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The Behrens-Fisher Problem: An Empirical Likelihood Ratio Approach

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Author Info
Lauren Bin Dong () (Statistics Canada)
Abstract

A new theoretical solution to the Behrens-Fisher (BF) problem is developed using empirical likelihood method. The sampling properties of the empirical likelihood ratio (ELR) test for the BF problem are derived using Monte Carlo simulation technique for a wide range of situations. A comparison of the size and power of the ELR test and the Welch-Aspin test is conducted for a special case of small sample sizes. The empirical results indicate that the ELR test for the BF problem has good power properties.

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File URL: http://web.uvic.ca/econ/research/papers/ewp0404.pdf
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Paper provided by Department of Economics, University of Victoria in its series Econometrics Working Papers with number 0404.

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Length: 29 pages
Date of creation: 06 Jul 2004
Date of revision:
Handle: RePEc:vic:vicewp:0404

Note: ISSN 1485-6441
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Postal: PO Box 1700, STN CSC, Victoria, BC, Canada, V8W 2Y2
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Web page: http://web.uvic.ca/econ
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Related research
Keywords: Behrens-Fisher Problem; Empirical Likelihood; Monte Carlo Simulation; Testing for Normality; Size and Power.;

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Find related papers by JEL classification:
C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Econometric and Statistical Methods; Specific Distributions

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Ron Mittelhammer & George Judge & Ron Schoenberg, 2003. "Empirical Evidence Concerning the Finite Sample Performance of EL-Type Structural Equation Estimation and Inference Methods," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series 945, Department of Agricultural & Resource Economics, UC Berkeley. [Downloadable!]
  2. Lauren Bin Dong & David E. A. Giles, 2004. "An Empirical Likelihood Ratio Test for Normality," Econometrics Working Papers 0401, Department of Economics, University of Victoria. [Downloadable!]
  3. Giles, Judith A & Giles, David E A, 1993. " Pre-test Estimation and Testing in Econometrics: Recent Developments," Journal of Economic Surveys, Blackwell Publishing, vol. 7(2), pages 145-97, June.
  4. Jing, Bing-Yi, 1995. "Two-sample empirical likelihood method," Statistics & Probability Letters, Elsevier, vol. 24(4), pages 315-319, September. [Downloadable!] (restricted)
  5. Weerahandi, Samaradasa, 1987. "Testing Regression Equality with Unequal Variances," Econometrica, Econometric Society, vol. 55(5), pages 1211-15, September. [Downloadable!] (restricted)
  6. Bera, Anil K. & Bilias, Yannis, 2002. "The MM, ME, ML, EL, EF and GMM approaches to estimation: a synthesis," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 51-86, March. [Downloadable!] (restricted)
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