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The Case Against JIVE

Author

Listed:
  • Russell Davidson

    () (McGill University)

  • James G. MacKinnon

    () (Queen's University)

Abstract

We perform an extensive series of Monte Carlo experiments to compare the performance of two variants of the "Jackknife Instrumental Variables Estimator," or JIVE, with that of the more familiar 2SLS and LIML estimators. We find no evidence to suggest that JIVE should ever be used. It is always more dispersed than 2SLS, often very much so, and it is almost always inferior to LIML in all respects. Interestingly, JIVE seems to perform particularly badly when the instruments are weak.

Suggested Citation

  • Russell Davidson & James G. MacKinnon, 2004. "The Case Against JIVE," Working Papers 1031, Queen's University, Department of Economics.
  • Handle: RePEc:qed:wpaper:1031
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    File URL: http://qed.econ.queensu.ca/working_papers/papers/qed_wp_1031.pdf
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    References listed on IDEAS

    as
    1. Nelson, Charles R & Startz, Richard, 1990. "The Distribution of the Instrumental Variables Estimator and Its t-Ratio When the Instrument Is a Poor One," The Journal of Business, University of Chicago Press, vol. 63(1), pages 125-140, January.
    2. Russell Davidson & James G. MacKinnon, 2007. "Moments of IV and JIVE estimators," Econometrics Journal, Royal Economic Society, vol. 10(3), pages 541-553, November.
    3. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
    4. Angrist, J D & Imbens, G W & Krueger, A B, 1999. "Jackknife Instrumental Variables Estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(1), pages 57-67, Jan.-Feb..
    5. Stock, James H & Wright, Jonathan H & Yogo, Motohiro, 2002. "A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 518-529, October.
    6. Nelson, Charles R & Startz, Richard, 1990. "Some Further Results on the Exact Small Sample Properties of the Instrumental Variable Estimator," Econometrica, Econometric Society, vol. 58(4), pages 967-976, July.
    7. Jinyong Hahn & Jerry Hausman & Guido Kuersteiner, 2004. "Estimation with weak instruments: Accuracy of higher-order bias and MSE approximations," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 272-306, June.
    8. Blomquist, Soren & Dahlberg, Matz, 1999. "Small Sample Properties of LIML and Jackknife IV Estimators: Experiments with Weak Instruments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(1), pages 69-88, Jan.-Feb..
    9. Fuller, Wayne A, 1977. "Some Properties of a Modification of the Limited Information Estimator," Econometrica, Econometric Society, vol. 45(4), pages 939-953, May.
    10. Phillips, Garry D A & Hale, C, 1977. "The Bias of Instrumental Variable Estimators of Simultaneous Equation Systems," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(1), pages 219-228, February.
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    Cited by:

    1. Emanuele Millemaci & Ferdinando Ofria, 2014. "Kaldor-Verdoorn's law and increasing returns to scale: A comparison across developed countries," Journal of Economic Studies, Emerald Group Publishing, vol. 41(1), pages 140-162, January.
    2. Chambers, Marcus J., 2013. "Jackknife estimation of stationary autoregressive models," Journal of Econometrics, Elsevier, vol. 172(1), pages 142-157.
    3. Alfonso Flores-Lagunes, 2007. "Finite sample evidence of IV estimators under weak instruments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(3), pages 677-694.
    4. Phillip, Garry & Xu, Yongdeng, 2016. "Almost Unbiased Variance Estimation in Simultaneous Equation Models," Cardiff Economics Working Papers E2016/10, Cardiff University, Cardiff Business School, Economics Section.
    5. Bekker, Paul A. & Crudu, Federico, 2012. "Symmetric Jackknife Instrumental Variable Estimation," MPRA Paper 37853, University Library of Munich, Germany.
    6. Russell Davidson & James G. MacKinnon, 2007. "Moments of IV and JIVE estimators," Econometrics Journal, Royal Economic Society, vol. 10(3), pages 541-553, November.
    7. Jeffrey R. Kling, 2006. "Incarceration Length, Employment, and Earnings," American Economic Review, American Economic Association, vol. 96(3), pages 863-876, June.
    8. Daniel A. Ackerberg & Paul J. Devereux, 2009. "Improved JIVE Estimators for Overidentified Linear Models with and without Heteroskedasticity," The Review of Economics and Statistics, MIT Press, vol. 91(2), pages 351-362, May.
    9. Arcand, Jean-Louis & Ai, Chunrong & Ethier, Francois, 2007. "Moral hazard and Marshallian inefficiency: Evidence from Tunisia," Journal of Development Economics, Elsevier, vol. 83(2), pages 411-445, July.
    10. Guilhem Bascle, 2008. "Controlling for endogeneity with instrumental variables in strategic management research," Post-Print hal-00576795, HAL.
    11. Madsen, Jakob B. & Raschky, Paul A. & Skali, Ahmed, 2015. "Does democracy drive income in the world, 1500–2000?," European Economic Review, Elsevier, vol. 78(C), pages 175-195.
    12. Millemaci, Emanuele & Ofria, Ferdinando, 2016. "Supply and demand-side determinants of productivity growth in Italian regions," Structural Change and Economic Dynamics, Elsevier, vol. 37(C), pages 138-146.
    13. Bhaven Sampat & Heidi L. Williams, 2015. "How Do Patents Affect Follow-On Innovation? Evidence from the Human Genome," NBER Working Papers 21666, National Bureau of Economic Research, Inc.
    14. Phillips, Garry D.A. & Liu-Evans, Gareth, 2016. "Approximating and reducing bias in 2SLS estimation of dynamic simultaneous equation models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 734-762.
    15. Battiston, Diego, 2013. "The impact of immigration on the labour market: Evidence from 20 years of cross-border migration to Argentina," MPRA Paper 52424, University Library of Munich, Germany.
    16. Bekker, Paul A. & Crudu, Federico, 2015. "Jackknife instrumental variable estimation with heteroskedasticity," Journal of Econometrics, Elsevier, vol. 185(2), pages 332-342.
    17. Chao, John C. & Swanson, Norman R. & Hausman, Jerry A. & Newey, Whitney K. & Woutersen, Tiemen, 2012. "Asymptotic Distribution Of Jive In A Heteroskedastic Iv Regression With Many Instruments," Econometric Theory, Cambridge University Press, vol. 28(01), pages 42-86, February.
    18. Matz Dahlberg & Sören Blomquist, 2006. "The case against JIVE: a comment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(6), pages 839-841.
    19. Iglesias, Emma M. & Phillips, Garry D.A., 2011. "Almost Unbiased Estimation in Simultaneous Equations Models with Strong and / or Weak Instruments," Cardiff Economics Working Papers E2011/19, Cardiff University, Cardiff Business School, Economics Section.

    More about this item

    Keywords

    two-stage least squares; LIML; JIVE; instrumental variables; weak instruments;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General

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