Training and retirement patterns

Abstract

Life-cycle theory predicts that employers enter into implicit contracts with newly hired employees to ensure rent-sharing and to decrease turnover after firm-specific training investments. Typically, these implicit contracts would include both upward sloping earning profiles and mandatory retirement. In this article, we empirically test the prediction that workers with firm-specific skills are restrained in their options to continue working. Therefore, they are more likely to retire at common mandatory retirement dates than those with general skills. Using the US National Longitudinal Survey of Older Men, we find that workers who participated in firm-specific training in their early careers do indeed retire earlier than those with general skills. The results show that compulsory retirement plans force these older workers to retire when they reach the common mandatory retirement age of 65. The results presented in this article are highly relevant for public policies in European and other industrialized countries that aim to increase labour force participation of the elderly. As our study demonstrates, the effectiveness of institutional arrangements to postpone retirement will also depend on training policies of employers and the type of skills workers acquired in the past.

Keywords:

• retirement
• firm specific skills
• general skills
• implicit contracts

JEL Classification::

• J14
• J31
• J26

Acknowledgements

We are indebted to Lex Borghans, Didier Fouarge, Daniel Hamermesh, Ben Kriechel, Pierre Mohnen, Gerhard Pfann, Jan Van Ours and Maarten Vendrik for their valuable comments. We thank Ann Bartel, Nachum Sicherman and Dale Jorgenson for providing us with the industry measures of productivity growth.

Notes

¹Montizaan et al. (2010) showed that postponing retirement of older workers increases their training participation. However, this only holds for those who are employed in large organizations.

²Informal bonding can also be used to encourage employees to be trustworthy and not to shirk (see, Lazear, 1979; Lazear and Moore, 1984) and to reduce transaction costs that accompany recruitment and hiring.

³There exists a large literature that investigated the productivity-wage gap for older workers (e.g. Lazear, 1979; Medoff and Abraham, 1981; Blinder, 1982; Kotlikoff and Gokhale, 1992; Dostie, 2011). These studies measure wage slopes in order to test the prediction that the wage curve will be steeper than the productivity curve, and found that (i) earnings exceed productivity when old, and that (ii) job tenure and wage growth affect the likelihood of early retirement positively.

⁴Montizaan et al. (2010) focused on the impact of the abolishment of generous early retirement systems on training participation and found, consistent with human capital theory, that postponement of retirement due to shocks to pension rights has a positive impact on the training participation of older men.

⁵As technological change variables such as ‘research and development intensity’ and the ‘extent of computer usage’ are not available for all industry sectors, we use the indirect measures of Jorgenson et al. (1987).

⁶Life-cycle literature predicts that firm-specific training increases tenure so that firms can benefit from the rents resulting from the investment. We analysed whether this assumption holds by estimating the correlation between training and tenure rates with Ordinary Least Squares (OLS) (including various control variables). We found that a worker's firm-specific training background is significantly positively correlated with tenure. Conversely, a general training background is significantly negatively correlated with tenure. These results remain robust when adding occupation fixed effects and when accounting for selectivity.

⁷We also estimated the model without including retirement preferences as a regressor and find that the coefficients of our training variables are not affected by the inclusion of this variable.

⁸Due to the imperfect measurement of training and the fact that we do not observe productivity at an individual level, we cannot draw direct conclusions from these results.

⁹In order to deal with potential self selection of workers into sectors that are more likely to provide mandatory retirement plans, we also performed regression analyses in which we added the average percentage of workers with a mandatory retirement plan by sector as a regressor (results available upon requests). The inclusion of this variable does not lead to different coefficients of our training variables.