Advanced Search
MyIDEAS: Login to save this paper or follow this series

Inference with Weak Instruments

Contents:

Author Info

  • Donald W.K. Andrews
  • James H. Stock

Abstract

This paper reviews recent developments in methods for dealing with weak instruments (IVs) in IV regression models. The focus is more on tests and confidence intervals derived from tests than on estimators. The paper also presents new testing results under "many weak IV asymptotics," which are relevant when the number of IVs is large and the coefficients on the IVs are relatively small. Asymptotic power envelopes for invariant tests are established. Power comparisons of the conditional likelihood ratio (CLR), Anderson- Rubin, and Lagrange multiplier tests are made. Numerical results show that the CLR test is on the asymptotic power envelope. This holds no matter what the relative magnitude of the IV strength to the number of IVs.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://www.nber.org/papers/t0313.pdf
Download Restriction: no

Bibliographic Info

Paper provided by National Bureau of Economic Research, Inc in its series NBER Technical Working Papers with number 0313.

as in new window
Length:
Date of creation: Aug 2005
Date of revision:
Handle: RePEc:nbr:nberte:0313

Contact details of provider:
Postal: National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.
Phone: 617-868-3900
Email:
Web page: http://www.nber.org
More information through EDIRC

Related research

Keywords:

Other versions of this item:

Find related papers by JEL classification:

This paper has been announced in the following NEP Reports:

References

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
as in new window
  1. Nelson, C.R. & Startz, R. & Zivot, E., 1996. "Valid Confidence Intervals and Inference in the Presence of Weak Instruments," Working Papers, University of Washington, Department of Economics 96-15, University of Washington, Department of Economics.
  2. Kleibergen, Frank, 2007. "Generalizing weak instrument robust IV statistics towards multiple parameters, unrestricted covariance matrices and identification statistics," Journal of Econometrics, Elsevier, Elsevier, vol. 139(1), pages 181-216, July.
  3. Jiahui Wang & Eric Zivot, 1998. "Inference on Structural Parameters in Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, Econometric Society, vol. 66(6), pages 1389-1404, November.
  4. James M. Nason & Gregor W. Smith, 2008. "Identifying the new Keynesian Phillips curve," Journal of Applied Econometrics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 23(5), pages 525-551.
  5. Frank Kleibergen & Herman K. van Dijk, 1998. "Bayesian Simultaneous Equations Analysis using Reduced Rank Structures," Tinbergen Institute Discussion Papers 98-025/4, Tinbergen Institute.
  6. Frank Kleibergen & Eric Zivot, 1998. "Bayesian and Classical Approaches to Instrumental Variables Regression," Econometrics, EconWPA 9812002, EconWPA.
  7. Nelson, Charles R & Startz, Richard, 1990. "Some Further Results on the Exact Small Sample Properties of the Instrumental Variable Estimator," Econometrica, Econometric Society, Econometric Society, vol. 58(4), pages 967-76, July.
  8. 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, American Statistical Association, vol. 20(4), pages 518-29, October.
  9. John Shea, 1996. "Instrument Relevance in Multivariate Linear Models: A Simple Measure," NBER Technical Working Papers, National Bureau of Economic Research, Inc 0193, National Bureau of Economic Research, Inc.
  10. Jean-Marie Dufour, 1997. "Some Impossibility Theorems in Econometrics with Applications to Structural and Dynamic Models," Econometrica, Econometric Society, Econometric Society, vol. 65(6), pages 1365-1388, November.
  11. Marcelo J. Moreira & Jack R. Porter & Gustavo A. Suarez, 2004. "Bootstrap and Higher-Order Expansion Validity When Instruments May Be Weak," Harvard Institute of Economic Research Working Papers, Harvard - Institute of Economic Research 2048, Harvard - Institute of Economic Research.
  12. Donald W.K. Andrews & Marcelo J. Moreira & James H. Stock, 2004. "Optimal Invariant Similar Tests for Instrumental Variables Regression," Cowles Foundation Discussion Papers, Cowles Foundation for Research in Economics, Yale University 1476, Cowles Foundation for Research in Economics, Yale University.
  13. Hausman, Jerry & Stock, James H. & Yogo, Motohiro, 2005. "Asymptotic properties of the Hahn-Hausman test for weak-instruments," Economics Letters, Elsevier, Elsevier, vol. 89(3), pages 333-342, December.
  14. Mehmet Caner, 2005. "Exponential Tilting with Weak Instruments: Estimation and Testing," Econometrics, EconWPA 0509017, EconWPA.
  15. Jean-Marie Dufour & Mohamed Taamouti, 2005. "Projection-Based Statistical Inference in Linear Structural Models with Possibly Weak Instruments," Econometrica, Econometric Society, Econometric Society, vol. 73(4), pages 1351-1365, 07.
  16. Dufour, Jean-Marie & Jasiak, Joann, 2001. "Finite Sample Limited Information Inference Methods for Structural Equations and Models with Generated Regressors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 42(3), pages 815-43, August.
  17. Alastair R. Hall & Glenn D. Rudebusch & David W. Wilcox, 1994. "Judging instrument relevance in instrumental variables estimation," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.) 94-3, Board of Governors of the Federal Reserve System (U.S.).
  18. Guggenberger, Patrik & Smith, Richard J., 2005. "Generalized Empirical Likelihood Estimators And Tests Under Partial, Weak, And Strong Identification," Econometric Theory, Cambridge University Press, Cambridge University Press, vol. 21(04), pages 667-709, August.
  19. Frank Kleibergen, 2002. "Pivotal Statistics for Testing Structural Parameters in Instrumental Variables Regression," Econometrica, Econometric Society, Econometric Society, vol. 70(5), pages 1781-1803, September.
  20. Leslie G. Godfrey, 1999. "Instrument Relevance in Multivariate Linear Models," The Review of Economics and Statistics, MIT Press, vol. 81(3), pages 550-552, August.
  21. John C. Chao & Norman Rasmus Swanson, 2004. "Alternative Approximations of the Bias and MSE of the IV Estimator Under Weak Identification with an Application to Bias Correction," Yale School of Management Working Papers, Yale School of Management ysm375, Yale School of Management.
  22. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, Econometric Society, vol. 65(3), pages 557-586, May.
  23. Chao, J. C. & Phillips, P. C. B., 1998. "Posterior distributions in limited information analysis of the simultaneous equations model using the Jeffreys prior," Journal of Econometrics, Elsevier, Elsevier, vol. 87(1), pages 49-86, August.
  24. In Choi & Peter C.B. Phillips, 1989. "Asymptotic and Finite Sample Distribution Theory for IV Estimators and Tests in Partially Identified Structural Equations," Cowles Foundation Discussion Papers, Cowles Foundation for Research in Economics, Yale University 929, Cowles Foundation for Research in Economics, Yale University.
  25. Donald W.K. Andrews & Vadim Marmer, 2005. "Exactly Distribution-free Inference in Instrumental Variables Regression with Possibly Weak Instruments," Cowles Foundation Discussion Papers, Cowles Foundation for Research in Economics, Yale University 1501, Cowles Foundation for Research in Economics, Yale University.
  26. Donald, Stephen G. & Whitney Newey, 1999. "Choosing the Number of Instruments," Working papers, Massachusetts Institute of Technology (MIT), Department of Economics 99-05, Massachusetts Institute of Technology (MIT), Department of Economics.
  27. Kajal Lahiri & Chuanming Gao, 2001. "A Comparison of Some Recent Bayesian and Classical Procedures for Simultaneous Equation Models with Weak Instruments," Discussion Papers, University at Albany, SUNY, Department of Economics 01-15, University at Albany, SUNY, Department of Economics.
  28. Motohiro Yogo, 2004. "Estimating the Elasticity of Intertemporal Substitution When Instruments Are Weak," The Review of Economics and Statistics, MIT Press, vol. 86(3), pages 797-810, August.
  29. Hall, Robert E, 1978. "Stochastic Implications of the Life Cycle-Permanent Income Hypothesis: Theory and Evidence," Journal of Political Economy, University of Chicago Press, University of Chicago Press, vol. 86(6), pages 971-87, December.
  30. Neely, Christopher J & Roy, Amlan & Whiteman, Charles H, 2001. "Risk Aversion versus Intertemporal Substitution: A Case Study of Identification Failure in the Intertemporal Consumption Capital Asset Pricing Model," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 19(4), pages 395-403, October.
  31. Rothenberg, Thomas J., 1984. "Approximating the distributions of econometric estimators and test statistics," Handbook of Econometrics, Elsevier, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 15, pages 881-935 Elsevier.
  32. Maddala, G S & Jeong, Jinook, 1992. "On the Exact Small Sample Distribution of the Instrumental Variable Estimator," Econometrica, Econometric Society, Econometric Society, vol. 60(1), pages 181-83, January.
  33. Moreira, Marcelo J., 2009. "Tests with correct size when instruments can be arbitrarily weak," Journal of Econometrics, Elsevier, Elsevier, vol. 152(2), pages 131-140, October.
  34. Hall, Peter, 1984. "Central limit theorem for integrated square error of multivariate nonparametric density estimators," Journal of Multivariate Analysis, Elsevier, Elsevier, vol. 14(1), pages 1-16, February.
  35. Zellner, Arnold, 1998. "The finite sample properties of simultaneous equations' estimates and estimators Bayesian and non-Bayesian approaches," Journal of Econometrics, Elsevier, Elsevier, vol. 83(1-2), pages 185-212.
  36. Marcelo J. Moreira, 2003. "A Conditional Likelihood Ratio Test for Structural Models," Econometrica, Econometric Society, Econometric Society, vol. 71(4), pages 1027-1048, 07.
  37. 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.
  38. Hahn, Jinyong, 2002. "Optimal Inference With Many Instruments," Econometric Theory, Cambridge University Press, Cambridge University Press, vol. 18(01), pages 140-168, February.
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 in new window

Cited by:
This item has more than 25 citations. To prevent cluttering this page, these citations are listed on a separate page.

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:nbr:nberte:0313. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ().

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

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