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VOL. 52 | 2006 Cowles commission structural equation approach in light of nonstationary time series analysis


We review the advancement of nonstationary time series analysis from the perspective of Cowles Commission structural equation approach. We argue that despite the rich repertoire nonstationary time series analysis provides to analyze how do variables respond dynamically to shocks through the decomposition of a dynamic system into long-run and short-run relations, nonstationarity does not invalid the classical concerns of structural equation modeling — identification and simultaneity bias. The same rank condition for identification holds for stationary and nonstationary data and some sort of instrumental variable estimators will have to be employed to yield consistency. However, nonstationarity does raise issues of inference if the rank of cointegration or direction of nonstationarity is not known a priori. The usual test statistics may not be chi-square distributed because of the presence of unit roots distributions. Classical instrumental variable estimators have to be modified to ensure valid inference.


Published: 1 January 2006
First available in Project Euclid: 28 November 2007

zbMATH: 1268.62114
MathSciNet: MR2427847

Digital Object Identifier: 10.1214/074921706000001030

Rights: Copyright © 2006, Institute of Mathematical Statistics


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