-do-private-
businesses-pay-workers.htm.
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 due to bad weather.
Current and historical data are available on the household survey's most requested
statistics page, please visit 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 143,000 businesses and government agencies,
representing approximately 588,000 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 105,000.
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
-55,000 to +155,000 (50,000 +/- 105,000). 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
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
Footnotes (1) The population figures are not adjusted for seasonal variation; therefore, identical numbers appear in the unadjusted and seasonally adjusted columns.
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
Footnotes (1) The population figures are not adjusted for seasonal variation; therefore, identical numbers appear in the unadjusted and seasonally adjusted columns.
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
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
Feb.
2014
Feb.
2015
Feb.
2014
Feb.
2015
Feb.
2014
Feb.
2015
VETERANS, 18 years and over
Civilian noninstitutional population
21,298
21,326
19,054
19,335
2,244
1,991
Civilian labor force
10,833
10,903
9,389
9,577
1,445
1,326
Participation rate
50.9
51.1
49.3
49.5
64.4
66.6
Employed
10,149
10,325
8,781
9,076
1,368
1,250
Employment-population ratio
47.7
48.4
46.1
46.9
61.0
62.8
Unemployed
684
578
608
502
76
76
Unemployment rate
6.3
5.3
6.5
5.2
5.3
5.7
Not in labor force
10,465
10,423
9,665
9,758
799
665
Gulf War-era II veterans
Civilian noninstitutional population
2,995
3,421
2,415
2,838
581
584
Civilian labor force
2,430
2,825
2,020
2,404
410
421
Participation rate
81.1
82.6
83.7
84.7
70.6
72.2
Employed
2,207
2,635
1,838
2,230
370
405
Employment-population ratio
73.7
77.0
76.1
78.6
63.7
69.3
Unemployed
223
190
183
174
40
17
Unemployment rate
9.2
6.7
9.0
7.2
9.9
4.0
Not in labor force
565
596
394
434
171
163
Gulf War-era I veterans
Civilian noninstitutional population
3,412
3,533
2,707
2,965
704
567
Civilian labor force
2,787
2,885
2,284
2,450
503
435
Participation rate
81.7
81.7
84.3
82.6
71.4
76.6
Employed
2,658
2,777
2,177
2,378
481
400
Employment-population ratio
77.9
78.6
80.4
80.2
68.3
70.5
Unemployed
128
107
107
72
22
35
Unemployment rate
4.6
3.7
4.7
2.9
4.3
8.1
Not in labor force
625
648
424
515
201
132
World War II, Korean War, and Vietnam-era veterans
Civilian noninstitutional population
9,554
9,057
9,195
8,735
359
322
Civilian labor force
2,817
2,419
2,718
2,293
99
127
Participation rate
29.5
26.7
29.6
26.2
27.6
39.4
Employed
2,633
2,293
2,539
2,177
95
116
Employment-population ratio
27.6
25.3
27.6
24.9
26.4
36.0
Unemployed
184
126
179
115
4
11
Unemployment rate
6.5
5.2
6.6
5.0
4.4
8.5
Not in labor force
6,737
6,638
6,477
6,442
260
195
Veterans of other service periods
Civilian noninstitutional population
5,337
5,315
4,737
4,797
600
518
Civilian labor force
2,799
2,774
2,367
2,431
432
343
Participation rate
52.4
52.2
50.0
50.7
72.0
66.2
Employed
2,650
2,620
2,227
2,290
422
330
Employment-population ratio
49.6
49.3
47.0
47.7
70.4
63.7
Unemployed
149
154
140
141
10
13
Unemployment rate
5.3
5.6
5.9
5.8
2.2
3.9
Not in labor force
2,538
2,541
2,370
2,366
168
175
NONVETERANS, 18 years and over
Civilian noninstitutional population
216,827
219,793
95,685
96,888
121,142
122,906
Civilian labor force
142,531
143,572
71,799
72,636
70,732
70,936
Participation rate
65.7
65.3
75.0
75.0
58.4
57.7
Employed
132,676
135,360
66,338
68,082
66,338
67,278
Employment-population ratio
61.2
61.6
69.3
70.3
54.8
54.7
Unemployed
9,854
8,212
5,460
4,554
4,394
3,658
Unemployment rate
6.9
5.7
7.6
6.3
6.2
5.2
Not in labor force
74,296
76,222
23,887
24,252
50,410
51,970
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.
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
Feb.
2014
Feb.
2015
Feb.
2014
Feb.
2015
TOTAL, 16 years and over
Civilian noninstitutional population
28,970
29,316
218,116
220,584
Civilian labor force
5,537
5,806
149,490
150,407
Participation rate
19.1
19.8
68.5
68.2
Employed
4,746
5,153
139,388
141,965
Employment-population ratio
16.4
17.6
63.9
64.4
Unemployed
792
653
10,102
8,442
Unemployment rate
14.3
11.2
6.8
5.6
Not in labor force
23,433
23,510
68,626
70,177
Men, 16 to 64 years
Civilian labor force
2,454
2,637
74,918
75,718
Participation rate
32.2
34.3
81.4
81.8
Employed
2,042
2,321
69,248
71,047
Employment-population ratio
26.8
30.1
75.3
76.8
Unemployed
412
316
5,670
4,671
Unemployment rate
16.8
12.0
7.6
6.2
Not in labor force
5,173
5,061
17,082
16,820
Women, 16 to 64 years
Civilian labor force
2,097
2,201
67,167
66,993
Participation rate
26.8
28.0
70.5
69.9
Employed
1,762
1,925
63,048
63,564
Employment-population ratio
22.6
24.5
66.2
66.3
Unemployed
334
276
4,119
3,429
Unemployment rate
15.9
12.5
6.1
5.1
Not in labor force
5,719
5,647
28,074
28,886
Both sexes, 65 years and over
Civilian labor force
986
967
7,405
7,696
Participation rate
7.3
7.0
24.0
23.9
Employed
941
907
7,092
7,354
Employment-population ratio
7.0
6.6
23.0
22.9
Unemployed
45
60
313
342
Unemployment rate
4.6
6.2
4.2
4.4
Not in labor force
12,541
12,802
23,470
24,471
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
Feb.
2014
Feb.
2015
Feb.
2014
Feb.
2015
Feb.
2014
Feb.
2015
Foreign born, 16 years and over
Civilian noninstitutional population
38,188
40,300
18,429
19,540
19,759
20,760
Civilian labor force
25,421
26,276
14,612
15,233
10,809
11,043
Participation rate
66.6
65.2
79.3
78.0
54.7
53.2
Employed
23,658
24,741
13,693
14,326
9,964
10,414
Employment-population ratio
61.9
61.4
74.3
73.3
50.4
50.2
Unemployed
1,763
1,536
919
907
845
629
Unemployment rate
6.9
5.8
6.3
6.0
7.8
5.7
Not in labor force
12,768
14,023
3,817
4,306
8,951
9,717
Native born, 16 years and over
Civilian noninstitutional population
208,897
209,600
100,877
101,108
108,020
108,492
Civilian labor force
129,606
129,937
67,342
67,807
62,264
62,130
Participation rate
62.0
62.0
66.8
67.1
57.6
57.3
Employed
120,476
122,378
61,994
63,497
58,482
58,880
Employment-population ratio
57.7
58.4
61.5
62.8
54.1
54.3
Unemployed
9,130
7,559
5,348
4,309
3,782
3,250
Unemployment rate
7.0
5.8
7.9
6.4
6.1
5.2
Not in labor force
79,291
79,663
33,535
33,301
45,756
46,362
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
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
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
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
Feb.
2014
Jan.
2015
Feb.
2015
Feb.
2014
Oct.
2014
Nov.
2014
Dec.
2014
Jan.
2015
Feb.
2015
NUMBER OF UNEMPLOYED
Job losers and persons who completed temporary jobs
6,024
4,912
4,721
5,403
4,349
4,480
4,325
4,242
4,180
On temporary layoff
1,341
1,328
1,349
1,037
847
1,070
959
902
1,021
Not on temporary layoff
4,682
3,584
3,372
4,366
3,501
3,410
3,366
3,339
3,158
Permanent job losers
3,366
2,491
2,316
3,190
2,505
2,446
2,388
2,371
2,212
Persons who completed temporary jobs
1,316
1,093
1,056
1,177
997
964
977
968
946
Job leavers
813
868
894
816
782
835
798
851
884
Reentrants
2,974
2,832
2,635
2,972
2,856
2,761
2,701
2,829
2,655
New entrants
1,083
885
845
1,232
1,058
1,045
971
1,033
972
PERCENT DISTRIBUTION
Job losers and persons who completed temporary jobs
55.3
51.7
51.9
51.8
48.1
49.1
49.2
47.4
48.1
On temporary layoff
12.3
14.0
14.8
10.0
9.4
11.7
10.9
10.1
11.7
Not on temporary layoff
43.0
37.7
37.1
41.9
38.7
37.4
38.3
37.3
36.3
Job leavers
7.5
9.1
9.8
7.8
8.6
9.2
9.1
9.5
10.2
Reentrants
27.3
29.8
29.0
28.5
31.6
30.3
30.7
31.6
30.5
New entrants
9.9
9.3
9.3
11.8
11.7
11.5
11.0
11.5
11.2
UNEMPLOYED AS A PERCENT OF THE
CIVILIAN LABOR FORCE
Job losers and persons who completed temporary jobs
3.9
3.1
3.0
3.5
2.8
2.9
2.8
2.7
2.7
Job leavers
0.5
0.6
0.6
0.5
0.5
0.5
0.5
0.5
0.6
Reentrants
1.9
1.8
1.7
1.9
1.8
1.8
1.7
1.8
1.7
New entrants
0.7
0.6
0.5
0.8
0.7
0.7
0.6
0.7
0.6
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
Feb.
2014
Jan.
2015
Feb.
2015
Feb.
2014
Oct.
2014
Nov.
2014
Dec.
2014
Jan.
2015
Feb.
2015
NUMBER OF UNEMPLOYED
Less than 5 weeks
2,145
2,780
2,185
2,388
2,455
2,505
2,375
2,383
2,431
5 to 14 weeks
3,091
2,468
2,662
2,558
2,322
2,378
2,293
2,318
2,223
15 weeks and over
5,657
4,250
4,248
5,402
4,321
4,225
4,059
4,180
4,044
15 to 26 weeks
1,771
1,396
1,485
1,597
1,416
1,403
1,274
1,380
1,335
27 weeks and over
3,886
2,853
2,763
3,804
2,904
2,822
2,785
2,800
2,709
Average (mean) duration, in weeks
36.3
30.3
31.1
36.9
32.9
33.0
32.8
32.3
31.7
Median duration, in weeks
16.0
12.3
13.1
16.2
13.5
12.8
12.6
13.4
13.1
PERCENT DISTRIBUTION
Less than 5 weeks
19.7
29.3
24.0
23.1
27.0
27.5
27.2
26.8
27.9
5 to 14 weeks
28.4
26.0
29.3
24.7
25.5
26.1
26.3
26.1
25.6
15 weeks and over
51.9
44.7
46.7
52.2
47.5
46.4
46.5
47.1
46.5
15 to 26 weeks
16.3
14.7
16.3
15.4
15.6
15.4
14.6
15.5
15.4
27 weeks and over
35.7
30.0
30.4
36.8
31.9
31.0
31.9
31.5
31.1
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
Agriculture and related private wage and salary workers
153
196
11.4
12.7
Government workers
683
513
3.2
2.4
Self-employed workers, unincorporated, and unpaid family workers
496
495
5.0
5.1
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
Feb.
2014
Jan.
2015
Feb.
2015
Feb.
2014
Oct.
2014
Nov.
2014
Dec.
2014
Jan.
2015
Feb.
2015
U-1 Persons unemployed 15 weeks or longer, as a percent of the civilian labor force
3.6
2.7
2.7
3.5
2.8
2.7
2.6
2.7
2.6
U-2 Job losers and persons who completed temporary jobs, as a percent of the civilian labor force
3.9
3.1
3.0
3.5
2.8
2.9
2.8
2.7
2.7
U-3 Total unemployed, as a percent of the civilian labor force (official unemployment rate)
7.0
6.1
5.8
6.7
5.7
5.8
5.6
5.7
5.5
U-4 Total unemployed plus discouraged workers, as a percent of the civilian labor force plus discouraged workers
7.5
6.5
6.3
7.1
6.2
6.2
6.0
6.1
6.0
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
8.4
7.4
7.1
8.0
7.1
7.1
6.9
7.0
6.8
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
13.1
12.0
11.4
12.6
11.5
11.4
11.2
11.3
11.0
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
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
Museums, historical sites, and similar institutions
134.0
138.5
133.7
133.0
144.9
145.2
145.4
144.3
-1.1
Amusements, gambling, and recreation
1,334.7
1,388.1
1,352.6
1,367.3
1,498.8
1,528.7
1,529.2
1,534.1
4.9
Accommodation and food services
12,034.0
12,629.3
12,380.8
12,491.9
12,446.2
12,814.7
12,857.6
12,917.8
60.2
Accommodation
1,791.8
1,829.1
1,802.7
1,816.2
1,881.8
1,896.9
1,902.4
1,903.9
1.5
Food services and drinking places
10,242.2
10,800.2
10,578.1
10,675.7
10,564.4
10,917.8
10,955.2
11,013.9
58.7
Other services
5,483
5,589
5,550
5,573
5,538
5,611
5,618
5,627
9
Repair and maintenance
1,217.7
1,243.0
1,244.1
1,256.3
1,230.0
1,253.3
1,259.6
1,267.2
7.6
Personal and laundry services
1,337.5
1,380.9
1,365.6
1,363.1
1,354.3
1,380.7
1,383.4
1,380.6
-2.8
Membership associations and organizations
2,927.5
2,965.3
2,940.0
2,953.8
2,953.3
2,976.5
2,975.0
2,978.8
3.8
Government
22,110
22,261
21,765
22,201
21,824
21,902
21,904
21,911
7
Federal
2,712.0
2,744.0
2,717.0
2,716.0
2,730.0
2,732.0
2,730.0
2,730.0
0.0
Federal, except U.S. Postal Service
2,124.6
2,133.0
2,124.8
2,122.9
2,139.7
2,134.6
2,138.3
2,135.2
-3.1
U.S. Postal Service
587.6
611.3
592.6
593.1
590.5
597.6
591.4
595.0
3.6
State government
5,182.0
5,194.0
4,984.0
5,211.0
5,061.0
5,079.0
5,080.0
5,083.0
3.0
State government education
2,539.7
2,555.0
2,350.5
2,578.4
2,408.0
2,430.5
2,434.3
2,438.7
4.4
State government, excluding education
2,642.5
2,639.1
2,633.8
2,632.6
2,652.6
2,648.9
2,646.0
2,644.1
-1.9
Local government
14,216.0
14,323.0
14,064.0
14,274.0
14,033.0
14,091.0
14,094.0
14,098.0
4.0
Local government education
8,069.7
8,109.7
7,901.8
8,101.2
7,765.4
7,796.7
7,799.0
7,800.2
1.2
Local government, excluding education
6,145.9
6,213.5
6,161.9
6,172.7
6,267.7
6,294.1
6,294.9
6,297.5
2.6
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
NOTE: Data have been revised to reflect March 2014 benchmark levels and updated seasonal adjustment factors.
ESTABLISHMENT DATA
Table B-2. Average weekly hours and overtime of all employees on private nonfarm payrolls by industry sector, seasonally adjusted
NOTE: Data have been revised to reflect March 2014 benchmark levels and updated seasonal adjustment factors.
ESTABLISHMENT DATA
Table B-4. Indexes of aggregate weekly hours and payrolls for all employees on private nonfarm payrolls by industry sector, seasonally adjusted
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
NOTE: Data have been revised to reflect March 2014 benchmark levels and updated seasonal adjustment factors.
ESTABLISHMENT DATA
Table B-5. Employment of women on nonfarm payrolls by industry sector, seasonally adjusted
NOTE: Data have been revised to reflect March 2014 benchmark levels and updated seasonal adjustment factors.
ESTABLISHMENT DATA
Table B-6. Employment of production and nonsupervisory employees on private nonfarm payrolls by industry sector, seasonally adjusted(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
NOTE: Data have been revised to reflect March 2014 benchmark levels and updated seasonal adjustment factors.
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)
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
NOTE: Data have been revised to reflect March 2014 benchmark levels and updated seasonal adjustment factors.
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)
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
NOTE: Data have been revised to reflect March 2014 benchmark levels and updated seasonal adjustment factors.
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)
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
NOTE: Data have been revised to reflect March 2014 benchmark levels and updated seasonal adjustment factors.
Story 1: Department of Labor Revised Job Numbers in November of 414,000 and December of 329,000 Plus 257,000 in January — Wages Increase 12 Cents Per Hour — Solid Jobs Report — U-3 Unemployment Rate Increased From 5.6% to 5.7% and 9 Million Unemployed — 1 Million Additional Americans Looking For Jobs — Spread The Message of Liberty — Videos
Gallup CEO: Labor Department Numbers Are Misleading
Are monthly jobs numbers misleading
Gallup CEO Jim Clifton The “Real” Unemployment Rate In America @ 11.2% Double What Obama Says
Gallup discovers Obama may not be truthful on unemployment (Limbaugh)
Latest Jobs Report Sparking Questions About The Quality Of Jobs Being Created – Cavuto
Ep 51: Despite Slowing Economy, Job Growth Speeds Up
Investor Jim Rogers Gives Warning to Investor
US Job Market Improves
US jobs market booms as recovery accelerates
Nightly Business Report — February 6, 2015
February 6, 2015 Financial News – Business News – Stock Exchange – NYSE – Market News
The H1-B visa scam
Bill Gates Asks Senate For Infinite Number Of H 1B Visas
Peter Schiff Inflation Deterring Economic Growth
Taylor at CFR: Rethinking the Fed’s Dual Mandate
Uncommon Knowledge with John B. Taylor
A Discussion of the Fed’s Dual Mandate Responsibilities
The Federal Reserve’s Stanley Fischer on Inflation and Financial Stability
Trump Rattles The American Okie Doke Obama Into Stuttering Empty Suit –The Great Pretender — The Truth Hurts — Get Out of Our Lives — Roll It Back To A Full Employment Growing Booming Economy with 67% Labor Participation Rate and Less Than 3% Unemployment Rate — Make America Great Again — Catch Me If You Can — Videos
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The Pronk Pops Show Podcasts
Pronk Pops Show 691: June 2, 2016
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Story 1: Trump Rattles The American Okie Doke Obama Into Stuttering Empty Suit –The Great Pretender — The Truth Hurts — Get Out of Our Lives — Roll It Back To A Full Employment Growing Booming Economy with 67% Labor Participation Rate and Less Than 3% Unemployment Rate — Make America Great Again — Catch Me If You Can — Videos
-A joke played on someone. Someone getting played for a fool.
-Also, someone who is fake or is a joke.
“I felt like a dumbass when that nigga hit me with the okie doke.”
“I keep it real homeboy. I ain’t no okie doke.”
Psychological projection is a theory in psychology in which humans defend themselves against their own unpleasant impulses by denying their existence while attributing them to others. For example, a person who is habitually rude may constantly accuse other people of being rude. It incorporates blame shifting.
Immigration moderation. Before any new green cards are issued to foreign workers abroad, there will be a pause where employers will have to hire from the domestic pool of unemployed immigrant and native workers. This will help reverse women’s plummeting workplace participation rate, grow wages, and allow record immigration levels to subside to more moderate historical averages.
https://www.donaldjtrump.com/positions/immigration-reform
George Carlin – The American Okie Doke
U.S. Labor Participation Rate – Graph of Reagan vs obama
Obama Tries to Trash Donald Trump and Turns into a Stuttering Mess
Obama attacks Trump in Indiana speech but won’t use his name
Obama Busts GOP Economic Myths
Obama takes a victory lap over Elkhart, Indiana’s resurgence
Why doesn’t Obama say Donald Trump’s name?
The Great Pretender Obama Says Don’t Fall For The Okie-Doke
No Help Wanted – Labor Participation Rate Lowest Since 1977 – Fox & Friends.
Labor participation has hit a 38-year low, and that’s a problem
Labor participation rate is down to unprecedented levels
Unemployment and the Unemployment Rate
Types of Unemployment
Top 10 Greatest Con Artists in Movies
Catch me if you can best scenes
Catch Me If You Can Movie- Check Fraud
Catch Me If You Can Trailer
To Tell the Truth: Frank William Abagnale Jr. (1977)
The Real Frank Abagnale, “Catch me if you can” man – CNN Red Chair
Catch Me If You Can: Frank Abagnale’s Story
Frank Abagnale, who evolved from being a brilliant young mastermind of international deception and fraud into one of the world’s most respected authorities on forgery and embezzlement, tells his life story. His intercontinental saga prompted Steven Spielberg to turn Abagnale’s life into the movie Catch Me If You Can starring Leonardo DiCaprio.
The Platters – The Great Pretender – HD (1955)
Data extracted on: June 2, 2016 (4:31:21 PM)
Labor Force Statistics from the Current Population Survey
Obama in Elkhart: Voters should beware of politicians ‘preying’ on economic fears
President Barack Obama says people should beware of politicians who are “preying” on Americans’ anxieties about the economy in a bid to win headlines and votes.
Obama isn’t naming names. But he says some politicians are running on anti-trade, anti-immigrant policies in an effort to play to people’s fears.
Obama made the remarks during a visit to Elkhart, Indiana. He’s holding up the manufacturing community as a symbol of the nation’s climb from recession to recovery.
Obama says his administration’s “smart” decisions played a part in helping Elkhart come back. He says he wants to bust “myths” that Democratic policies are bad for the economy.
Indiana’s Republican governor, Mike Pence, says Elkhart had rebounded “in spite of Obama’s policies” and that those policies inflicted onerous federal burdens on Indiana.
To Obama, lingering challenges aren’t enough to forestall a planned victory lap. Arguing that his controversial $840 billion stimulus package was ultimately vindicated, Obama will call on the next president to be willing to spend big to enable further economic growth.
The president is making his eighth visit to the state since taking office in January 2009. Here are details on the visits:
Obama in Elkhart: Voters should beware of politicians ‘preying’ on economic fears
Psychological projection
Psychological projection is a theory in psychology in which humans defend themselves against their own unpleasant impulses by denying their existence while attributing them to others.[1] For example, a person who is habitually rudemay constantly accuse other people of being rude. It incorporates blame shifting.
According to some research, the projection of one’s negative qualities onto others is a common process in everyday life.[2]
Historical precursors
A prominent precursor in the formulation of the projection principle was Giambattista Vico,[3][4] and an early formulation of it is found in ancient Greek writer Xenophanes, which observed that “the gods of Ethiopians were inevitably black with flat noses while those of the Thracians were blond with blue eyes.”[citation needed] In 1841, Ludwig Feuerbach was the first to employ this concept as the basis for a systematic critique of religion.[5][6][7]
Psychoanalytic developments
Projection (German: Projektion) was conceptualised by Freud in his letters to Wilhelm Fliess,[8] and further refined by Karl Abraham and Anna Freud. Freud considered that in projection thoughts, motivations, desires, and feelings that cannot be accepted as one’s own are dealt with by being placed in the outside world and attributed to someone else.[9] What the ego repudiates is split off and placed in another.[10]
Freud would later come to believe that projection did not take place arbitrarily, but rather seized on and exaggerated an element that already existed on a small scale in the other person.[11] (The related defence of projective identification differs from projection in that there the other person is expected to become identified with the impulse or desire projected outside,[12] so that the self maintains a connection with what is projected, in contrast to the total repudiation of projection proper.)[13]
Melanie Klein saw the projection of good parts of the self as leading potentially to over-idealisation of the object.[14] Equally, it may be one’s conscience that is projected, in an attempt to escape its control: a more benign version of this allows one to come to terms with outside authority.[15]
Theoretical examples
Projection tends to come to the fore in normal people at times of crisis, personal or political[16] but is more commonly found in the neurotic or psychotic[17] in personalities functioning at a primitive level as in narcissistic personality disorder or borderline personality disorder.[18]
Carl Jung considered that the unacceptable parts of the personality represented by the Shadow archetype were particularly likely to give rise to projection, both small-scale and on a national/international basis.[19] Marie-Louise Von Franz extended her view of projection, stating that “wherever known reality stops, where we touch the unknown, there we project an archetypal image”.[20]
Psychological projection is one of the medical explanations of bewitchment used to explain the behavior of the afflicted children at Salem in 1692. The historian John Demos asserts that the symptoms of bewitchment experienced by the afflicted girls were due to the girls undergoing psychological projection of repressed aggression.[21]
Practical examples
Counter-projection
Jung wrote, “All projections provoke counter-projection when the object is unconscious of the quality projected upon it by the subject.”[27] Thus, what is unconscious in the recipient will be projected back onto the projector, precipitating a form of mutual acting out.[28]
In a rather different usage, Harry Stack Sullivan saw counter-projection in the therapeutic context as a way of warding off the compulsive re-enactment of apsychological trauma, by emphasising the difference between the current situation and the projected obsession with the perceived perpetrator of the original trauma.[29]
Clinical approaches
Drawing on Gordon Allport‘s idea of the expression of self onto activities and objects, projective techniques have been devised to aid personality assessment, including the Rorschach ink-blots and the Thematic Apperception Test (TAT).[30]
Projection may help a fragile ego reduce anxiety, but at the cost of a certain dissociation, as in dissociative identity disorder.[31] In extreme cases, an individual’s personality may end up becoming critically depleted.[32] In such cases, therapy may be required which would include the slow rebuilding of the personality through the “taking back” of such projections.[33]
Criticism
Some studies were critical of Freud’s theory. Research supports the existence of a false-consensus effect whereby humans have a broad tendency to believe that others are similar to themselves, and thus “project” their personal traits onto others. This applies to good traits as well as bad traits and is not a defense mechanism for denying the existence of the trait within the self.[34]
Instead, Newman, Duff, and Baumeister (1997) proposed a new model of defensive projection. In this view, people try to suppress thoughts of their undesirable traits, and these efforts make those trait categories highly accessible—so that they are then used all the more often when forming impressions of others. The projection is then only a by-product of the real defensive mechanism.[35]
See also
https://en.wikipedia.org/wiki/Psychological_projection
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