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Small-sample properties of tests for heteroscedasticity in the conditional logit model

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  • Arne Risa Hole

Abstract

This paper compares the small-sample properties of several asymp- totically equivalent tests for heteroscedasticity in the conditional logit model. While no test outperforms the others in all of the experiments conducted, the likelihood ratio test and a particular variety of theWald test are found to have good properties in moderate samples as well as being relatively powerful.

Suggested Citation

  • Arne Risa Hole, 2006. "Small-sample properties of tests for heteroscedasticity in the conditional logit model," Health, Econometrics and Data Group (HEDG) Working Papers 06/04, HEDG, c/o Department of Economics, University of York.
  • Handle: RePEc:yor:hectdg:06/04
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    References listed on IDEAS

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    1. DeShazo, J. R. & Fermo, German, 2002. "Designing Choice Sets for Stated Preference Methods: The Effects of Complexity on Choice Consistency," Journal of Environmental Economics and Management, Elsevier, vol. 44(1), pages 123-143, July.
    2. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
    3. Louviere, Jordan J, 2001. " What If Consumer Experiments Impact Variances as Well as Means? Response Variability as a Behavioral Phenomenon," Journal of Consumer Research, Oxford University Press, vol. 28(3), pages 506-511, December.
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    Cited by:

    1. repec:eee:ecoser:v:23:y:2017:i:c:p:228-237 is not listed on IDEAS
    2. Jürgen Meyerhoff & Malte Oehlmann & Priska Weller, 2015. "The Influence of Design Dimensions on Stated Choices in an Environmental Context," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 61(3), pages 385-407, July.
    3. repec:spr:pharme:v:35:y:2017:i:9:d:10.1007_s40273-017-0518-0 is not listed on IDEAS
    4. Besedeš, Tibor & Deck, Cary & Sarangi, Sudipta & Shor, Mikhael, 2012. "Decision-making strategies and performance among seniors," Journal of Economic Behavior & Organization, Elsevier, vol. 81(2), pages 524-533.
    5. Davis, Katrina J & Burton, Michael & Kragt, Marit E, 2016. "Discrete choice models: scale heterogeneity and why it matters," Working Papers 235373, University of Western Australia, School of Agricultural and Resource Economics.
    6. Gaetano Martino & Paolo Polinori, 2011. "Productive process innovation as sequential adjustment of the hybrid governance structure: the case of the poultry sector," Quaderni del Dipartimento di Economia, Finanza e Statistica 88/2011, Università di Perugia, Dipartimento Economia.
    7. repec:eee:touman:v:48:y:2015:i:c:p:467-476 is not listed on IDEAS
    8. Burton, Michael & Davis, Katrina & Kragt, Marit Ellen, 2016. "Interpretation issues in heteroscedastic conditional logit models," Working Papers 235296, University of Western Australia, School of Agricultural and Resource Economics.
    9. Achyut Kafle & Stephen K. Swallow & Elizabeth C. Smith, 2015. "Does Public Funding Affect Preferred Tradeoffs and Crowd-In or Crowd-Out Willingness to Pay? A Watershed Management Case," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 60(3), pages 471-495, March.
    10. Lancsar, Emily & Louviere, Jordan & Donaldson, Cam & Currie, Gillian & Burgess, Leonie, 2013. "Best worst discrete choice experiments in health: Methods and an application," Social Science & Medicine, Elsevier, vol. 76(C), pages 74-82.
    11. Bansback, Nick & Hole, Arne Risa & Mulhern, Brendan & Tsuchiya, Aki, 2014. "Testing a discrete choice experiment including duration to value health states for large descriptive systems: Addressing design and sampling issues," Social Science & Medicine, Elsevier, vol. 114(C), pages 38-48.

    More about this item

    Keywords

    conditional logit; heteroscedasticity;

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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