Evaluating Forecasts, Narratives and Policy Using a Test of Invariance
AbstractEconomic 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
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Castle, J.L.; Hendry, D.F.; Martinez, A.B. Evaluating Forecasts, Narratives and Policy Using a Test of Invariance. Econometrics 2017, 5, 39.
Castle JL, Hendry DF, Martinez AB. Evaluating Forecasts, Narratives and Policy Using a Test of Invariance. Econometrics. 2017; 5(3):39.Chicago/Turabian Style
Castle, Jennifer L.; Hendry, David F.; Martinez, Andrew B. 2017. "Evaluating Forecasts, Narratives and Policy Using a Test of Invariance." Econometrics 5, no. 3: 39.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.