Asymptotic Inference in Censored Regression Models Revisited

Author(s)/Creator(s)

Chihwa Kao, Syracuse University. Center for Policy ResearchFollow

Description/Abstract

This paper establishes that regressors in the models with censored dependent variables need not be bounded for the standard asymptotic results to apply. Thus, regressors that grow monotonically with the observation index may be acceptable. It also purports to provide an upper bound on the rate at which regressors may grow.

Document Type

Working Paper

Date

2001

Keywords

panel data, single equation models, censored dependent variables

Language

English

Series

Working Papers Series

Disciplines

Mathematics

Additional Information

Harvest from RePEc at http://repec.org

Recommended Citation

Kao, Chihwa, "Asymptotic Inference in Censored Regression Models Revisited" (2001). Center for Policy Research. 119.
https://surface.syr.edu/cpr/119

Source

Metadata from RePEc