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The First Stage in HendryÕs Reduction Theory Revisited

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Author Info
Genaro, SUCARRAT (UNIVERSITE CATHOLIQUE DE LOUVAIN, Department of Economics)
Abstract

The reduction theory of David F. Hendry provides a comprehensive probabilistic framework for the analysis and classification of the reductions associated with empirical econometric models. However, it is unable to provide an analysis on the same underlying probability space of the first reduction - and hence the subsequent reductions - given a commonplace theory of social reality, namely the joint hypotheses that the course of history is indeterministic, that history does not repeat itsself, and that the future depends on the past. As a solution this essay proposes that the elements of the underlying outcome space in HendryÕs theory are interpreted as indeterministic worlds made up of historically inherited particulars.

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Paper provided by Université catholique de Louvain, Département des Sciences Economiques in its series Discussion Papers (ECON - Département des Sciences Economiques) with number 2006041.

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Length: 26
Date of creation: 15 Sep 2006
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Handle: RePEc:ctl:louvec:2006041

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Related research
Keywords: Theory of recution; DGP; Possible worlds; Measurement error; Probabilistic causality;

Find related papers by JEL classification:
B40 - Schools of Economic Thought and Methodology - - Economic Methodology - - - General
C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Engle, Robert F & Kozicki, Sharon, 1993. "Testing for Common Features," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(4), pages 369-80, October.
    Other versions:
  2. Hendry, David F. & Massmann, Michael, 2007. "Co-Breaking: Recent Advances and a Synopsis of the Literature," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 33-51, January. [Downloadable!] (restricted)
  3. Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Volatility Forecasting," NBER Working Papers 11188, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    Other versions:
  4. Geweke, John, 1984. "Inference and causality in economic time series models," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 19, pages 1101-1144 Elsevier. [Downloadable!] (restricted)
  5. Bauwens, Luc & Peter Boswijk, H. & Urbain, Jean-Pierre, 2006. "Causality and exogeneity in econometrics," Journal of Econometrics, Elsevier, vol. 132(2), pages 305-309, June. [Downloadable!] (restricted)
  6. Robert F. Engle & Jose Gonzalo Rangel, 2005. "The Spline GARCH Model for Unconditional Volatility and its Global Macroeconomic Causes," Working Papers 2005/13, Czech National Bank, Research Department. [Downloadable!]
  7. Engle, Robert F & Kozicki, Sharon, 1993. "Testing for Common Features: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(4), pages 393-95, October.
  8. Andersen, Torben G. & Bollerslev, Tim & Lange, Steve, 1999. "Forecasting financial market volatility: Sample frequency vis-a-vis forecast horizon," Journal of Empirical Finance, Elsevier, vol. 6(5), pages 457-477, December. [Downloadable!] (restricted)
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