IDEAS home Printed from https://ideas.repec.org/p/wyi/wpaper/001999.html
   My bibliography  Save this paper

Reducing the Asymptotic Bias of Weak Instruments Estimation Using Independently Repeated Cross-sectional Information

Author

Listed:
  • Zongwu Cai
  • Ying Fang

Abstract

We show that independently repeated cross-sectional data can reduce the asymptotic bias when instruments are weakly correlated to the endogenous variables. When both N and T go to infinite, we can obtain consistent estimators even if instruments are weak.

Suggested Citation

  • Zongwu Cai & Ying Fang, 2013. "Reducing the Asymptotic Bias of Weak Instruments Estimation Using Independently Repeated Cross-sectional Information," Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    • Handle: RePEc:wyi:wpaper:001999
    as

    Download full text from publisher

    File URL: https://econpub.xmu.edu.cn/research/repec/upload/200810231010537055475115776.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. Berkowitz, Daniel & Caner, Mehmet & Fang, Ying, 2008. "Are "Nearly Exogenous Instruments" reliable?," Economics Letters, Elsevier, vol. 101(1), pages 20-23, October.
    3. 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.
    4. Gruber, Jonathan & Hungerman, Daniel M., 2007. "Faith-based charity and crowd-out during the great depression," Journal of Public Economics, Elsevier, vol. 91(5-6), pages 1043-1069, June.
    5. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
    6. 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.
    7. John C. Chao & Norman R. Swanson, 2005. "Consistent Estimation with a Large Number of Weak Instruments," Econometrica, Econometric Society, vol. 73(5), pages 1673-1692, September.
    8. Arellano, Manuel, 2003. "Panel Data Econometrics," OUP Catalogue, Oxford University Press, number 9780199245291.
    9. Joshua D. Angrist & Alan B. Keueger, 1991. "Does Compulsory School Attendance Affect Schooling and Earnings?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 106(4), pages 979-1014.
    10. Berkowitz, Daniel & Caner, Mehmet & Fang, Ying, 2012. "The validity of instruments revisited," Journal of Econometrics, Elsevier, vol. 166(2), pages 255-266.
    11. Price V. Fishback & Michael R. Haines & Shawn Kantor, 2002. "The Welfare of Children During the Great Depression," NBER Working Papers 8902, National Bureau of Economic Research, Inc.
    12. Frank Kleibergen, 2002. "Pivotal Statistics for Testing Structural Parameters in Instrumental Variables Regression," Econometrica, Econometric Society, vol. 70(5), pages 1781-1803, September.
    13. Card, David, 2001. "Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems," Econometrica, Econometric Society, vol. 69(5), pages 1127-1160, September.
    14. James Andreoni & Abigail Payne, 2007. "Crowding out Both Sides of the Philanthropy Market: Evidence from a Panel of Charities," Levine's Bibliography 122247000000001769, UCLA Department of Economics.
    15. James Andreoni & A. Abigail Payne, 2003. "Do Government Grants to Private Charities Crowd Out Giving or Fund-raising?," American Economic Review, American Economic Association, vol. 93(3), pages 792-812, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zongwu Cai & Linna Chen & Ying Fang, 2015. "Semiparametric Estimation of Partially Varying-Coefficient Dynamic Panel Data Models," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 695-719, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. repec:wyi:journl:002148 is not listed on IDEAS
    2. repec:wyi:journl:002137 is not listed on IDEAS
    3. Guilhem Bascle, 2008. "Controlling for endogeneity with instrumental variables in strategic management research," Post-Print hal-00576795, HAL.
    4. Bekker, Paul A. & Lawford, Steve, 2008. "Symmetry-based inference in an instrumental variable setting," Journal of Econometrics, Elsevier, vol. 142(1), pages 28-49, January.
    5. D.S. Poskitt & C.L. Skeels, 2005. "Small Concentration Asymptotics and Instrumental Variables Inference," Department of Economics - Working Papers Series 948, The University of Melbourne.
    6. Murray Michael P., 2017. "Linear Model IV Estimation When Instruments Are Many or Weak," Journal of Econometric Methods, De Gruyter, vol. 6(1), pages 1-22, January.
    7. Dufour, Jean-Marie & Taamouti, Mohamed, 2007. "Further results on projection-based inference in IV regressions with weak, collinear or missing instruments," Journal of Econometrics, Elsevier, vol. 139(1), pages 133-153, July.
    8. repec:bla:ecorec:v:91:y:2015:i::p:1-24 is not listed on IDEAS
    9. Alastair R. Hall, 2015. "Econometricians Have Their Moments: GMM at 32," The Economic Record, The Economic Society of Australia, vol. 91(S1), pages 1-24, June.
    10. Doko Tchatoka, Firmin Sabro, 2012. "Specification Tests with Weak and Invalid Instruments," MPRA Paper 40185, University Library of Munich, Germany.
    11. Joel L. Horowitz, 2018. "Non-Asymptotic Inference in Instrumental Variables Estimation," Papers 1809.03600, arXiv.org.
    12. Firmin Doko Tchatoka & Wenjie Wang, 2020. "Uniform Inference after Pretesting for Exogeneity," School of Economics and Public Policy Working Papers 2020-05, University of Adelaide, School of Economics and Public Policy.
    13. Dufour, Jean-Marie & Khalaf, Lynda & Kichian, Maral, 2006. "Inflation dynamics and the New Keynesian Phillips Curve: An identification robust econometric analysis," Journal of Economic Dynamics and Control, Elsevier, vol. 30(9-10), pages 1707-1727.
    14. Marcellino, Massimiliano & Kapetanios, George & Khalaf, Lynda, 2015. "Factor based identification-robust inference in IV regressions," CEPR Discussion Papers 10390, C.E.P.R. Discussion Papers.
    15. Manuel Denzer & Constantin Weiser, 2021. "Beyond F-statistic - A General Approach for Assessing Weak Identification," Working Papers 2107, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    16. Doko Tchatoka, Firmin, 2011. "Testing for partial exogeneity with weak identification," MPRA Paper 39504, University Library of Munich, Germany, revised Mar 2012.
    17. Richard Startz & Charles Nelson & Eric Zivot, 1999. "Improved Inference for the Instrumental Variable Estimator," Working Papers 0039, University of Washington, Department of Economics.
    18. Jean-Louis ARCAND & Béatrice D'HOMBRES & Paul GYSELINCK, 2004. "Instrument Choice and the Returns to Education: New Evidence from Vietnam," Working Papers 200422, CERDI.
    19. Tam, Henry & Lai, Liona, 2009. "Explaining the equity premium in Hong Kong with C-CAPM: The use of emigration growth as an instrument," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(3), pages 520-533, July.
    20. Doko Tchatoka, Firmin & Wang, Wenjie, 2021. "Uniform Inference after Pretesting for Exogeneity with Heteroskedastic Data," MPRA Paper 106408, University Library of Munich, Germany.
    21. Han Zhang & Jing Qin & Sonja I. Berndt & Demetrius Albanes & Lu Deng & Mitchell H. Gail & Kai Yu, 2020. "On Mendelian randomization analysis of case‐control study," Biometrics, The International Biometric Society, vol. 76(2), pages 380-391, June.
    22. Mikusheva, Anna, 2013. "Survey on statistical inferences in weakly-identified instrumental variable models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 29(1), pages 117-131.
    23. D. S. Poskitt & C. L. Skeels, 2004. "Approximating the Distribution of the Instrumental Variables Estimator when the Concentration Parameter is Small," Monash Econometrics and Business Statistics Working Papers 19/04, Monash University, Department of Econometrics and Business Statistics.

    More about this item

    Keywords

    Bias reduction; Weak instruments; Panel data.;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wyi:wpaper:001999. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: WISE Technical Team (email available below). General contact details of provider: https://www.wise.xmu.edu.cn/english/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.