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Shrinkage Estimators for Structural Parameters

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  • Tirthankar Chakravarty

    () (Department of Economics, UC San Diego)

Abstract

IV estimators of parameters in single equation structural models, like 2SLS and the LIML, are the most commonly used econometric estimators. Hausman-type tests are commonly used to choose between OLS and IV estimators. However, recent research has revealed troublesome size properties of Wald tests based on these pre-test estimators. These problems can be circumvented by usage of shrinkage estimators, particularly James-Stein estimators. We introduce the -ivshrink- command which encompasses nearly 20 distinct variants of the shrinkage-type estimators proposed in the econometrics literature, based on optimal risk properties, including fixed (k-class estimators are a special case) and data-dependent shrinkage estimators (random convex combinations of OLS and IV estimators, for example). Analytical standard errors, to be used in Wald-type tests are provided where appropriate, and bootstrap standard errors are reported otherwise. Where the variance-covariance matrices of the resulting estimators are expected to be degenerate, options for matrix norm regularization are also provided. We illustrate the techniques using a widely used dataset in the econometric literature.

Suggested Citation

  • Tirthankar Chakravarty, 2012. "Shrinkage Estimators for Structural Parameters," SAN12 Stata Conference 22, Stata Users Group.
  • Handle: RePEc:boc:scon12:22
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