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Detecting and testing causality in linear econometric models

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Summary

The ultimate objective of this paper is to arrive at an operational testing procedure enabling us to diagnose the causal or non-causal nature of an econometric relationship in a linear framework. The profferred approach to the problem relies on a close examination of causal issues in simultaneous equation models and on a sensible definition of the bidirectionality concept inherently associated with feedback mechanisms.

After recalling the essentials of causal structure's algebra, the article:

  1. i)

    provides a closed-form expression, in terms of a Hadamard product of forward and backward (i.e., feedback) effects, for two-way connections among the variables of a linear equation;

  2. ii)

    sets the issue of verifying a causality conjecture regarding a model's relationship in the context of significance test theory;

  3. iii)

    builds up, in a constrained maximum-likelihood setting, an effective causality test of the Lagrange-multipler (scoring) class.

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Additional information

Invited paper at the Conference held in Bologna, Italy, 27–28 May 1993, on «Statistical Tests: Methodology and Econometric Applications».

Support from the Italian Research Council (CNR) is gratefully acknowledged. The paper is the result of a joint research of M. Faliva and M. G. Zoia. The two authors share the responsability for Section 3; Sections 1 and 2 are due to M. Faliva and Section 4 is due to M. G. Zoia.

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Faliva, M., Zoia, M.G. Detecting and testing causality in linear econometric models. J. It. Statist. Soc. 3, 61–76 (1994). https://doi.org/10.1007/BF02589041

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  • DOI: https://doi.org/10.1007/BF02589041

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