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

Downloads

Published

2010-05-22

Issue

Vol. 3 No. 3 (2010): Special Issue on Granger Econometrics and Statistical Modeling

Section

Special Issue on Granger Econometrics and Statistical Modeling

License

Upon acceptance of an article by the European Journal of Pure and Applied Mathematics, the author(s) retain the copyright to the article. However, by submitting your work, you agree that the article will be published under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). This license allows others to copy, distribute, and adapt your work, provided proper attribution is given to the original author(s) and source. However, the work cannot be used for commercial purposes.

By agreeing to this statement, you acknowledge that:

  • You retain full copyright over your work.
  • The European Journal of Pure and Applied Mathematics will publish your work under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).
  • This license allows others to use and share your work for non-commercial purposes, provided they give appropriate credit to the original author(s) and source.

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