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Decomposition of Differences in Distribution under Sample Selection and the Gender Wage Gap

Santiago Pereda-Fernández

arXiv 1 Apr 2022 · Econometrics · publishedJournal of Business and Economic Statistics (2024) · 1 citations (OpenAlex)

arXiv:2204.00551 · PDF · DOI · OpenAlex · Extracted main text

Abstract

I address the decomposition of the differences between the distribution of outcomes of two groups when individuals self-select themselves into participation. I differentiate between the decomposition for participants and the entire population, highlighting how the primitive components of the model affect each of the distributions of outcomes. Additionally, I introduce two ancillary decompositions that help uncover the sources of differences in the distribution of unobservables and participation between the two groups. The estimation is done using existing quantile regression methods, for which I show how to perform uniformly valid inference. I illustrate these methods by revisiting the gender wage gap, finding that changes in female participation and self-selection have been the main drivers for reducing the gap.

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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Arellano, M. and S. Bonhomme (2017) Quantile selection models0.96510590%
2Pereda-Fernández, S (2022) Identification and estimation of triangular models with a binary treatment0.92843100%
3Maasoumi, E. and L. Wang (2019) The gender gap between earnings distributions0.90916375%
4Fortin, N., T. Lemieux, and S. Firpo (2011) Decomposition methods in economics0.8434375%
5Chernozhukov, V., I. Fernández-Val, and B. Melly (2013) Inference on counterfactual distributions0.7639644%
6Chernozhukov, V., I. Fernández-Val, and S. Luo (2019) Distribution regression with sample selection, with an application to wage decompositions in the uk0.73732100%
7Maasoumi, E. and L. Wang (2017) What can we learn about the racial gap in the presence of sample selection?0.64422100%
8Fernández-Val, I., F. Peracchi, A. van Vuuren, F. Vella, et al (2022) Selection and the us distribution of real female hourly wage0.58531100%
9DiNardo, J., N. Fortin, and T. Lemieux (1996) Labor market institutions and the distribution of wages, 1973-1992: A semiparametric approach0.5112250%
10Firpo, S. P., N. M. Fortin, and T. Lemieux (2018) Decomposing wage distributions using recentered influence function regressions0.5112250%

Showing the top 10 of 55 scored citations.