Growth in Euro Area Labour Quality
Guido Schwerdt (European University Institute)
and Jarkko Turunen (ECB)
OECD Workshop on Productivity Analysis and Measurement
Bern, 17 October 2006
1
Motivation
• Composition of euro area work force changes over time:
– Share of workers with higher education tends to increase
– Workers with different education levels, work experience and skills move
in an out of employment
• Raw measures of labour input such as total hours worked or
employment provide biased measures of actual labour input
• Adjusting for labour quality is important for understanding
sources of labour productivity growth and fluctuations in labour
input over the business cycle
• Evidence suggests that positive labour quality growth contributes
significantly to growth in labour productivity (Jorgensen, 2004)
2
Significant increase in the share of workers with
university level education in the euro area
Figure 1.Total hours worked by education (percentages)
Low
Medium
High
0.5
0.4
0.3
0.2
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1992
0.1
Sources: Labour Force Survey and author’s calculations. Note: Low refers to those with lower
secondary education or less, medium to those with upper secondary education and high to those
with tertiary education.
3
Related questions
• Has there been a shift in the composition towards workers with
lower skills in the 1990s?
• What drives sustained decline in euro area labour productivity
growth?
• How should economic policies be designed to “further improve
knowledge and innovation” (mid-term review of the Lisbon
agenda)
4
Outline
• Literature
• How do we measure labour quality?
• Main results:
– Index of labour quality for the euro area and some euro area countries
– Robustness to alternative assumptions
– Changes in composition over the business cycle?
• Decomposition of labour productivity growth = the case of
disappearing TFP growth!
5
Literature
• Studies on the US provide methodological background:
– Bureau of Labor Statistics (BLS) (1993), Ho and Jorgenson (1999), Aaronson
and Sullivan (2001)
• Few studies on euro area countries:
– Jorgenson (2004) for France, Germany and Italy
– Brandolini and Cipollone (2001) for Italy, Card and Freeman (2004) for
Germany, Melka and Nayman (2004) for France
– O’Mahony and Van Ark (2004) provide sectoral evidence for France,
Germany and the Netherlands
• No evidence for the euro area as a whole, country evidence too
scattered to draw firm euro area conclusions
6
Measuring labour quality: an overview
• Task: construct an estimate of labour quality adjusted labour
input in the euro area
• Combining information from microdata of individuals with official
aggregate data
• Step 1: Take data of individual wages and personal characteristics
from the European Community Household Panel (ECHP) and
construct weights for worker groups (by age, sex, education and
country) using wage regressions
• Step 2: Combine weights with data of hours worked for each
worker group from the European Labour Force Survey (LFS)
• Alternative estimates using entirely microdata based regression
method in Aaronson and Sullivan (2001)
7
Method, step 1: Weights
Wit =   EDU it  e  AGEit  a   it
• Dependent variable is individual real hourly wage
• Regressors are dummy variables for age and education, equation is
estimated using weighted OLS separately for males and females
and for each country (30 times 12 worker-country groups)
• Predicted wages for each worker-country group are used to
construct weights (the share of worker group i of total labour
compensation):
~
Wi H i
si 
~
Wi H i
i
8
Method, step 2: Quality index
 ln Lt   s i  ln H it
i
• Growth in total labour input is constructed as the weighted
growth in total hours for worker group i
 ln Qt   ln Lt   ln H t
• Growth in labour quality is defined as the difference between
growth in total labour input and unweighted growth in hours
worked
9
Data
• Micro data from ECHP
– Longitudinal information on wages and other individual characteristics (e.g.
education, age, gender)
– All euro area countries for the 1994-2001 time period
• Aggregate data from European LFS
– Hours worked and employment for worker groups cross-classified by
education, age, gender and country (also sectors and full/part-time status)
– All euro area countries for (currently) the 1983-2004 time period
– Note: Breakdown by education only available from 1992 onwards: additional
information from the Luxembourg Income Study (LIS) and the German
Socio-Economic Panel (GSOEP) is used
10
Caveats
• Common to all studies of labour quality:
– Individual wages are assumed to accurately reflect productivity differences:
union bargaining, search frictions, discrimination etc. suggest that this
assumptions is likely to be violated
– Proxies for measuring composition are imperfect: e.g. work experience is
inaccurately proxied by age, no measure of quality of education exists
• Specific to our study:
– Data for detailed classification pre-1992 is partly intrapolated
– Assume fixed weights, i.e. that returns to individual characteristics do not
change over time: evidence for Europe suggest that relative wages are rigid
(e.g. Brunello and Lauer, 2004)
– Measurement error in survey data?
11
Continuous increase in euro area labour quality
Figure 2. Labour quality growth
(index 1983 = 100)
115
110
105
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
100
Sources: Authors calculations.
12
Changes in quality growth over time and significant
impact on quality adjusted labour input
Figure 3. Labour quality adjusted labour input
(average annual growth rate)
1984-89
1990-94
1995-99
2000-04
1984-2004
Labour quality
0.56
0.90
0.46
0.57
0.62
Unadjusted labour input
0.53
-0.48
0.75
0.68
0.38
Quality adjusted labour input
1.09
0.42
1.21
1.25
1.00
Sources: Authors calculations.
13
Validation: comparing country results with existing
estimates
Figure 4. Comparing country estimates
(average annual growth rate)
1984-89
1990-94
1995-99
2000-04
1984-2001
Germany
0.13
0.44
0.15
0.33
0.24
France
1.25
1.35
0.63
0.48
1.03
Italy
0.32
0.35
0.69
0.54
0.44
Germany
0.58
0.62
0.46
na.
0.52
France
0.65
1.44
1.09
na.
0.86
Italy
0.32
0.65
0.71
na.
0.51
Jorgensen (2004):
Sources: Authors calculations and Jorgensen (2004).
14
Robustness
• Validation using country estimates supports robustness of our
calculation for the euro area
• Alternative data and methods available for a shorter time period:
• Robust to including additional determinants of labour quality
(sector and part/full-time status): 1993-2004 average annual
growth goes from 0.61% to 0.65%
• Robust to accounting for changing weights using the regression
approach: 1995-2001 average annual growth goes from 0.47% to
0.44%
15
Changes in composition over the business cycle are
expected to be countercyclical
• Previous evidence suggests that labour quality growth is likely to
be counter-cyclical (Aaronson and Sullivan, 2001 and Solon et al.
1994)
• “Down-skilling” in upturns as the share of workers with lower
skills increases: firms lower skill requirements, and increased
likelihood of finding a job and possibly higher wages encourage
lower skilled workers to enter the labour market
• “Up-skilling” in downturns (in reverse)
16
Confounding factors and data weaknesses
• Business cycle effects may be confounded by the impact of
changing trends
– Labour market reforms in the late 1990s may have resulted in increased
participation of lower skilled workers
– Demographics: ageing of the baby boom generation
• Measure of skills may not be accurate enough to fully capture
cyclical effects
– Unobserved characteristics (e.g. motivation) matter, but are likely to be
correlated with observables
17
Some evidence of lagged countercyclicality in euro
area labour quality
Figure 5.Trend/cycle decomposition
(log levels and deviations from trend)
Cycle (lhs)
Trend (rhs)
0.3
2.08
2.06
2.04
2.02
2
1.98
1.96
0.2
0.1
0
-0.1
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
-0.2
Sources: Authors calculations. Note:The trend and cycle have been extracted using a
band-pass filter (with cycle length between 2 and 8 years).
18
Education and work experience the main
determinants of growth in human capital
Figure 6. Main determinants of labour quality growth
(annual growth rates)
S ex
Ag e
E duca tion
2004
2003
2002
2001
2000
1999
1998
1997
1996
1995
1994
1993
1
0.8
0.6
0.4
0.2
0
-0.2
Sources: Authors calculations.
19
Implications for measuring total factor productivity
•
•
Best practice in productivity measurement suggests taking into
account labour quality adjustment (OECD, 2001)
Decomposing labour productivity (measured per hours worked)
growth into:
– Capital deepening (growth in capital services per hours worked)
– Labour quality growth
– TFP growth (residual)
•
Previous decompositions of euro area labour productivity have
not considered quality adjustment, thus overestimating TFP
growth (e.g. ECB, 2004,Vijselaar and Albers, 2004)
20
The case of the disappearing TFP growth!
Figure 7. Decomposition of labour productivity growth
(averages of annual growth)
Labour quality
Capital deepening
TFP
3.0
2.5
2.0
1.5
1.0
0.5
0.0
-0.5
1984-1989
1990-1994
1995-1999
2000-2004
Sources: ECB calculations. Except for the estimate of labour quality growth, data are from the
Groningen Growth and Development Centre.
21
Other (possible) applications
• Done:
– Quality-adjusted measure of wage growth: lower growth in quality adjusted
real wages, weak cyclicality
– Quality of the available labour force: quality growth of the unemployed
higher than for the employed in the late 1990s
• Further research:
– Forecasts of labour quality growth: looking forward, population ageing may
lower the contribution of human capital to growth
– Reconsider previous work using TFP estimates for the euro area
22
Summary and conclusions
• A robust estimate of labour quality growth in the euro area
• Positive labour quality growth in the past 20 years
• Some (weak) evidence of changes in composition over the
business cycle, especially in the 1990s: “down-skilling” in upturns
and “up-skilling” in downturns
• Implications for productivity growth:
– Approximately 1/3 of labour productivity growth due to improvements in
labour quality
– Accounting for labour quality lowers estimates of euro area TFP growth
23