On the Formulation of Empirical Models in Dynamic Econometrics

David F. Hendry and Jean‐François Richard

in Econometrics: Alchemy or Science?

Published in print October 2000 | ISBN: 9780198293545
Published online November 2003 | e-ISBN: 9780191596391 | DOI:
 On the Formulation of Empirical Models in Dynamic Econometrics

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Investigates the constructs of innovation errors, invariance, encompassing, and data admissibility, relates these to exogeneity and progressive research strategies, and introduces the notion of designing models to satisfy certain criteria to extend the manual of ‘good empirical practice’ through delineating more rigorous quality‐control procedures. Empirical models derive from the data generation process by reduction operations (such as marginalizing and conditioning), which induce transformed parameters and corresponding disturbance terms, which together determine the quality of an empirical model. A taxonomy of information sets exhaustively partitions available data into the six disjoint sets of the (relative) past, present, and future of the investigators own data, theory and measurement information, and evidence from rival models. Specific concepts correspond to each of the six elements in that partition, namely, innovation processes, exogeneity, invariance, theory consistency, data admissibility, and encompassing, These characterize the primary null hypotheses against which tests of different alternatives are conducted. Dynamic simulation is shown to be an inadequate model evaluation criterion.

Keywords: data admissibility; dynamic simulation; encompassing; innovation errors; invariance; model design; progressive research strategy; taxonomy of information; theory consistency; weak exogeneity

Chapter.  15743 words.  Illustrated.

Subjects: Econometrics and Mathematical Economics

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