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Analyzing Censored and Sample-Selected Data with Tobit and Heckit Models

Published online by Cambridge University Press:  04 January 2017

Lee Sigelman  and
Langche Zeng
Lee Sigelman
Affiliation:
The George Washington University
Langche Zeng
Affiliation:
The George Washington University
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Abstract

Political scientists are making increasing use of the Tobit and Heckit models. This paper addresses some common problems in the application and interpretation of these models. Through numerical experiments and reanalysis of data from a study by Romer and Snyder (1994), we illustrate the consequences of using the standard Tobit model, which assumes a censoring point at zero, when the zeros are not due to censoring mechanisms or when actual censoring is not at zero. In the latter case, we also show that Greene's (1981) well-known results on the direction and size of the bias of the OLS estimator in the standard Tobit model do not necessarily hold. Because the Heckit model is often used as an alternative to Tobit, we examine its assumptions and discuss the proper interpretation of the Heckit/Tobit estimation results using Grier and co-workers' (1994) Heckit model of campaign contribution data. Sensitivity analyses of the Heckit estimation results suggest some conclusions rather different from those reached by Grier et al.

Type
Research Article
Information
Political Analysis , Volume 8 , Issue 2 , 16 December 1999 , pp. 167 - 182
Copyright
Copyright © 1999 by the Society for Political Methodology 

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References

Achen, Christopher H. 1986. The Statistical Analysis of Quasi-Experiments. Berkeley: University of California Press.Google Scholar
Amemiya, Takeshi. 1984. “Tobit Models: A Survey.” Journal of Econometrics 84: 3–61.Google Scholar
Beck, Nathaniel, and Tucker, Richard. 1998. “Democracy and Peace: General Law or Limited Phenomenon?” Paper presented at the Annual Meeting of the Midwest Political Science Association, Chicago, IL.Google Scholar
Beck, Nathaniel, King, Gary, and Zeng, Langche. 1998. The Problem with Quantitative Studies of International Conflict. Paper presented at the Political Methodology Summer Meeting, UC San Diego.Google Scholar
Box-Steffensmeier, Janet, and Jones, Bradford. 1997. “Time Is of the Essence: Event History Models in Political Science.” American Journal of Political Science 41: 1414.CrossRefGoogle Scholar
Breen, Richard. 1998. Regression Models: Censored, Sample Selected, or Truncated Data. Quantitative Applications, No. 111. Beverly Hills, CA: Sage.Google Scholar
Chappell, Henry W. Jr. 1982. “Campaign Contributions and Congressional Voting: A Simultaneous Probit-Tobit Model.” Review of Economics and Statistics 62: 77–83.Google Scholar
Dubin, Jeffrey A., and Rivers, Douglas. 1989–1990. “Selection Bias in Linear Regression, Logit and Probit Models.” Sociological Methods and Research 18: 360–390.CrossRefGoogle Scholar
Goldberger, Arthur S. 1972. “Selection Bias in Evaluating Treatment Effects: Some Formal Illustrations,” Institute for Research on Poverty Discussion Paper 123-72. Madison: University of Wisconsin.Google Scholar
Greene, William. 1981. “On the Asymptotic Bias of the Ordinary Least Squares Estimator of the Tobit Model.” Econometrica 49: 505–513.Google Scholar
Greene, William. 1995. LIMDEP, Version 7.0. Bellport, NY: Econometric Software.Google Scholar
Greene, William. 1997. Econometric Analysis, 3rd ed. New York: Macmillan.Google Scholar
Grier, Kevin B., and Munger, Michael C. 1993. “Comparing Interest Group PAC Contributions to House and Senate Incumbents, 1980–1986.” Journal of Politics 55: 615–643.CrossRefGoogle Scholar
Grier, Kevin B., Munger, Michael C., and Roberts, Brian E. 1994. “The Determinants of Industry Political Activity, 1978–1986.” American Political Science Review 88: 911–926.CrossRefGoogle Scholar
Heckman, James. 1979. “Sample Selection Bias as a Specification Error.” Econometrica 47: 153–161.Google Scholar
Herron, Michael C. 1998. “The Presidential Election of 1988: Low Voter Turnout and the Defeat of Michael Dukakis,” Unpublished paper.Google Scholar
Jacobs, David, and O’Brien, Robert M. 1998. “The Determinants of Deadly Force: A Structural Analysis of Police Violence.” American Journal of Sociology 103: 837–862.Google Scholar
King, Gary. 1989. Unifying Political Methodology: The Likelihood Theory of Statistical Inference. New York: Cambridge University Press.Google Scholar
King, Gary, Honaker, James, Joseph, Anne, and Scheve, Kenneth. 1998. “Listwise Deletion is Evil: What to Do About Missing Data in Political Science.” Paper presented at the Political Methodology Summer Meeting, UC San Diego.Google Scholar
King, Gary, Tomz, Michael, and Wittenberg, Jason. 1998. “How to Intepret and Present Statistical Results or Enough with the Logit Coefficients Already” Paper prepared for the annual meetings of the American Political Science Association.Google Scholar
Laitila, Thomas. 1993. “A Pseudo-R 2 Measure for Limited and Qualitative Dependent Variable Models.” Journal of Econometrics 56: 341–356.CrossRefGoogle Scholar
Maddala, G. S. 1983. Limited-Dependent and Qualitative Variables in Econometrics. New York: Cambridge University Press.Google Scholar
Maddala, G. S. 1992. Introduction to Econometrics, 2nd ed. New York: Macmillan.Google Scholar
McCarty, Nolan, and Rothenberg, Lawrence S. 1996. “Commitment and the Campaign Contribution Contract.” American Journal of Political Science 40: 872–904.Google Scholar
McDonald, John F., and Moffitt, Robert A. 1980. “The Uses of Tobit Analysis.” Review of Economics and Statistics 62: 318–321.Google Scholar
Merrnik, James. 1994. “Presidential Decision Making and the Political Use of Military Force.” International Studies Quarterly 38: 121–138.Google Scholar
Morgan, T. Clifton, and Bickers, Kenneth N. 1992. “Domestic Discontent and the External Use of Force.” Journal of Conflict Resolution 36: 25–52.Google Scholar
Nagler, Jonathan. 1994. “Scobit: An Alternative Estimator to Logit and Probit.” American Journal of Political Science 38: 230–255.CrossRefGoogle Scholar
Romer, Thomas, and Snyder, James M. Jr. 1994. “An Empirical Investigation of the Dynamics of PAC Contributions.” American Journal of Political Science 38: 745–769.CrossRefGoogle Scholar
Roncek, Dennis W. 1992. “Learning More from Tobit Coefficients: Extending a Comparative Analysis of Political Protest.” American Sociological Review 57: 503–507.CrossRefGoogle Scholar
Tobin, James. 1958. “Estimation of Relationships for Limited Dependent Variables.” Econometrica 26: 24–36.Google Scholar
Veall, Michael R., and Zimmerman, Klaus F. 1994. “Goodness of Fit Measures in the Tobit Model.” Oxford Bulletin of Economics and Statistics 56: 485–499.CrossRefGoogle Scholar
Walton, John, and Ragin, Charles. 1990. “Global and National Sources of Political Protest: Third World Responses to the Debt Crisis.” American Sociological Review 55: 876–890.Google Scholar
Wang, Kevin H. 1996. “Presidential Responses to Foreign Policy Crises.” Journal of Conflict Resolution 40: 68–97.Google Scholar