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Probit with heteroscedasticity: an application to Indian poverty analysis

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  • Ashok Parikh
  • Kunal Sen

Abstract

This study argues that in limited dependent variable models, when there is heteroscedasticity, a probit model with a heteroscedastic structure should be estimated. The problem is illustrated using unit record data from the Indian National Sample Survey to analyse the determinants of poverty at household level. It is found that these biases are large even with large number of observations because in the limited dependent variable case, the bias does not vanish asymptotically when the assumption of homoscedasticity breaks down. Both regression coefficients and marginal effects differ widely between probit and hetprobit models in this study.

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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal Applied Economics Letters.

Volume (Year): 13 (2006)
Issue (Month): 11 ()
Pages: 699-707

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Handle: RePEc:taf:apeclt:v:13:y:2006:i:11:p:699-707

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  1. Dreze, Jean & Srinivasan, P. V., 1997. "Widowhood and poverty in rural India: Some inferences from household survey data," Journal of Development Economics, Elsevier, vol. 54(2), pages 217-234, December.
  2. Ashwini Deshpande, 2000. "Does Caste Still Define Disparity? A Look at Inequality in Kerala, India," American Economic Review, American Economic Association, vol. 90(2), pages 322-325, May.
  3. Meenakshi, J. V. & Ray, Ranjan, 2002. "Impact of household size and family composition on poverty in rural India," Journal of Policy Modeling, Elsevier, vol. 24(6), pages 539-559, October.
  4. Vani Borooah & Sriya Iyer, 2005. "Vidya, Veda, and Varna: The influence of religion and caste on education in rural India," Journal of Development Studies, Taylor & Francis Journals, vol. 41(8), pages 1369-1404.
  5. Mark N. Harris & Mark Rogers & Anthony Siouclis, 2001. "Modelling Firm Innovation using Panel Probit Estimators," Melbourne Institute Working Paper Series wp2001n20, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
  6. Blundell, Richard W. & Laisney, François & Lechner, Michael, 1991. "Alternative interpretations of hours information in an econometric model of labour supply," ZEW Discussion Papers 91-01, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
  7. J.V. Meenakshi & Ranjan Ray, 1999. "Impact of Household Size, Family Composition and Socio Economic Characteristics on Poverty in Rural India," Working papers 68, Centre for Development Economics, Delhi School of Economics.
  8. Gunewardena, Dileni & Van de Walle, Dominique, 2000. "Sources of ethnic inequality in Vietnam," Policy Research Working Paper Series 2297, The World Bank.
  9. Horowitz, Joel L., 1993. "Semiparametric estimation of a work-trip mode choice model," Journal of Econometrics, Elsevier, vol. 58(1-2), pages 49-70, July.
  10. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
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Cited by:
  1. Yong Tu & Seow Ong & Ying Han, 2009. "Turnovers and Housing Price Dynamics: Evidence from Singapore Condominium Market," The Journal of Real Estate Finance and Economics, Springer, vol. 38(3), pages 254-274, April.

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