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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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Bibliographic Info

Article provided by MIT Press in its journal The Review of Economics and Statistics.

Volume (Year): 91 (2009)
Issue (Month): 2 (May)
Pages: 351-362

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Handle: RePEc:tpr:restat:v:91:y:2009:i:2:p:351-362

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  1. Joshua Angrist & Alan Krueger, 1990. "Does Compulsory School Attendance Affect Schooling and Earnings?," Working Papers, Princeton University, Department of Economics, Industrial Relations Section. 653, Princeton University, Department of Economics, Industrial Relations Section..
  2. John Chao & Norman Swanson, 2004. "Estimation and Testing Using Jackknife IV in Heteroskedastic Regressions With Many Weak Instruments," Departmental Working Papers, Rutgers University, Department of Economics 200420, Rutgers University, Department of Economics.
  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, Econometric Society, vol. 3(2), pages 211-255, 07.
  4. Angrist, J D & Imbens, G W & Krueger, A B, 1999. "Jackknife Instrumental Variables Estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 14(1), pages 57-67, Jan.-Feb..
  5. Paul J. Devereux & Daniel A. Ackerberg, 2006. "Comment on 'The case against JIVE'," Journal of Applied Econometrics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 21(6), pages 835-838.
  6. John C. Chao & Norman Rasmus Swanson, 2004. "Consistent Estimation with a Large Number of Weak Instruments," Yale School of Management Working Papers, Yale School of Management ysm374, Yale School of Management.
  7. Angrist, Joshua D & Krueger, Alan B, 1995. "Split-Sample Instrumental Variables Estimates of the Return to Schooling," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 13(2), pages 225-35, April.
  8. Daniel A. Ackerberg & Paul J. Devereux, 2008. "Improved Jive Estimators for Overidentified Linear Models with and without Heteroskedasticity," Working Papers, School Of Economics, University College Dublin 200817, School Of Economics, University College Dublin.
  9. Paul J Devereux, 2006. "Improved Errors-in-Variables Estimators for Grouped Data," Working Papers, School Of Economics, University College Dublin 200602, School Of Economics, University College Dublin.
  10. 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., John Wiley & Sons, Ltd., vol. 14(1), pages 69-88, Jan.-Feb..
  11. Paul J Devereux, 2006. "Small Sample Bias in Synthetic Cohort Models of Labor Supply," Working Papers, School Of Economics, University College Dublin 200606, School Of Economics, University College Dublin.
  12. Bekker, Paul A, 1994. "Alternative Approximations to the Distributions of Instrumental Variable Estimators," Econometrica, Econometric Society, Econometric Society, vol. 62(3), pages 657-81, May.
  13. Whitney Newey & Richard Smith, 2003. "Higher order properties of GMM and generalised empirical likelihood estimators," CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies CWP04/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  14. James G. MacKinnon & Russell Davidson, 2006. "The case against JIVE," Journal of Applied Econometrics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 21(6), pages 827-833.
  15. Jinyong Hahn & Jerry Hausman & Guido Kuersteiner, 2004. "Estimation with weak instruments: Accuracy of higher-order bias and MSE approximations," Econometrics Journal, Royal Economic Society, Royal Economic Society, vol. 7(1), pages 272-306, 06.
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