Prediction in linear index models with endogenous regressors

• Autores: Christopher L. Skeels, Larry W. Taylor
• Localización: The Stata journal, ISSN 1536-867X, Vol. 15, Nº. 3, 2015, págs. 627-644
• Idioma: inglés
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• Resumen

  • 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.