Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/295917 
Year of Publication: 
2024
Series/Report no.: 
IZA Discussion Papers No. 16894
Publisher: 
Institute of Labor Economics (IZA), Bonn
Abstract: 
We evaluate the distributional effects of a minimum wage introduction based on a data set with a moderate sample size but a large number of potential covariates. Therefore, the selection of relevant control variables at each distributional threshold is crucial to test hypotheses about the impact of the treatment. To this end, we use the post-double selection logistic distribution regression approach proposed by Belloni et al. (2018a), which allows for uniformly valid inference about the target coefficients of our low-dimensional treatment variables across the entire outcome distribution. Our empirical results show that the minimum wage crowded out hourly wages below the minimum threshold, benefitted monthly wages in the lower middle but not the lowest part of the distribution, and did not significantly affect the distribution of hours worked.
Subjects: 
wage structure
automatic specification search
double machine learning
JEL: 
J31
C3
Document Type: 
Working Paper

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