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Determinants of Child Labour and School Attendance: The Role of Household Unobservables

We develop a random effects multinomial logit model to distinguish between unobserved and observed household characteristics as determinants of child labor and school attendance. Using a semi-parametric approach, the random effect is drawn from a discrete distribution of latent classes of households. The results show that household-level unobserved heterogeneity is substantial. Household-level unobserved heterogeneity swamps observed income and wealth heterogeneity. Households that belong to the class with a high latent propensity to send their children to work are not influenced by marginal changes in the explanatory variables. Households most sensitive to changes in explanatory variables are those with a high propensity to have their children neither in school nor working. Policy interventions and changes in external conditions are likely to produce large changes in the behavior of this group of families.

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Paper provided by Understanding Children's Work (UCW Programme) in its series UCW Working Paper with number 9.

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Date of creation: Dec 2002
Date of revision:
Handle: RePEc:ucw:worpap:9
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  1. Browning, Martin & Francois Bourguignon & Pierre-Andre Chiappori & Valerie Lechene, 1994. "Income and Outcomes: A Structural Model of Intrahousehold Allocation," Journal of Political Economy, University of Chicago Press, vol. 102(6), pages 1067-96, December.
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  3. Kaushik Basu, 1999. "Child Labor: Cause, Consequence, and Cure, with Remarks on International Labor Standards," Journal of Economic Literature, American Economic Association, vol. 37(3), pages 1083-1119, September.
  4. James J. Heckman, 2001. "Micro Data, Heterogeneity, and the Evaluation of Public Policy: Nobel Lecture," Journal of Political Economy, University of Chicago Press, vol. 109(4), pages 673-748, August.
  5. George J. Borjas & Glenn T. Sueyoshi, 1993. "A Two-Stage Estimator for Probit Models with Structural Group Effects," NBER Technical Working Papers 0146, National Bureau of Economic Research, Inc.
  6. Ranjan, Priya, 2001. "Credit constraints and the phenomenon of child labor," Journal of Development Economics, Elsevier, vol. 64(1), pages 81-102, February.
  7. Ray, R., 1998. "Analysis of Child Labour in Peru and Pakistan: a Comparative Study," Papers 1998-05, Tasmania - Department of Economics.
  8. Lee, Lung-fei, 2000. "A numerically stable quadrature procedure for the one-factor random-component discrete choice model," Journal of Econometrics, Elsevier, vol. 95(1), pages 117-129, March.
  9. Sin, Chor-Yiu & White, Halbert, 1996. "Information criteria for selecting possibly misspecified parametric models," Journal of Econometrics, Elsevier, vol. 71(1-2), pages 207-225.
  10. Behrman, Jere R., 1993. "Intrahousehold distribution and the family," Handbook of Population and Family Economics, in: M. R. Rosenzweig & Stark, O. (ed.), Handbook of Population and Family Economics, edition 1, volume 1, chapter 4, pages 125-187 Elsevier.
  11. Ravallion, Martin & Wodon, Quentin, 2000. "Does Child Labour Displace Schooling? Evidence on Behavioural Responses to an Enrollment Subsidy," Economic Journal, Royal Economic Society, vol. 110(462), pages C158-75, March.
  12. Jean-Marie Baland & James A. Robinson, 2000. "Is Child Labor Inefficient?," Journal of Political Economy, University of Chicago Press, vol. 108(4), pages 663-679, August.
  13. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
  14. Jensen, P. & Nielsen, H.S., 1996. "Child Labour or School Attendance? Evidence from Zambia," Papers 96-14, Centre for Labour Market and Social Research, Danmark-.
  15. Deb, Partha & Trivedi, Pravin K., 2002. "The structure of demand for health care: latent class versus two-part models," Journal of Health Economics, Elsevier, vol. 21(4), pages 601-625, July.
  16. Jain, Dipak C & Vilcassim, Naufel J & Chintagunta, Pradeep K, 1994. "A Random-Coefficients Logit Brand-Choice Model Applied to Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 317-28, July.
  17. Butler, J S & Moffitt, Robert, 1982. "A Computationally Efficient Quadrature Procedure for the One-Factor Multinomial Probit Model," Econometrica, Econometric Society, vol. 50(3), pages 761-64, May.
  18. Keane, Michael, 1993. "Simulation estimation for panel data models with limited dependent variables," MPRA Paper 53029, University Library of Munich, Germany.
  19. FurioCamillo Rosati & Zafiris Tzannatos, 2006. "Child Labour In Vietnam," Pacific Economic Review, Wiley Blackwell, vol. 11(1), pages 1-31, 02.
  20. Pudney, Stephen & Galassi, Francesco L & Mealli, Fabrizia, 1998. "An Econometric Model of Farm Tenures in Fifteenth-Century Florence," Economica, London School of Economics and Political Science, vol. 65(260), pages 535-56, November.
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