Enhancing GDP nowcasts with ChatGPT: a novel application of PMI news releases

Yiqiao Sun and Gabe de Bondt

No 3063, Working Paper Series from European Central Bank

Abstract: This study involves tasking ChatGPT with classifying an “activity sentiment score” based on PMI news releases. It explores the predictive power of this score for euro area GDP nowcasting. We find that the PMI text scores enhance GDP nowcasts beyond what is embedded in ECB/Eurosystem Staff projections and Eurostat’s first GDP estimate. The ChatGPT-derived activity score retains its significance in regressions that also include the composite output PMI diffusion index. GDP nowcasts are significantly enhanced with PMI text scores even when accounting for methodological variations, excluding extraordinary economic events like the pandemic, and for different GDP growth quantiles. However, the forecast gains from the enhancement of GDP nowcasts with ChatGPT scores are time dependent, varying by calendar years. Sizeable forecast gains of on average about 20% were obtained apart from the two most recent years due to exceptionally low forecast errors of the two benchmarks, especially the first GDP estimate. JEL Classification: C8, E32, C22

Keywords: chat generative pre-training transformer; nowcasting GDP; purchasing managers’ index (PMI); text analysis; zero-shot sentiment analysis (search for similar items in EconPapers)
Date: 2025-06
New Economics Papers: this item is included in nep-eec
Note: 2759141
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Persistent link: https://EconPapers.repec.org/RePEc:ecb:ecbwps:20253063

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