IDEAS home Printed from https://ideas.repec.org/a/spr/empeco/v49y2015i4p1153-1171.html
   My bibliography  Save this article

Sensitivity analysis for inference in 2SLS/GMM estimation with possibly flawed instruments

Author

Listed:
  • Richard Ashley
  • Christopher Parmeter

Abstract

Credible inference requires attention to the possible fragility of the results ( $$p$$ p values for key hypothesis tests) to flaws in the model assumptions, notably accounting for the validity of the instruments used. Past sensitivity analysis has mainly consisted of experimentation with alternative model specifications and with tests of over-identifying restrictions which actually presuppose instrument validity. We provide a feasible sensitivity analysis of two-stage least-squares and GMM estimation, quantifying the fragility/robustness of inference with respect to possible flaws in the exogeneity assumptions made, and also indicating which of these assumptions are most crucial. The method is illustrated via application to a well-known study of the education–earnings relationship. Copyright Springer-Verlag Berlin Heidelberg 2015

Suggested Citation

  • Richard Ashley & Christopher Parmeter, 2015. "Sensitivity analysis for inference in 2SLS/GMM estimation with possibly flawed instruments," Empirical Economics, Springer, vol. 49(4), pages 1153-1171, December.
    • Handle: RePEc:spr:empeco:v:49:y:2015:i:4:p:1153-1171
    DOI: 10.1007/s00181-015-0916-0
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s00181-015-0916-0
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s00181-015-0916-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Joshua D. Angrist & Jörn-Steffen Pischke, 2010. "The Credibility Revolution in Empirical Economics: How Better Research Design Is Taking the Con out of Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 24(2), pages 3-30, Spring.
    2. James H. Stock, 2010. "The Other Transformation in Econometric Practice: Robust Tools for Inference," Journal of Economic Perspectives, American Economic Association, vol. 24(2), pages 83-94, Spring.
    3. Donald, Stephen G & Newey, Whitney K, 2001. "Choosing the Number of Instruments," Econometrica, Econometric Society, vol. 69(5), pages 1161-1191, September.
    4. Kraay, Aart, 2008. "Instrumental variables regressions with honestly uncertain exclusion restrictions," Policy Research Working Paper Series 4632, The World Bank.
    5. Kasey S. Buckles & Daniel M. Hungerman, 2013. "Season of Birth and Later Outcomes: Old Questions, New Answers," The Review of Economics and Statistics, MIT Press, vol. 95(3), pages 711-724, July.
    6. Richard A. Ashley & Christopher F. Parmeter, 2013. "Sensitivity Analysis of Inference in GMM Estimation With Possibly-Flawed Moment Conditions," Working Papers e07-40, Virginia Polytechnic Institute and State University, Department of Economics.
    7. Hall, Alastair R. & Inoue, Atsushi, 2003. "The large sample behaviour of the generalized method of moments estimator in misspecified models," Journal of Econometrics, Elsevier, vol. 114(2), pages 361-394, June.
    8. Leamer, Edward E, 1983. "Let's Take the Con Out of Econometrics," American Economic Review, American Economic Association, vol. 73(1), pages 31-43, March.
    9. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
    10. John Bound & David A. Jaeger, 1996. "On the Validity of Season of Birth as an Instrument in Wage Equations: A Comment on Angrist & Krueger's "Does Compulsory School Attendance Affect Scho," NBER Working Papers 5835, National Bureau of Economic Research, Inc.
    11. Donald, Stephen G. & Imbens, Guido W. & Newey, Whitney K., 2009. "Choosing instrumental variables in conditional moment restriction models," Journal of Econometrics, Elsevier, vol. 152(1), pages 28-36, September.
    12. Richard Ashley, 2009. "Assessing the credibility of instrumental variables inference with imperfect instruments via sensitivity analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(2), pages 325-337, March.
    13. Small, Dylan S., 2007. "Sensitivity Analysis for Instrumental Variables Regression With Overidentifying Restrictions," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1049-1058, September.
    14. Michael P. Murray, 2006. "Avoiding Invalid Instruments and Coping with Weak Instruments," Journal of Economic Perspectives, American Economic Association, vol. 20(4), pages 111-132, Fall.
    15. Christopher A. Sims, 2010. "But Economics Is Not an Experimental Science," Journal of Economic Perspectives, American Economic Association, vol. 24(2), pages 59-68, Spring.
    16. Peter Ebbes & Michel Wedel & Ulf Böckenholt, 2009. "Frugal IV alternatives to identify the parameter for an endogenous regressor," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(3), pages 446-468, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ashley, Richard A. & Parmeter, Christopher F., 2015. "When is it justifiable to ignore explanatory variable endogeneity in a regression model?," Economics Letters, Elsevier, vol. 137(C), pages 70-74.
    2. Matthew A. Masten & Alexandre Poirier, 2021. "Salvaging Falsified Instrumental Variable Models," Econometrica, Econometric Society, vol. 89(3), pages 1449-1469, May.
    3. Kiviet, Jan F., 2016. "When is it really justifiable to ignore explanatory variable endogeneity in a regression model?," Economics Letters, Elsevier, vol. 145(C), pages 192-195.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hans Gersbach & Hans Haller & Hideo Konishi, 2015. "Household formation and markets," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 59(3), pages 461-507, August.
    2. Richard A. Ashley & Guo Li, 2013. "Re-Examining the Impact of Housing Wealth and Stock Wealth on Household Spending: Does Persistence in Wealth Changes Matter?," Working Papers e07-39, Virginia Polytechnic Institute and State University, Department of Economics.
    3. Jan F. Kiviet & Jerzy Niemczyk, 2014. "On the Limiting and Empirical Distributions of IV Estimators When Some of the Instruments are Actually Endogenous," Advances in Econometrics, in: Essays in Honor of Peter C. B. Phillips, volume 33, pages 425-490, Emerald Group Publishing Limited.
    4. Kiviet, Jan F., 2016. "When is it really justifiable to ignore explanatory variable endogeneity in a regression model?," Economics Letters, Elsevier, vol. 145(C), pages 192-195.
    5. P. Dorian Owen, 2017. "Evaluating Ingenious Instruments for Fundamental Determinants of Long-Run Economic Growth and Development," Econometrics, MDPI, vol. 5(3), pages 1-33, September.
    6. Ashley, Richard A. & Parmeter, Christopher F., 2015. "When is it justifiable to ignore explanatory variable endogeneity in a regression model?," Economics Letters, Elsevier, vol. 137(C), pages 70-74.
    7. Doko Tchatoka, Firmin Sabro, 2012. "Specification Tests with Weak and Invalid Instruments," MPRA Paper 40185, University Library of Munich, Germany.
    8. Christopher Conlon & Julie Holland Mortimer, 2021. "Empirical properties of diversion ratios," RAND Journal of Economics, RAND Corporation, vol. 52(4), pages 693-726, December.
    9. Christopher J. Ruhm, 2019. "Shackling the Identification Police?," Southern Economic Journal, John Wiley & Sons, vol. 85(4), pages 1016-1026, April.
    10. Timothy B. Armstrong & Michal Kolesár, 2021. "Sensitivity analysis using approximate moment condition models," Quantitative Economics, Econometric Society, vol. 12(1), pages 77-108, January.
    11. Shakil, Golam Saroare & Marsh, Thomas L., 2021. "One Instrument to Rule Them All?," 2021 Annual Meeting, August 1-3, Austin, Texas 314047, Agricultural and Applied Economics Association.
    12. Hans (J.L.W.) van Kippersluis & Niels (C.A.) Rietveld, 2017. "Beyond Plausibly Exogenous," Tinbergen Institute Discussion Papers 17-096/V, Tinbergen Institute.
    13. Gyuhyeong Goh & Jisang Yu, 2022. "Causal inference with some invalid instrumental variables: A quasi‐Bayesian approach," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(6), pages 1432-1451, December.
    14. Hyunseung Kang & Anru Zhang & T. Tony Cai & Dylan S. Small, 2016. "Instrumental Variables Estimation With Some Invalid Instruments and its Application to Mendelian Randomization," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(513), pages 132-144, March.
    15. Eckert, C. & J. Hohberger (Jan) & Franses, Ph.H.B.F., 2022. "Gaussian Copula Regression in the Presence of Thresholds," Econometric Institute Research Papers 2022-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    16. Stephan B. Bruns, 2013. "Identifying Genuine Effects in Observational Research by Means of Meta-Regressions," Jena Economics Research Papers 2013-040, Friedrich-Schiller-University Jena.
    17. Alm, James & Martinez-Vazquez, Jorge & McClellan, Chandler, 2016. "Corruption and firm tax evasion," Journal of Economic Behavior & Organization, Elsevier, vol. 124(C), pages 146-163.
    18. Doan, Tinh & Stevens, Philip, 2011. "Labour market returns to higher education in Vietnam," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 5, pages 1-21.
    19. Alastair R. Hall, 2015. "Econometricians Have Their Moments: GMM at 32," The Economic Record, The Economic Society of Australia, vol. 91(S1), pages 1-24, June.
    20. Christopher T. Conlon & Julie Holland Mortimer, 2010. "Effects of Product Availability: Experimental Evidence," NBER Working Papers 16506, National Bureau of Economic Research, Inc.

    More about this item

    Keywords

    Robustness; Invalid instruments; Flawed instruments; Instrumental variables; Sensitivity analysis ; Two-stage least squares; C23;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:empeco:v:49:y:2015:i:4:p:1153-1171. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.