IDEAS home Printed from https://ideas.repec.org/p/cwl/cwldpp/803.html
   My bibliography  Save this paper

Temporal Dependence in Limited Dependent Variable Models: Theoretical and Monte-Carlo Results

Author

Abstract

This paper analyzes the consistency properties of classical estimators for limited dependent variables models, under conditions of serial correlation in the unobservables. A unified method of proof is used to show that for certain cases (e.g., Probit, Tobit and Normal Switching Regimes models, which are normality-based) estimators that neglect particular types of serial dependence (specifically, corresponding to the class of "mixing" processes) are still consistent. The same line of proof fails for the analogues to the above models that impose logistic distributional assumptions, thus indicating that normality plays a special role in these problems. Sets of Monte-Carlo experiments are then carried out to investigate these theoretical results.

Suggested Citation

  • Vassilis A. Hajivassiliou, 1986. "Temporal Dependence in Limited Dependent Variable Models: Theoretical and Monte-Carlo Results," Cowles Foundation Discussion Papers 803, Cowles Foundation for Research in Economics, Yale University.
    • Handle: RePEc:cwl:cwldpp:803
    as

    Download full text from publisher

    File URL: https://cowles.yale.edu/sites/default/files/files/pub/d08/d0803.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Avery, Robert B & Hansen, Lars Peter & Hotz, V Joseph, 1983. "Multiperiod Probit Models and Orthogonality Condition Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 24(1), pages 21-35, February.
    2. Butler, J S & Moffitt, Robert, 1982. "A Computationally Efficient Quadrature Procedure for the One-Factor Multinomial Probit Model," Econometrica, Econometric Society, vol. 50(3), pages 761-764, May.
    3. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    4. Levine, David, 1983. "A remark on serial correlation in maximum likelihood," Journal of Econometrics, Elsevier, vol. 23(3), pages 337-342, December.
    5. White, Halbert & Domowitz, Ian, 1984. "Nonlinear Regression with Dependent Observations," Econometrica, Econometric Society, vol. 52(1), pages 143-161, January.
    6. Lee, Lung-Fei, 1984. "The likelihood function and a test for serial correlation in a disequilibrium market model," Economics Letters, Elsevier, vol. 14(2-3), pages 195-200.
    7. Olsen, Randall J, 1978. "Note on the Uniqueness of the Maximum Likelihood Estimator for the Tobit Model," Econometrica, Econometric Society, vol. 46(5), pages 1211-1215, September.
    8. Quandt, Richard E., 1981. "Autocorrelated errors in simple disequilibrium models," Economics Letters, Elsevier, vol. 7(1), pages 55-61.
    9. Fair, Ray C & Jaffee, Dwight M, 1972. "Methods of Estimation for Markets in Disequilibrium," Econometrica, Econometric Society, vol. 40(3), pages 497-514, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hajivassiliou, V A, 1994. "A Simulation Estimation Analysis of the External Debt Crises of Developing Countries," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 9(2), pages 109-131, April-Jun.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jacquinot, Pascal & Mihoubi, F., 1996. "Dynamique et hétérogénéité de l’emploi en déséquilibre," L'Actualité Economique, Société Canadienne de Science Economique, vol. 72(2), pages 113-148, juin.
    2. Lee, Lung-Fei, 1997. "A smooth likelihood simulator for dynamic disequilibrium models," Journal of Econometrics, Elsevier, vol. 78(2), pages 257-294, June.
    3. Yongmiao Hong & Jin Lee, 2000. "Wavelet-based Estimation for Heteroskedasticity and Autocorrelation Consistent Variance-Covariance Matrices," Econometric Society World Congress 2000 Contributed Papers 1211, Econometric Society.
    4. Timothy Conley & Silvia Gonçalves & Christian Hansen, 2018. "Inference with Dependent Data in Accounting and Finance Applications," Journal of Accounting Research, Wiley Blackwell, vol. 56(4), pages 1139-1203, September.
    5. Laisney, François & Pohlmeier, Winfried & Staat, Matthias, 1991. "Estimation of labour supply functions using panel data: a survey," ZEW Discussion Papers 91-05, ZEW - Leibniz Centre for European Economic Research.
    6. Jörg Breitung & Michael Lechner, 1996. "Estimation de modèles non linéaires sur données de panel par la méthode des moments généralisés," Économie et Prévision, Programme National Persée, vol. 126(5), pages 191-203.
    7. Chauvet, Marcelle & Potter, Simon, 2002. "Predicting a recession: evidence from the yield curve in the presence of structural breaks," Economics Letters, Elsevier, vol. 77(2), pages 245-253, October.
    8. Su, Liangjun & Jin, Sainan, 2012. "Sieve estimation of panel data models with cross section dependence," Journal of Econometrics, Elsevier, vol. 169(1), pages 34-47.
    9. Raffaella Giacomini & Halbert White, 2006. "Tests of Conditional Predictive Ability," Econometrica, Econometric Society, vol. 74(6), pages 1545-1578, November.
    10. Breitung, Jörg & Lechner, Michael, 1998. "Alternative GMM methods for nonlinear panel data models," SFB 373 Discussion Papers 1998,81, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    11. Hirukawa, Masayuki, 2023. "Robust Covariance Matrix Estimation in Time Series: A Review," Econometrics and Statistics, Elsevier, vol. 27(C), pages 36-61.
    12. Conley, T. G., 1999. "GMM estimation with cross sectional dependence," Journal of Econometrics, Elsevier, vol. 92(1), pages 1-45, September.
    13. Rappoport, Peter & White, Eugene N., 1993. "Was There a Bubble in the 1929 Stock Market?," The Journal of Economic History, Cambridge University Press, vol. 53(3), pages 549-574, September.
    14. Inkmann, Joachim, 2000. "Misspecified heteroskedasticity in the panel probit model: A small sample comparison of GMM and SML estimators," Journal of Econometrics, Elsevier, vol. 97(2), pages 227-259, August.
    15. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    16. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, January.
    17. William H. Greene & David A. Hensher, 2008. "Modeling Ordered Choices: A Primer and Recent Developments," Working Papers 08-26, New York University, Leonard N. Stern School of Business, Department of Economics.
    18. Hajivassiliou, V A, 1994. "A Simulation Estimation Analysis of the External Debt Crises of Developing Countries," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 9(2), pages 109-131, April-Jun.
    19. Chung-Ki Min, 2010. "Estimation of SEs for heteroscedastic and cross-sectionally correlated data," Applied Economics, Taylor & Francis Journals, vol. 42(14), pages 1825-1832.
    20. James G. MacKinnon, 2012. "Thirty Years Of Heteroskedasticity-robust Inference," Working Paper 1268, Economics Department, Queen's University.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cwl:cwldpp:803. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Brittany Ladd (email available below). General contact details of provider: https://edirc.repec.org/data/cowleus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.