IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/7989.html
   My bibliography  Save this paper

Interpreting Instrumental Variables Estimates of the Returns to Schooling

Author

Listed:
  • Jeffrey R. Kling

Abstract

This paper synthesizes economic insights from theoretical models of schooling choice based on individual benefits and econometric work interpreting instrumental variables estimates as weighted averages of individual-specific causal effects. Linkages are illustrated using college proximity to instrument for schooling. After characterizing groups differentially affected by the instrument according to family background, I directly compute weights underlying estimation of the overall return. In analyzing the level of schooling at which individuals change their behavior in response to the instrument, I demonstrate that this instrument has its greatest impact on the transition from high school to college. Specification robustness is also examined.

Suggested Citation

  • Jeffrey R. Kling, 2000. "Interpreting Instrumental Variables Estimates of the Returns to Schooling," NBER Working Papers 7989, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:7989
    Note: LS CH
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w7989.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. David Card, 1994. "Earnings, Schooling, and Ability Revisited," Working Papers 710, Princeton University, Department of Economics, Industrial Relations Section..
    2. 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.
    3. James Heckman & Edward Vytlacil, 1998. "Instrumental Variables Methods for the Correlated Random Coefficient Model: Estimating the Average Rate of Return to Schooling When the Return is Correlated with Schooling," Journal of Human Resources, University of Wisconsin Press, vol. 33(4), pages 974-987.
    4. Joshua D. Angrist, 1998. "Estimating the Labor Market Impact of Voluntary Military Service Using Social Security Data on Military Applicants," Econometrica, Econometric Society, vol. 66(2), pages 249-288, March.
    5. Wooldridge, Jeffrey M., 1997. "On two stage least squares estimation of the average treatment effect in a random coefficient model," Economics Letters, Elsevier, vol. 56(2), pages 129-133, October.
    6. Meyer, Bruce D, 1995. "Natural and Quasi-experiments in Economics," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(2), pages 151-161, April.
    7. Joshua D. Angrist & Guido W. Imbens & D.B. Rubin, 1993. "Identification of Causal Effects Using Instrumental Variables," NBER Technical Working Papers 0136, National Bureau of Economic Research, Inc.
    8. repec:eee:labchp:v:1:y:1986:i:c:p:525-602 is not listed on IDEAS
    9. Caroline M. Hoxby, 1997. "How the Changing Market Structure of U.S. Higher Education Explains College Tuition," NBER Working Papers 6323, National Bureau of Economic Research, Inc.
    10. Joshua D. Angrist & Alan B. Keueger, 1991. "Does Compulsory School Attendance Affect Schooling and Earnings?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 106(4), pages 979-1014.
    11. Griliches, Zvi, 1977. "Estimating the Returns to Schooling: Some Econometric Problems," Econometrica, Econometric Society, vol. 45(1), pages 1-22, January.
    12. Stephen Cameron & Christopher Taber, 2000. "Borrowing Constraints and the Returns to Schooling," NBER Working Papers 7761, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Card, David, 2001. "Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems," Econometrica, Econometric Society, vol. 69(5), pages 1127-1160, September.
    2. Joshua D. Angrist & Alan B. Krueger, 2001. "Instrumental Variables and the Search for Identification: From Supply and Demand to Natural Experiments," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 69-85, Fall.
    3. Bryan S. Graham & James Powell, 2008. "Identification and Estimation of 'Irregular' Correlated Random Coefficient Models," NBER Working Papers 14469, National Bureau of Economic Research, Inc.
    4. Thomas Lemieux, 2014. "Occupations, fields of study and returns to education," Canadian Journal of Economics, Canadian Economics Association, vol. 47(4), pages 1047-1077, November.
    5. Aakvik, Arild & Salvanes, Kjell G. & Vaage, Kjell, 2003. "Measuring Heterogeneity in the Returns to Education in Norway Using Educational Reforms," IZA Discussion Papers 815, Institute of Labor Economics (IZA).
    6. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    7. Klein, Tobias J., 2010. "Heterogeneous treatment effects: Instrumental variables without monotonicity?," Journal of Econometrics, Elsevier, vol. 155(2), pages 99-116, April.
    8. Richard Blundell & Lorraine Dearden & Barbara Sianesi, 2003. "Evaluating the impact of education on earnings in the UK: Models, methods and results from the NCDS," IFS Working Papers W03/20, Institute for Fiscal Studies.
    9. Xiaolin Sun, 2022. "Estimation of Heterogeneous Treatment Effects Using a Conditional Moment Based Approach," Papers 2210.15829, arXiv.org, revised Oct 2024.
    10. Michael Lechner & Ruth Miquel, 2010. "Identification of the effects of dynamic treatments by sequential conditional independence assumptions," Empirical Economics, Springer, vol. 39(1), pages 111-137, August.
    11. Matt Dickson, 2013. "The Causal Effect of Education on Wages Revisited," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(4), pages 477-498, August.
    12. Jean-Louis ARCAND & Béatrice D'HOMBRES & Paul GYSELINCK, 2004. "Instrument Choice and the Returns to Education: New Evidence from Vietnam," Working Papers 200422, CERDI.
    13. Doan, Tinh & Stevens, Philip, 2011. "Labour market returns to higher education in Vietnam," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 5, pages 1-21.
    14. Khan, Bilal Muhammad, 2019. "Education Occupation Mismatch in Developing countries," MPRA Paper 92324, University Library of Munich, Germany.
    15. Li, Mingliang & Tobias, Justin L., 2011. "Bayesian inference in a correlated random coefficients model: Modeling causal effect heterogeneity with an application to heterogeneous returns to schooling," Journal of Econometrics, Elsevier, vol. 162(2), pages 345-361, June.
    16. John K. Dagsvik & Torbjørn Hægeland & Arvid Raknerud, 2006. "Estimation of Earnings- and Schooling Choice Relations: A Likelihood Approach," Discussion Papers 486, Statistics Norway, Research Department.
    17. Guillermo Cruces & Sebastian Galiani, 2003. "Generalizing the Causal Effect of Fertility on Female Labor Supply," Labor and Demography 0310002, University Library of Munich, Germany.
    18. Joshua D. Angrist, 2004. "Treatment effect heterogeneity in theory and practice," Economic Journal, Royal Economic Society, vol. 114(494), pages 52-83, March.
    19. Schultz, T. Paul, 2010. "Population and Health Policies," Handbook of Development Economics, in: Dani Rodrik & Mark Rosenzweig (ed.), Handbook of Development Economics, edition 1, volume 5, chapter 0, pages 4785-4881, Elsevier.
    20. Belzil, Christian & Hansen, Jorgen, 2007. "A structural analysis of the correlated random coefficient wage regression model," Journal of Econometrics, Elsevier, vol. 140(2), pages 827-848, October.

    More about this item

    JEL classification:

    • J3 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:7989. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.