IDEAS home Printed from https://ideas.repec.org/p/nbr/nberte/0069.html
   My bibliography  Save this paper

The Distribution of the Instrumental Variables Estimator and Its t-RatioWhen the Instrument is a Poor One

Author

Listed:
  • Charles R. Nelson
  • Richard Startz

Abstract

When the instrumental variable is a poor one, in the sense of being weakly correlated with the variable it proxies, the small sample distribution of the IV estimator is concentrated around a value that is inversely related to the feedback in the system and which is often further from the true value than is the plim of OLS. The sample variance of residuals similarly becomes concentrated around a value which reflects feedback and not the variance of the disturbance. The distribution of the t-ratio reflects both of these effects, stronger feedback producing larger t-ratios. Thus, in situations where OLS is badly biased, a poor instrument will lead to spurious inferences under IV estimation with high probability, and generally perform worse than OLS.

Suggested Citation

  • Charles R. Nelson & Richard Startz, 1988. "The Distribution of the Instrumental Variables Estimator and Its t-RatioWhen the Instrument is a Poor One," NBER Technical Working Papers 0069, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberte:0069
    Note: ME
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/t0069.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Hall, Robert E, 1978. "Stochastic Implications of the Life Cycle-Permanent Income Hypothesis: Theory and Evidence," Journal of Political Economy, University of Chicago Press, vol. 86(6), pages 971-987, December.
    2. 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.
    3. Hansen, Lars Peter & Singleton, Kenneth J, 1982. "Generalized Instrumental Variables Estimation of Nonlinear Rational Expectations Models," Econometrica, Econometric Society, vol. 50(5), pages 1269-1286, September.
    Full references (including those not matched with items on IDEAS)

    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. Michele Boldrin & Lawrence J. Christiano & Jonas D.M. Fisher, 1995. "Asset Pricing Lessons for Modeling Business Cycles," NBER Working Papers 5262, National Bureau of Economic Research, Inc.
    2. Lawrence J. Christiano & Michele Boldrin & Jonas D. M. Fisher, 2001. "Habit Persistence, Asset Returns, and the Business Cycle," American Economic Review, American Economic Association, vol. 91(1), pages 149-166, March.
    3. Sule Alan & Orazio Attanasio & Martin Browning, 2009. "Estimating Euler equations with noisy data: two exact GMM estimators," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(2), pages 309-324, March.
    4. Charlotte Ostergaard & Bent E. Serensen & Oved Yosha, 2002. "Consumption and Aggregate Constraints: Evidence from U.S. States and Canadian Provinces," Journal of Political Economy, University of Chicago Press, vol. 110(3), pages 634-645, June.
    5. Clémentine Florens & Eric Jondeau & Hervé Le Bihan, 2001. "Assessing GMM Estimates of the Federal Reserve Reaction Function," Econometrics 0111003, University Library of Munich, Germany.
    6. Escanciano, Juan Carlos & Hoderlein, Stefan & Lewbel, Arthur & Linton, Oliver & Srisuma, Sorawoot, 2021. "Nonparametric Euler Equation Identification And Estimation," Econometric Theory, Cambridge University Press, vol. 37(5), pages 851-891, October.
    7. Attanasio, Orazio P & Browning, Martin, 1995. "Consumption over the Life Cycle and over the Business Cycle," American Economic Review, American Economic Association, vol. 85(5), pages 1118-1137, December.
    8. Hatzinikolaou, Dimitris & Ahking, Francis, 1995. "Government Spending and Consumer Attitudes Toward Risk, Time Preference, and Intertemporal Substitution: An Econometric Analysis," MPRA Paper 46164, University Library of Munich, Germany.
    9. Athanasopoulos, George & de Carvalho Guillén, Osmani Teixeira & Issler, João Victor & Vahid, Farshid, 2011. "Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions," Journal of Econometrics, Elsevier, vol. 164(1), pages 116-129, September.
    10. Donald W.K. Andrews & James H. Stock, 2005. "Inference with Weak Instruments," NBER Technical Working Papers 0313, National Bureau of Economic Research, Inc.
    11. Grigoli, Francesco & Herman, Alexander & Schmidt-Hebbel, Klaus, 2018. "Saving in the world," World Development, Elsevier, vol. 104(C), pages 257-270.
    12. Bennett T. McCallum, 2002. "Recent developments in monetary policy analysis: the roles of theory and evidence," Economic Quarterly, Federal Reserve Bank of Richmond, issue Win, pages 67-96.
    13. Guvenen, Fatih, 2006. "Reconciling conflicting evidence on the elasticity of intertemporal substitution: A macroeconomic perspective," Journal of Monetary Economics, Elsevier, vol. 53(7), pages 1451-1472, October.
    14. Alexandros P. Bechlioulis & Sophocles N. Brissimis, 2021. "Are household consumption decisions affected by past due unsecured debt? Theory and evidence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 3040-3053, April.
    15. Jonathan D. Ostry & Carmen M. Reinhart, 1992. "Private Saving and Terms of Trade Shocks: Evidence from Developing Countries," IMF Staff Papers, Palgrave Macmillan, vol. 39(3), pages 495-517, September.
    16. Willman, Alpo, 2007. "Sequential optimization, front-loaded information, and U.S. consumption," Working Paper Series 765, European Central Bank.
    17. Tim A. Kroencke, 2017. "Asset Pricing without Garbage," Journal of Finance, American Finance Association, vol. 72(1), pages 47-98, February.
    18. Gesteira Costa, Marcos & Carrasco-Gutierrez, Carlos Enrique, 2015. "Testing the Optimality of Consumption Decisions of the Representative Household: Evidence from Brazil," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 69(3), September.
    19. Crump, Richard K. & Eusepi, Stefano & Tambalotti, Andrea & Topa, Giorgio, 2022. "Subjective intertemporal substitution," Journal of Monetary Economics, Elsevier, vol. 126(C), pages 118-133.
    20. Orazio P. Attanasio & Martin Browning, 1994. "Testing the life cycle model consumption: what can we learn from micro and macro data?," Investigaciones Economicas, Fundación SEPI, vol. 18(3), pages 433-463, September.

    More about this item

    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:nbr:nberte:0069. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.html .

    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.