ChatMacro: Evaluating Inflation Forecasts of Generative AI
Author
Abstract
Suggested Citation
DOI: 10.24148/wp2026-04
Note: PDF date: January 27, 2006.
Download full text from publisher
References listed on IDEAS
- Zarifhonarvar, Ali, 2026. "Generating inflation expectations with large language models," Journal of Monetary Economics, Elsevier, vol. 157(C).
- 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.).
- 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.
- Songrun He & Linying Lv & Asaf Manela & Jimmy Wu, 2025. "Chronologically Consistent Large Language Models," Papers 2502.21206, arXiv.org, revised Jul 2025.
- 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.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Alexander Eliseev & Sergei Seleznev, 2026. "Fake Date Tests: Can We Trust In-sample Accuracy of LLMs in Macroeconomic Forecasting?," Papers 2601.07992, arXiv.org, revised Mar 2026.
- Alexander Eliseev & Sergei Seleznev, 2026. "Fake Date Tests: Can We Trust In-sample Accuracy of LLMs in Macroeconomic Forecasting?," Bank of Russia Working Paper Series wps167, Bank of Russia.
- Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015.
"Realtime nowcasting with a Bayesian mixed frequency model with stochastic volatility,"
Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(4), pages 837-862, October.
- Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2012. "Real-time nowcasting with a Bayesian mixed frequency model with stochastic volatility," Working Papers (Old Series) 1227, Federal Reserve Bank of Cleveland.
- Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2013. "Real-Time Nowcasting with a Bayesian Mixed Frequency Model with Stochastic Volatility," CEPR Discussion Papers 9312, C.E.P.R. Discussion Papers.
- Warne, Anders, 2023. "DSGE model forecasting: rational expectations vs. adaptive learning," Working Paper Series 2768, European Central Bank.
- S. Boragan Aruoba & Francis X. Diebold, 2010.
"Real-Time Macroeconomic Monitoring: Real Activity, Inflation, and Interactions,"
American Economic Review, American Economic Association, vol. 100(2), pages 20-24, May.
- S. Boragan Aruoba & Francis X. Diebold, 2010. "Real-Time Macroeconomic Monitoring: Real Activity, Inflation, and Interactions," PIER Working Paper Archive 10-002, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- S. Boragan Aruoba & Francis X. Diebold, 2010. "Real-time macroeconomic monitoring: real activity, inflation, and interactions," Working Papers 10-5, Federal Reserve Bank of Philadelphia.
- S. Boragan Aruoba & Francis X. Diebold, 2010. "Real-Time Macroeconomic Monitoring: Real Activity, Inflation, and Interactions," NBER Working Papers 15657, National Bureau of Economic Research, Inc.
- Sean Cao & Wei Jiang & Hui Xu, 2026. "Seeing the Goal, Missing the Truth: Human Accountability for AI Bias," Papers 2602.09504, arXiv.org.
- Clements, Michael P. & Beatriz Galvão, Ana, 2010.
"First announcements and real economic activity,"
European Economic Review, Elsevier, vol. 54(6), pages 803-817, August.
- Clements, Michael P. & Beatriz Galvao, Ana, "undated". "First Announcements and Real Economic Activity," Economic Research Papers 271314, University of Warwick - Department of Economics.
- Clements, Michael P. & Galvão, Ana Beatriz, 2009. "First Announcements and Real Economic Activity," The Warwick Economics Research Paper Series (TWERPS) 885, University of Warwick, Department of Economics.
- Knut Are Aastveit & Karsten R. Gerdrup & Anne Sofie Jore & Leif Anders Thorsrud, 2014.
"Nowcasting GDP in Real Time: A Density Combination Approach,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(1), pages 48-68, January.
- Knut Are Aastveit & Karsten R. Gerdrup & Anne Sofie Jore & Leif Anders Thorsrud, 2011. "Nowcasting GDP in real-time: A density combination approach," Working Paper 2011/11, Norges Bank.
- Knut Are Aastveit & Karsten R. Gerdrup & Anne Sofie Jore & Leif Anders Thorsrud, 2011. "Nowcasting GDP in Real-Time: A Density Combination Approach," Working Papers No 1/2011, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
- Aastveit, Knut Are & Anundsen, André K. & Herstad, Eyo I., 2019.
"Residential investment and recession predictability,"
International Journal of Forecasting, Elsevier, vol. 35(4), pages 1790-1799.
- Knut Are Aastveit & André K. Anundsen & Eyo I. Herstad, 2017. "Residential investment and recession predictability," Working Paper 2017/24, Norges Bank.
- Knut Are Aastveit & Andr K. Anundsen & Eyo I. Herstad, 2017. "Residential investment and recession predictability," Working Papers No 8/2017, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
- Clements Michael P., 2012. "Forecasting U.S. Output Growth with Non-Linear Models in the Presence of Data Uncertainty," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(1), pages 1-27, January.
- Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2016.
"Common Drifting Volatility in Large Bayesian VARs,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(3), pages 375-390, July.
- Marcellino, Massimiliano & Carriero, Andrea & Clark, Todd, 2012. "Common Drifting Volatility in Large Bayesian VARs," CEPR Discussion Papers 8894, C.E.P.R. Discussion Papers.
- Andrea CARRIERO & Todd E. CLARK & Massimiliano MARCELLINO, 2012. "Common Drifting Volatility in Large Bayesian VARs," Economics Working Papers ECO2012/08, European University Institute.
- Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2012. "Common drifting volatility in large Bayesian VARs," Working Papers (Old Series) 1206, Federal Reserve Bank of Cleveland.
- Garnitz, Johanna & Lehmann, Robert & Wohlrabe, Klaus, 2019.
"Forecasting GDP all over the world using leading indicators based on comprehensive survey data,"
EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 51(54), pages 5802-5816.
- Johanna Garnitz & Robert Lehmann & Klaus Wohlrabe, 2019. "Forecasting GDP all over the world using leading indicators based on comprehensive survey data," Applied Economics, Taylor & Francis Journals, vol. 51(54), pages 5802-5816, November.
- Garnitz, Johanna & Lehmann, Robert & Wohlrabe, Klaus, 2019. "Forecasting GDP all over the world using leading indicators based on comprehensive survey data," Munich Reprints in Economics 78264, University of Munich, Department of Economics.
- Johanna Garnitz & Robert Lehmann & Klaus Wohlrabe, 2019. "Forecasting GDP all over the world using leading indicators based on comprehensive survey data," CESifo Working Paper Series 7691, CESifo.
- Nikoleta Anesti & Ana Beatriz Galvao & Silvia Miranda-Agrippino, 2018.
"Uncertain Kingdom: Nowcasting GDP and its Revisions,"
Discussion Papers
1824, Centre for Macroeconomics (CFM).
- Nikoleta Anesti & Ana Galvão & Silvia Miranda-Agrippino, 2018. "Uncertain Kingdom: nowcasting GDP and its revisions," Bank of England working papers 764, Bank of England.
- Anesti, Nikoleta & Galvao, Ana Beatriz & Miranda-Agrippino, Silvia, 2018. "Uncertain kingdom: nowcasting GDP and its revisions," LSE Research Online Documents on Economics 90382, London School of Economics and Political Science, LSE Library.
- Stefan Neuwirth, 2017. "Time-varying mixed frequency forecasting: A real-time experiment," KOF Working papers 17-430, KOF Swiss Economic Institute, ETH Zurich.
- Davide Delle Monache & Andrea De Polis & Ivan Petrella, 2024.
"Modeling and Forecasting Macroeconomic Downside Risk,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(3), pages 1010-1025, July.
- Delle Monache, Davide & De Polis, Andrea & Petrella, Ivan, 2021. "Modeling and forecasting macroeconomic downside risk," Temi di discussione (Economic working papers) 1324, Bank of Italy, Economic Research and International Relations Area.
- Delle Monache, Davide & De Polis, Andrea & Petrella, Ivan, 2022. "Modeling and Forecasting Macroeconomic Downside Risk," CEPR Discussion Papers 15109, C.E.P.R. Discussion Papers.
- Barbara Rossi, 2021.
"Forecasting in the Presence of Instabilities: How We Know Whether Models Predict Well and How to Improve Them,"
Journal of Economic Literature, American Economic Association, vol. 59(4), pages 1135-1190, December.
- Barbara Rossi, 2019. "Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them," Economics Working Papers 1711, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2021.
- Barbara Rossi, 2020. "Forecasting in the Presence of Instabilities: How Do We Know Whether Models Predict Well and How to Improve Them," Working Papers 1162, Barcelona School of Economics.
- Rossi, Barbara, 2020. "Forecasting in the Presence of Instabilities: How Do We Know Whether Models Predict Well and How to Improve Them," CEPR Discussion Papers 14472, C.E.P.R. Discussion Papers.
- Yutong Yan & Raphael Tang & Zhenyu Gao & Wenxi Jiang & Yao Lu, 2026. "DatedGPT: Preventing Lookahead Bias in Large Language Models with Time-Aware Pretraining," Papers 2603.11838, arXiv.org.
- Allen Yikuan Huang & Zheqi Fan, 2026. "Beyond Prompting: An Autonomous Framework for Systematic Factor Investing via Agentic AI," Papers 2603.14288, arXiv.org, revised Apr 2026.
- Michael Pfarrhofer, 2024.
"Forecasts with Bayesian vector autoregressions under real time conditions,"
Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(3), pages 771-801, April.
- Michael Pfarrhofer, 2020. "Forecasts with Bayesian vector autoregressions under real time conditions," Papers 2004.04984, arXiv.org.
- Massimiliano Marcellino, 2008. "A linear benchmark for forecasting GDP growth and inflation?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(4), pages 305-340.
More about this item
Keywords
; ; ;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
NEP fields
This paper has been announced in the following NEP Reports:- NEP-AIN-2026-02-16 (Artificial Intelligence)
- NEP-BIG-2026-02-16 (Big Data)
- NEP-CMP-2026-02-16 (Computational Economics)
- NEP-FOR-2026-02-16 (Forecasting)
- NEP-MON-2026-02-16 (Monetary Economics)
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:fip:fedfwp:102407. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Federal Reserve Bank of San Francisco Research Library (email available below). General contact details of provider: https://edirc.repec.org/data/frbsfus.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.
Printed from https://ideas.repec.org/p/fip/fedfwp/102407.html