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Improved JIVE Estimators for Overidentified Linear Models with and without Heteroskedasticity

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  • Daniel A. Ackerberg

    (UCLA)

  • Paul J. Devereux

    (University College Dublin, CEPR, and IZA)

Abstract

We introduce two simple new variants of the jackknife instrumental variables (JIVE) estimator for overidentified linear models and show that they are superior to the existing JIVE estimator, significantly improving on its small-sample-bias properties. We also compare our new estimators to existing Nagar (1959) type estimators. We show that, in models with heteroskedasticity, our estimators have superior properties to both the Nagar estimator and the related B2SLS estimator suggested in Donald and Newey (2001). These theoretical results are verified in a set of Monte Carlo experiments and then applied to estimating the returns to schooling using actual data. Copyright by the President and Fellows of Harvard College and the Massachusetts Institute of Technology.

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  • 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.
    • Handle: RePEc:tpr:restat:v:91:y:2009:i:2:p:351-362
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    Cited by:

    1. Isaiah Andrews & Timothy B. Armstrong, 2017. "Unbiased instrumental variables estimation under known first‐stage sign," Quantitative Economics, Econometric Society, vol. 8(2), pages 479-503, July.
    2. Chao, John C. & Hausman, Jerry A. & Newey, Whitney K. & Swanson, Norman R. & Woutersen, Tiemen, 2014. "Testing overidentifying restrictions with many instruments and heteroskedasticity," Journal of Econometrics, Elsevier, vol. 178(P1), pages 15-21.
    3. Jerry A. Hausman & Whitney K. Newey & Tiemen Woutersen & John C. Chao & Norman R. Swanson, 2012. "Instrumental variable estimation with heteroskedasticity and many instruments," Quantitative Economics, Econometric Society, vol. 3(2), pages 211-255, July.
    4. Eric Gautier & Christiern Rose, 2022. "Fast, Robust Inference for Linear Instrumental Variables Models using Self-Normalized Moments," Papers 2211.02249, arXiv.org, revised Nov 2022.
    5. 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(1), pages 42-86, February.
    6. Benjamin G. Hyman, 2022. "Can Displaced Labor Be Retrained? Evidence from Quasi-Random Assignment to Trade Adjustment Assistance," Working Papers 22-05, Center for Economic Studies, U.S. Census Bureau.
    7. Kirill S. Evdokimov & Michal Kolesár, 2018. "Inference in Instrumental Variable Regression Analysis with Heterogeneous Treatment Effects," Working Papers 2018-16, Princeton University. Economics Department..
    8. Michal Kolesár, 2013. "Estimation in an Instrumental Variables Model With Treatment Effect Heterogeneity," Working Papers 2013-2, Princeton University. Economics Department..
    9. Johannes W. Ligtenberg, 2023. "Inference in IV models with clustered dependence, many instruments and weak identification," Papers 2306.08559, arXiv.org, revised Mar 2024.
    10. Lei & Wang, 2023. "Estimating overidentified linear models with heteroskedasticity and outliers," Papers 2305.17615, arXiv.org, revised Mar 2024.
    11. Matsushita, Yukitoshi & Otsu, Taisuke, 2022. "A jackknife Lagrange multiplier test with many weak instruments," LSE Research Online Documents on Economics 116392, London School of Economics and Political Science, LSE Library.
    12. Michal Kolesár & Raj Chetty & John Friedman & Edward Glaeser & Guido W. Imbens, 2015. "Identification and Inference With Many Invalid Instruments," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(4), pages 474-484, October.
    13. Jörn-Steffen Pischke & Hannes Schwandt, 2012. "A Cautionary Note on Using Industry Affiliation to Predict Income," NBER Working Papers 18384, National Bureau of Economic Research, Inc.
    14. Xuexin WANG, 2021. "Instrumental variable estimation via a continuum of instruments with an application to estimating the elasticity of intertemporal substitution in consumption," Working Papers 2021-11-06, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    15. Gregor Singer, 2024. "Complementary Inputs and Industrial Development: Can Lower Electricity Prices Improve Energy Efficiency?," CESifo Working Paper Series 10944, CESifo.
    16. 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.
    17. Chao, John C. & Swanson, Norman R. & Woutersen, Tiemen, 2023. "Jackknife estimation of a cluster-sample IV regression model with many weak instruments," Journal of Econometrics, Elsevier, vol. 235(2), pages 1747-1769.
    18. Pischke, Jorn-Steffen, 2011. "Money and Happiness: Evidence from the Industry Wage Structure," CEPR Discussion Papers 8409, C.E.P.R. Discussion Papers.
    19. Keisuke Hirano & Jack R. Porter, 2015. "Location Properties of Point Estimators in Linear Instrumental Variables and Related Models," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 720-733, December.
    20. Bekker, Paul A. & Crudu, Federico, 2012. "Symmetric Jackknife Instrumental Variable Estimation," MPRA Paper 37853, University Library of Munich, Germany.
    21. Devereux, Paul J., 2007. "Improved Errors-in-Variables Estimators for Grouped Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 278-287, July.
    22. John C. Chao & Jerry A. Hausman & Whitney K. Newey & Norman R. Swanson & Tiemen Woutersen, 2012. "Combining Two Consistent Estimators," Advances in Econometrics, in: Essays in Honor of Jerry Hausman, pages 33-53, Emerald Group Publishing Limited.
    23. Devereux, Paul J. & Fan, Wen, 2011. "Earnings returns to the British education expansion," Economics of Education Review, Elsevier, vol. 30(6), pages 1153-1166.
    24. 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.

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