Multiple regression with inequality constraints: Pretesting bias, hypothesis testing and efficiency

Michael C. Lovell, Edward Prescott

Research output: Contribution to journalArticle

37 Scopus citations

Abstract

This article analyzes, within the context of the standard multiple regression model, the problem of handling inequality constraints specifying the signs of certain regression coefficients. It is common econometric practice when regression coefficients are encountered with incorrect sign to delete the variables in question and reestimate the equation. This article shows that this procedure causes bias and can lead to inefficient parameter estimates. Furthermore, we show that grossly exaggerated statements concerning significance levels are likely to be made when other regression coefficients in the model are tested with the final regression obtained after deleting variables with incorrect sign.

Original languageEnglish (US)
Pages (from-to)913-925
Number of pages13
JournalJournal of the American Statistical Association
Volume65
Issue number330
DOIs
StatePublished - Jun 1970
Externally publishedYes

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ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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