We develop point-identification for the local average treatment effect when the binary treatment contains a measurement error. The standard instrumental variable estimator is inconsistent for the parameter since the measurement error is non-classical by construction. We correct the problem by...

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...

This study proposes the use of semiparametric varying-coefficient methods to estimate the preference heterogeneity within stated choice data. Semiparametric varying-coefficient methods have the potential to overcome the disadvantages of conventional random parameter models and latent class...

This study investigates the identification of parameters in semiparametric binary response models of the form y=1(x′β+v+ε0) when there are nonignorable nonresponses. We propose an estimation procedure for the identified set, the set of parameters that are observationally indistinguishable...

Effective and efficient planning and development of residential environments require clarifying the nature of residential preferences. In reality, residential preferences are heterogeneous, so the standard econometric models that assume only one type of preference are not optimal. In this study,...

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...