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European Department, IMF. I thank Albert Jaeger and Hamid Faruqee for many discussions. Seminar participants at the IMF and at the European Commission gave valuable suggestions. All errors and omissions are solely mine.
Basic identity: Growth in GDP per capita = Growth in GDP per hours of work + Growth in employment as a ratio of total population + Growth in average hours of work per person. Data used in this section come primarily from the AMECO database, produced by the European Commission. Data on economywide average hours of work come from the new OECD productivity database.
Decressin and others (2001) analyze macroeconomic data for the largest four euro-area countries and claim that wage moderation by unions was likely behind job-rich growth. Estevão and Nargis (2002) make the same claim for France after a detailed analysis.
Estevão and Nargis (2002) use household-level data for France to show that the trade-off between unemployment and real wages did improve in the 1990s. However, they caution that other factors beyond wage moderation could be behind the clear structural improvement in French labor markets.
Several papers since Blanchflower and Oswald (1994) show that there may be some variation around the -0.1 estimate. Card (1995), in particular, raises doubts about their basic specification and notices that elasticities for the United States could be smaller than their estimate. More recently, Estevão and Nigar (2002) use micro data from the French labor force survey and estimate a wage-setting elasticity of -0.1. This general result does not seem to be unique to more developed industrial economies: Estevão (2003b) estimates, also using micro data and different methods, an elasticity of about the same size (but a bit smaller) for Poland. Finally, Estevão (2003a) has estimated the same -0.1 elasticity using aggregate information for a panel of 15 OECD countries, suggesting that the results are not dependent on the use of household-level data.
All the data described here are explained in detail in “Data Sources and Methodology” by R. Inklaar and others, published as Chapter 7 in O’Mahony and Van Ark (2003).
The results for labor productivity growth using information from this database will differ from the ones using the Industry Productivity Database for many reasons. First, the tables using the Growth Accounting Database will stop with averages up to 2000. The addition of 2001 in the tables based on the Industry Productivity Database lowers productivity growth slightly in the last sample period. Second, the aggregation by ICT grouping will differ because there is not a perfect match between the classification put together for the 56 industries in the Industry Productivity Database and the 26 industries included in the Growth Accounting Database. Third, small differences can be attributed to approximations made in the aggregation process.