BALANCED VARIABLE ADDITION IN LINEAR MODELS

Giuseppe De Luca, Jan R. Magnus, Franco Peracchi*

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

This paper studies what happens when we move from a short regression to a long regression in a setting where both regressions are subject to misspecification. In this setup, the least-squares estimator in the long regression may have larger inconsistency than the least-squares estimator in the short regression. We provide a simple interpretation for the comparison of the inconsistencies and study under which conditions the additional regressors in the long regression represent a “balanced addition” to the short regression.

Original languageEnglish
Pages (from-to)1183-1200
Number of pages18
JournalJournal of Economic Surveys
Volume32
Issue number4
DOIs
Publication statusPublished - Sep 2018

Keywords

  • Bias amplification
  • Inconsistency
  • Least-squares estimators
  • Mean squared error
  • Omitted variables
  • Proxy variables

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