Generalized Selection Bias and the Decomposition of Wage Differentials

Arbeitspapier

The major contribution of this paper is ending a new and flexible way to measure the effects of selection on log-wages. In this context, we offer a general approach to performing decomposition analysis when selection effects are present. We call the difference between unconditional and conditional expectations of the log-wages a generalized selection bias (GSB) when the two expectations are measured using the estimates from the joint estimation of the whole model (log-wages and selection equations) by the MLE method. The unconditional and conditional expectations are, respectively, the deterministic component of log-wages, and the deterministic component plus the conditional expectation of the stochastic component of log-wages, where the deterministic component is computed using the estimates from the joint estimation. That is, the GSB is the expectation of the residuals estimated from the joint estimation. It is appropriate to apply the Blinder-Oaxaca decomposition method to the wage differentials adjusted for the GSB. The GSB approach to decomposition analysis is not only easy to implement and flexible enough to apply to virtually any kind of selection issue, but also efficient because it uses full information. We illustrate the GSB approach by applying it to the racial wage differentials among women using data from the Current Population Survey. We discuss the possibility of using semiparametric or Bayesian sampling method for the joint estimation and related modifications of decomposition analysis.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: IZA Discussion Papers ; No. 69

Classification and Topics

• Classification: Wirtschaft ; Multiple or Simultaneous Equation Models: Truncated and Censored Models; Switching Regression Models ; Wage Level and Structure; Wage Differentials ; Labor Discrimination
• Subject: Decomposition analysis of wage differentials ; discrimination ; generalized selection bias ; maximum likelihood estimation ; Heckman's two-step method ; Dekompositionsverfahren ; Maximum-Likelihood-Methode ; Schätztheorie ; Lohndifferenzierung ; Theorie ; Schätzung ; USA

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Yun, Myeong-Su
• Event: Veröffentlichung
• (who): Institute for the Study of Labor (IZA)
• (where): Bonn
• (when): 1999

Further information

• Handle: http://hdl.handle.net/10419/20904
• Last update: 10.03.2025, 11:45 AM CET