2012年-CEPS欧洲政策研究中心_Differences_in_the_Productivity_Levels_of_Older_Workers_in_the_EU_24页_406kb

Summary of "Differences in the Productivity Levels of Older Workers in the EU - A Cross-Country Analysis of the Age-Wage Relationship"

Core Content

This research report explores the differences in productivity levels of older workers across the EU, with a particular focus on the new member states (NMS) compared to the EU-15. The study is motivated by the increasing population ageing and the potential impact on economic competitiveness due to declining productivity among older workers. It investigates the age-wage relationship as a proxy for productivity, despite the inherent risks and criticisms of this approach.

Main Points

• Context and Aim:
  The report addresses the growing concern that an ageing workforce could lead to lower productivity growth and reduced competitiveness in European economies. It aims to:

  1. Examine whether older workers in NMS are less productive than those in the EU-15.
  2. Investigate whether this productivity gap influences employment rates of older workers in NMS.

• Assumption and Methodology:
  The study assumes that wages correlate with productivity at the individual level and uses wage data as a proxy for productivity. This assumption is used primarily for groups where the correlation is expected to be substantial. The research employs a log-linear wage model to estimate age-wage profiles, which are used to infer age-productivity profiles.

• Key Findings:

  • Older workers in NMS have lower relative productivity compared to those in the EU-15.
  • The age at which earnings peak (age of maximum earnings) is lower in NMS than in EU-15.
  • The point of return, where earnings equal those at age 30, is significantly higher in NMS, indicating that older workers in these countries are more likely to be discriminated against in the labor market.
  • The earnings distance (ratio of maximum earnings to earnings at age 30) is also lower in NMS, suggesting a less pronounced productivity increase with age.

Structural Differences

• Labour Market and Education:
  NMS have lower participation in continuous education and less developed educational systems compared to EU-15. This results in a lower quality of human capital and slower accumulation of skills, contributing to lower productivity among older workers.

• Technological Change:
  The NMS are undergoing rapid technological change and restructuring, which increases the depreciation of knowledge and skills. This is exacerbated by the lower levels of education and continuous learning, leading to a faster decline in productivity with age.

• Employment Rates:
  Lower productivity of older workers in NMS is associated with lower employment rates. The report suggests that wage arrangements and productivity differences play a significant role in determining the employment rates of older workers.

Data and Analysis

• Countries Analyzed:
  The study uses data from six countries: three from the EU-15 (Germany, Italy, UK) and three from the NMS (Estonia, Hungary, Poland).

• Model Specification:
  The log-linear wage model includes variables such as age, tenure, education level, gender, profession, and sector of employment. The model is used to estimate age-wage curves for different worker categories.

• Results by Group:
  The report presents detailed results for various worker groups, including those with different education levels and working in different sectors. These results show that productivity declines with age are more pronounced in NMS, particularly for unskilled workers and those in lower education categories.

Conclusion

The report concludes that the productivity of older workers in the NMS is lower than in the EU-15, and this difference is linked to lower employment rates. The structural differences in labor markets and education systems, combined with rapid technological change, contribute to this productivity gap. These findings have implications for the future competitiveness of NMS economies and their ability to meet employment targets, particularly in the context of the Lisbon strategy.

Key Information

• Productivity Decline with Age:
  Productivity tends to decline with age, especially in jobs that require physical strength and quick learning.

• Impact of Education and Continuous Learning:
  Lower education levels and less participation in continuous learning in NMS contribute to lower productivity among older workers.

• Technological Change:
  The pace of technological change is higher in NMS, which increases the depreciation of knowledge and skills, leading to a faster decline in productivity with age.

• Employment Rates and Productivity:
  Lower productivity of older workers is associated with lower employment rates, which is a concern for NMS economies.

• Data Sources:
  The study uses data from the Labour Force Survey, the German Socio-Economic Panel, and the IPSOS survey of Italian households’ income and wealth.

• Model and Variables:
  The log-linear wage model is used to estimate age-wage profiles. Variables include age, tenure, education level, gender, profession, and sector of employment.

• Implications for Policy:
  The findings suggest that policy interventions aimed at improving education and continuous learning, as well as adapting to technological change, may be necessary to address the productivity gap and its impact on employment rates in NMS.