David F. Hendry, Robert F. Engle and Jean‐François Richard

in Econometrics: Alchemy or Science?

Published in print October 2000 | ISBN: 9780198293545
Published online November 2003 | e-ISBN: 9780191596391 | DOI:

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Exogenous variables play a crucial role in econometrics, yet ‘exogeneity’ is often imprecise. Exogenous connotes ‘being determined outside of (the model under analysis)’, so it cannot be a property of variables per se. Rather, exogeneity is a step in model reduction, concerning when inferences about parameters of interest based on a complete analysis of the joint density function of all the observable variables coincide with inferences based on only the conditional density of one sub‐set of variables given another sub‐set. If there is no loss of information from only analysing the conditional sub‐model, then the conditioning variables are weakly exogenous for its parameters of interest, and the marginal process is irrelevant. To forecast conditionally more than one period ahead also requires Granger non‐causality, leading to the concept of strong exogeneity. To justify conditional policy analyses, which change the marginal model, parameter invariance is required in the conditional model, leading to super exogeneity.

Keywords: conditional model; Granger non‐causality; marginal process; model reduction; parameter invariance; parameters of interest; strong exogeneity; super exogeneity; weak exogeneity

Chapter.  15458 words. 

Subjects: Econometrics and Mathematical Economics

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