Beschreibung
The standard methodology of measuring gender discrimination through the use of wages is to isolate unexplained factors in differing wages between men and women. This is the basis of the Blinder-Oaxaca Decomposition, a method which dominates the empirical measurement of pay gaps. The Blinder-Oaxaca Decomposition attempts to distinguish observable or explainable differences in the wage distribution from the unexplainable, and argues that this unexplained portion of the wage gap is a quantified measure for discrimination. Most studies in the field do not report standard errors or confidence intervals in the decomposition components. It is hard to evaluate the significance of reported decomposition results to be found in the literature without knowing anything about their sampling distribution. This indicates to use a Bayesian rather than a least squares approach to decomposition analysis, based upon Markov Chain Monte Carlo (MCMC) estimation. And this approach allows - without relying on asymptotic theory - to test the significance of characteristics and discrimination effects estimates. Variance estimates derived from MCMC estimation are known to reflect the true posterior variance when a sufficiently large sample of MCMC draws is carried out (Gelfand and Smith 1990). Through this Bayesian approach, it is hoped to gain a better understanding of these underlying factors which influence gender wage gaps in European labour markets.| Zeitraum | 27 Aug. 2013 → 31 Aug. 2013 |
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| Ereignistitel | 53rd Congress of the ERSA |
| Veranstaltungstyp | Keine Angaben |
| Bekanntheitsgrad | International |