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Wage Indexation and Jobs. A Machine Learning Approach

Author

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  • Gert Bijnens
  • Shyngys Karimov
  • Jozef Konings

Abstract

In 2015 Belgium suspended the automatic wage indexation for a period of 12 months in order to boost competitiveness and increase employment. This paper uses a novel, machine learning based approach to construct a counterfactual experiment. This artificial counterfactual allows us to analyze the employment impact of suspending the indexation mechanism. We find a positive impact on employment of 0.5 percent which corresponds to a labor demand elasticity of -0.25. This effect is more pronounced for manufacturing firms, where the impact on employment can reach 2 percent, which corresponds to a labor demand elasticity of -1.

Suggested Citation

  • Gert Bijnens & Shyngys Karimov & Jozef Konings, 2019. "Wage Indexation and Jobs. A Machine Learning Approach," Working Papers of Department of Economics, Leuven 643831, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    • Handle: RePEc:ete:ceswps:643831
    Note: paper number 82
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    Keywords

    labor demand; wage elasticity; counterfactual analysis; artificial control; machine learning;
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