Economists have long sought to develop quantitative models of economic behaviour, which blend economic theory with data evidence. Econometric modelling of economic time series has strived to achieve this by seeking to discover sustainable and interpretable relationships. This important two-volume collection focuses on a central method used in selecting such models, namely simplification of an initially general model that adequately characterizes the empirical evidence within the investigators' theoretical framework.
The volumes feature a wealth of evidence that has accrued over the last five years displaying its excellent abilities for model selection, based on Monte Carlo studies of automatic algorithms. These also throw light on several major methodological issues, and prompt many new ideas, which are discussed.
The collection will be valuable to all empirical economists and econometricians.
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Edited by Julia Campos, Professor of Econometrics, Universidad de Salamanca, Spain, Neil R. Ericsson, Federal Reserve Board, US and David F. Hendry, Professor of Economics, Fellow, Nuffield College and Chairman, Economics Department, University of Oxford, UK
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