Balanced Variable Addition in Linear Models

18 Pages Posted: 20 Aug 2018

See all articles by Giuseppe De Luca

Giuseppe De Luca

University of Palermo

J.R. Magnus

Vrije Universiteit Amsterdam, School of Business and Economics

Franco Peracchi

Georgetown University - Department of Economics

Date Written: September 2018

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.

Keywords: Bias amplification, Inconsistency, Least‐squares estimators, Mean squared error, Omitted variables, Proxy variables

Suggested Citation

De Luca, Giuseppe and Magnus, Jan R. and Peracchi, Franco, Balanced Variable Addition in Linear Models (September 2018). Journal of Economic Surveys, Vol. 32, Issue 4, pp. 1183-1200, 2018. Available at SSRN: https://ssrn.com/abstract=3233252 or http://dx.doi.org/10.1111/joes.12245

Giuseppe De Luca (Contact Author)

University of Palermo ( email )

Viale delle Scienza
Palermo, 90128
Italy

Jan R. Magnus

Vrije Universiteit Amsterdam, School of Business and Economics ( email )

De Boelelaan 1105
Amsterdam, 1081HV
Netherlands

Franco Peracchi

Georgetown University - Department of Economics ( email )

Washington, DC 20057
United States

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