Empirical Bayes Regression With Many Regressors

Thomas Knox, James Stock and Mark Watson
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Thomas Knox: University of Chicago
James Stock: Harvard University
Mark Watson: Princeton University

Working Papers from Princeton University. Economics Department.

Abstract: We consider frequentist and empirical Bayes estimation of linear regression coefficients with T observations and K orthonormal regressors. The frequentist formulation considers estimators that are equivariant under permutations of the regressors. The empirical Bayes formulation (both parametric and nonparametric) treats the coefficients as i.i.d. and estimates their prior. Asymptotically; when K =Ï Î¤Î´ for 0

Keywords: Large model regression; equivariant estimation; minimax estimation; shrinkage estimation (search for similar items in EconPapers)
JEL-codes: C13 C20 (search for similar items in EconPapers)
Date: 2004-01
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:pri:econom:2004-1

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