Optimizing Policymakers' Loss Functions in Crisis Prediction: Before, Within or After?

Peter Sarlin and Gregor von Schweinitz

No 6/2015, IWH Discussion Papers from Halle Institute for Economic Research (IWH)

Abstract: Early-warning models most commonly optimize signaling thresholds on crisis probabilities. The ex-post threshold optimization is based upon a loss function accounting for preferences between forecast errors, but comes with two crucial drawbacks: unstable thresholds in recursive estimations and an in-sample overfit at the expense of out-ofsample performance. We propose two alternatives for threshold setting: (i) including preferences in the estimation itself and (ii) setting thresholds ex-ante according to preferences only. We provide simulated and real-world evidence that this simplification results in stable thresholds and improves out-of-sample performance. Our solution is not restricted to binary-choice models, but directly transferable to the signaling approach and all probabilistic early-warning models.

Keywords: early-warning models; loss functions; threshold setting; predictive performance (search for similar items in EconPapers)
JEL-codes: C35 C53 G01 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Related works:
Journal Article: OPTIMIZING POLICYMAKERS’ LOSS FUNCTIONS IN CRISIS PREDICTION: BEFORE, WITHIN OR AFTER? (2021)
Working Paper: Optimizing policymakers' loss functions in crisis prediction: before, within or after? (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:iwhdps:iwh-6-15

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