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Reformulating empirical macro-econometric modelling

  • Hendry, David F.
  • Mizon, Grayham E.

The policy implications of estimated macro-econometric systems depend on the formulations of their equations, the methodology of empirical model selection and evaluation, the techniques of policy analysis, and their forecast performance. Drawing on recent results in the theory of forecasting, we question the role of `rational expectations'; criticize a common approach to testing economic theories; show that impulse-response methods of evaluating policy are seriously flawed; and question the mechanistic derivation of forecasts from econometric systems. In their place, we propose that expectations should be treated as instrumental to agents' decisions; discuss a powerful new approach to the empirical modelling of econometric relationships; offer viable alternatives to studying policy implications; and note modifications to forecasting devices that can enhance their robustness to unanticipated structural breaks. Keywords; economic policy analysis, macro-econometric systems, empirical model selection and evaluation, forecasting, rational expectations, impulse-response analysis, structural breaks

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Paper provided by Economics Division, School of Social Sciences, University of Southampton in its series Discussion Paper Series In Economics And Econometrics with number 0104.

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Date of creation: 01 Jan 2001
Date of revision:
Handle: RePEc:stn:sotoec:0104
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  4. Hendry, David F. & Richard, Jean-Francois, 1982. "On the formulation of empirical models in dynamic econometrics," Journal of Econometrics, Elsevier, vol. 20(1), pages 3-33, October.
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  10. Hendry, David F, 1994. "HUS Revisited," Oxford Review of Economic Policy, Oxford University Press, vol. 10(2), pages 86-106, Summer.
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  13. Hendry, David F & Doornik, Jurgen A, 1997. "The Implications for Econometric Modelling of Forecast Failure," Scottish Journal of Political Economy, Scottish Economic Society, vol. 44(4), pages 437-61, September.
  14. Hendry, David F., 1995. "Dynamic Econometrics," OUP Catalogue, Oxford University Press, number 9780198283164.
  15. Sims, Christopher A & Stock, James H & Watson, Mark W, 1990. "Inference in Linear Time Series Models with Some Unit Roots," Econometrica, Econometric Society, vol. 58(1), pages 113-44, January.
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  18. Hendry, David F, 1995. "Econometrics and Business Cycle Empirics," Economic Journal, Royal Economic Society, vol. 105(433), pages 1622-36, November.
  19. Preston J. Miller, 1978. "Forecasting with econometric methods: a comment," Working Papers 104, Federal Reserve Bank of Minneapolis.
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  22. Kevin D. Hoover & Stephen J. Perez, 2004. "Truth and Robustness in Cross-country Growth Regressions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(5), pages 765-798, December.
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  25. Hans-Martin Krolzig, 2001. "General--to--Specific Reductions of Vector Autoregressive Processes," Computing in Economics and Finance 2001 164, Society for Computational Economics.
  26. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
  27. Grayham E. Mizon & David F. Hendry, 1998. "Exogeneity, causality, and co-breaking in economic policy analysis of a small econometric model of money in the UK," Empirical Economics, Springer, vol. 23(3), pages 267-294.
  28. Runkle, David E, 1987. "Vector Autoregressions and Reality: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(4), pages 454, October.
  29. Davidson, James E H, et al, 1978. "Econometric Modelling of the Aggregate Time-Series Relationship between Consumers' Expenditure and Income in the United Kingdom," Economic Journal, Royal Economic Society, vol. 88(352), pages 661-92, December.
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  31. Muellbauer, John, 1994. "The Assessment: Consumer Expenditure," Oxford Review of Economic Policy, Oxford University Press, vol. 10(2), pages 1-41, Summer.
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