Transcript Leisure Inequality Mark Aguiar and Erik Hurst September 2007

Lecture 4:
Time Series and Business Cycle
Patterns in Labor Supply
Part A:
Time Series Patterns in Labor Supply,
Some Facts
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
50
Men, Unconditional (U.S. CPS)
45
40
35
30
25
20
Series2
Series3
Series4
Series5
Series6
Growth in Hours vs Growth in Per Capita Income
.2
Men 25-65 Annual Hours Unadjusted
WV
.1
PA
0
NH
AL
AR
MS
-.2
-.1
DE
RI CT
OH
MA
WA
NJ
IL
MI ME IN UT
KY
CA
CO VA
WY
MD
NY
TN
OK
KS NC
OR
NV
MOAZ
TX LA
NM
MT
SC
GA
ID MN NE ND
SD
WI
IA
FL
VT
.5
1
1.5
Growth in Per Capita Income
Fitted values
gr_annual_hours_m_2_40_80
2
Growth in Participation vs Growth in Per Capita Income
0
Men 25-65 Participation Unadjusted 1940 - 1980
CO
NH
WY NE
-.05
DE
UT
CT IL
IAMN
MA
WI
WA
IN
NJ
CA
MD
NV
OH
RI
ID
MEOR MO
NY
PAMTVT
AZ
MI
KS
SD
VATX
ND
OK
NM LA
NC
GA
TN
SC
-.1
WV
FL
KY
AL
MS
-.15
AR
.5
1
1.5
Growth in Per Capita Income
Fitted values
gr_working_m_2_40_80
2
Growth in Hours vs Growth in Per Capita Income
Men 25-65 Annual Hours Unadjusted 1980-2000
-.05
0
FL
VA
MD
MI ARPA
GA
TN VT NJ
NH
CO
IL
AZ
OH
CT
NC
WI IN WA RI
MNNY
DE MO KYNE
CA OR
IA
AL ME
ID
KS
UT
SC
ND
TX
NV
-.1
OK LA
MT
MS
SD
NM WV
-.15
WY
.1
.2
.3
.4
Growth in Per Capita Income
Fitted values
gr_annual_hours_m_2_80_00
.5
MA
Growth in Participation vs Growth in Per Capita Income
Men 25-65 Participation Unadjusted 1980-2000
-.04
-.02
VT
IA
FL
-.06
WI
UT
WA
OR
AR
PA
KS
ID
MO
OH DE
IN
-.08
AZ
MN
NE
ND
RI MD
VA
MT
OK
ME
IL
-.1
NV
-.12
WY
TN
NC
CT
GA
NJ
KY
CA
TX
MA
SD
CO
MI
NH
AL
NY
SC
MS
LA
NM WV
.1
.2
.3
.4
Growth in Per Capita Income
Fitted values
gr_working_m_2_80_00
.5
Part B:
Time Series Patterns in Labor Supply,
Some Explanations
Trends in The Natural Rate In Unemployment
•
Did labor market conditions improve during the 1980s and 1990s?
-
•
Unemployment rates fell substantially
Related concept:
Do income or substitution effects dominate with respect to
labor supply decisions?
•
Must reads:
Murphy, Topel, and Juhn “Current Unemployment, Historically
Contemplated” (Brookings Papers on Economic Activity, 2002(1)).
Real Wages Over Time
Juhn, Murphy, Topel: Evolution of Wage Inequality
Trends in Unemployment and Nonemployment
Breakdown of the Non-Participators: Rising Disability
Rising Disability Among the Persistently Unemployed
Autor and Duggan (QJE 2003)
•
For a detailed analysis of the intersection of the role of disability and
labor supply, see Autor and Duggan’s:
“The Rise in the Disability Rolls and the Decline in Unemployment”
•
Show that during recessions, the disability margin is much more relevant
now than it was during the 1980s (the benefits to the disabled are now
more comparable to unemployment benefits than before).
Autor and Duggan
More Juhn, Murphy, Topel
Increase in Long Term Non-employment Duration
Increase in Long Term Unemployment Duration
Real Wages Over Time
Unemployment Trends Throughout the Wage Distribution
Nonparticipation Trends Throughout the Wage Distribution
Non-employment Trends Throughout the Wage Distribution
Income or Substitution Effects?
Income of Substitution Effect
Conclusions
• Decline in unemployment rate may not represent accurately the trends in
labor market performance.
• Large decline in participation rates for men.
• Non employment has declined much less than unemployment.
• The decline is much more pronounced for low wage men.
• Does it tell us substitution effects are important? What about changes in
transfers?
Part C:
A Recent Story – Elsby and Shapiro (AER, 2011)
Why Does Trend Growth Affect Equilibrium
Employment? A New Explanation of an Old
Puzzle
(Note: I am using some of Elsby’s slides)
Existing Explanations
• Juhn, Murphy, and Topel (1991, 2002)
suggest decline in demand for low-skilled
labor in 1970s and 1980s.
• Autor & Duggan (2003), Bound &
Waidmann (1992) suggest increase in
generosity of disability insurance accounts
for declines in employment rates among
older men (45+).
Our Contribution
• We emphasize the role of wage growth in
reducing work incentives through 2
channels:
a) Reductions in the returns to experience
among low-skilled workers; and
b) Reductions in the rate of aggregate wage
growth that accompanied the productivity
slowdown.
Preview of Findings
Given observed trends in wage growth we
find that the model can account for:
a) Most of the long run rise in
nonemployment among high school
dropouts.
b) One half of the rise in economy-wide
nonemployment.
c) The observed age structure of these
effects.
The Basic Idea
Consider the following simple problem:
• Infinitely lived worker
• Once-and-for-all decision at start of
working life between:
a) Working forever; and
b) Not working forever.
• What is the optimal labor supply policy?
The Decision to Work
Work Forever
• Accumulate experience, x
• Payoff:
ln w
x, tln w
0, 0
g w t Agg. Growth
Not Work Forever
• Do not accumulate x
• Payoff:
ln b
tln b
0
g b t
g x x Return to Exp.
• Present value:
w
0, t
PV
work r g w g x
• Present value:
b
t
PV
not work r g b
The Reservation Wage
It follows that the worker will choose to work
if:
w
0, twR
t b
t
where:
r g w g x
  r g b
Steady State Employment
Imagine an economy populated by workers facing different
wages,
wi 
x, t i w
x, t
, where i is “skill”
and different payoffs from nonemployment,
b i
t i b
t
Then, aggregate employment is given by:
L Pr
wi 
0, tb i 
t1 

where Ω = c.d.f. of ω/β & ρ = replacement rate (bi/wi).
Implications of Simple Model
L 1 

1. [Well understood.] Increases in ρ, the
replacement rate, reduce L*.
2. In the long run, it must be that gb = gw.
Otherwise, ρ = b(t)/w(0,t) → 0 or ∞,
and
L* → 0 or 1 in the limit.
r g w g x
gx
Thus,   r g
1  r g w
b
Implications of Simple Model
gx
L 1  1  r g w 

3. Increases in the return to experience gx
reduce α and raise aggregate employment.
– gx > 0 drives reservation wage below payoff from
nonemployment.
– Future returns to work  forgo current earnings.
– Increases in gx reduce res. wages still
further.
– Effect will be powerful since r – gw likely
small.
Implications of Simple Model
gx
L 1  1  r g w 

4. Increases in aggregate wage growth gw
reduce α and raise aggregate employment, IFF
gx > 0.
– Increases in gw have a greater impact on PV of
earnings for those in work—they compound the
return to experience.
– N.B. this effect is absent if gx = 0!
Relates to Blanchard’s neutrality critique:
when gx = 0, gw is neutral w.r.t. employment.
A More General Model
Simple model introduced before, while intuitive, is
very stylized in a number of ways:
• Once-and-for-all labor supply decision.
• Linear return to experience.
• Infinite lifetimes.
To get a sense of the quantitative implications of
the model, we now relax these restrictions.
Summary of Qualitative
Predictions
a) Increases in the return to experience
stimulate employment.
b) If there is a positive return to experience,
increases in aggregate wage growth also
stimulate employment.
c) These effects are strongest among lowskilled who are marginal to employment
decision.
Evidence
We now present evidence on these two
forms of wage growth for the US:
• Changes in the return to experience
among low-skilled;
• Changes in aggregate wage growth.
Changes in the Return to
Experience
Data from 1960–00 Censuses and 2001–07
ACS
Earnings:
Education:
college+.
Experience:
Sample:
Annual wages and salary.
dropouts (9-11 yrs), high
school, some college,
Age – education – 6.
Full-time, full-year nonimmigrant white males.
A. 9-11 Years of Education
2
1.75
Log Earnings, Normalized
1.5
1.25
1
0.75
0.5
0.25
1960
1970
1980
1990
2000
2001-07
0
0
10
20
Potential Experience, Years
30
B. 12 Years of Education
2
1.75
Log Earnings, Normalized
1.5
1.25
1
0.75
0.5
0.25
1960
1970
1980
1990
2000
2001-07
0
0
10
20
Potential Experience, Years
30
D. 16+ Years of Education
2
1.75
Log Earnings, Normalized
1.5
1.25
1
0.75
0.5
0.25
1960
1970
1980
1990
2000
2001-07
0
0
10
20
Potential Experience, Years
30
Sensitivity
1. Actual vs. Synthetic Cohorts
– Similar picture.
2. Potential vs. Actual Experience
– Effects likely to be small.
3. Selection
– Hard to generate flattening profile.
4. Relation to Existing Literature
– Similar picture using different data/methods.
Cohort Earnings Profiles: A Similar
Pattern
A: 9-11 Years of Education
2
1.75
Log Earnings, Normalized
1.5
1.25
1
0.75
0.5
0.25
1960
1970
1990
2000
1980
0
0
5
10
15
Potential Experience, Years
20
25
30
Summary
This paper (hopefully) has:
• Provided an analytical framework in which
the labor supply effects of wage growth can
be understood.
• Documented the substantial decline in the
returns to experience among low-skilled
workers.
• Demonstrated that the employment effects of
reduced returns to experience and aggregate
wage growth are potentially substantial.
Erik’s Comments
Do not allow bi to differ by group
o
o
Value of leisure
Transfer policy
Conduct all analysis using pre-tax dollars
o
Do not allow for changes in Tax policy
Assumes changes in wage profile are known ex-ante
o
Is that realistic?
Part D:
Some Work in Progress
Aguiar, Hurst, and Karabarbounis (in progress)
• Calibrate preference parameters for labor supply (and potentially
home production and leisure production function parameters) given:
o
o
o
o
o
Observed hours/participation for different skill groups
Observed home production time for different skill groups
Observed wages for different groups
Observed prices of home production, leisure, and other goods
Observed taxes and transfers for different groups
• Goal:
o
To match both the time series and cross sectional trends
• Focus on a group where disability is much less of a concern.
Part E:
Unemployment in Current Recession
Some Facts About The Recent Labor Market
• “The Labor Market In The Great Recession”
Mike Elsby, Bart Hobijn, and Aysegul Sahin
• Compares the labor market during the recent recession to the labor
market during all other previous post war recessions.
• Conclusions:
(1)
From a wide range of labor market outcomes, the recent recession
was the deepest recession in post war period.
(2)
Early on, the nature of labor adjustment in the recent recession
displayed a notable resemblance to that of other severe recessions.
(3)
During the latter part of recession (and recovery), the path of
adjustment exhibited important departures from other deep
recessions.
Figure 3. Okun’s Law, 1949-2010 Q4
Unemployment gap
6
2009Q4
2009Q3 2010Q1
2010Q2
2010Q4
2010Q3
2009Q2
4
2009Q1
2
2008Q4
2008Q3
2008Q2
2008Q1
0
No recession
Recessions
-2
-4
-6
-10
-8
-6
-4
-2
0
2
4
Output gap
Source: Bureau of Economic Analysis, Bureau of Labor Statistics, and Congressional Budget Office
6
8
Revisions led to partial reversal Okun’s Law
Okun's Law
Based on CBO potential output and NAIRU estimates (1949Q1-now) Unemployment gap
6
5
4
2011Q2
3
2
2007 Recession
and after
1
0
-1
-2
-3
-4
-10
-8
-6
-4
-2
Output gap
0
2
4
6
Source: Bureau of Economic Analysis, Bureau of Labor Statistics, Congressional Budget Office, FRBSF staff
Elsby/Hobijn/Sahin/Valle
tta 9/16/2011
Labor Market In the Great
Recession: An Update
70
Recent drop in unemployment through participation
Unemployment and Labor Force Participation rates
Monthly observations; seasonally adjusted
Percent
12
Percent
68
Labor force participation rate
10
67
8
66
6
65
4
64
Unemployment rate
2
63
0
1990
62
1995
2000
2005
2010
Source: Bureau of Labor Statistics
Elsby/Hobijn/Sahin/Valle
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Labor Market In the Great
Recession: An Update
72
Unemployment Rate by Gender
Seasonally Adjusted
Unemployment Rate
Unemployment Rate
12
12
10
10
2.7
1.1
8
8
Men
6
6
Women
4
4
2
1990
2
1993
1996
1999
Source: Bureau of Labor Statistics
2002
2005
2008
2011
Unemployment to Non-Participation by Gender
Seasonally Adjusted
Percent Women
Percent Men
0.3
0.4
0.25
Women
0.3
0.2
Men
0.2
0.15
0.1
1990
1994
1998
Source: Bureau of Labor Statistics
0.1
2002
2006
2010
Unemployment to Employment by Gender
Seasonally Adjusted
Percent
Percent
0.4
0.4
Men
0.3
0.2
0.1
1990
1994
1998
Source: Bureau of Labor Statistics
0.3
0.2
Women
0.1
2002
2006
2010
Employment to Unemployment by Gender
Seasonally Adjusted
Percent
Percent
0.03
0.03
0.02
0.02
Men
0.01
0
1990
1994
1998
Source: Bureau of Labor Statistics
0.01
Women
0
2002
2006
2010
Nonparticipation to Unemployment by Gender
Seasonally Adjusted
Percent
Percent
0.05
0.05
0.04
0.04
Men
0.03
0.03
0.02
0.02
Women
0.01
0
1990
1994
1998
Source: Bureau of Labor Statistics
0.01
0
2002
2006
2010
Change in Unemployment Rates
Table 1: Change in Unemployment Rates (ppt)
Change in Unemployment Rate
Gender
Male
Female
Age
16-24
25-54
55+
Education
Less than High Scool
High School
Some College
College or Higher
Race
White
Black
Hispanic
Recession
Recovery
5.5
-0.9
6.5
4.3
-1.6
-0.2
8.8
5.4
4.0
-1.6
-0.9
-0.3
8.3
6.5
5.3
2.9
-0.6
-1.0
-0.9
-0.4
5.2
7.5
7.2
-1.1
0.3
-1.1
Notes: The recession refers to 2007Q2 to 2009Q4 and the recovery
2009Q4 to 2011Q2
Elsby/Hobijn/Sahin/Valle
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The Unemployment Rate By Skills: All (20-45)
2007
Unemp
Rate
2011
Unemp
Rate
Change
in
Rate
Share
of
Pop.
Share
Weighted
Change
Percent of
Total
Unemp
Rate
Explained
High School
or Less
7.1%
15.2%
8.2%
41%
3.3%
~65%
Some College
4.2%
8.9%
4.7%
30%
1.5%
~25%
College or
More
1.9%
4.5%
2.6%
29%
0.7%
~10%
All
4.6%
9.9%
Education
5.3%
The Unemployment Rate By Skills: All (20-45)
2007
Unemp
Rate
2011
Unemp
Rate
Change
in
Rate
Share
of
Pop.
Share
Weighted
Change
Percent of
Total
Unemp
Rate
Explained
High School
or Less
7.1%
15.2%
8.2%
41%
3.3%
~65%
Some College
4.2%
8.9%
4.7%
30%
1.5%
~25%
College or
More
1.9%
4.5%
2.6%
29%
0.7%
~10%
All
4.6%
9.9%
Education
5.3%
The Non Participation Rate By Skills: All
2007
Non-Emp
Rate
2011
Non-Emp
Rate
Change
in
Rate
Share
of
Pop.
Share
Weighted
Change
Percent of
Total
Non-Emp
Rate
Explained
High School
or Less
22.1%
24.1%
2.0%
41%
0.8%
~50%
Some College
19.0%
21.8%
2.8%
31%
0.9%
~50%
College or
More
12.1%
12.2%
0.1
29%
0%
0%
All
18.4%
19.9%
1.5%
Education
The Non Participation Rate By Skills: All
2007
Non-Emp
Rate
2011
Non-Emp
Rate
Change
in
Rate
Share
of
Pop.
Share
Weighted
Change
Percent of
Total
Non-Emp
Rate
Explained
High School
or Less
22.1%
24.1%
2.0%
41%
0.8%
~50%
Some College
19.0%
21.8%
2.8%
31%
0.9%
~50%
College or
More
12.1%
12.2%
0.1
29%
0%
0%
All
18.4%
19.9%
1.5%
Education
The Non Employment Rate By Skills: All
2007
Non-Emp
Rate
2011
Non-Emp
Rate
Change
in
Rate
Share
of
Pop.
Share
Weighted
Change
Percent of
Total
Non-Emp
Rate
Explained
High School
or Less
27.6%
35.7%
8.1%
41%
3.3%
~60%
Some College
22.4%
28.7%
6.3%
31%
2.0%
~30%
College or
More
13.7%
16.1%
3.4%
29%
1.0%
~10%
All
22.2%
27.7%
5.5%
Education
Long-term Unemployment Still High
Unemployment rate by duration
Seasonally adjusted monthly observations
Percent
79 weeks and over
10
52-78 weeks
26-52 weeks
15-26 weeks
5-14 weeks
8
<5 weeks
6
4
2
0
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Source: Bureau of Labor Statistics, Current Population Survery, and authors' calculations
Elsby/Hobijn/Sahin/Valle
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Labor Market In the Great
Recession: An Update
84
Unemployment Duration
Historically Low Outflows Even After Recession
Flow hazard rates into and out of unemployment
Monthly hazard based on Shimer (2005); 3-month moving averages
Outflow hazard
120%
Inflow hazard
6.0%
Inflow hazard, s(t)
100%
5.0%
80%
4.0%
60%
3.0%
40%
Outflow hazard, f(t)
2.0%
20%
1.0%
0%
0.0%
1948 1953 1958 1963 1968 1973 1978 1983 1988 1993 1998 2003 2008
Source: Bureau of Labor Statistics and authors' calculations
Elsby/Hobijn/Sahin/Valle
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Labor Market In the Great
Recession: An Update
86
Pick-up in Outflows to Non-participation
Outflow rates out of unemployment by destination
Seasonally adjusted; 3-month moving average
Percent of unemployed
40
35
To Employment
30
25
20
To Non-participation
15
10
5
0
1967
1972
1977
1982
1987
1992
1997
2002
2007
Source: Shimer (2007), based on Ritter data provided by Hoyt Bleakley, Bureau of Labor Statistics, authors' calculations
Elsby/Hobijn/Sahin/Valle
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Labor Market In the Great
Recession: An Update
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Outflow Rates by Duration and Destination
Monthly outflow rates out of unemployment
Average July 2010 - June 2011
Percent
60
50
Total
40
30
to out of the labor force
20
10
to employment
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23 24+
Duration (months)
Source: Current Population Survey and authors' calculations
Elsby/Hobijn/Sahin/Valle
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Labor Market In the Great
Recession: An Update
88
Very High Inflows from Non-participation
Inflow rates into unemployment by origin
Seasonally adjusted; 3-month moving average
Percent of labor force
2.5
From Employment
2
1.5
From Non-participation
1
0.5
0
1967
1972
1977
1982
1987
1992
1997
2002
2007
Source: Shimer (2007), based on Ritter data provided by Hoyt Bleakley, Bureau of Labor Statistics, authors' calculations
Elsby/Hobijn/Sahin/Valle
tta 9/16/2011
Labor Market In the Great
Recession: An Update
89
Evidence of increased frictions
Actual and fitted Beveridge Curve
Monthly observations; pre-2007-recession fit
Job openings rate
5%
Fitted
4%
before 2007 recession
3%
Jun-11
Gap: 2.6%
2%
since 2007 recession
2%
3%
4%
5%
6%
7%
Unemployment rate
8%
9%
10%
1%
11%
Source: JOLTS, CPS, and authors' calculations
Elsby/Hobijn/Sahin/Valle
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Labor Market In the Great
Recession: An Update
90
Evidence of increased frictions
Fitted and "New" Beveridge Curve
Monthly observations; pre-2007-recession fit
Job openings rate
5%
Fitted "New" BC
4%
before
2007 recession
3%
Jun-11
2%
since 2007 recession
2%
3%
4%
5%
6%
7%
Unemployment rate
8%
9%
10%
1%
11%
Source: JOLTS, CPS, and authors' calculations
Elsby/Hobijn/Sahin/Valle
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Labor Market In the Great
Recession: An Update
91
Broadbased decline in finding rates
Unemployment Outflow Hazards by Industry
12-m moving averages of monthly data
Monthly outflow hazard
0.8
0.7
0.6
Construction
0.5
Total
0.4
0.3
Information
Durable Goods
0.2
Financial
0.1
0
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Source: Bureau of Labor Statistics and authors' calculations
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Labor Market In the Great
Recession: An Update
92
Part F:
Long Run Trends And Current Recession
Interactions
Where Are Potential Long Term Unemployment
Forces Coming From
1.
2.
Economic boom from the late 1990s through the mid 2000s
o
Housing boom
o
Credit boom
Persistent decline in manufacturing over last 30 years.
Note:
These two forces could have important interactions.
Background: Male Labor Force Participation
Rate (All)
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Share of “Prime Age” Men Working in
Manufacturing
0.18
0.16
0.14
0.12
0.1
0.08
0.06
0.04
0.02
0
Rise of China: Autor et al. (2011)
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Share of Prime Age Men Out of the Labor Force
0.16
0.14
0.12
0.1
0.08
0.06
0.04
0.02
0
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Share of Prime Age Lower Educated Men
Working in Manufacturing
25
20
15
10
5
0
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Share of Prime Age Lower Educated Men
Out of the Labor Force
16
14
12
10
8
6
4
2
0
Some More Conclusions
• Manufacturing has been steadily declining over past few decades.
• The decline has been felt most by lower educated men.
• The decline has been associated with an exit of lower educated men from the
labor force.
House Price Growth
House Price Growth
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Share of Prime Age
Men Working in Construction
0.14
0.12
0.1
0.08
0.06
0.04
0.02
0
Share of Prime Age Low Educated
Men Working in Construction
20
18
16
14
12
10
8
6
4
2
0
Construction Share
Interaction Between the Construction and
Manufacturing: Low Educated Men
25
20
15
10
5
0
Construction Share
Manufacturing Share
Construction Share of Lower Educated Men
Relative To High Skill Men
25
20
15
10
5
0
Manufacturing Share - Low Ed
Manufacturing Share - High Ed
Manufacturing Share - Difference
Construction Share of Lower Educated Men
Relative To High Skill Men
20
18
16
14
12
10
8
6
4
2
0
Construction Share - Low Ed
Construction Share - High Ed
Construction Share - Difference
Out of Labor Force of Low Skill Men Relative to
High Skill Men
16
14
12
10
8
6
4
2
0
-2
-4
Home Share - Low Ed
Home Share - High Ed
Home Share - Difference
Wages of Lower Educated Men
17
16
15
14
13
12
11
10
Men Share Low Ed (Age < 30)
60.0%
58.0%
56.0%
54.0%
52.0%
50.0%
48.0%
46.0%
44.0%
42.0%
40.0%
Share Low Ed
Labor Market Break Down of
Younger Low Educated (<= 12)Men
Labor Market Status
1997
2007
2010
Out of Labor Force
10.7
12.5
13.9
Unemployed
7.3
6.6
16.0
Construction
13.6
18.8
13.1
Manufacturing
15.5
11.0
8.8
Other
52.1
51.1
48.2
Incarceration Rate about 5% in 2010.
Labor Market Break Down of
Younger High Educated (>= 16) Men
Labor Market Status
1997
2007
2010
Out of Labor Force
4.2
5.0
5.6
Unemployed
1.9
1.6
4.7
Construction
1.9
2.4
1.5
Manufacturing
2.1
1.9
1.7
Other
89.9
89.1
86.8
A Potential Hypothesis About Current
Unemployment
•
The decline of manufacturing would have gradually caused an exodus of
low skilled men from the labor market.
•
Decline in manufacturing puts downward pressure on wages of low skilled
men.
•
During previous two decades, such forces was associated with an exodus of
low skilled men out of the labor force.
•
During the past decade, the housing (construction) boom may have delayed
the inevitable (giving low skill men another employment option)
•
As construction returns to “normal” and manufacturing has
disappeared, what will low skill men do?
•
May transition through unemployment before exiting the labor force.