Abstract

http://ssrn.com/abstract=1663486
 
 

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Treating Measurement Error in Tobin’s Q


Timothy Erickson


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

Toni M. Whited


University of Rochester - Simon Business School; National Bureau of Economic Research

October 23, 2011

Simon School Working Paper No. FR 10-27

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.

Number of Pages in PDF File: 59

Keywords: Measurement Error, Investment, Minimum Distance, GMM

JEL Classification: C15, C26, E22, G31

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Date posted: August 23, 2010 ; Last revised: October 24, 2011

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: http://ssrn.com/abstract=1663486 or http://dx.doi.org/10.2139/ssrn.1663486

Contact Information

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 Rochester - Simon Business School ( email )
Rochester, NY 14627
United States
HOME PAGE: http://toni.marginalq.com

National Bureau of Economic Research ( email )
1050 Massachusetts Avenue
Cambridge, MA 02138
United States
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