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Journal of Applied Sciences

Year: 2004 | Volume: 4 | Issue: 4 | Page No.: 590-595
DOI: 10.3923/jas.2004.590.595
Sequential Probit Model for Infant Mortality Modelling in Turkey
Ozlem Alpu and Hatice Fidan

Abstract: This study analyzes the socioeconomic and demographic characteristics of infant mortality in Turkey using 1998 Turkish Demographic and Health Survey data, held by the Hacettepe Institute of Population Studies. A Sequential Probit model, assumed that decisions are made in a hierarchical manner, is used for analyzing this data. The effect of various demographic and socioeconomic characteristics on the probability of infant mortality is estimated via two stages sequential probit model for both correlated and uncorrelated error terms. The results of the analysis show that the correlation between the error terms, p, is significant. For this reason, it is needed to be examined two stages together.

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How to cite this article
Ozlem Alpu and Hatice Fidan, 2004. Sequential Probit Model for Infant Mortality Modelling in Turkey. Journal of Applied Sciences, 4: 590-595.

Keywords: discrete choice, heteroscedasticity, infant mortality, sequential choice model and sequential probit model

REFERENCES

  • Vasconcelos, A.G.G., R.M.V. Almeida and F.F. Nobre, 1988. The path analysis approach for the multivariate analsis of infant mortality data. Ann. Epidemiol., 8: 262-271.


  • Sufian, A.J.M., 1990. The extent and causes of mortality in developing countries. Turk. J. Popul. Stud., 12: 19-30.


  • Ulusoy, M., 1988. Regression analysis for infant mortality in Turkey. Turk. J. Popul. Stud., 10: 5-20.


  • Suwal, J.V., 2001. The main determinants of infant mortality in Nepal. Social Sci. Med., 53: 1667-1681.


  • Turrel, G. and K. Mengersen, 2000. Socioeconomic status and infant mortality in Australia: A national study of small urban areas 1985-89. Social Sci. Med., 50: 1209-1225.


  • Agha, S., 2000. The determinant of infant mortality in Pakistan. Social Sci. Med., 51: 199-208.


  • Ozarici, O., 2002. Bivariate probit model with full observability and heteroscedasticity and an application. Ph.D. Thesis, Osmangazi University, Turkey.


  • Waelbroeck, P., 2000. Effects of information search on innovation decisions bayesian analysis of the sequential probit model. GREQUAM, Vol. 25.


  • Waelbroeck, P., 2002. Econometric analysis of the sequential probit model application to innovatian surveys. ECARES FNRS, Vol. 25.


  • Cannings, K., C. Montmarquette and S. Mahseredjian, 1994. Entrance quotas and admission to medical schools a sequential probit model. IRANO Scientific Series No. 945-10, Montreal, 20. http://ideas.repec.org/p/mtl/montec/9418.html.


  • Waelbroeck, P., 2003. Comparison of simulated maximum likelihood and bayesian mcmc in the sequential probit model a monte carlo study. ECARES FNRS, Vol. 21.


  • Eklof, J.A. and S. Karlsson, 1999. Testing and correcting for sample selection bias in discrete choice contingent valuation studies. SSE/EFI Working Paper Series in Economics and Finance, No. 171. http://econpapers.repec.org/paper/hhshastef/0171.htm.


  • HIPS (Hacettepe Institute of Population Studies), 1998. Turkish Demographic and Health Survey (TDHS-98). Hacettepe University, Institute of Population Studies and Macro International Inc., Ankara


  • Grooraert, C. and H.A. Patrinos, 1999. A Four-Country Comparative Study of Child Labor, Policy Analysis of Child Labor A Comparative Study, St. Martin Press, New York

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