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Labor-Market Returns to the GED Using Regression Discontinuity Analysis

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  • Jepsen, Christopher

    () (University College Dublin)

  • Mueser, Peter R.

    () (University of Missouri-Columbia)

  • Troske, Kenneth

    () (University of Kentucky)

Abstract

We evaluate the labor-market returns to General Educational Development (GED) certification using state administrative data. We develop a fuzzy regression discontinuity (FRD) method to account for the fact that GED test takers can repeatedly retake the test until they pass it. Our technique can be applied to other situations where program participation is determined by a score on a "retake-able" test. Previous regression discontinuity estimates of the returns to GED certification have not accounted for retaking behavior, so these estimates may be biased. We find that the effect of GED certification on either employment or earnings is not statistically significant. GED certification increases postsecondary participation by up to four percentage points for men and up to eight percentage points for women.

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Bibliographic Info

Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 6758.

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Length: 54 pages
Date of creation: Jul 2012
Date of revision:
Handle: RePEc:iza:izadps:dp6758

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Keywords: GED; high school dropouts;

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References

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  1. Stephen V. Cameron & James J. Heckman, 1991. "The Nonequivalence of High School Equivalents," NBER Working Papers 3804, National Bureau of Economic Research, Inc.
  2. Richard J. Murnane & John B. Willett & John H. Tyler, 2000. "Who Benefits from Obtaining a GED? Evidence from High School and Beyond," The Review of Economics and Statistics, MIT Press, vol. 82(1), pages 23-37, February.
  3. John H. Tyler & Richard J. Murnane & John B. Willett, 2000. "Estimating The Labor Market Signaling Value Of The GED," The Quarterly Journal of Economics, MIT Press, vol. 115(2), pages 431-468, May.
  4. Tyler, John H. & Murnane, Richard J. & Willett, John B., 2003. "Who benefits from a GED? Evidence for females from High School and Beyond," Economics of Education Review, Elsevier, vol. 22(3), pages 237-247, June.
  5. James J. Heckman & Paul A. LaFontaine & Pedro L. Rodriguez, 2008. "Taking the Easy Way Out: How the GED Testing Program Induces Students to Drop Out," Working Papers 200829, Geary Institute, University College Dublin.
  6. John H. Tyler & Richard J. Murnane & John B. Willett, 1999. "Do the Cognitive Skills of School Dropouts Matter in the Labor Market?," NBER Working Papers 7101, National Bureau of Economic Research, Inc.
  7. David S. Lee & Thomas Lemieux, 2009. "Regression Discontinuity Designs in Economics," NBER Working Papers 14723, National Bureau of Economic Research, Inc.
  8. Guido Imbens & Thomas Lemieux, 2007. "Regression Discontinuity Designs: A Guide to Practice," NBER Working Papers 13039, National Bureau of Economic Research, Inc.
  9. John H. Tyler, 2004. "Does the G.E.D. improve earnings? Estimates from a sample of both successful and unsuccessful G.E.D. candidates," Industrial and Labor Relations Review, ILR Review, Cornell University, ILR School, vol. 57(4), pages 579-598, July.
  10. Jian Cao & Ernst W. Stromsdorfer & Gregory Weeks, 1996. "The Human Capital Effect of General Education Development Certificates on Low Income Women," Journal of Human Resources, University of Wisconsin Press, vol. 31(1), pages 206-228.
  11. James J. Heckman & Paul A. LaFontaine, 2006. "Bias-Corrected Estimates of GED Returns," Journal of Labor Economics, University of Chicago Press, vol. 24(3), pages 661-700, July.
  12. David S. Lee & David Card, 2006. "Regression Discontinuity Inference with Specification Error," NBER Technical Working Papers 0322, National Bureau of Economic Research, Inc.
  13. McCrary, Justin, 2008. "Manipulation of the running variable in the regression discontinuity design: A density test," Journal of Econometrics, Elsevier, vol. 142(2), pages 698-714, February.
  14. Papay, John P. & Willett, John B. & Murnane, Richard J., 2011. "Extending the regression-discontinuity approach to multiple assignment variables," Journal of Econometrics, Elsevier, vol. 161(2), pages 203-207, April.
  15. Lofstrom, Magnus & Tyler, John, 2007. "Modeling the Signaling Value of the GED with an Application to an Exogenous Passing Standard Increase in Texas," IZA Discussion Papers 2953, Institute for the Study of Labor (IZA).
  16. Hahn, Jinyong & Todd, Petra & Van der Klaauw, Wilbert, 2001. "Identification and Estimation of Treatment Effects with a Regression-Discontinuity Design," Econometrica, Econometric Society, vol. 69(1), pages 201-09, January.
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