Bootstrapping the Shrinkage Least Absolute Deviations Estimator

Authors

  • Tae-Hwan Kim School of Economics, Yonsei University, 134 Shinchon-dong, Seodaemungu, Seoul, 120-749, Korea
  • Halbert White Department of Economics, University of California, San Diego

Keywords:

Shrinkage, James-Stein type estimators

Abstract

Kim and White (2001) studied a James-Stein type estimator that shrinks towards a data-dependent point rather than a fixed point. This was subsequently extended and applied to combining the OLS and 2SLS estimators by Judge and Mittelhammer (2004) and Mittelhammer and Judge (2005). This approach can be used to combine any two estimators in an optimal way. While the risk dominance properties of the new shrinkage estimator have been well established, a clear prescription for how to conduct inference and hypothesis testing has been missing. In this paper, we close this gap using a bootstrap approach.

Author Biographies

  • Tae-Hwan Kim, School of Economics, Yonsei University, 134 Shinchon-dong, Seodaemungu, Seoul, 120-749, Korea
    School of Economics, Yonsei University, 134 Shinchon-dong, Seodaemungu, Seoul, 120-749, Korea
  • Halbert White, Department of Economics, University of California, San Diego
    Department of Economics, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0508

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Published

2010-05-22

Issue

Section

Special Issue on Granger Econometrics and Statistical Modeling

How to Cite

Bootstrapping the Shrinkage Least Absolute Deviations Estimator. (2010). European Journal of Pure and Applied Mathematics, 3(3), 371-381. https://www.ejpam.com/index.php/ejpam/article/view/798

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