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Average and marginal returns to upper secondary schooling in Indonesia

Author

Listed:
  • Pedro Carneiro

    (Institute for Fiscal Studies and University College London)

  • Michael Lokshin

    (Institute for Fiscal Studies)

  • Cristobal Ridao-Cano

    (Institute for Fiscal Studies)

  • Nithin Umapathi

    (Institute for Fiscal Studies and World Bank)

Abstract

This paper estimates average and marginal returns to schooling in Indonesia using a non-parametric selection model. Identification of the model is given by exogenous geographic variation in access to upper secondary schools. We find that the return to upper secondary schooling varies widely across individuals: it can be as high as 50 percent per year of schooling for those very likely to enroll in upper secondary schooling, or as low as -10 percent for those very unlikely to do so. Average returns for the student at the margin are well below those for the average student attending upper secondary schooling.

Suggested Citation

  • Pedro Carneiro & Michael Lokshin & Cristobal Ridao-Cano & Nithin Umapathi, 2011. "Average and marginal returns to upper secondary schooling in Indonesia," CeMMAP working papers CWP36/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Handle: RePEc:ifs:cemmap:36/11
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    File URL: http://cemmap.ifs.org.uk/wps/cwp3611.pdf
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    References listed on IDEAS

    as
    1. Willis, Robert J & Rosen, Sherwin, 1979. "Education and Self-Selection," Journal of Political Economy, University of Chicago Press, vol. 87(5), pages 7-36, October.
    2. Pedro Carneiro & James J. Heckman & Edward Vytlacil, 2010. "Evaluating Marginal Policy Changes and the Average Effect of Treatment for Individuals at the Margin," Econometrica, Econometric Society, vol. 78(1), pages 377-394, January.
    3. James J. Heckman, 2010. "Building Bridges between Structural and Program Evaluation Approaches to Evaluating Policy," Journal of Economic Literature, American Economic Association, vol. 48(2), pages 356-398, June.
    4. Pedro Carneiro & James J. Heckman, 2002. "The Evidence on Credit Constraints in Post--secondary Schooling," Economic Journal, Royal Economic Society, vol. 112(482), pages 705-734, October.
    5. Robinson, Peter M, 1988. "Root- N-Consistent Semiparametric Regression," Econometrica, Econometric Society, vol. 56(4), pages 931-954, July.
    6. Esther Duflo, 2001. "Schooling and Labor Market Consequences of School Construction in Indonesia: Evidence from an Unusual Policy Experiment," American Economic Review, American Economic Association, vol. 91(4), pages 795-813, September.
    7. James J. Heckman & Edward Vytlacil, 2005. "Structural Equations, Treatment Effects, and Econometric Policy Evaluation," Econometrica, Econometric Society, vol. 73(3), pages 669-738, May.
    8. Kling, Jeffrey R, 2001. "Interpreting Instrumental Variables Estimates of the Returns to Schooling," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(3), pages 358-364, July.
    9. George Psacharopoulos & Harry Anthony Patrinos, 2004. "Returns to investment in education: a further update," Education Economics, Taylor & Francis Journals, vol. 12(2), pages 111-134.
    10. Pedro Carneiro & James J. Heckman & Edward J. Vytlacil, 2011. "Estimating Marginal Returns to Education," American Economic Review, American Economic Association, vol. 101(6), pages 2754-2781, October.
    11. James J. Heckman & Xuesong Li, 2004. "Selection bias, comparative advantage and heterogeneous returns to education: evidence from China in 2000," Pacific Economic Review, Wiley Blackwell, vol. 9(3), pages 155-171, October.
    12. Janet Currie & Enrico Moretti, 2003. "Mother's Education and the Intergenerational Transmission of Human Capital: Evidence from College Openings," The Quarterly Journal of Economics, Oxford University Press, vol. 118(4), pages 1495-1532.
    13. Heckman, James J. & Vytlacil, Edward J., 2000. "The relationship between treatment parameters within a latent variable framework," Economics Letters, Elsevier, vol. 66(1), pages 33-39, January.
    14. Carneiro, Pedro & Heckman, James J., 2003. "Human Capital Policy," IZA Discussion Papers 821, Institute of Labor Economics (IZA).
    15. Duflo, Esther, 2004. "The medium run effects of educational expansion: evidence from a large school construction program in Indonesia," Journal of Development Economics, Elsevier, vol. 74(1), pages 163-197, June.
    16. Edward Vytlacil & James J. Heckman, 2001. "Policy-Relevant Treatment Effects," American Economic Review, American Economic Association, vol. 91(2), pages 107-111, May.
    17. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-475, March.
    18. Wang, Xiaojun & Fleisher, Belton M. & Li, Haizheng & Li, Shi, 2007. "Access to Higher Education and Inequality: The Chinese Experiment," IZA Discussion Papers 2823, Institute of Labor Economics (IZA).
    19. Carneiro, Pedro & Lee, Sokbae, 2009. "Estimating distributions of potential outcomes using local instrumental variables with an application to changes in college enrollment and wage inequality," Journal of Econometrics, Elsevier, vol. 149(2), pages 191-208, April.
    20. Pedro Carneiro & Sokbae Lee, 2011. "Trends in Quality-Adjusted Skill Premia in the United States, 1960-2000," American Economic Review, American Economic Association, vol. 101(6), pages 2309-2349, October.
    21. Hidehiko Ichimura & Christopher R. Taber, 2000. "Direct Estimation of Policy Impacts," NBER Technical Working Papers 0254, National Bureau of Economic Research, Inc.
    22. 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.
    23. Susanne M. Schennach, 2012. "Measurement error in nonlinear models - a review," CeMMAP working papers CWP41/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    24. Kane, Thomas J & Rouse, Cecilia Elena, 1995. "Labor-Market Returns to Two- and Four-Year College," American Economic Review, American Economic Association, vol. 85(3), pages 600-614, June.
    25. Lorraine Dearden & Leslie McGranahan & Leslie McGranahan & Barbara Sianesi, 2004. "Returns to Education for the Marginal Learner: Evidence from the BCS70," CEE Discussion Papers 0045, Centre for the Economics of Education, LSE.
    26. Carneiro, Pedro & Lee, Sokbae, 2010. "Trends in Quality Adjusted Skill Premia in the US, 1960-2000," CEPR Discussion Papers 8108, C.E.P.R. Discussion Papers.
    27. Card, David, 2001. "Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems," Econometrica, Econometric Society, vol. 69(5), pages 1127-1160, September.
    28. Bjorklund, Anders & Moffitt, Robert, 1987. "The Estimation of Wage Gains and Welfare Gains in Self-selection," The Review of Economics and Statistics, MIT Press, vol. 69(1), pages 42-49, February.
    29. Edward Vytlacil, 2002. "Independence, Monotonicity, and Latent Index Models: An Equivalence Result," Econometrica, Econometric Society, vol. 70(1), pages 331-341, January.
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    Cited by:

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    4. Thomas Cornelissen & Christian Dustmann & Anna Raute & Uta Schönberg, 2018. "Who Benefits from Universal Child Care? Estimating Marginal Returns to Early Child Care Attendance," Journal of Political Economy, University of Chicago Press, vol. 126(6), pages 2356-2409.
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    6. Pessino, Carola & Izquierdo, Alejandro & Vuletin, Guillermo, 2018. "Better Spending for Better Lives: How Latin America and the Caribbean Can Do More with Less," IDB Publications (Books), Inter-American Development Bank, number 9152, September.
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    8. Xinxin Chen & Yaojiang Shi & Di Mo & James Chu & Prashant Loyalka & Scott Rozelle, 2013. "Impact of a Senior High School Tuition Relief Program on Poor Junior High School Students in Rural China," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 21(3), pages 80-97, May.
    9. Biewen, Martin & (neé Tapalaga), Madalina Thiele, 2020. "Early tracking, academic vs. vocational training, and the value of ‘second-chance’ options," Labour Economics, Elsevier, vol. 66(C).
    10. Gathmann, Christina & Vonnahme, Christina & Busse, Anna & Kim, Jongoh, 2021. "Marginal returns to citizenship and educational performance," Ruhr Economic Papers 920, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
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    13. Eckhoff Andresen, Martin & Huber, Martin, 2018. "Instrument-based estimation with binarized treatments: Issues and tests for the exclusion restriction," FSES Working Papers 492, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.

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    JEL classification:

    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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