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Testing for Nonparametric Identification of Causal Effects in the Presence of a Quasi-Instrument

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  • de Luna, Xavier

    ()
    (Umeå University)

  • Johansson, Per

    ()
    (IFAU)

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.

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Bibliographic Info

Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 6692.

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Length: 23 pages
Date of creation: Jun 2012
Date of revision:
Handle: RePEc:iza:izadps:dp6692

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Keywords: testing; endogeneity; monotonicity; potential outcomes;

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References

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  1. 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.
  2. 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.
  3. Monica Costa Dias & Hidehiko Ichimura & Gerard J.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.
  4. Markus Froelich, 2002. "Nonparametric IV estimation of local average treatment effects with covariates," University of St. Gallen Department of Economics working paper series 2002 2002-19, Department of Economics, University of St. Gallen.
  5. 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).
  6. Fredriksson, Peter & Johansson, Per, 2008. "Dynamic Treatment Assignment," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 435-445.
  7. 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).
  8. Abadie, Alberto, 2003. "Semiparametric instrumental variable estimation of treatment response models," Journal of Econometrics, Elsevier, vol. 113(2), pages 231-263, April.
  9. 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.
  10. de Luna, Xavier & Johansson, Per, 2006. "Exogeneity in structural equation models," Journal of Econometrics, Elsevier, vol. 132(2), pages 527-543, 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. 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.
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Cited by:
  1. Huber, Martin, 2013. "A simple test for the ignorability of non-compliance in experiments," Economics Working Paper Series 1312, University of St. Gallen, School of Economics and Political Science.

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