IDEAS home Printed from https://ideas.repec.org/p/nbr/nberte/0027.html
   My bibliography  Save this paper

The Effect of Ignoring Heteroscedasticity on Estimates of the Tobit Model

Author

Listed:
  • Charles Brown
  • Robert Moffitt

Abstract

We consider the sensitivity of the Tobit estimator to heteroscedasticity. Our single independent variable is a dummy variable whose coefficient is a difference between group means, and the error variance differs between groups. Heteroscedasticity biases the Tobit estimate of the two means in opposite directions, so the bias in estimating their difference can be significant. This bias is not monotonically related to the true difference, and is greatly increased if the limit observations are not available. Perhaps surprisingly, the Tobit estimates are sometimes more severely biased than are OLS estimates.

Suggested Citation

  • Charles Brown & Robert Moffitt, 1983. "The Effect of Ignoring Heteroscedasticity on Estimates of the Tobit Model," NBER Technical Working Papers 0027, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberte:0027
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/t0027.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Amemiya, Takeshi, 1973. "Regression Analysis when the Dependent Variable is Truncated Normal," Econometrica, Econometric Society, vol. 41(6), pages 997-1016, November.
    2. Arabmazar, Abbas & Schmidt, Peter, 1981. "Further evidence on the robustness of the Tobit estimator to heteroskedasticity," Journal of Econometrics, Elsevier, vol. 17(2), pages 253-258, November.
    3. Olsen, Randall J, 1982. "Distributional Tests for Selectivity Bias and a More Robust Likelihood Estimator," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 23(1), pages 223-240, February.
    4. James Tobin, 1956. "Estimation of Relationships for Limited Dependent Variables," Cowles Foundation Discussion Papers 3R, Cowles Foundation for Research in Economics, Yale University.
    5. Hurd, Michael, 1979. "Estimation in truncated samples when there is heteroscedasticity," Journal of Econometrics, Elsevier, vol. 11(2-3), pages 247-258.
    6. Greene, William H, 1981. "On the Asymptotic Bias of the Ordinary Least Squares Estimator of the Tobit Model," Econometrica, Econometric Society, vol. 49(2), pages 505-513, March.
    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. Melvin Stephens, 2002. "Worker Displacement and the Added Worker Effect," Journal of Labor Economics, University of Chicago Press, vol. 20(3), pages 504-537, July.
    2. Cory Koedel & Julian Betts, 2010. "Value Added to What? How a Ceiling in the Testing Instrument Influences Value-Added Estimation," Education Finance and Policy, MIT Press, vol. 5(1), pages 54-81, January.
    3. Wang, Jiangbo & Yamamoto, Toshiyuki & Liu, Kai, 2021. "Spatial dependence and spillover effects in customized bus demand: Empirical evidence using spatial dynamic panel models," Transport Policy, Elsevier, vol. 105(C), pages 166-180.
    4. Melvin Stephens Jr., 2003. ""3rd of tha Month": Do Social Security Recipients Smooth Consumption Between Checks?," American Economic Review, American Economic Association, vol. 93(1), pages 406-422, March.
    5. Bundervoet, Tom, 2010. "Assets, Activity Choices, and Civil War: Evidence from Burundi," World Development, Elsevier, vol. 38(7), pages 955-965, July.
    6. Daniel Pollmann & Thomas Dohmen & Franz Palm, 2020. "Robust Estimation of Wage Dispersion with Censored Data: An Application to Occupational Earnings Risk and Risk Attitudes," De Economist, Springer, vol. 168(4), pages 519-540, December.

    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. Cox, Thomas L. & Briggs, Hugh, 1989. "Heteroscedastic Tobit Models: The Household Demand for Fresh Potatoes Revisited," Staff Papers 200482, University of Wisconsin-Madison, Department of Agricultural and Applied Economics.
    2. Daniel Pollmann & Thomas Dohmen & Franz Palm, 2020. "Dispersion estimation; Earnings risk; Censoring; Quantile regression; Occupational choice; Sorting; Risk preferences; SOEP; IABS," ECONtribute Discussion Papers Series 028, University of Bonn and University of Cologne, Germany.
    3. Daniel Pollmann & Thomas Dohmen & Franz Palm, 2020. "Robust Estimation of Wage Dispersion with Censored Data: An Application to Occupational Earnings Risk and Risk Attitudes," De Economist, Springer, vol. 168(4), pages 519-540, December.
    4. K. -L. Wang & Y. -T. Tseng & C. -C. Weng, 2003. "A study of production efficiencies of integrated securities firms in Taiwan," Applied Financial Economics, Taylor & Francis Journals, vol. 13(3), pages 159-167.
    5. Fernández Sainz, Ana Isabel & Rodríguez Poo, Juan M. & Villanúa Martín, Inmaculada, 1999. "Finite sample behavior of two step estimators in selection models," BILTOKI 1134-8984, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).
    6. Georg Stadtmann & Dirk Czarnitzki, 2002. "Uncertainty of outcome versus reputation: Empirical evidence for the First German Football Division," Empirical Economics, Springer, vol. 27(1), pages 101-112.
    7. Wetzstein, Michael E. & Ziemer, Rod F., 1982. "A Truncated Regression Model Of Recreation Demand For California Wilderness Areas," 1982 Annual Meeting, August 1-4, Logan, Utah 279126, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    8. MoonJoong Tcha & Vitaly Pershin, 2002. "Reconsidering Performance at the Summer Olympics and Revealed Comparative Advantage," Economics Discussion / Working Papers 02-09, The University of Western Australia, Department of Economics.
    9. James J. Heckman, 2001. "Micro Data, Heterogeneity, and the Evaluation of Public Policy: Nobel Lecture," Journal of Political Economy, University of Chicago Press, vol. 109(4), pages 673-748, August.
    10. Mroz, Thomas A., 1999. "Discrete factor approximations in simultaneous equation models: Estimating the impact of a dummy endogenous variable on a continuous outcome," Journal of Econometrics, Elsevier, vol. 92(2), pages 233-274, October.
    11. Hasan, Syed Akif & Subhani, Muhammad Imtiaz & Osman, Ms. Amber, 2011. "Marketing is all about taking money from customers (an application of Tobit model)," MPRA Paper 34762, University Library of Munich, Germany.
    12. Fumio Hayashi, 1985. "The Effect of Liquidity Constraints on Consumption: A Cross-Sectional Analysis," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 100(1), pages 183-206.
    13. Kohei Enami & John Mullahy, 2009. "Tobit at fifty: a brief history of Tobin's remarkable estimator, of related empirical methods, and of limited dependent variable econometrics in health economics," Health Economics, John Wiley & Sons, Ltd., vol. 18(6), pages 619-628, June.
    14. Melenberg, Bertrand & van Soest, Arthur, 1996. "Parametric and Semi-parametric Modelling of Vacation Expenditures," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(1), pages 59-76, Jan.-Feb..
    15. Bloom, David E. & Killingsworth, Mark R., 1985. "Correcting for truncation bias caused by a latent truncation variable," Journal of Econometrics, Elsevier, vol. 27(1), pages 131-135, January.
    16. Cory Koedel & Julian Betts, 2010. "Value Added to What? How a Ceiling in the Testing Instrument Influences Value-Added Estimation," Education Finance and Policy, MIT Press, vol. 5(1), pages 54-81, January.
    17. Darryl Holden, 2011. "Testing for heteroskedasticity in the tobit and probit models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(4), pages 735-744, November.
    18. Jolliffe, Dean, 2002. "The Gender Wage Gap in Bulgaria: A Semiparametric Estimation of Discrimination," Journal of Comparative Economics, Elsevier, vol. 30(2), pages 276-295, June.
    19. Ho, Anson T.Y. & Morin, Lealand & Paarsch, Harry J. & Huynh, Kim P., 2022. "A flexible framework for intervention analysis applied to credit-card usage during the coronavirus pandemic," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1129-1157.
    20. Kohei Enami & John Mullahy, 2008. "Tobit at Fifty: A Brief History of Tobin's Remarkable Estimator, of Related Empirical Methods, and of Limited Dependent Variable Econometrics in Health Economics," NBER Working Papers 14512, National Bureau of Economic Research, Inc.

    More about this item

    Statistics

    Access and download statistics

    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:nbr:nberte:0027. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.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.