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Testing for nonparametric identification of causal effects in the presence of a quasi-instrument

Author

Listed:
  • de Luna, Xavier

    () (Umeå School of Business and Economics, Umeå University)

  • Johansson, Per

    () (IFAU - Institute for Evaluation of Labour Market and Education Policy)

Abstract

The identification of average causal effects of a treatment in observational studies is typically based either on the unconfoundedness assumption or on the availability of an instrument. When available, instruments may also be used to test for the unconfoundedness assumption (exogeneity of the treatment). In this paper, we define variables which we call quasi-instruments because they allow us to test for the unconfoundedness assumption although they do not necessarily yield nonparametric identification of the average causal effect. A quasi-instrument is defined as an instrument except for that its relation to the treatment is allowed to be confounded by unobservables, thereby resulting in a wider range of potential applications. We propose a test for the unconfoundedness assumption based on a quasi-instrument and give conditions under which the test has power. We perform a simulation study and apply the results to a case study where the interest lies in evaluating the effect of job practice on employment.

Suggested Citation

  • de Luna, Xavier & Johansson, Per, 2012. "Testing for nonparametric identification of causal effects in the presence of a quasi-instrument," Working Paper Series 2012:14, IFAU - Institute for Evaluation of Labour Market and Education Policy.
  • Handle: RePEc:hhs:ifauwp:2012_014
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    References listed on IDEAS

    as
    1. Monica Costa Dias & Hidehiko Ichimura & Gerard Van Den Berg, 2007. "The matching method for treatment evaluation with selective participation and ineligibles," CeMMAP working papers CWP33/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Stephen G. Donald & Yu-Chin Hsu & Robert P. Lieli, 2014. "Testing the Unconfoundedness Assumption via Inverse Probability Weighted Estimators of (L)ATT," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(3), pages 395-415, July.
    3. de Luna, Xavier & Johansson, Per, 2009. "Non-Parametric Inference for the Effect of a Treatment on Survival Times with Application in the Health and Social Sciences," IZA Discussion Papers 3966, Institute for the Study of Labor (IZA).
    4. Fredriksson, Peter & Johansson, Per, 2008. "Dynamic Treatment Assignment," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 435-445.
    5. Frolich, Markus, 2007. "Nonparametric IV estimation of local average treatment effects with covariates," Journal of Econometrics, Elsevier, vol. 139(1), pages 35-75, July.
    6. Battistin, Erich & Rettore, Enrico, 2008. "Ineligibles and eligible non-participants as a double comparison group in regression-discontinuity designs," Journal of Econometrics, Elsevier, vol. 142(2), pages 715-730, February.
    7. Stephen G. Donald & Yu-Chin Hsu & Robert P. Lieli, 2012. "Testing the Unconfoundedness Assumption via Inverse Probability Weighted Estimators of (L)ATT," IEAS Working Paper : academic research 12-A017, Institute of Economics, Academia Sinica, Taipei, Taiwan, revised Jan 2014.
    8. Abadie, Alberto, 2003. "Semiparametric instrumental variable estimation of treatment response models," Journal of Econometrics, Elsevier, vol. 113(2), pages 231-263, April.
    9. de Luna, Xavier & Johansson, Per & Sjöstedt-de Luna, Sara, 2010. "Bootstrap Inference for K-Nearest Neighbour Matching Estimators," IZA Discussion Papers 5361, Institute for the Study of Labor (IZA).
    10. Johansson, Per, 2008. "The importance of employer contacts: Evidence based on selection on observables and internal replication," Labour Economics, Elsevier, vol. 15(3), pages 350-369, June.
    11. Rivers, Douglas & Vuong, Quang H., 1988. "Limited information estimators and exogeneity tests for simultaneous probit models," Journal of Econometrics, Elsevier, vol. 39(3), pages 347-366, November.
    12. de Luna, Xavier & Johansson, Per, 2006. "Exogeneity in structural equation models," Journal of Econometrics, Elsevier, vol. 132(2), pages 527-543, June.
    13. Joshua Angrist & Ivan Fernandez-Val, 2010. "ExtrapoLATE-ing: External Validity and Overidentification in the LATE Framework," NBER Working Papers 16566, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Huber, Martin, 2013. "A simple test for the ignorability of non-compliance in experiments," Economics Letters, Elsevier, vol. 120(3), pages 389-391.
    2. Gerry H. Makepeace & Michael J. Peel, 2013. "Combining information from Heckman and matching estimators: testing and controlling for hidden bias," Economics Bulletin, AccessEcon, vol. 33(3), pages 2422-2436.

    More about this item

    Keywords

    Quasi-instrument; causal effects;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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