Counterfactual Distributions with Sample Selection Adjustments: Econometric Theory and an Application to the Netherlands

Several recent papers use the quantile regression decomposition method of Machado and Mata (2005) to analyze the gender gap across log wage distributions. In this paper, we prove that this procedure yields consistent and asymptotically normal estimates of the quantiles of the counterfactual distribution that it is designed to simulate. Since employment rates often differ substantially by gender, sample selection is potentially a serious issue for such studies. To address this issue, we extend the Machado-Mata technique to account for selection. We illustrate our approach to adjusting for sample selection by analyzing the gender log wage gap for full-time workers in the Netherlands. Georgetown University, Department of Economics, Washington, DC 20057, USA and IZA, Bonn, e-mail:[email protected]. Free University Amsterdam, Department of Economics, De Boelelaan 1105, 1081HV Amsterdam, The Netherlands, email:[email protected] Georgetown University, Department of Economics, Washington, DC 20057, USA and IZA, Bonn, e-mail: [email protected].