Treating Measurement Error in Tobin’s Q

59 Pages Posted: 23 Aug 2010 Last revised: 24 Oct 2011

Timothy Erickson

U.S. Department of Labor - Bureau of Labor Statistics

Toni M. Whited

University of Michigan, Stephen M. Ross School of Business; National Bureau of Economic Research

Date Written: October 23, 2011

Abstract

We compare the ability of three measurement error remedies to deliver unbiased estimates of coefficients in investment regressions. We examine high-order moment estimators, dynamic panel estimators, and simple instrumental variables estimators that use lagged mismeasured regressors as instruments. We show that recent investigations of this question are largely uninformative. We find that all estimators can perform well under correct specification, all can be biased under misspecification, and misspecification is easiest to detect in the case of high-order moment estimators. We develop and demonstrate a minimum distance technique that extends the high-order moment estimators to be used on unbalanced panel data.

Keywords: Measurement Error, Investment, Minimum Distance, GMM

JEL Classification: C15, C26, E22, G31

Suggested Citation

Erickson, Timothy and Whited, Toni M., Treating Measurement Error in Tobin’s Q (October 23, 2011). Simon School Working Paper No. FR 10-27. Available at SSRN: https://ssrn.com/abstract=1663486 or http://dx.doi.org/10.2139/ssrn.1663486

Timothy Erickson

U.S. Department of Labor - Bureau of Labor Statistics ( email )

2 Massachusetts Avenue, NE
Postal Square Building, Room 3105
Washington, DC 20212
United States
202-691-6575 (Phone)
202-691-6583 (Fax)

Toni M. Whited (Contact Author)

University of Michigan, Stephen M. Ross School of Business ( email )

701 Tappan Street
Ann Arbor, MI MI 48109
United States

National Bureau of Economic Research ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

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