We consider a semiparametric transformation model, in which the regression function has an additive nonparametric structure and the transformation of the response is assumed to belong to some parametric family. We suppose that endogeneity is present in the explanatory variables. Using a control function approach, we show that the proposed model is identified under suitable assumptions, and propose a profile likelihood estimation method for the transformation. The proposed estimator is shown to be asymptotically normal under certain regularity conditions. A simulation study shows that the estimator behaves well in practice. Finally, we give an empirical example using the U.K. Family Expenditure Survey
This paper proposes consistent estimators for transformation parameters in semiparametric models. Th...
An alternative to estimation of microeconometric models under the assumption of normality of the dis...
This paper addresses the problem of estimation of a nonparametric regression function from selective...
We consider a semiparametric transformation model, in which the regression function has an additive ...
© 2018 Cambridge University Press. We consider a semiparametric transformation model, in which the r...
We consider a semiparametric transformation model, in which the regression func- tion has an additiv...
We consider a semiparametric transformation model, in which the regression func- tion has an additiv...
This paper considers a linear regression model with an endogenous regressor which arises from a nonl...
We study the identification and estimation of semiparametric models with mismeasured endogenous regr...
We analyze a semiparametric model for data that suffer from the problems of incidental truncation, w...
This paper derives sufficient conditions for nonparametric trans-formation models to be identified a...
This paper addresses the problem of estimation of a nonparametric regression function from selective...
In this paper, we propose a two-step semiparametric maximum likelihood (SML) estimator for the coeff...
An alternative to estimation of microeconometric models under the assumption of normality of the dis...
We develop a three-step, oracle-efficient estimator for a structural semiparametric smooth coefficie...
This paper proposes consistent estimators for transformation parameters in semiparametric models. Th...
An alternative to estimation of microeconometric models under the assumption of normality of the dis...
This paper addresses the problem of estimation of a nonparametric regression function from selective...
We consider a semiparametric transformation model, in which the regression function has an additive ...
© 2018 Cambridge University Press. We consider a semiparametric transformation model, in which the r...
We consider a semiparametric transformation model, in which the regression func- tion has an additiv...
We consider a semiparametric transformation model, in which the regression func- tion has an additiv...
This paper considers a linear regression model with an endogenous regressor which arises from a nonl...
We study the identification and estimation of semiparametric models with mismeasured endogenous regr...
We analyze a semiparametric model for data that suffer from the problems of incidental truncation, w...
This paper derives sufficient conditions for nonparametric trans-formation models to be identified a...
This paper addresses the problem of estimation of a nonparametric regression function from selective...
In this paper, we propose a two-step semiparametric maximum likelihood (SML) estimator for the coeff...
An alternative to estimation of microeconometric models under the assumption of normality of the dis...
We develop a three-step, oracle-efficient estimator for a structural semiparametric smooth coefficie...
This paper proposes consistent estimators for transformation parameters in semiparametric models. Th...
An alternative to estimation of microeconometric models under the assumption of normality of the dis...
This paper addresses the problem of estimation of a nonparametric regression function from selective...