Hostname: page-component-78c5997874-v9fdk Total loading time: 0 Render date: 2024-11-09T07:16:07.504Z Has data issue: false hasContentIssue false
  • English
  • Français

Who Invented Local Power Analysis?

Published online by Cambridge University Press:  11 February 2009

Douglas A. McManus
Get access Rights & Permissions [Opens in a new window]

Abstract

Asymptotic local power analysis has become an important and increasingly used technique in econometrics. This paper reviews the history of local power analysis and delineates the contribution of J.Neyman, E.J.G. Pitman, and G. Noether.

Type
Brief Report
Information
Econometric Theory , Volume 7 , Issue 2 , June 1991 , pp. 265 - 268
Copyright
Copyright © Cambridge University Press 1991

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

1. Davidson, R. & MacKinnon, J.G.. Implicit alternatives and the local power of test statistics. Econometrica 55 (1987): 1305–1329.10.2307/1913558CrossRefGoogle Scholar
2. Eisenhart, C. The power of the X 2 test (abstract). Bulletin of the American Mathematical Society 44 (1938): 32.Google Scholar
3. Gallant, A.R. Nonlinear Statistical Models. New York: Wiley, 1987.10.1002/9780470316719CrossRefGoogle Scholar
4. Gallant, A.R. & White, H.. A Unified Theory of Estimation and Inference for Nonlinear Dynamic Models. New York: Basil Blackwell, 1988.Google Scholar
5. Hendry, D.F. Monte Carlo experimentation in econometrics. In Griliches, Z. and Intriligator, M. (eds.). Handbook of Econometrics, Vol. 2, Chapter 16. Amsterdam: North Holland, 1984.Google Scholar
6. LeCam, L. & Lehmann, E.L.. , J. Neyman-on the occasion of his 80th birthday. Annals of Statistics 2 (1974): vii-xiii.10.1214/aos/1176342703CrossRefGoogle Scholar
7. Nelson, F.D. & Savin, N.E.. The danger of extrapolating asymptotic local power. Econometrica 58 (1990): 977–981.10.2307/2938360CrossRefGoogle Scholar
8. Newey, W.K. Maximum likelihood specification testing and conditional moment tests. Econometrica 53 (1985): 1047–1070.10.2307/1911011CrossRefGoogle Scholar
9. Neyman, J. “Smooth” test for goodness of fit. Skandinavisk Aktuarietiskrift 20 (1937): 149–199.Google Scholar
10. Neyman, J. Comments on, W. Hoeffding's asymptotically optimal tests for multinomial distributions. Annals of Mathematical Statistics 36 (1965): 401–405.10.1214/aoms/1177700151CrossRefGoogle Scholar
11. Neyman, J. & Pearson, E.S.. On the use and interpretation of certain test criteria for purposes of statistical inference. Biometrica 20-A (1928): 175–240 and 263–294.Google Scholar
12. Neyman, J. & Pearson, E.S.. On the problem of the most efficient tests of statistical hypotheses. Philosophic Transactions of the Royal Society of London, Series A 231 (1933): 289–337.10.1098/rsta.1933.0009Google Scholar
13. Neyman, J. & Pearson, E.S.. The testing of statistical hypotheses in relation to probabilities a priori. Proceedings of the Cambridge Philosophical Society 29 (1933): 492–510.10.1017/S030500410001152XCrossRefGoogle Scholar
14. Noether, G.E. Asymptotic properties of the Wald-Wolfowitz test of randomness. Annals of Mathematical Statistics 21 (1950): 231–246.10.1214/aoms/1177729841CrossRefGoogle Scholar
15. Noether, G.E. On a theorem of Pitman. Annals of Mathematical Statistics 26 (1955): 64–68.10.1214/aoms/1177728593CrossRefGoogle Scholar
16. Noether, G.E. Nonparametrics: the early years–impressions and recollections. The American Statistician 38 (1984): 173–178.Google Scholar
17. Pitman, E.J.G. Lectures on non-parametric inference. Columbia University, Spring Semester, 1948.Google Scholar
18. Pitman, E.J.G. Some Basic Theory for Statistical Inference. New York: Wiley, 1979.Google Scholar
19. Rothenberg, T.J. Comparing alternative asymptotically equivalent tests. In Hildenbrand, W. (ed.), Advances in Econometrics. New York: Cambridge University Press, 1982.Google Scholar
20. Rothenberg, T.J. Approximating the distributions of econometric estimators and test statistics. In Griliches, Z. & Intriligator, M. (eds.), Handbook of Econometrics, Vol. 2, Chapter 14. Amsterdam: North Holland, 1984.Google Scholar
21. Rothenberg, T.J. Approximate power functions for some robust tests of regression coefficients. Econometrica 56 (1988): 997–1019.10.2307/1911356CrossRefGoogle Scholar
22. Saikkonen, P. Asymptotic relative efficiency of the classical test statistics under misspecification. Journal of Econometrics 42 (1989): 351–369.10.1016/0304-4076(89)90058-4CrossRefGoogle Scholar