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Does Automatic Wage Indexation Destroy Jobs? A Machine Learning Approach.

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¹National Bank of Belgium, de Berlaimontlaan 14, 1000 Brussels, Belgium.

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|February 23, 2023

Summary

Belgium

Keywords:

Counterfactual analysis Labor demand Machine learning Wage elasticity

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Area of Science:

Labor Economics
Applied Econometrics

Background:

Belgium suspended automatic wage indexation in 2015 to enhance competitiveness and employment.
This policy change led to a 2% reduction in real wages for all workers.

Purpose of the Study:

To analyze the impact of automatic wage indexation suspension on employment levels.
To quantify the labor demand elasticity resulting from this policy.

Main Methods:

Utilized machine learning to construct a synthetic control group for difference-in-difference analysis.
Employed pre-treatment data to model the counterfactual evolution of treated firms.

Main Results:

Found a 1.2% positive impact on employment following the suspension of automatic wage indexation.
Calculated a labor demand elasticity of -0.6, with a more significant effect (-1) in manufacturing.
The suspension of automatic wage indexation proved effective in preserving employment.

Conclusions:

Suspending automatic wage indexation can be an effective policy tool for employment preservation.
The findings suggest a notable impact on labor demand, particularly within the manufacturing sector.