Document Type

Article

Date

1-2003

Embargo Period

12-2-2011

Keywords

tbd

Disciplines

Economics

Description/Abstract

The conditions under which ordinary least squares (OLS) is an unbiased and consistent estimator of the linear probability model (LPM) are unlikely to hold in many instances. Yet the LPM still may be the correct model or a good approximation to the probability generating process. A sequential least squares (SLS) estimation procedure is introduced that may outperform OLS in terms of finite sample bias and yields a consistent estimator. Monte Carlo simulations reveal that SLS outperforms OLS, probit and logit in terms of mean squared error of the predicted probabilities.

Additional Information

This manuscript is from the Social Science Research Network, for more information see http://papers.ssrn.com/sol3/papers.cfm?abstract_id=383102#280291

Source

Harvested from ssrn.com

Included in

Economics Commons

Share

COinS