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Model Identification and Non-unique Structure

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Abstract

Identification is an essential attribute of any model's parameters, so we consider its three aspects of 'uniqueness', 'correspondence to reality' and 'interpretability'. Observationally-equivalent over-identified models can co-exist, and are mutually encompassing in the population; correctly-identified models need not correspond to the underlying structure; and may be wrongly interpreted. That a given model is over-identified with all over-identifying restrictions valid (even asymptotically) is insufficient to demonstrate that it is a unique representation. Moreover, structre (as invariance under extended information) need not be identifiable. We consider the role of structural breaks to discriminate between such representations.

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  • David Hendry & Maozu Lu & Grayham E. Mizon, 2001. "Model Identification and Non-unique Structure," Economics Papers 2002-W10, Economics Group, Nuffield College, University of Oxford.
    • Handle: RePEc:nuf:econwp:0210
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    Cited by:

    1. Matteo Richiardi, 2003. "The Promises and Perils of Agent-Based Computational Economics," LABORatorio R. Revelli Working Papers Series 29, LABORatorio R. Revelli, Centre for Employment Studies.
    2. Mark P. Taylor, 2004. "Estimating structural macroeconomic shocks through long-run recursive restrictions on vector autoregressive models: the problem of identification," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 9(3), pages 229-244.

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