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Decomposition of the Gender Wage Gap using the LASSO Estimator

René Böheim and Philipp Stöllinger

No 2020-03, Economics working papers from Department of Economics, Johannes Kepler University Linz, Austria

Abstract: We use the LASSO estimator to select among a large number of explanatory variables in wage regressions for a decomposition of the gender wage gap. The LASSO selection with a one standard error rule removes about a quarter of the regressors. We use the LASSO-selected regressors for OLSbased gender wage decompositions. This approach results in a smaller error variance than in OLS without LASSO-selection. The explained gender wage gap is 1%-point greater than in the conventional OLS model.

Keywords: gender wage gap; LASSO; decomposition (search for similar items in EconPapers)
JEL-codes: J31 J71 (search for similar items in EconPapers)
Date: 2020-01
New Economics Papers: this item is included in nep-gen and nep-ore
Note: English
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Persistent link: https://EconPapers.repec.org/RePEc:jku:econwp:2020-03

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