KOBAYASHI GENYA    Department   Undergraduate School  , School of Commerce    Position   Professor
Research Period	2015/04～2018/03
Research Topic	Bayesian quantile regression wiht endogeneity for various type of data
Research Type	KAKENHI Research
Consignor	Japan Society for the Promotion of Science
Research Program Type	Grant-in-Aid for Young Scientists (B)
KAKENHI Grant No.	15K17036
Responsibility	Representative Researcher
Representative Person	Kobayashi Genya
Details	In this project, we developed the Bayesian quantile regression models with endogeneous covariates and estimation methods for the proposed models. The proposed model consists of two equation as in the conventional instrumental regression where the second stage regression includes the residuals from the first stage regression in order to remove the bias from the endogeneity. We also considered introducing nonlinear effects of endogenous covariates on the quantiles of the response variable. Although the nonlinear quantile regression is a flexible approach to quantile estimation, the estimates are knwon to be unstable in when the sample size is small or when the quantiles in the tails are estimated. We replace the asymmetric Laplace distribution, whose shape is severely restrictive for a data distribution, with the generalised asymmetric Laplace distribution for improved estimation performance.