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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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Serial Correlation as a Convenient Simplification, not a Nuisance: A Comment on a Study of the Demand for Money by the Bank of England

Serial Correlation as a Convenient Simplification, not a Nuisance: A Comment on a Study of the Demand for Money by the Bank of England

Chapter:
(p.129) 6 Serial Correlation as a Convenient Simplification, not a Nuisance: A Comment on a Study of the Demand for Money by the Bank of England
Source:
Econometrics: Alchemy or Science?
Author(s):

David F. Hendry (Contributor Webpage)

Grayham E. Mizon

Publisher:
Oxford University Press
DOI:10.1093/0198293542.003.0007

Sargan's COMFAC procedure for single equations (common factors in lag polynomials) is exposited. Four important conceptual clarifications arise. First, residual autocorrelation does not entail error autoregression. Secondly, autoregressive errors are common factor dynamics. Thirdly, discriminating between systematic dynamics and error dynamics can only be done in the context of a general‐to‐simple strategy, with autocorrelated errors potentially reducing the parameterization. Fourthly, differencing imposes common factors of unity. The empirical performance of COMFAC was illustrated for modelling broad money demand, and for integrating economic analysis with statistical modelling; long‐run money demand theory guided the empirical estimates of the equilibrium‐correction model.

Keywords:   autoregressive errors, broad money demand, COMFAC, differencing, equilibrium‐correction model, error dynamics, general‐to‐simple, residual autocorrelation, systematic dynamics

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