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On the Interpretation of Instrumental Variables in the Presence of Specification Errors

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  • Stephen G. Hall,
  • P. A. V. B. Swamy
  • George S. Tavlas

Abstract

The method of instrumental variables (IV) and the generalized method of moments (GMM), and their applications to the estimation of errors-in-variables and simultaneous equations models in econometrics, require data on a sufficient number of instrumental variables that are both exogenous and relevant. We argue that, in general, such instruments (weak or strong) cannot exist.

Suggested Citation

  • Stephen G. Hall, & P. A. V. B. Swamy & George S. Tavlas, 2014. "On the Interpretation of Instrumental Variables in the Presence of Specification Errors," Discussion Papers in Economics 14/19, Division of Economics, School of Business, University of Leicester.
    • Handle: RePEc:lec:leecon:14/19
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    References listed on IDEAS

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    1. Stephen Hall & P. Swamy & George Tavlas, 2012. "Generalized cointegration: a new concept with an application to health expenditure and health outcomes," Empirical Economics, Springer, vol. 42(2), pages 603-618, April.
    2. Xu Cheng & Zhipeng Liao, 2011. "Select the Valid and Relevant Moments: An Information-Based LASSO for GMM with Many Moments, Second Version," PIER Working Paper Archive 13-062, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 21 Oct 2013.
    3. Timothy G. Conley & Christian B. Hansen & Peter E. Rossi, 2012. "Plausibly Exogenous," The Review of Economics and Statistics, MIT Press, vol. 94(1), pages 260-272, February.
    4. Guggenberger, Patrik, 2012. "On The Asymptotic Size Distortion Of Tests When Instruments Locally Violate The Exogeneity Assumption," Econometric Theory, Cambridge University Press, vol. 28(2), pages 387-421, April.
    5. Cheng, Xu & Liao, Zhipeng, 2015. "Select the valid and relevant moments: An information-based LASSO for GMM with many moments," Journal of Econometrics, Elsevier, vol. 186(2), pages 443-464.
    6. Swamy, P.A.V.B. & Tavlas, G.S. & Hall, S.G., 2015. "Microproduction Functions With Unique Coefficients And Errors: A Reconsideration And Respecification," Macroeconomic Dynamics, Cambridge University Press, vol. 19(2), pages 311-333, March.
    7. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
    8. Pratt, John W. & Schlaifer, Robert, 1988. "On the interpretation and observation of laws," Journal of Econometrics, Elsevier, vol. 39(1-2), pages 23-52.
    9. P. Swamy & George Tavlas, 2007. "The New Keynesian Phillips Curve and Inflation Expectations: Re-Specification and Interpretation," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 31(2), pages 293-306, May.
    10. Granger Clive W.J., 2008. "Non-Linear Models: Where Do We Go Next - Time Varying Parameter Models?," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(3), pages 1-11, September.
    11. 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.
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    Citations

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    Cited by:

    1. P.A.V.B. Swamy & I-Lok Chang & Jatinder S. Mehta & William H. Greene & Stephen G. Hall & George S. Tavlas, 2016. "Removing Specification Errors from the Usual Formulation of Binary Choice Models," Econometrics, MDPI, vol. 4(2), pages 1-21, June.
    2. P.A.V.B. Swamy & Stephen G. Hall & George S. Tavlas & I-Lok Chang & Heather D. Gibson & William H. Greene & Jatinder S. Mehta, 2016. "A Method for Measuring Treatment Effects on the Treated without Randomization," Econometrics, MDPI, vol. 4(2), pages 1-23, March.
    3. Duo Qin, 2019. "Let’s take the bias out of econometrics," Journal of Economic Methodology, Taylor & Francis Journals, vol. 26(2), pages 81-98, April.
    4. 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.
    5. Sergio Scicchitano, 2015. "Exploring the gender wage gap in the managerial labour market:a counterfactual decomposition analysis," Working Papers 2, Department of the Treasury, Ministry of the Economy and of Finance.
    6. Burkhard Raunig, 2017. "On The Interpretation of Instrumental Variables in the Presence of Specification Errors: A Causal Comment," Econometrics, MDPI, vol. 5(3), pages 1-6, July.
    7. Duo Qin & Sophie Van Huellen & Qing-Chao Wang, 2015. "How Credible Are Shrinking Wage Elasticities of Married Women Labour Supply?," Econometrics, MDPI, vol. 4(1), pages 1-31, December.

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    More about this item

    Keywords

    instrumental variables; generalized method of moments; random coefficient models;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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