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Identification And Dichotomization Of Long- And Short-Run Relations Of Cointegrated Vector Autoregressive Models

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  • Hsiao, Cheng

Abstract

We show that the usual rank condition is necessary and sufficient to identify a vector autoregressive process whether the variables are I(0) or I(d) for d = 1,2,.... We then use this rank condition to demonstrate the interdependence between the identification of short-run and long-run relations of cointegrated process. We find that both the short-run and long-run relations can be identified without the existence of prior information to identify either relation. But if there exists a set of prior restrictions to identify the short-run relation, then this same set of restrictions is sufficient to identify the corresponding long-run relation. On the other hand, it is in general not possible to identify the long-run relations without information on the complete structure. The relationship between the identification of a vector autoregressive process and a Cowles Commission dynamic simultaneous equations model is also clarified.

Suggested Citation

  • Hsiao, Cheng, 2001. "Identification And Dichotomization Of Long- And Short-Run Relations Of Cointegrated Vector Autoregressive Models," Econometric Theory, Cambridge University Press, vol. 17(5), pages 889-912, October.
    • Handle: RePEc:cup:etheor:v:17:y:2001:i:05:p:889-912_17
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    Cited by:

    1. Juan F. Rubio-Ramírez & Daniel F. Waggoner & Tao Zha, 2010. "Structural Vector Autoregressions: Theory of Identification and Algorithms for Inference," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 77(2), pages 665-696.
    2. Lightwood, James & Glantz, Stanton, 2011. "Effect of the Arizona tobacco control program on cigarette consumption and healthcare expenditures," Social Science & Medicine, Elsevier, vol. 72(2), pages 166-172, January.
    3. Hsiao, Cheng & Wang, Siyan, 2006. "Modified two-stage least-squares estimators for the estimation of a structural vector autoregressive integrated process," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 427-463.
    4. Rangarajan, C. & Srivastava, D.K., 2005. "Fiscal deficits and government debt in India: Implications for growth and stabilisation," Working Papers 05/35, National Institute of Public Finance and Policy.
    5. repec:wyi:journl:002065 is not listed on IDEAS

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