1. Estimating the variance of decomposition effects
- Author
-
Takuya Hasebe
- Subjects
Decomposition Analysis, Asymptotic Variance, m-estimation ,Economics and Econometrics ,Mean squared error ,Estimator ,jel:C10 ,Variance (accounting) ,jel:J70 ,Control variates ,Law of total variance ,Delta method ,Econometrics ,Variance decomposition of forecast errors ,Applied mathematics ,Variance-based sensitivity analysis ,Mathematics - Abstract
We derive the asymptotic variance of the Blinder–Oaxaca decomposition effects. We show that the delta method approach that builds on the assumption of fixed regressors understates true variability of the decomposition effects when regressors are stochastic. Our proposed variance estimator takes randomness of regressors into consideration. Our approach is applicable to both the linear and nonlinear decompositions. Previously, only a bootstrap method has been a valid option for nonlinear decompositions. As our derivation follows the general framework of m-estimation, it is straightforward to extend our variance estimator to a cluster-robust variance estimator. We demonstrate the finite-sample performance of our variance estimator with a Monte Carlo study and present a real-data application.
- Published
- 2015