Pseudo-Panel Decomposition of the Blinder–Oaxaca Gender Wage Gap

This article introduces a novel approach to decomposing the Blinder–Oaxaca gender wage gap using pseudo-panel data. In many developing countries, panel data are not available; however, understanding the evolution of the gender wage gap over time requires tracking individuals longitudinally. When individuals change across time periods, estimators tend to be inconsistent and inefficient. To address this issue, and building upon the traditional Blinder–Oaxaca methodology, we propose an alternative procedure that follows cohorts over time rather than individuals. This approach enables the estimation of both the explained and unexplained components—“endowment effect” and “remuneration effect”—of the wage gap, along with their respective standard errors, even in the absence of true panel data. We apply this methodology to the case of Colombia, finding a gender wage gap of approximately 15% in favor of male cohorts. This gap comprises a −5.6% explained component and a 20% unexplained component without controls. When we control by informality, size of the firm and sector the gap comprises a −3.5% explained component and a 18.7% unexplained component.

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Publication Details

Journal
Econometrics
Published
2025-07-19
DOI
https://doi.org/10.3390/econometrics13030027
Citations
1
Primary Topic
Labor market dynamics and wage inequality
Type
article
Field-Weighted Citation Impact
3.13
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article

Pseudo-Panel Decomposition of the Blinder–Oaxaca Gender Wage Gap

Jhon James Mora, Diana Yaneth Herrera Duque
1 citations
Econometrics
Labor market dynamics and wage inequality
3.13
article

Pseudo-Panel Decomposition of the Blinder–Oaxaca Gender Wage Gap

Jhon James Mora, Diana Yaneth Herrera Duque
article en
1 citations

Abstract

This article introduces a novel approach to decomposing the Blinder–Oaxaca gender wage gap using pseudo-panel data. In many developing countries, panel data are not available; however, understanding the evolution of the gender wage gap over time requires tracking individuals longitudinally. When individuals change across time periods, estimators tend to be inconsistent and inefficient. To address this issue, and building upon the traditional Blinder–Oaxaca methodology, we propose an alternative procedure that follows cohorts over time rather than individuals. This approach enables the estimation of both the explained and unexplained components—“endowment effect” and “remuneration effect”—of the wage gap, along with their respective standard errors, even in the absence of true panel data. We apply this methodology to the case of Colombia, finding a gender wage gap of approximately 15% in favor of male cohorts. This gap comprises a −5.6% explained component and a 20% unexplained component without controls. When we control by informality, size of the firm and sector the gap comprises a −3.5% explained component and a 18.7% unexplained component.

EconometricsVol. 13(3)
Icesi University (CO)
Openalex Percentile: Top 7%
Labor market dynamics and wage inequality
3.13
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