Minimum Distance Estimation of the Errors-In-Variables Model Using Linear Cumulant Equations

31 Pages Posted: 3 Feb 2013 Last revised: 6 Dec 2015

Timothy Erickson

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

Colin H. Jiang

University of Chicago - Booth School of Business

Toni M. Whited

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

Date Written: June 16, 2014

Abstract

We consider a multiple mismeasured regressor errors-in-variables model. We develop closed-form minimum distance estimators from any number of estimating equations, which are linear in the third and higher cumulants of the observable variables. Using the cumulant estimators alters qualitative inference relative to ordinary least squares in two applications related to investment and leverage regressions. The estimators perform well in Monte Carlos calibrated to resemble the data from our applications. Although the cumulant estimators are asymptotically equivalent to the moment estimators from Erickson and Whited (2002), the finite-sample performance of the cumulant estimators exceeds that of the moment estimators.

Keywords: errors-in-variables, higher cumulants, investment, leverage

JEL Classification: C15, C26, E22, G31

Suggested Citation

Erickson, Timothy and Jiang, Colin H. and Whited, Toni M., Minimum Distance Estimation of the Errors-In-Variables Model Using Linear Cumulant Equations (June 16, 2014). Available at SSRN: https://ssrn.com/abstract=2209789 or http://dx.doi.org/10.2139/ssrn.2209789

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)

Colin Huan Jiang

University of Chicago - Booth School of Business ( email )

5807 S. Woodlawn Avenue
Chicago, IL 60637
United States

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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