Estimation of a censored regression panel data model using conditional moment restrictions efficiently

Inference on Randomly Censored Regression Models Using Conditional Moment Inequalities∗

Under a conditional quantile restriction, randomly censored regression models can be written in terms of conditional moment inequalities. We study the identified features of these moment inequalities with respect to the regression parameters. These inequalities restrict the parameters to a set. We then show regular point identification can be achieved under a set of interpretable sufficient con...

Conditional density estimation in a censored single-index regression model

Quantile Regression Estimation of Panel Duration Models with Censored Data∗

This paper studies the estimation of quantile regression panel duration models. We allow for the possibility of endogenous covariates and correlated individual effects in the quantile regression models. We propose a quantile regression approach for panel duration models under conditionally independent censoring. The procedure involves minimizing l1 convex objective functions and is motivated by...

Quantile Estimation of Non-Stationary Panel Data Censored Regression Models

We propose an estimation procedure for (semiparametric) panel data censored regression models in which the error terms may be subject to general forms of non-stationarity, thus permitting heteroscedasticity over time. The proposed estimator exploits a weak structural form imposed on the individual speci ̄c e®ect. This is in contrast to the estimators introduced in Honor¶e(1992) where the individ...

Consistent Parameter Estimation for Conditional Moment Restrictions

In estimating conditional moment restrictions, a well known difficulty is that the estimator based on a set of implied unconditional moments may lose its consistency when the parameters of interest are not globally identified. In this paper, we consider a continuum of unconditional moments that are equivalent to the postulated conditional moments and can identify the parameters of interest. We ...