A semi-parametric estimator for censored selection models with endogeneity

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

First-difference estimator for panel censored-selection models

We propose a semiparametric first-difference estimator for panel censored-selection models where the selection equation is of tobit type. The estimator allows the unit-specific term to be arbitrarily related to regressors. The estimator minimizes a convex function and does not require any smoothing. A simulation study is provided comparing our proposal with the estimators of Wooldridge (Journal...

متن کامل

Minimum Distance Estimation of Randomly Censored Regression Models with Endogeneity

This paper proposes minimum distance estimation procedures for the slope coefficients and location parameter in randomly censored regression models that are used in duration and competing risk models. The proposed procedure generalizes existing work in terms of weakening the restrictions imposed on the distribution of the error term and the censoring variable. Examples of such generalizations i...

متن کامل

Bandwidth selection for the presmoothed density estimator with censored data

This paper is concerned with the problem of selecting a suitable bandwidth for the presmoothed density estimator from right censored data. An asymptotic expression for the mean integrated squared error (MISE) of this estimator is given, and the smoothing parameters minimizing it are proved to be consistent approximations of the MISE bandwidths. As consequence, a bandwidth selector based on plug...

متن کامل

Unified variable selection in semi-parametric models.

We propose a Bayesian variable selection method in semi-parametric models with applications to genetic and epigenetic data (e.g., single nucleotide polymorphisms and DNA methylation, respectively). The data are individually standardized to reduce heterogeneity and facilitate simultaneous selection of categorical (single nucleotide polymorphisms) and continuous (DNA methylation) variables. The G...

متن کامل

Variable selection in semi-parametric models.

We propose Bayesian variable selection methods in semi-parametric models in the framework of partially linear Gaussian and problit regressions. Reproducing kernels are utilized to evaluate possibly non-linear joint effect of a set of variables. Indicator variables are introduced into the reproducing kernels for the inclusion or exclusion of a variable. Different scenarios based on posterior pro...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Journal of Econometrics

سال: 2006

ISSN: 0304-4076

DOI: 10.1016/j.jeconom.2004.11.001