The New Palgrave Dictionary of Economics

2018 Edition
| Editors: Macmillan Publishers Ltd

Extreme Bounds Analysis

  • Edward E. Leamer
Reference work entry
DOI: https://doi.org/10.1057/978-1-349-95189-5_2167

Abstract

Extreme bounds analysis is a global sensitivity analysis that applies to the choice of variables in a linear regression. Rather than a discrete search over models that include or exclude subsets of the variables, this sensitivity analysis answers the question: how extreme can the estimates be if any linear homogenous restrictions on a selected subset of the coefficients are allowed? When these bounds are too wide to be useful, narrower bounds can be found by restricting the set of prior distributions that underlie the sensitivity analysis.

Keywords

Bayesian econometrics Extreme bounds analysis Heteroscedasticity Nonparametric models and methods Probability White-corrected standard errors 

JEL Classifications

C13 C14 C21 C41 C51 C53 
This is a preview of subscription content, log in to check access.

Bibliography

  1. Leamer, E. 1978. Specification searches: Ad Hoc Inference with Non experimental data. New York: John Wiley and Sons.Google Scholar
  2. Leamer, E. 1981. Sets of estimates of location. Econometrica 49: 193–204.CrossRefGoogle Scholar
  3. Leamer, E. 1982. Sets of posterior means with bounded variance priors. Econometrica 50: 725–736.CrossRefGoogle Scholar
  4. Leamer, E., and G. Chamberlain. 1976. Matrix weighted averages and posterior bounds. Journal of the Royal Statistical Society, Series B 38: 73–84.Google Scholar

Copyright information

© Macmillan Publishers Ltd. 2018

Authors and Affiliations

  • Edward E. Leamer
    • 1
  1. 1.