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December 2006. ON THE MEASUREMENT OF ILLEGAL WAGE DISCRIMINATION Juan Prieto, Juan G. Rodríguez and Rafael Salas . Overview. Motivation Discrimination: classical view A new appoach: endogenous allocation to groups Application to Germany and the UK Discussion .
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December 2006 ON THE MEASUREMENT OF ILLEGAL WAGE DISCRIMINATION Juan Prieto, Juan G. Rodríguez and Rafael Salas
Overview • Motivation • Discrimination: classical view • A new appoach: endogenous allocation to groups • Application to Germany and the UK • Discussion
Discrimination: classical view • Oaxaca-Blinder (1973) gender discrimination: • Two wage equations for men (m), women (w): • The women wage discriminatory gap (w.r.t men):
Discrimination: classical view (2) • Oaxaca-Blinder (1973) gender discrimination: • The average women wage discriminatory gap (w. r. to men): • Quantiles analysis can improve estimates locally: • Newell and Reilly, 2001 • Albrecht, Björklund and Vroman, 2003 • Gardeazábal and Ugidos, 2005.
Discrimination: latent class view • Latent class models for gender discrimination: • Two wage equations for two different structures type/class 1 and type/class 2: • Plus a vector of probabilities of individual i belonging to groups 1,2. • This is estimated simultaneous and endogenously by maximum likelihood estimators that allocates individuals to groups according to their human capital characteristics, observed wages and sex, and trying to reduce internal errors of the two wage equations (by maximizing the log likelihood function)…
Discrimination: latent class view (2) • The log likelihood function: • Where f(·) is the standard normal density function
Discrimination: latent class view (3) • The vector of probabilities of individual i belonging to groups 1,2 are estimated as follows: • First, we estimate a priori probabilities of i belonging to j: Pij • By maximaizing the log likelihood function. • Then we update ex post probabilities by using the Bayes rule and we obtain:
Discrimination: latent class view (4) • The women wage discriminatory gap (w.r.t men) for i=women : • which is more general than Oaxaca-Blinder, for i=women (and 1 is the high wage class)
Example: let i = Hillary Clinton [HC] • Pick XHC the human capital characteristics of HC:
Example: i= Hillary Clinton [HC] (2) • The HC gap is: which is “normaly” positive since: Oaxaca-Blinder assume
Applications • European households panel data: • Germany 1994-2001: • Model 1 and 2 (extended) • UK 1994-2001: • Model 1 and 2 (extended) • Tables
Discrimination orderings • Distributional appoach: • Jenkins 1994: • discrimination curves from discrimination gaps in a decreasing order • del Río et al. 2006: • discrimination curves from discrimination gaps in an increasing order, eliminating negative gaps
Results • Germany unambiguously more discrimination than in the UK
Conclusions • A new appoach: endogenous allocation to groups • Application to Germany and the UK shows positive discrimination bias of Oaxaca-Blinder model • Positive gender discrimination in both countries
July 2006 ON THE MEASUREMENT OF ILLEGAL WAGE DISCRIMINATION: THE MICHAEL JORDAN PARADOX Juan Prieto, Juan G. Rodríguez and Rafael Salas