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Econometrics 2017, 5(3), 39; doi:10.3390/econometrics5030039

Evaluating Forecasts, Narratives and Policy Using a Test of Invariance

1
Magdalen College and Institute for New Economic Thinking, Oxford Martin School, University of Oxford, OX1 4AU Oxford, UK
2
Department of Economics, and Institute for New Economic Thinking, Oxford Martin School, University of Oxford, OX1 3UQ Oxford, UK
*
Author to whom correspondence should be addressed.
Academic Editors: Rocco Mosconi and Paolo Paruolo
Received: 17 December 2016 / Revised: 14 August 2017 / Accepted: 23 August 2017 / Published: 1 September 2017
(This article belongs to the Special Issue Celebrated Econometricians: Katarina Juselius and Søren Johansen)
View Full-Text   |   Download PDF [511 KB, uploaded 1 September 2017]   |  

Abstract

Economic policy agencies produce forecasts with accompanying narratives, and base policy changes on the resulting anticipated developments in the target variables. Systematic forecast failure, defined as large, persistent deviations of the outturns from the numerical forecasts, can make the associated narrative false, which would in turn question the validity of the entailed policy implementation. We establish when systematic forecast failure entails failure of the accompanying narrative, which we call forediction failure, and when that in turn implies policy invalidity. Most policy regime changes involve location shifts, which can induce forediction failure unless the policy variable is super exogenous in the policy model. We propose a step-indicator saturation test to check in advance for invariance to policy changes. Systematic forecast failure, or a lack of invariance, previously justified by narratives reveals such stories to be economic fiction. View Full-Text
Keywords: forediction; invariance; super exogeneity; indicator saturation; co-breaking; Autometrics forediction; invariance; super exogeneity; indicator saturation; co-breaking; Autometrics
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Castle, J.L.; Hendry, D.F.; Martinez, A.B. Evaluating Forecasts, Narratives and Policy Using a Test of Invariance. Econometrics 2017, 5, 39.

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