Labor Economics
Barcelona GSE
Spring 2014
1
The Course
• Instructor: Libertad González
• TA: María Lombardi
• Evaluation
– Final exam (June 23), 50%.
– Referee report, 20%.
– Research proposal, 30%.
2
The referee report
• 2-3 pages with a critical assessment of a recent
research paper in labor economics (due May 5).
• In groups of 2 students.
• Structure: summary, recommendation,
comments.
• Where to choose the paper from:
– NBER wp in Labor Studies.
3
Recent NBER working papers
• w19979 Sandra Black, Paul J. Devereux, Kjell Salvanes: “Does grief
transfer across generations? In-utero deaths and child outcomes”
• w19962 Petra Moser, Alessandra Voena, Fabian Waldinger:
“German-Jewish Emigres and U.S. Invention”
• w19936 Casey B. Mulligan: “The Economics of Work Schedules
under the New Hours and Employment Taxes”
• w19944 Tom Chang, Joshua S. Graff Zivin, Tal Gross, Matthew J.
Neidell: “Particulate Pollution and the Productivity of Pear Packers”
• w19932 Andri Chassamboulli, Giovanni Peri: “The Labor Market
Effects of Reducing Undocumented Immigrants”
• w19884 Jessamyn Schaller, Ann Huff Stevens: “Short-run Effects of
Job Loss on Health Conditions, Health Insurance, and Health Care
Utilization”
4
The project
• Obviously the course project will not be a
finished paper.
– But it should represent some progress.
• You should have your theoretical background,
your identification strategy, and some
preliminary empirical analysis.
• The in-class presentations will take place in
early June, and the final written version will be
due June 16.
– 8 pages max (1 page intro, 1 methods, 1 data, 2
results, 1 conclusions and references, 2 tables and
figures).
5
Textbooks
• George Borjas, Labor Economics,
McGraw Hill, 6th edition (2012).
• Ronald G. Ehrenberg and Robert S.
Smith, Modern Labor Economics,
Pearson, 11th edition (2011).
• Pierre Cahuc and André Zylbergerg, Labor
Economics, The MIT Press (2004).
6
Outline of Topics
• Lectures 2, 3. Labor Supply.
• Lectures 4, 5. Labor Demand.
• Lectures 6, 7. Labor Market Equilibrium.
• Lectures 8, 9. Education and Human Capital.
• Lectures 10, 11. Changes in the Wage Structure.
• Lectures 12, 13. Labor Mobility
• Lectures 14, 15. Discrimination
• Lecture 16. Unions
• Lectures 17, 18. Unemployment
7
Goals of the course
• Understanding research in labor
economics
• Being able to generate your own research
in labor economics
8
Today’s Outline
1. The field of Labor Economics.
2. Overview of the labor market.
9
Today’s Reading List
• Borjas, Chapter 1.
• Ehrenberg & Smith, Chapters 1 & 2.
• Cahuc & Zylberberg, Introduction.
10
1. Labor Economics
• “Labor economics studies how labor markets
work” (Borjas)
• “The study of the workings and outcomes of the
market for labor” (Ehrenberg)
• “The study of the markets in which labor
services are exchanged for wages” (Cahuc).
11
Why Do We Study Labor
Economics?
• Income earned by working is a large fraction of
total income.
• Most of the population are wage-earners.
• Many social policy issues concern the labor
market experience of certain workers or the
employment relationship between workers and
firms.
12
A Brief History of the Discipline
• Adam Smith.
• Labor Economics as an autonomous discipline,
US 1940’s.
• Profound transformation in the last 3 decades of
the 20th century.
• Labor Economics today.
– Theory, testable implications, empirical analysis.
13
2. Overview of the Labor
Market
• Agents: workers and firms (and
government).
• Households. Households decide how much
labor to supply.
• Firms. Firms decide where, what and how
much to produce, and whom to hire.
• The labor market allocates workers to jobs
and coordinates employment decisions.
14
Households
15
Households
demand
for goods
16
Households
demand
for goods
Firms
supply of
goods
17
Households
Firms
MARKET
demand
for goods
prices of goods
(D=S)
supply of
goods
18
Households
Firms
MARKET
demand
for goods
supply of hours
to diff. occupations,
as a f. of wage
prices of goods
(D=S)
supply of
goods
demand for hours
by occup., as a f. of
wages, p. of K, r
19
Households
Firms
MARKET
demand
for goods
prices of goods
(D=S)
supply of hours
to diff. occupations,
as a f. of wage
Labor
market
equilibrium
D=S
supply of
goods
demand for hours
by occup., as a f. of
wages, p. of K, r
20
Households
Firms
MARKET
demand
for goods
prices of goods
(D=S)
supply of hours
to diff. occupations,
as a f. of wage
Labor
market
equilibrium
D=S
supply of
goods
demand for hours
by occup., as a f. of
wages, p. of K, r
-Level of employment
-Wage distribution
-Frictional unemployment
21
Households
Firms
MARKET
demand
for goods
prices of goods
(D=S)
supply of hours
to diff. occupations,
as a f. of wage
Labor
market
equilibrium
D=S
supply of
goods
demand for hours
by occup., as a f. of
wages, p. of K, r
-Level of employment
-Wage distribution
-Frictional unemployment
Non-competitive
features and
institutions
22
Households
Firms
MARKET
demand
for goods
prices of goods
(D=S)
supply of hours
to diff. occupations,
as a f. of wage
Labor
market
equilibrium
D=S
supply of
goods
demand for hours
by occup., as a f. of
wages, p. of K, r
-Level of employment
-Wage distribution
-Frictional unemployment
Non-competitive
features and
institutions
discrimination
market power
(unions,
monopsony)
23
wage barriers
Main outcomes
• Wages
• Employment
• Unemployment
24
Data and recent trends
• How to measure the aggregate levels of
wages and employment?
• Household survey data
– CPS (US), EPA (Spain), …
• Administrative data
– Social Security, etc.
• Firm survey data
25
i) Wages
• Terminology: wages, earnings and
income.
26
The wage distribution
• The wage distribution is usually quite
asymmetric, with a long right tail.
• Dispersion varies a lot across countries
and over time.
27
0
5.0e-04
.001
Density
.0015
.002
Weekly earnings distribution, US
(CPS, April 2013, ft men 25-64)
0
1000
2000
earn
3000
28
.002
Weekly earnings distribution, US
(CPS, April 2013, ft men 25-64)
0
5.0e-04
.001
Density
.0015
Median = 640
0
1000
2000
earn
3000
29
.002
Weekly earnings distribution, US
(CPS, April 2013, ft men 25-64)
Median = 640
0
5.0e-04
.001
Density
.0015
Mean = 780
0
1000
2000
earn
3000
30
.002
Weekly earnings distribution, US
(CPS, April 2013, ft men 25-64)
Median = 640
10th
Percentile
= 370
0
5.0e-04
.001
Density
.0015
Mean = 780
0
1000
2000
earn
3000
31
.002
Weekly earnings distribution, US
(CPS, April 2013, ft men 25-64)
Median = 640
10th
Percentile
= 370
90th percentile
= 1280
0
5.0e-04
.001
Density
.0015
Mean = 780
0
1000
2000
earn
3000
32
1.0e-05
0
5.0e-06
Density
1.5e-05
2.0e-05
Yearly earnings distribution, Spain
(EES 2010, full-time workers)
0
500000
1000000
earnings
1500000
33
Median = 25.384
p10
= 12.258 Mean = 31.579
2.0e-05
p90 = 55.930
0
1.0e-05
Density
3.0e-05
4.0e-05
Yearly earnings distribution, Spain
(EES 2010, full-time workers)
0
50000
100000
earnings
150000
200000
34
Measures of wage inequality
• Gini coefficient
• Percentile ratios
– 90/10
– 90/50
– 50/10
35
Examples
• US 2013 (weekly)
– 90/10:
– 90/50:
– 50/10:
3.5
2
1.7
• Spain 2010 (yearly)
– 90/10:
– 90/50:
– 50/10:
4.6
2.2
2.1
36
Why do wages vary so much?
• The human capital model as a starting
point.
• Wage regressions à la Mincer.
– Age, education.
– Augmented with: region, sex, ethnicity, marital
status…
37
How much can we explain?
“Explained” fraction of total wage variance:
Years of education
10.7
89.3
38
How much can we explain?
“Explained” fraction of total wage variance:
Education and age
19.4
80.6
39
How much can we explain?
“Explained” fraction of total wage variance:
Education, age and sex
23.7
76.3
40
How much can we explain?
“Explained” fraction of total wage variance:
Education, age, sex and race
25.1
74.9
41
How much can we explain?
“Explained” fraction of total wage variance:
Education, age,
sex, race, marital status
and region
26.7
73.3
42
Average annual earnings by education
(Spain, 2010)
49,762
37,879
30,793
24,018
22,450
Primaria
Secundaria I
Secundaria II
Diplomatura
43
Licenciatura
Changes over time
• In some rich countries (USA, UK), large
increases in wage inequality since the
1970’s.
• Not so much in others (France, Germany,
Japan, Spain).
44
The case of the USA
• Between 1980 and 2000, wage inequality
increased dramatically.
• Between workers with different education
levels, years of experience, and age.
• But also between workers with the same
demographic characteristics.
– Education, experience, sex, occupation, industry.
45
What can explain these trends?
• Supply changes?
• International trade?
• “Skill-biased technological change”?
• Institutional changes?
– Unions, minimum wage.
46
ii) Employment
• In equilibrium, the labor market determines
the level of employment.
– The number of people working.
– In different regions, industries and
occupations.
• This level can be affected by different
factors.
– Both supply and demand factors.
47
Recent trends
• One of the most pronounced international
trends in the past few decades has been
the dramatic increase in female
employment.
48
Employment rate, female/male ratio, Spain 1976-2009
0,750
0,700
0,650
0,600
0,550
0,500
0,450
0,400
0,350
49
What can explain this trend?
• Technological progress
– Household appliances, processed foods…
• Falling fertility
– Modern contraceptive methods.
• The increasing weight of the services sector.
• Higher salaries
– Less discrimination (both via legislation and
changes in social norms).
50
iii) Unemployment
• Definition
• Measurement
• Trends
51
Working-age
population
52
Labor force
Working-age
population
Inactives
53
Employed
Labor force
Working-age
population
Unemployed
Inactives
54
Employed
Labor force
Working-age
population
Unemployed
Inactives
55
Employed
Labor force
Working-age
population
Unemployed
30 m
Inactives
56
Employed
22.5 m
Labor force
Working-age
population
Unemployed
30 m
Inactives
7.5 m
57
16.6 m
Employed
22.5 m
Labor force
Working-age
population
5.9 m
Unemployed
30 m
Inactives
7.5 m
58
The unemployment rate
UR = N. Unemployed / Labor Force
= N. Unemp. / (N. Employed + N. Unemployed)
• Spain 4th q. 2013: UR = 5.9/22.5 = 26.1%
• But: the unemployed are 19.6% of the workingage population.
• 44.6% of the working-age population are not
working (unemployed+inactives).
59
How do we measure it?
• How do we “count” the employed, unemployed and
inactive?
• Labor Force Surveys:
– Periodic surveys to a representative sample of households.
• Spain: “Encuesta de Población Activa”.
– A quarterly survey to a representative sample of 60.000
households.
• Who “counts” as unemployed?
– Those not working, but “actively” looking for a job.
– Otherwise, “inactive”.
60
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
2011
2012
Unemployment rate in Spain, 1980-2012
25
23
21
19
17
15
13
11
9
7
5
61
Unemployment rate by province,
Spain 2012
62
Unemployment rate by characteristics
(Spain, 1st q. 2013)
Total
27,3
Young (<35)
37,1
Old
22,6
Native
25,1
Immigrants
39,2
Men
26,9
Women
27,8
Top region (AND)
36,9
Bottom region (PV)
16,3
No high school
43,3
High school
28,4
College degree
15,0
63
63
Unemployment rate, USA 1950-2013
64
International unemployment rates, 1983-2013
65
Next: Labor Supply
66