This paper studies endogenous treatment effect models in which individuals are classified into unobserved groups based on heterogeneous treatment choice rules. Such heterogeneity may arise, for example, when multiple treatment eligibility criteria and different preference patterns exist. Using a...

This study considers the estimation of spatial autoregressive models with censored dependent variables, where the spatial autocorrelation exists within the uncensored latent dependent variables. The estimator proposed in this paper is semiparametric, in the sense that the error distribution is...

This study considers treatment effect models in which others' treatment decisions can affect one's own treatment and outcome. Focusing on the case of two-player interactions, we formulate treatment decision behavior as a complete information game with multiple equilibria. Using a latent index...

We empirically assess the treatment effects of a place-based policy in Japan and propose a socially desirable and practically feasible treatment assignment rule for the program. To account for heterogeneity of treatment effects, we estimate the conditional average treatment effect for each...

In this study, we consider cross-sectional interaction models including spatial autoregressive models and peer effects models as special cases. Our model allows the endogenous effect---the effect of others' outcomes on one's own outcome--- to be nonlinear and nonparametric. For the model...

In this study, we consider linear social interaction models under incomplete information that allow for missing outcome data due to sample selection. For model estimation, assuming that each individual forms his/her belief about the other members' outcomes based on heterogeneous rational...

We empirically assess the treatment effects of a place-based policy in Japan and propose socially desirable and practically feasible treatment assignment rules for the program. To account for the heterogeneity of treatment effects, we estimate the conditional average treatment effect for each...

In this paper, we consider sieve instrumental variable quantile regression (IVQR) estimation of functional coefficient models where the coefficients of endogenous regressors are unknown functions of some exogenous covariates. We approximate the unknown functional coefficients by some basis...