1 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

2 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)

3 Significant increase in the share of workers with university level education in the euro area 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. Figure 1. Total hours worked by education (percentages)

4 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)

5 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! Outline

6 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 Literature

7 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)

8 Method, step 1: Weights 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):

9 Method, step 2: Quality index Growth in total labour input is constructed as the weighted growth in total hours for worker group i Growth in labour quality is defined as the difference between growth in total labour input and unweighted growth in hours worked

10 Data Micro data from ECHP –Longitudinal information on wages and other individual characteristics (e.g. education, age, gender) –All euro area countries for the 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 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

11 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?

12 Continuous increase in euro area labour quality Sources: Authors calculations. Figure 2. Labour quality growth (index 1983 = 100)

13 Changes in quality growth over time and significant impact on quality adjusted labour input Sources: Authors calculations. Figure 3. Labour quality adjusted labour input (average annual growth rate)

14 Validation: comparing country results with existing estimates Sources: Authors calculations and Jorgensen (2004). Figure 4. Comparing country estimates (average annual growth rate)

15 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): average annual growth goes from 0.61% to 0.65% Robust to accounting for changing weights using the regression approach: average annual growth goes from 0.47% to 0.44%

16 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) Changes in composition over the business cycle are expected to be countercyclical

17 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 Confounding factors and data weaknesses

18 Some evidence of lagged countercyclicality in euro area labour quality Sources: Authors calculations. Note: The trend and cycle have been extracted using a band-pass filter (with cycle length between 2 and 8 years). Figure 5. Trend/cycle decomposition (log levels and deviations from trend)

19 Education and work experience the main determinants of growth in human capital Sources: Authors calculations. Figure 6. Main determinants of labour quality growth (annual growth rates)

20 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)

21 The case of the disappearing TFP growth! Sources: ECB calculations. Except for the estimate of labour quality growth, data are from the Groningen Growth and Development Centre. Figure 7. Decomposition of labour productivity growth (averages of annual growth)

22 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

23 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