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Boosting the employment rate of older men and women

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  • Vincent VANDENBERGHE

    () (UNIVERSITE CATHOLIQUE DE LOUVAIN, Institut de Recherches Economiques et Sociales (IRES))

Abstract

European countries need to expand employment among older individuals. Many papers have examined this issue from different angles. However, very few seem to have considered its gender dimension properly, despite evidence that lifting the overall senior employment rate requires significantly raising that of women older than 50. The key issue examined by this paper is whether employers are willing to employ more older workers, in particular older women. The answer depends to a large extent on the ratio of older individuals’ productivity to their cost to employers. To address this question we tap into a unique firm-level panel of Belgian data to produce robust evidence on the causal effect of age/gender on productivity and labour costs. We take advantage of the panel structure to identify age/gender-related differences from within-firm variation. Moreover, inspired by recent developments in the production function estimation literature, we address the problem of endogeneity of the age/gender mix, using a structural production function estimator (Olley & Pakes, 1996; Levinsohn & Petrin, 2003) alongside IV-GMM methods where lagged value of labour inputs are used as instruments. Our results indicate a small negative impact of larger shares of older men on the productivity-labour cost ratio. An increment of 10%-points of in their share causes a 0.17 to 0.69%-point contraction. However, the main result is that the equivalent handicap with older women is larger, ranging from 1.3 to 2.0%-points. This is not good news for older women’s employability. And the vast services industry does not seem to offer working conditions that mitigate older women’s disadvantage, on the contrary.

Suggested Citation

  • Vincent VANDENBERGHE, 2011. "Boosting the employment rate of older men and women," Discussion Papers (IRES - Institut de Recherches Economiques et Sociales) 2011010, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
  • Handle: RePEc:ctl:louvir:2011010
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    References listed on IDEAS

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    Cited by:

    1. Liis Roosaar & Jaan Masso & Urmas Varblane, 2017. "The Structural Change And Labour Productivity Of Firms: Do Changes In The Age And Wage Structure Of Employees Matter?," University of Tartu - Faculty of Economics and Business Administration Working Paper Series 103, Faculty of Economics and Business Administration, University of Tartu (Estonia).
    2. François Rycx & Yves Saks & Ilan Tojerow, 2016. "Misalignment of Productivity and Wages Across Regions ?Evidence from Belgian Matched Panel Data," Working Papers CEB 16-043, ULB -- Universite Libre de Bruxelles.
    3. Christian Pfeifer & Joachim Wagner, 2012. "Age and gender composition of the workforce, productivity and profits: Evidence from a new type of data for German enterprises," Working Paper Series in Economics 232, University of Lüneburg, Institute of Economics.
    4. François Rycx & Yves Saks & Ilan Tojerow, 2016. "Misalignment of Productivity and Wages Across Regions ?Evidence from Belgian Matched Panel Data," Working Papers CEB 16-043, ULB -- Universite Libre de Bruxelles.
    5. Lara Lebedinski & Vincent Vandenberghe, 2014. "Assessing education’s contribution to productivity using firm-level evidence," International Journal of Manpower, Emerald Group Publishing, vol. 35(8), pages 1116-1139, October.
    6. Stephan Kampelmann & François Rycx, 2012. "Are Occupations Paid What They are Worth? An Econometric Study of Occupational Wage Inequality and Productivity," De Economist, Springer, pages 257-287.
    7. Lovász, Anna & Rigó, Mariann, 2013. "Vintage effects, aging and productivity," Labour Economics, Elsevier, pages 47-60.
    8. Christian Pfeifer & Joachim Wagner, 2014. "Age and gender effects of workforce composition on productivity and profits: Evidence from a new type of data for German enterprises," Contemporary Economics, University of Finance and Management in Warsaw.
    9. Olivia D'Aoust & Olivier Sterck, 2016. "Who Benefits from Customary Justice? Rent-seeking, Bribery and Criminality in sub-Saharan Africa," Journal of African Economies, Centre for the Study of African Economies (CSAE), vol. 25(3), pages 439-467.
    10. Stephan Humpert, 2012. "Age and Gender Differences in Job Opportunities," Working Paper Series in Economics 235, University of Lüneburg, Institute of Economics.
    11. Y. Saks, 2014. "Employees: too expensive at 50? The age component in wage-setting," Economic Review, National Bank of Belgium, pages 61-74.
    12. Vandenberghe, V., 2013. "Are firms willing to employ a greying and feminizing workforce?," Labour Economics, Elsevier, pages 30-46.

    More about this item

    Keywords

    Ageing; Labour Productivity; Panel Data Analysis;

    JEL classification:

    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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