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Evaluating Econometric Evaluations of Post-Secondary Aid

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Listed:
  • Josh Angrist
  • David Autor
  • Sally Hudson
  • Amanda Pallais

Abstract

In an ongoing evaluation of post-secondary financial aid, we use random assignment to assess the causal effects of large privately-funded aid awards. Here, we compare the unbiased causal effect estimates from our RCT with two types of non-experimental econometric estimates. The first applies a selection-on-observables assumption in data from an earlier, nonrandomized cohort; the second uses a regression discontinuity design. Selection-on-observables methods generate estimates well below the experimental benchmark. Regression discontinuity estimates are similar to experimental estimates for students near the cutoff, but sensitive to controlling for the running variable, which is unusually coarse.

Suggested Citation

  • Josh Angrist & David Autor & Sally Hudson & Amanda Pallais, 2015. "Evaluating Econometric Evaluations of Post-Secondary Aid," American Economic Review, American Economic Association, vol. 105(5), pages 502-507, May.
    • Handle: RePEc:aea:aecrev:v:105:y:2015:i:5:p:502-07
    Note: DOI: 10.1257/aer.p20151025
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    References listed on IDEAS

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    1. LaLonde, Robert J, 1986. "Evaluating the Econometric Evaluations of Training Programs with Experimental Data," American Economic Review, American Economic Association, vol. 76(4), pages 604-620, September.
    2. Rebecca A. Maynard & Kenneth A. Couch & Coady Wing & Thomas D. Cook, 2013. "Strengthening The Regression Discontinuity Design Using Additional Design Elements: A Within‐Study Comparison," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 32(4), pages 853-877, September.
    3. Joshua Angrist & Miikka Rokkanen, 2012. "Wanna Get Away? RD Identification Away from the Cutoff," NBER Working Papers 18662, National Bureau of Economic Research, Inc.
    4. Joshua Angrist & David Autor & Sally Hudson & Amanda Pallais, 2014. "Leveling Up: Early Results from a Randomized Evaluation of Post-Secondary Aid," NBER Working Papers 20800, National Bureau of Economic Research, Inc.
    5. Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2003. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," Econometrica, Econometric Society, vol. 71(4), pages 1161-1189, July.
    6. Zhuan Pei & Jörn-Steffen Pischke & Hannes Schwandt, 2019. "Poorly Measured Confounders are More Useful on the Left than on the Right," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(2), pages 205-216, April.
    7. David Deming & Susan Dynarski, 2009. "Into College, Out of Poverty? Policies to Increase the Postsecondary Attainment of the Poor," NBER Working Papers 15387, National Bureau of Economic Research, Inc.
    8. Patrick Kline, 2011. "Oaxaca-Blinder as a Reweighting Estimator," American Economic Review, American Economic Association, vol. 101(3), pages 532-537, May.
    9. 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.
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    Citations

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    Cited by:

    1. Scott-Clayton, Judith & Zafar, Basit, 2019. "Financial aid, debt management, and socioeconomic outcomes: Post-college effects of merit-based aid," Journal of Public Economics, Elsevier, vol. 170(C), pages 68-82.
    2. Aydin, Deniz & Kim, Olivia S., 2024. "Precautionary Debt Capacity," EconStor Preprints 281672, ZBW - Leibniz Information Centre for Economics.
    3. Lindsay C. Page & Judith Scott-Clayton, 2015. "Improving College Access in the United States: Barriers and Policy Responses," NBER Working Papers 21781, National Bureau of Economic Research, Inc.
    4. Vivian C. Wong & Peter M. Steiner & Kylie L. Anglin, 2018. "What Can Be Learned From Empirical Evaluations of Nonexperimental Methods?," Evaluation Review, , vol. 42(2), pages 147-175, April.
    5. Steven Jacob Bosworth, 2019. "Higher education fees as signals," Economics Discussion Papers em-dp2019-16, Department of Economics, University of Reading.
    6. Riaz Ahmed & Adeel Ahmed & Waseem Barkat & Rehmat Ullah, 2022. "Impact of Scholarships on Student Success: A Case Study of the University of Turbat, Pakistan (Article)," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 61(2), pages 231-258.
    7. Page, Lindsay C. & Scott-Clayton, Judith, 2016. "Improving college access in the United States: Barriers and policy responses," Economics of Education Review, Elsevier, vol. 51(C), pages 4-22.
    8. Tim Bartik, 2023. "Seize the Time: Needed Research on Local Economic Development in an Era of Increased Attention to Problems of Place," Economic Development Quarterly, , vol. 37(1), pages 7-13, February.

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    More about this item

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • I22 - Health, Education, and Welfare - - Education - - - Educational Finance; Financial Aid
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions

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