Prediction in linear index models with endogenous regressors

Christopher Skeels and Larry W. Taylor ()
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Larry W. Taylor: Lehigh University

Stata Journal, 2015, vol. 15, issue 3, 627-644

Abstract: In this article, we examine prediction in the context of linear index models when one or more of the regressors are endogenous. To facilitate both within-sample and out-of-sample predictions, Stata offers the postestimation command predict (see [R] predict). We believe that the usefulness of the predictions provided by this command is limited, especially if one is interested in out-of-sample predictions. We demonstrate our point using a probit model with continuous endogenous regressors, although it clearly generalizes readily to other linear index models. We subsequently provide a program that offers one possible implementation of a new command, ivpredict, that can be used to address this shortcoming of predict, and we then illustrate its use with an empirical example. Copyright 2015 by StataCorp LP.

Keywords: predict; probit; logit; ivprobit; prediction; linear index; endogenous regressors; ivpredict; out-of-sample prediction (search for similar items in EconPapers)
Date: 2015
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