ChatGPT and Corporate Policies

Manish Jha, Jialin Qian, Michael Weber and Baozhong Yang

Papers from arXiv.org

Abstract: We create a firm-level ChatGPT investment score, based on conference calls, that measures managers' anticipated changes in capital expenditures. We validate the score with interpretable textual content and its strong correlation with CFO survey responses. The investment score predicts future capital expenditure for up to nine quarters, controlling for Tobin's $q$ and other determinants, implying the investment score provides incremental information about firms' future investment opportunities. The investment score also separately forecasts future total, intangible, and R\&D investments. Consistent with theoretical predictions, high-investment-score firms experience significant positive short-term returns upon disclosure, and negative long-run future abnormal returns. We demonstrate ChatGPT's applicability to measure other policies, such as dividends and employment.

Date: 2024-09, Revised 2025-02
New Economics Papers: this item is included in nep-ain and nep-cfn
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://arxiv.org/pdf/2409.17933 Latest version (application/pdf)

Related works:
Working Paper: ChatGPT and Corporate Policies (2024)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2409.17933

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().