Assessing the magnitude of the concentration parameter in a simultaneous equations model
AbstractThis paper provides the practitioner with a method of ascertaining when the concentration parameter in a simultaneous equations model is small. We provide some exact distribution theory for a proposed statistic and show that the statistic possesses the minimal desirable characteristics of a test statistic when used to test that the concentration parameter is zero. The discussion is then extended to consider how to test for weak instruments using this statistic as a basis for inference. We also discuss the statistic's relationship to various other procedures that have appeared in the literature. Copyright The Author(s). Journal compilation Royal Economic Society 2009
Download InfoIf 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.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Royal Economic Society in its journal Econometrics Journal.
Volume (Year): 12 (2009)
Issue (Month): 1 (03)
Contact details of provider:
Postal: Office of the Secretary-General, School of Economics and Finance, University of St. Andrews, St. Andrews, Fife, KY16 9AL, UK
Phone: +44 1334 462479
Web page: http://www.res.org.uk/
More information through EDIRC
Other versions of this item:
- D. S. Poskitt & C. L. Skeels, 2004. "Assessing the Magnitude of the Concentration Parameter in a Simultaneous Equations Model," Monash Econometrics and Business Statistics Working Papers 29/04, Monash University, Department of Econometrics and Business Statistics.
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C39 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Other
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
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.:
- Phillips, P.C.B., 1983.
"Exact small sample theory in the simultaneous equations model,"
Handbook of Econometrics,
in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 1, chapter 8, pages 449-516
- Peter C.B. Phillips, 1982. "Exact Small Sample Theory in the Simultaneous Equations Model," Cowles Foundation Discussion Papers 621, Cowles Foundation for Research in Economics, Yale University.
- Phillips, P C B, 1980. "The Exact Distribution of Instrumental Variable Estimators in an Equation Containing n + 1 Endogenous Variables," Econometrica, Econometric Society, vol. 48(4), pages 861-78, May.
- Alastair R. Hall & Glenn D. Rudebusch & David W. Wilcox, 1994.
"Judging instrument relevance in instrumental variables estimation,"
Finance and Economics Discussion Series
94-3, Board of Governors of the Federal Reserve System (U.S.).
- Hall, Alastair R & Rudebusch, Glenn D & Wilcox, David W, 1996. "Judging Instrument Relevance in Instrumental Variables Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 37(2), pages 283-98, May.
- Cragg, John G. & Donald, Stephen G., 1993. "Testing Identifiability and Specification in Instrumental Variable Models," Econometric Theory, Cambridge University Press, vol. 9(02), pages 222-240, April.
- John Shea, 1996.
"Instrument Relevance in Multivariate Linear Models: A Simple Measure,"
NBER Technical Working Papers
0193, National Bureau of Economic Research, Inc.
- John Shea, 1997. "Instrument Relevance in Multivariate Linear Models: A Simple Measure," The Review of Economics and Statistics, MIT Press, vol. 79(2), pages 348-352, May.
- Mariano, Roberto S, 1982. "Analytical Small-Sample Distribution Theory in Econometrics: The Simultaneous-Equations Case," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 23(3), pages 503-33, October.
- 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 518-29, October.
- 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.
- Doko Tchatoka, Firmin, 2010.
"Subset hypotheses testing and instrument exclusion in the linear IV regression,"
29611, University Library of Munich, Germany, revised 02 Feb 2012.
- Firmin Doko Tchatoka, 2011. "Subset hypotheses testing and instrument exclusion in the linear IV regression," Working Papers 10668, University of Tasmania, School of Economics and Finance.
- Pham, Vivienne & Prentice, David, 2010.
"An empirical analysis of the counterfactual: a merger and divestiture in the Australian cigarette industry,"
26713, University Library of Munich, Germany.
- Vivienne Pham & David Prentice, 2010. "An empirical Analysis of the Counter-factual: A Merger and Divestiture in the Australian Cigarette Industry," Working Papers 2010.08, School of Economics, La Trobe University.
- Poskitt, D.S. & Skeels, C.L., 2007. "Approximating the distribution of the two-stage least squares estimator when the concentration parameter is small," Journal of Econometrics, Elsevier, vol. 139(1), pages 217-236, July.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing) or (Christopher F. Baum).
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.