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Survey on statistical inferences in weakly-identified instrumental variable models

  • Mikusheva, Anna

    ()

    (Massachusetts Institute of Technology (MIT))

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    This paper provides a brief review of the current state of knowledge on the topic of weakly-identified instrumental variable regression. We describe the essence of the problem of weak identification, possible methods for detecting it in applied work as well as methods robust to weak identification. Special attention is devoted to the question of hypothesis testing in the presence of weak identification.

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    File URL: http://pe.cemi.rssi.ru/pe_2013_1_117-131.pdf
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    Article provided by Publishing House "SINERGIA PRESS" in its journal Applied Econometrics.

    Volume (Year): 29 (2013)
    Issue (Month): 1 ()
    Pages: 117-131

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    Handle: RePEc:ris:apltrx:0206
    Contact details of provider: Web page: http://appliedeconometrics.cemi.rssi.ru/

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    7. Nelson, C. & Startz, R., 1988. "Some Furthere Results On The Exact Small Sample Properties Of The Instrumental Variable Estimator," Working Papers 88-06, University of Washington, Department of Economics.
    8. Patrik Guggenberger & Frank Kleibergen & Sophocles Mavroeidis & Linchun Chen, 2012. "On the Asymptotic Sizes of Subset Anderson–Rubin and Lagrange Multiplier Tests in Linear Instrumental Variables Regression," Econometrica, Econometric Society, vol. 80(6), pages 2649-2666, November.
    9. Saraswata Chaudhuri & Eric Zivot, 2008. "A new method of projection-based inference in GMM with weakly identified nuisance parameters," Working Papers UWEC-2008-26, University of Washington, Department of Economics.
    10. Kleibergen, Frank, 2007. "Generalizing weak instrument robust IV statistics towards multiple parameters, unrestricted covariance matrices and identification statistics," Journal of Econometrics, Elsevier, vol. 139(1), pages 181-216, July.
    11. Robin, J.M. & Smith, R.J., 1995. "Tests of Rank," Cambridge Working Papers in Economics 9521, Faculty of Economics, University of Cambridge.
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    13. Cragg, John G. & Donald, Stephen G., 1993. "Testing Identifiability and Specification in Instrumental Variable Models," Econometric Theory, Cambridge University Press, vol. 9(02), pages 222-240, April.
    14. Jean-Marie Dufour & Mohamed Taamouti, 2005. "Projection-Based Statistical Inference in Linear Structural Models with Possibly Weak Instruments," Econometrica, Econometric Society, vol. 73(4), pages 1351-1365, 07.
    15. Jinyong Hahn & Jerry Hausman, 1999. "A New Specification Test for the Validity of Instrumental Variables," Working papers 99-11, Massachusetts Institute of Technology (MIT), Department of Economics.
    16. Hausman, Jerry & Stock, James H. & Yogo, Motohiro, 2005. "Asymptotic properties of the Hahn-Hausman test for weak-instruments," Economics Letters, Elsevier, vol. 89(3), pages 333-342, December.
    17. James H. Stock & Jonathan Wright, 2000. "GMM with Weak Identification," Econometrica, Econometric Society, vol. 68(5), pages 1055-1096, September.
    18. Frank Kleibergen & Richard Paap, 2003. "Generalized Reduced Rank Tests using the Singular Value Decomposition," Tinbergen Institute Discussion Papers 03-003/4, Tinbergen Institute.
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    23. Mikusheva, Anna, 2010. "Robust confidence sets in the presence of weak instruments," Journal of Econometrics, Elsevier, vol. 157(2), pages 236-247, August.
    24. Jean-Marie Dufour, 1997. "Some Impossibility Theorems in Econometrics with Applications to Structural and Dynamic Models," Econometrica, Econometric Society, vol. 65(6), pages 1365-1388, November.
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