Salīdzināt metodes

	Gender Gap Decomposition	Kvantīļu regresija
Nozare	Gender Studies	Ekonometrija
Saime	Regression model	Regression model
Izcelsmes gads	1973	1978
Autors	Ronald Oaxaca & Alan Blinder	Koenker & Bassett
Tips	Regression-based decomposition of a mean group difference	Conditional quantile regression
Pirmavots	Oaxaca, R. (1973). Male-female wage differentials in urban labor markets. International Economic Review, 14(3), 693–709.	Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50.
Citi nosaukumi	Oaxaca-Blinder Decomposition, Blinder-Oaxaca Decomposition, Wage Gap Decomposition	conditional quantile regression, regression quantiles, Kantil Regresyon
Saistītās	3	5
Kopsavilkums	Gender gap decomposition, most often implemented as the Oaxaca-Blinder decomposition, splits the mean difference in an outcome such as wages between men and women into a part explained by differences in measured characteristics (education, experience, occupation) and an unexplained residual part attributed to differences in how those characteristics are rewarded. Introduced independently by Ronald Oaxaca and Alan Blinder in 1973, it is the workhorse method for quantifying how much of the gender pay gap reflects composition versus differential treatment.	Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails.