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ChatMacro: Evaluating Inflation Forecasts of Generative AI

Author

Listed:
  • M.Jahangir Alam

  • Shane Boyle

  • Huiyu Li
  • Tatevik Sekhposyan

Abstract

Recent research suggests that generic large language models (LLMs) can match the accuracy of traditional methods when forecasting macroeconomic variables in pseudo out-of-sample settings generated via prompts. This paper assesses the out-of-sample forecasting accuracy of LLMs by eliciting real-time forecasts of U.S. inflation from ChatGPT. We find that out-of-sample predictions are largely inaccurate and stale, even though forecasts generated in pseudo out-of-sample environments are comparable to existing benchmarks. Our results underscore the importance of out-of-sample benchmarking for LLM predictions.

Suggested Citation

  • M.Jahangir Alam & Shane Boyle & Huiyu Li & Tatevik Sekhposyan, 2026. "ChatMacro: Evaluating Inflation Forecasts of Generative AI," Working Paper Series 2026-04, Federal Reserve Bank of San Francisco.
    • Handle: RePEc:fip:fedfwp:102407
    DOI: 10.24148/wp2026-04
    Note: PDF date: January 27, 2006.
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    References listed on IDEAS

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    1. Zarifhonarvar, Ali, 2026. "Generating inflation expectations with large language models," Journal of Monetary Economics, Elsevier, vol. 157(C).
    2. Leland D. Crane & Akhil Karra & Paul E. Soto, 2025. "Total Recall? Evaluating the Macroeconomic Knowledge of Large Language Models," Finance and Economics Discussion Series 2025-044, Board of Governors of the Federal Reserve System (U.S.).
    3. Songrun He & Linying Lv & Asaf Manela & Jimmy Wu, 2025. "Chronologically Consistent Large Language Models," Papers 2502.21206, arXiv.org, revised Jul 2025.
    4. Croushore, Dean, 2006. "Forecasting with Real-Time Macroeconomic Data," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 17, pages 961-982, Elsevier.
    5. Sophia Kazinnik & Tara M. Sinclair, 2025. "FOMC In Silico: A Multi-Agent System for Monetary Policy Decision Modeling," Working Papers 2025-005, The George Washington University, The Center for Economic Research.
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    Cited by:

    1. Dalibor Stevanovic, 2026. "Who Saw It Coming? Historical Experience and the 2021 Inflation Forecast Failure," Papers 2604.14467, arXiv.org.

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    Keywords

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    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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