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Simple Tests for Selection: Learning More from Instrumental Variables

Author

Listed:
  • Dan A. Black
  • Joonhwi Joo
  • Robert LaLonde
  • Jeffrey Andrew Smith
  • Evan J. Taylor
Abstract
We provide simple tests for selection on unobserved variables in the Vytlacil-Imbens-Angrist framework for Local Average Treatment Effects. The tests allow researchers not only to test for selection on either or both of the treated and untreated outcomes, but also to assess the magnitude of the selection effect. The tests are quite simple; undergraduates after an introductory econometrics class should be able to implement these tests. We illustrate our tests with two empirical applications: the impact of children on female labor supply from Angrist and Evans (1998) and the impact of training on adult women from the Job Training Partnership Act (JTPA) experiment.

Suggested Citation

  • Dan A. Black & Joonhwi Joo & Robert LaLonde & Jeffrey Andrew Smith & Evan J. Taylor, 2017. "Simple Tests for Selection: Learning More from Instrumental Variables," CESifo Working Paper Series 6392, CESifo.
    • Handle: RePEc:ces:ceswps:_6392
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    Cited by:

    1. Tarek Azzam & Michael Bates & David Fairris, 2019. "Do Learning Communities Increase First Year College Retention? Testing Sample Selection and External Validity of Randomized Control Trials," Working Papers 202002, University of California at Riverside, Department of Economics.
    2. Nocito, Samuel, 2021. "The effect of a university degree in english on international labor mobility," Labour Economics, Elsevier, vol. 68(C).
    3. Jeffrey Smith, 2022. "Treatment Effect Heterogeneity," Evaluation Review, , vol. 46(5), pages 652-677, October.
    4. Azzam, Tarek & Bates, Michael D. & Fairris, David, 2022. "Do learning communities increase first year college retention? Evidence from a randomized control trial," Economics of Education Review, Elsevier, vol. 89(C).
    5. Valentina Corradi & Daniel Gutknecht, 2019. "Testing for Quantile Sample Selection," Papers 1907.07412, arXiv.org, revised Jan 2021.
    6. Ainoa Aparicio Fenoll & Nadia Campaniello & Ignacio Monzón, 2023. "Parental Love Is Not Blind: Identifying Selection into Early School Start," Working Papers 286, Red Nacional de Investigadores en Economía (RedNIE).
    7. Seth Gershenson & Cassandra M. D. Hart & Joshua Hyman & Constance A. Lindsay & Nicholas W. Papageorge, 2022. "The Long-Run Impacts of Same-Race Teachers," American Economic Journal: Economic Policy, American Economic Association, vol. 14(4), pages 300-342, November.
    8. Daniel Litwok, 2023. "Estimating the Impact of Emergency Assistance on Educational Progress for Low-Income Adults: Experimental and Nonexperimental Evidence," Evaluation Review, , vol. 47(2), pages 231-263, April.
    9. Kim, Jun Hyung & Schulz, Wolfgang & Zimmermann, Tanja & Hahlweg, Kurt, 2018. "Parent–child interactions and child outcomes: Evidence from randomized intervention," Labour Economics, Elsevier, vol. 54(C), pages 152-171.

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    More about this item

    Keywords

    instrumental variable; local average treatment effect; selection; test;
    All these keywords.

    JEL classification:

    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments

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