Friday, July 19, 2013

Econometrics: Alchemy or Science?: Essays in Econometric Methodology

Econometrics: Alchemy or Science?: Essays in Econometric Methodology

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Product Description

"Econometrics: Alchemy or Science?" analyses the effectiveness and validity of applying econometric methods to economic time series. The methodological dispute is long-standing, and no claim can be made for a single valid method, but recent results on the theory and practice of model selection bid fair to resolve many of the contentious issues.

The book presents criticisms and evaluations of competing approaches, based on theoretical economic and econometric analyses, empirical applications, and Monte Carlo simulations, which interact to determine best practice. It explains the evolution of an approach to econometric modelling founded in careful statistical analyses of the available data, using economic theory to guide the general model specification. From a strong foundation in the theory of reduction, via a range of applied and
simulation studies, it demonstrates that general-to-specific procedures have excellent properties.

The book is divided into four Parts: Routes and Route Maps; Empirical Modelling Strategies; Formalization; and Retrospect and Prospect. A short preamble to each chapter sketches the salient themes, links to earlier and later developments, and the lessons learnt or missed at the time. A sequence of detailed empirical studies of consumers' expenditure and money demand illustrate most facets of the approach. Material new to this revised edition describes recent major advances in computer-automated
model selection, embodied in the powerful new software program PcGets, which establish the operational success of the modelling strategy.

Econometrics: Alchemy or Science?: Essays in Econometric Methodology Review

An outstanding collection of papers by Oxford University Professor David Hendry.

Taken collectively, the body of work presents a tremendous contribution to econometric modelling.

Relevant for both practitioners and academics alike. Also a great read for current graduate students of time series econometrics.

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