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Econometrics: Alchemy or Science?Essays in Econometric Methodology$
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David F. Hendry

Print publication date: 2000

Print ISBN-13: 9780198293545

Published to Oxford Scholarship Online: November 2003

DOI: 10.1093/0198293542.001.0001

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Exogeneity

Exogeneity

Chapter:
(p.330) 15 Exogeneity
Source:
Econometrics: Alchemy or Science?
Author(s):

David F. Hendry (Contributor Webpage)

Robert F. Engle

Jean‐François Richard

Publisher:
Oxford University Press
DOI:10.1093/0198293542.003.0016

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

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