Identification Of Covariance Structures
AbstractThe issue of identification of covariance structures, which arises in a number of different contexts, has been so far linked to conditions on the true parameters to be estimated. In this paper, this limitation is removed.As done by Johansen (1995, Journal of Econometrics 69, 112 132) in the context of linear models, the present paper provides necessary and sufficient conditions for the identification of a covariance structure that depends only on the constraints and can therefore be checked independently of estimated parameters.A structure condition is developed, which only depends on the structure of the constraints. It is shown that this condition, if coupled with the familiar order condition, provides a sufficient condition for identification. In practice, because the structure condition holds if and only if a certain matrix, constructed from the constraint matrices, is invertible, automatic software checking for identification is feasible even for large-scale systems.Most of the paper focuses on structural vector autoregressions, but extensions to other statistical models are also briefly discussed.I thank all the participants at the meeting held in Pavia on June 11, 2004, in honor of Carlo Giannini for their comments; it goes without saying that Carlo himself provided not only acute observations on the day but also the main inspiration for this piece of work. Sadly, Carlo passed away on September 11, 2004, and this paper is dedicated to his memory. P r sterholm spotted several mistakes in an earlier version and helped me clarify some implementation details. Thanks are also due to Gianni Amisano, Bruce Hansen, Giulio Palomba, Paolo Paruolo, and two anonymous referees. The usual disclaimer obviously applies.
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.
Bibliographic InfoArticle provided by Cambridge University Press in its journal Econometric Theory.
Volume (Year): 22 (2006)
Issue (Month): 02 (April)
Contact details of provider:
Postal: The Edinburgh Building, Shaftesbury Road, Cambridge CB2 2RU UK
Fax: +44 (0)1223 325150
Web page: http://journals.cambridge.org/jid_ECTProvider-Email:firstname.lastname@example.org
Other versions of this item:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
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.:
- Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
- Johansen, Soren, 1995. "Identifying restrictions of linear equations with applications to simultaneous equations and cointegration," Journal of Econometrics, Elsevier, vol. 69(1), pages 111-132, September.
- Renato BALDUCCI, 2005. "Public Expenditure and Economic Growth. A critical extension of Barro's (1990) model," Working Papers 240, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
- Stefania BUSSOLETTI & Roberto ESPOSTI, 2004. "Regional Convergence, Structural Funds and the Role of Agricolture in the EU. A Panel-Data Approach," Working Papers 220, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
- Par Osterholm, 2008. "A structural Bayesian VAR for model-based fan charts," Applied Economics, Taylor and Francis Journals, vol. 40(12), pages 1557-1569.
- PÃ¤r Ã–sterholm & Lisandro Abrego, 2008.
"External Linkages and Economic Growth in Colombia: Insights from A Bayesian VAR Model,"
IMF Working Papers
08/46, International Monetary Fund.
- Lisandro Abrego & Pär Österholm, 2010. "External Linkages and Economic Growth in Colombia: Insights from a Bayesian VAR Model," The World Economy, Wiley Blackwell, vol. 33(12), pages 1788-1810, December.
- Meredith Beechey & P�R �Sterholm, 2008. "A Bayesian Vector Autoregressive Model with Informative Steady-state Priors for the Australian Economy," The Economic Record, The Economic Society of Australia, vol. 84(267), pages 449-465, December.
- Caporin Massimiliano & Paruolo Paolo, 2005. "Spatial effects in multivariate ARCH," Economics and Quantitative Methods qf0501, Department of Economics, University of Insubria.
- Roberto ESPOSTI & Pierpaolo PIERANI, 2005. "Price, Private Demand and Optimal Provision of Public R&D in Italian Agriculture," Working Papers 238, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
- Roberto ESPOSTI, 2007. "On the Decline of Agriculture. Evidence from Italian Regions in the Post-WWII Period," Working Papers 300, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Duncan Rule).
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.