Generative AI, Managerial Expectations, and Economic Activity -- by Manish Jha, Jialin Qian, Michael Weber, Baozhong Yang

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2026, 18th Annual Feldstein Lecture, Mark Duggan, "Social Security Reform in an Era of Fiscal Deficits" Primary tabs
  • Acknowledgements and Disclosures

    For helpful comments, we thank Vineet Bhagwat, Jiayin Hu, Haibo Jiang, Sophia Kazinnik, Sophia Zhengzi Li, Dexin Zhou, and participants at the NBER Forecasting & Empirical Methods, China International Conference in Finance, Conference on Financial Economics and Accounting, Indian School of Business Summer Research Conference, Financial Intermediation Research Society Conference, Northern Finance Association, Society of Quantitative Analysts Conference, Fidelity Quantitative Research, Georgia State University, International Conference on Information Technology and Quantitative Management, McMaster University, Peking University, Rutgers University, University of Oxford, and Winter Institute of AISSEAI. All errors are our own. An earlier version of this paper was circulated under the title “Harnessing Generative AI for Economic Insights.” The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.


  • Citation and Citation DataCopy Citation Manish Jha, Jialin Qian, Michael Weber, and Baozhong Yang, "Generative AI, Managerial Expectations, and Economic Activity," NBER Working Paper 35949 (2026), https://doi.org/10.3386/w35949. Copy to Clipboard Download Citation
SI 2026 Methods Lecture
Using AI in Household Finance Research: A Practical Guide

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This story was first published by NBER on 22 Oct 2026. HUE Legacy Ventures did not write it.

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