Assessing the Early Warning Capabilities of GaR: A Probabilistic Approach to Recession Detection in CEE Economies

Gheorghe-Alexandru Tarta

Prague Economic Papers, 2025, vol. 2025, issue 3, 304-346

Abstract: This paper introduces a novel application of Growth-at-Risk (GaR) as an early warning system (EWS) for predicting recessions. By transforming GaR into a classification model, we assess its ability to signal economic downturns across 11 Central and Eastern European (CEE) economies from 2005 to 2024. We compare GaR's performance with logistic regression across eight forecasting horizons. Our findings indicate that GaR slightly outperforms the logit model when financial conditions are used as the primary predictor. However, when additional factors such as agents' expectations and financial flows are incorporated, the performance gap narrows. Our results suggest that Growth-at-Risk can function as an effective early warning system without significant performance trade-offs, while offering a flexible and theoretically grounded alternative. Policymakers can leverage Growth-at-Risk not only as a tail risk instrument but also as a classifier, enhancing their forecasting capabilities.

Keywords: Growth-at-Risk; early warning systems; financial conditions; recession probability (search for similar items in EconPapers)
JEL-codes: C18 E44 G01 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.18267/j.pep.897

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