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Treating Measurement Error in Tobin's q

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  • Timothy Erickson
  • Toni M. Whited

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. Published by Oxford University Press 2011., Oxford University Press.

Suggested Citation

  • Timothy Erickson & Toni M. Whited, 2012. "Treating Measurement Error in Tobin's q," Review of Financial Studies, Society for Financial Studies, vol. 25(4), pages 1286-1329.
  • Handle: RePEc:oup:rfinst:v:25:y:2012:i:4:p:1286-1329
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    References listed on IDEAS

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