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Returns to Compulsory Schooling in Britain: Evidence from a Bayesian Fuzzy Regression Discontinuity Analysis

Author

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  • Chib, Siddhartha

    (Washington University, St. Louis)

  • Jacobi, Liana

    (University of Melbourne)

Abstract

In this paper we reevaluate the returns to education based on the increase in the compulsory schooling age from 14 to 15 in the UK in 1947. We provide a Bayesian fuzzy regression discontinuity approach to infer the effect on earnings for a subset of subjects who turned 14 in a narrow window around the policy change and whose schooling was affected by the policy change. Our approach and our results are quite different from previous work that has focused on large sets of cohorts and 2SLS based approaches and has reported positive earnings and wage effects of 5% and above. Our empirical analysis, using data from the UK General Household Surveys, yields considerably lower earnings and wage effects for the additional year of compulsory schooling than previous work. These findings are consistent with the implementation of the policy change that affected students at the lower end of the schooling distribution and did not lead students to acquire additional qualifications. The results add further evidence to a number of recent studies that have found no effect from this policy change on socio-economic outcomes correlated with earnings.

Suggested Citation

  • Chib, Siddhartha & Jacobi, Liana, 2011. "Returns to Compulsory Schooling in Britain: Evidence from a Bayesian Fuzzy Regression Discontinuity Analysis," IZA Discussion Papers 5564, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp5564
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    References listed on IDEAS

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    1. Jörn-Steffen Pischke & Till von Wachter, 2008. "Zero Returns to Compulsory Schooling in Germany: Evidence and Interpretation," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 592-598, August.
    2. Lindeboom, Maarten & Llena-Nozal, Ana & van der Klaauw, Bas, 2009. "Parental education and child health: Evidence from a schooling reform," Journal of Health Economics, Elsevier, vol. 28(1), pages 109-131, January.
    3. Daron Acemoglu & Joshua Angrist, 2001. "How Large Are Human Capital Externalities? Evidence from Compulsory Schooling Laws," NBER Chapters, in: NBER Macroeconomics Annual 2000, Volume 15, pages 9-74, National Bureau of Economic Research, Inc.
    4. Harmon, Colm & Walker, Ian, 1995. "Estimates of the Economic Return to Schooling for the United Kingdom," American Economic Review, American Economic Association, vol. 85(5), pages 1278-1286, December.
    5. Julien Grenet, 2013. "Is Extending Compulsory Schooling Alone Enough to Raise Earnings? Evidence from French and British Compulsory Schooling Laws," Scandinavian Journal of Economics, Wiley Blackwell, vol. 115(1), pages 176-210, January.
    6. Philip Oreopoulos, 2006. "Estimating Average and Local Average Treatment Effects of Education when Compulsory Schooling Laws Really Matter," American Economic Review, American Economic Association, vol. 96(1), pages 152-175, March.
    7. Harmon, Colm & Walker, Ian, 1999. "The marginal and average returns to schooling in the UK," European Economic Review, Elsevier, vol. 43(4-6), pages 879-887, April.
    8. Chib, Siddhartha, 2007. "Analysis of treatment response data without the joint distribution of potential outcomes," Journal of Econometrics, Elsevier, vol. 140(2), pages 401-412, October.
    9. Damon Clark & Heather Royer, 2010. "The Effect of Education on Adult Health and Mortality: Evidence from Britain," NBER Working Papers 16013, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Hart, Robert A & Moro, Mirko & Roberts, J Elizabeth, 2012. "Date of birth, family background, and the 11 plus exam: short- and long-term consequences of the 1944 secondary education reforms in England and W ales," Stirling Economics Discussion Papers 2012-10, University of Stirling, Division of Economics.

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    More about this item

    Keywords

    regression discontinuity; principal stratification; natural experiment; imperfect compliance; causal effects; Bayesian inference; returns to schooling;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education

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