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Bootstrapping a conditional moments test for normality after tobit estimation

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  • David M. Drukker

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    (Stata Corporation)

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    Abstract

    Categorical and limited dependent variable models are routinely estimated via maximum likelihood. It is well-known that the ML estimates of the parameters are inconsistent if the distribution or the skedastic component is misspecified. When conditional moment tests were first developed by Newey (1985) and Tauchen (1985),they appeared to offer a wide range of easy-to-compute specification tests for categorical and limited dependent variable models estimated by maximum likelihood. However, subsequent studies found that using the asymptotic critical values produced severe size distortions. This paper presents simulation evidence that the standard conditional moment test for normality after tobit estimation has essentially no size distortion and reasonable power when the critical values are obtained via a parametric bootstrap. Copyright 2002 by Stata Corporation.

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    Bibliographic Info

    Article provided by StataCorp LP in its journal Stata Journal.

    Volume (Year): 2 (2002)
    Issue (Month): 2 (May)
    Pages: 125-139

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    Handle: RePEc:tsj:stataj:v:2:y:2002:i:2:p:125-139

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    Related research

    Keywords: conditional moment tests; bootstrap; tobit; normality;

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    1. Jeffrey M. Wooldridge, 2001. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262232197, December.
    2. Pagan, Adrian & Vella, Frank, 1989. "Diagnostic Tests for Models Based on Individual Data: A Survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 4(S), pages S29-59, Supplemen.
    3. Ericson, Peter & Hansen, Jorgen, 1999. " A Note on the Performance of Simple Specification Tests for the Tobit Model," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(1), pages 121-27, February.
    4. Christopher Skeels & Franics Vella, 1997. "Monte carlo evidence on the robustness of conditional moment tests in tobit and probit models," Econometric Reviews, Taylor & Francis Journals, vol. 16(1), pages 69-92.
    5. Moffitt, Robert, 1984. "The Estimation of a Joint Wage-Hours Labor Supply Model," Journal of Labor Economics, University of Chicago Press, vol. 2(4), pages 550-66, October.
    6. Newey, Whitney K, 1985. "Maximum Likelihood Specification Testing and Conditional Moment Tests," Econometrica, Econometric Society, vol. 53(5), pages 1047-70, September.
    7. Tauchen, George, 1985. "Diagnostic testing and evaluation of maximum likelihood models," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 415-443.
    8. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
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    Cited by:
    1. Koul, Hira L. & Song, Weixing & Liu, Shan, 2014. "Model checking in Tobit regression via nonparametric smoothing," Journal of Multivariate Analysis, Elsevier, vol. 125(C), pages 36-49.
    2. Olsson, Ola & Siba, Eyerusalem, 2013. "Ethnic cleansing or resource struggle in Darfur? An empirical analysis," Journal of Development Economics, Elsevier, vol. 103(C), pages 299-312.
    3. Wilhelm, Mark Ottoni & Brown, Eleanor & Rooney, Patrick M. & Steinberg, Richard, 2008. "The intergenerational transmission of generosity," Journal of Public Economics, Elsevier, vol. 92(10-11), pages 2146-2156, October.
    4. López-Feldman, Alejandro & Edward Taylor, J., 2009. "Labor allocation to non-timber extraction in a Mexican rainforest community," Journal of Forest Economics, Elsevier, vol. 15(3), pages 205-221, August.

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