Transformation of a continuous to a discrete variable: An application of the ordered logit model to examine effects of education on income in Turkey

Transformation of a continuous to a discrete variable: An application of the ordered logit model to examine effects of education on income in Turkey

The aim of this study is to put forward income differences for Turkey according to the ordered logit and human capital models. For this reason, data of the Budget Survey between 2002 and 2006 by TurkStat were used. The dependent variable was the annual yearly disposable income from the main job acquired by an individual, who brought income to the household from his main job. Interpolation was used in categorizing income, a continuous variable, and curve fitting was performed with the least squares approach. In the study, the probabilities in income groups and the changes in probabilities were calculated by the ordered logit model. Later on, it was aimed to put forward the factors that determine income differences for Turkey by using the information on education, age, occupation and marital status of individuals and the social and economic information for a household through the Mincer type of human capital model.

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  • [1] Borooah, V.K. Logit and Probit–Ordered and Multinomial Models (Sage University Paper 138, California, 2002).
  • [2] Chapra, S.C. and Canale, R.P. M¨uhendisler i¸cin Sayısal Y¨ontemler (Literat¨ur Yayınları (In Turkish), Ankara, 2008).
  • [3] Erdo˘gan, S. Temel ˙Insan Sermayesi Modeli : Se¸cilmi¸s ˙ Illerde Ekonometrik Yakla¸sım (In Turkish), D. E. ¨U. ˙ I. ˙ I. B. F. Dergisi, ˙ Izmir 14 (1), 75–95, 1999.
  • [4] Goodman, A., Johnson, P. and Webb, S. Inequality in the UK (Oxford University Press, Oxford, UK, 1997).
  • [5] Greene, W. Econometrics Analysis (Prentice Hall, New Jersey, 2003).
  • [6] Jiang, S., Li, X. and Zheng, Q. Approximate Equal Frequency Discretization Method, Intelligent Systems, GCSI’09. ERI, 514–518, 2009.
  • [7] Lee, C. Discretizing continuous attributes using information theory, Computer and Information Sciences 3733, 493–502, 2005.
  • [8] Long, J. S. Regression Models for Categorical and Limited Dependent Variables (Sage Publications, California, 1997).
  • [9] McKelvey, R.D. and Zavoina, W. A statistical model for the analysis of ordinal dependent variable, The Journal of Mathematical Sociology 4, 103–120, 1975.
  • [10] Metin, K. and ¨U¸cdo˘gruk, S¸. ˙ Istanbul ilinde gelir farklılıklarını belirleyen etmenler: ˙ Insan Sermayesi Modeli (1994), Ekonomik Yakla¸sım 8 (27) (In Turkish), 283–302, 1997.
  • [11] Mincer, J. Schooling and Earnings (Columbia University Press, New York, 1974).
  • [12] Odekon, M. The Impact of Education on The Size Distribution of Earnings in Turkey (Unpublished Ph.D. Dissertation, State University of New York, Albany, 1977).
  • [13] ¨Oks¨uzler, O. E˘gitim ve gelir ili¸skisi: T¨urkiye ¨Orne˘gi (In Turkish), T¨U ˙ IK 16. ˙ Istatistik Ara¸stırma Sempozyumu Bildiriler Kitabı, 291–300, 2007.
  • [14] Pohlmann, J.T. and Leitner, D.W. A comparison of ordinary least squares and logistic regression, Ohio J. Sci, 103 (5), 118–125, 2003.
  • [15] Smith, K. Determinants of household and labor income in the Baltic States: Soviet and post-Soviet results, The European Journal of Comparative Economics 4 (1), 3–24, 2007.
  • [16] Tun¸c, M. Kalkınmada ˙ Insan Sermayesi Yakla¸sımları ve T¨urkiye’de ˙ Insan Sermayesi Boyutunun Analizi (Unpublished PhD Thesis (In Turkish), DE¨U, Sosyal Bilimler Enstit¨us¨u, ˙Izmir, 1997).
  • [17] Winkelmann, R. and Boes, S. Analysis of Microdata (Springer-Verlag, Berlin, Heidelberg, 2006), 200–201.
  • [18] Wooldridge, M. J. Introductory Econometrics:A Modern Approach (5th Edition, Prentice Hall, Ohio, 2003).