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Econometric Methods for Research in Education

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  • Meghir, Costas
  • Rivkin, Steven

Abstract

This paper reviews some of the econometric methods that have been used in the economics of education. The focus is on understanding how the assumptions made to justify and implement such methods relate to the underlying economic model and the interpretation of the results. We start by considering the estimation of the returns to education both within the context of a dynamic discrete choice model inspired by Willis and Rosen (1979) and in the context of the Mincer model. We discuss the relationship between the econometric assumptions and economic behavior. We then discuss methods that have been used in the context of assessing the impact of education quality, the teacher contribution to pupils' achievement, and the effect of school quality on housing prices. In the process we also provide a summary of some of the main results in this literature.

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This chapter was published in:

  • Erik Hanushek & Stephen Machin & Ludger Woessmann (ed.), 2011. "Handbook of the Economics of Education," Handbook of the Economics of Education, Elsevier, edition 1, volume 3, number 3, June.
    This item is provided by Elsevier in its series Handbook of the Economics of Education with number 3-01.

    Handle: RePEc:eee:educhp:3-01

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    Web page: http://www.elsevierdirect.com/product.jsp?isbn=9780444513991

    Related research

    Keywords: human capital; cognitive skills; international student achievement tests; education production function;

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    References

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    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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    1. Jesse Rothstein, 2009. "Student Sorting and Bias in Value-Added Estimation: Selection on Observables and Unobservables," Education Finance and Policy, MIT Press, vol. 4(4), pages 537-571, October.
    2. Christopher Jepsen & Steven Rivkin, 2009. "Class Size Reduction and Student Achievement: The Potential Tradeoff between Teacher Quality and Class Size," Journal of Human Resources, University of Wisconsin Press, vol. 44(1).
    3. Pedro Carneiro & James Heckman & Edward Vytlacil, 2009. "Evaluating marginal policy changes and the average effect of treatment for individuals at the margin," CeMMAP working papers CWP21/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Kennan,J. & Walker,J.R., 2003. "The effect of expected income on individual migration decisions," Working papers 7, Wisconsin Madison - Social Systems.
    5. Susanne Schennach & James Heckman & Flavio Cunha, 2007. "Estimating the Technology of Cognitive and Noncognitive Skill Formation," 2007 Meeting Papers 973, Society for Economic Dynamics.
    6. Patrick Bayer & Fernando Ferreira & Robert McMillan, 2007. "A Unified Framework for Measuring Preferences for Schools and Neighborhoods," Working Papers 07-27, Center for Economic Studies, U.S. Census Bureau.
    7. Donghoon Lee, 2005. "An Estimable Dynamic General Equilibrium Model Of Work, Schooling, And Occupational Choice," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 46(1), pages 1-34, 02.
    8. Julie Berry Cullen & Brian A Jacob & Steven Levitt, 2006. "The Effect of School Choice on Participants: Evidence from Randomized Lotteries," Econometrica, Econometric Society, vol. 74(5), pages 1191-1230, 09.
    9. Steve Gibbons & Stephen Machin & Olmo Silva, 2009. "Valuing School Quality Using Boundary Discontinuities," SERC Discussion Papers 0018, Spatial Economics Research Centre, LSE.
    10. Daniel Aaronson & Lisa Barrow & William Sander, 2007. "Teachers and Student Achievement in the Chicago Public High Schools," Journal of Labor Economics, University of Chicago Press, vol. 25, pages 95-135.
    11. Michael P. Keane & Kenneth I. Wolpin, 1995. "The career decisions of young men," Working Papers 559, Federal Reserve Bank of Minneapolis.
    12. Douglas N. Harris & Tim R. Sass, 2009. "The effects of NBPTS-certified teachers on student achievement," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 28(1), pages 55-80.
    13. Weili Ding & Steven Lehrer, 2005. "Class Size and Student Achievement: Experimental Estimates of Who Benefits and Who Loses from Reductions," Working Papers 1046, Queen's University, Department of Economics.
    14. Abbring, Jaap H. & Heckman, James J., 2007. "Econometric Evaluation of Social Programs, Part III: Distributional Treatment Effects, Dynamic Treatment Effects, Dynamic Discrete Choice, and General Equilibrium Policy Evaluation," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 72 Elsevier.
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    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Meghir and Rivkin NBER - Econometric Methods for Research in Education
      by Liam Delaney in Geary Behaviour Centre on 2010-07-19 08:07:00
    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
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    Cited by:
    1. De Simone, Gianfranco, 2013. "Render unto primary the things which are primary's: Inherited and fresh learning divides in Italian lower secondary education," Economics of Education Review, Elsevier, vol. 35(C), pages 12-23.
    2. Deborah A. Cobb-Clark & Nikhil Jha, 2013. "Educational Achievement and the Allocation of School Resources," Melbourne Institute Working Paper Series wp2013n27, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    3. Zimmerman, Seth D, 2011. "The Returns to Four-Year College for Academically Marginal Students," IZA Discussion Papers 6107, Institute for the Study of Labor (IZA).

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