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Year 2020, Volume 6, Issue 1, 63 - 74, 31.03.2020

Abstract

References

  • [1] Gujarati, D. N., “Basic Econometrics”, 5th ed. Boston: McGraw-Hill, 2009.
  • [2] Aldric J. H. and Nelson, F. D., "Linear Probability, Logit and Probit Models", Sage Publications, USA, 1984.
  • [3] Long, J. S., “Regression Models for Categorical and Limited Dependent Variables”, Sage Pubications, USA, 1977.
  • [4] Tobin, J., “Estimation of Relationships for Limited Dependent Variables”, Econometrica, 46-1, 24-36 (1958).
  • [5] Üçdoğruk, Ş., Akın, F. and Emeç, H., “Türkiye Hane Halkı Eğlence Kültür Harcamalarında Tobit Modelin Kullanımı”, G.Ü. İ.İ.B.F. Dergisi, 3, 13-26 (2001).
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  • [7] Özdamar, K., “Paket Programlar ile istatistiksel Veri Analizi-I”, Kaan Kitabevi, Eskişehir, 1999.
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  • [9] Amemiya, T., "Qualitative Response Models: A Survey", Journal of Economic Literature, 19-4, 481-536 (1981).
  • [10] McFadden, D., “Conditional Logit Analysis of Qualitative Choice Behavior”, Academic Press, New York, 1973.
  • [11] Demaris, A., “Regression with Social Data: Modeling Continuous and Limited Response Variables”, John Wiley & Sons, Inc. Hoboken, New Jersey, 2004.
  • [12] Schmidheiny, K., “Limited Dependent Variable Models”, Unversitat Pompeu Fabra, Lecture Notes in Microeconometrics, 2007.
  • [13] Greene, W. H., “Econometric Analysis”, New Jersey: Prentice Hall, 2002.
  • [14] Chay, K. Y. and Powell, J. L., “Semiparametric Censored Regression Models, Journal of Economic Perspectives, 15-4, 29-42 (2001).
  • [15] Powell, J. L., "Symmetrically Trimmed Least Squares Estimation for Tobit Models", Econometrica, 54-6, 1435-60 (1986).
  • [16] Cameron, A., “Limited Dependent Variable Models (Brief) Binary, Multinomial, Censored, Treatment Effects”,2011, http://cameron.econ.ucdavis.edu/bgpe2011/bgpev2_ldv.pdf . [17] Katchova, A. L. and Miranda, M. J., “Two-Step Econometric Estimation of Farm Characteristics Affecting Marketing Contract Decisions”, American Journal of Agricultural Economics, 86-1, 88-102 (2004).
  • [18] Sigelman, L. and Langche, Z., “Analyzing Censored and Sample-Selected Data with Tobit and Heckit Models” Political Analysis, 8, 167–182 (1999).
  • [19] McDonald, J. F. and Mofitt, R. A., “The Uses of Tobit Analysis”, The Review of Economics and Statistics, 62-2, 318-321 (1980).
  • [20] Akaike, H., “Information Theory and an Extension of the Maximum Likelihood Principle”, 2nd International Symposium on Information Theory, 267-281 (1973).
  • [21] Sugiuna, N., “Further Analysis of the Data by Akaike’s Information Criterion and the Finite Corrections”, Communication in Statistics-Theory and Methods, 57, 13-26 (1978).
  • [22] Hurvich, C. M. and Tsai, C., “Regression and Time Series Model Selection in Small Samples”, Biometrika, 76, 297-307 (1989).
  • [23] McQuarrie, A. D. and Tsai, C. L., “Regression and Time Series Model Selection”, World Sciencetific, 1998.
  • [24] Raftery, A. E., “Bayesian Model Selection in Social Research (with Discussion by Andrew Gelman, Donald B. Rubin and Robert M. Hauser)”, In P.V. Marsdn (Ed.), Socialogical Methodology, 111-196 (1995).
  • [25] Wasserman, L., “Bayesian Model selection and Model averaging,” Jounal of Mathematical Psychology, 44, 92-107 (2000).

Dependent Dummy Variable Models: An Application of Logit, Probit and Tobit Models on Survey Data

Year 2020, Volume 6, Issue 1, 63 - 74, 31.03.2020

Abstract

In the current study, logit, probit and tobit models which are commonly used among dependent dummy variable models are included. These models are also known as limited dependent variable models in the literature. Surveys, which are widely used in the field of social sciences, are carried out with limited options due to their nature. Linear regression models cannot be used in statistical estimations since they do not provide assumptions in limited analysis. In this case, different regression models may be preferred. The main purpose of this study is to compare the Tobit model used in censored data and the binary logit and binary probit regression models derived from this model. For this purpose, analysis were conducted on survey data. Logit, probit and Tobit model coefficient estimates and marginal effects were calculated. In addition, AIC and BIC values were obtained from the model selection criteria for these 3 models.

References

  • [1] Gujarati, D. N., “Basic Econometrics”, 5th ed. Boston: McGraw-Hill, 2009.
  • [2] Aldric J. H. and Nelson, F. D., "Linear Probability, Logit and Probit Models", Sage Publications, USA, 1984.
  • [3] Long, J. S., “Regression Models for Categorical and Limited Dependent Variables”, Sage Pubications, USA, 1977.
  • [4] Tobin, J., “Estimation of Relationships for Limited Dependent Variables”, Econometrica, 46-1, 24-36 (1958).
  • [5] Üçdoğruk, Ş., Akın, F. and Emeç, H., “Türkiye Hane Halkı Eğlence Kültür Harcamalarında Tobit Modelin Kullanımı”, G.Ü. İ.İ.B.F. Dergisi, 3, 13-26 (2001).
  • [6] Freese, J. and Long, J. S., “Regression Models for Categorical Dependent Variables Using Stata”, College Station: Stata Pres, 2006.
  • [7] Özdamar, K., “Paket Programlar ile istatistiksel Veri Analizi-I”, Kaan Kitabevi, Eskişehir, 1999.
  • [8] Sümbüloğlu, K., “Lojistik Regresyon Analizi”, 2009, http://78.189.53.61/-/bs/ess/k_sumbuloglu.pdf .
  • [9] Amemiya, T., "Qualitative Response Models: A Survey", Journal of Economic Literature, 19-4, 481-536 (1981).
  • [10] McFadden, D., “Conditional Logit Analysis of Qualitative Choice Behavior”, Academic Press, New York, 1973.
  • [11] Demaris, A., “Regression with Social Data: Modeling Continuous and Limited Response Variables”, John Wiley & Sons, Inc. Hoboken, New Jersey, 2004.
  • [12] Schmidheiny, K., “Limited Dependent Variable Models”, Unversitat Pompeu Fabra, Lecture Notes in Microeconometrics, 2007.
  • [13] Greene, W. H., “Econometric Analysis”, New Jersey: Prentice Hall, 2002.
  • [14] Chay, K. Y. and Powell, J. L., “Semiparametric Censored Regression Models, Journal of Economic Perspectives, 15-4, 29-42 (2001).
  • [15] Powell, J. L., "Symmetrically Trimmed Least Squares Estimation for Tobit Models", Econometrica, 54-6, 1435-60 (1986).
  • [16] Cameron, A., “Limited Dependent Variable Models (Brief) Binary, Multinomial, Censored, Treatment Effects”,2011, http://cameron.econ.ucdavis.edu/bgpe2011/bgpev2_ldv.pdf . [17] Katchova, A. L. and Miranda, M. J., “Two-Step Econometric Estimation of Farm Characteristics Affecting Marketing Contract Decisions”, American Journal of Agricultural Economics, 86-1, 88-102 (2004).
  • [18] Sigelman, L. and Langche, Z., “Analyzing Censored and Sample-Selected Data with Tobit and Heckit Models” Political Analysis, 8, 167–182 (1999).
  • [19] McDonald, J. F. and Mofitt, R. A., “The Uses of Tobit Analysis”, The Review of Economics and Statistics, 62-2, 318-321 (1980).
  • [20] Akaike, H., “Information Theory and an Extension of the Maximum Likelihood Principle”, 2nd International Symposium on Information Theory, 267-281 (1973).
  • [21] Sugiuna, N., “Further Analysis of the Data by Akaike’s Information Criterion and the Finite Corrections”, Communication in Statistics-Theory and Methods, 57, 13-26 (1978).
  • [22] Hurvich, C. M. and Tsai, C., “Regression and Time Series Model Selection in Small Samples”, Biometrika, 76, 297-307 (1989).
  • [23] McQuarrie, A. D. and Tsai, C. L., “Regression and Time Series Model Selection”, World Sciencetific, 1998.
  • [24] Raftery, A. E., “Bayesian Model Selection in Social Research (with Discussion by Andrew Gelman, Donald B. Rubin and Robert M. Hauser)”, In P.V. Marsdn (Ed.), Socialogical Methodology, 111-196 (1995).
  • [25] Wasserman, L., “Bayesian Model selection and Model averaging,” Jounal of Mathematical Psychology, 44, 92-107 (2000).

Details

Primary Language English
Subjects Basic Sciences
Journal Section Research Articles
Authors

Öznur İŞÇİ GÜNERİ
Muğla Sıtkı Koçman University
0000-0003-3677-7121
Türkiye


Burcu DURMUŞ (Primary Author)
MUĞLA SITKI KOÇMAN ÜNİVERSİTESİ, REKTÖRLÜK
0000-0002-0298-0802
Türkiye

Publication Date March 31, 2020
Application Date December 27, 2019
Acceptance Date March 17, 2020
Published in Issue Year 2020, Volume 6, Issue 1

Cite

APA İşçi Güneri, Ö. & Durmuş, B. (2020). Dependent Dummy Variable Models: An Application of Logit, Probit and Tobit Models on Survey Data . International Journal of Computational and Experimental Science and Engineering , 6 (1) , 63-74 . Retrieved from https://dergipark.org.tr/en/pub/ijcesen/issue/51113/666512

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