TY - GEN
T1 - GPT Deciphering Fedspeak
T2 - 2023 Findings of the Association for Computational Linguistics: EMNLP 2023
AU - Peskoff, Denis
AU - Wachspress, Benjamin
AU - Visokay, Adam
AU - Blinder, Alan
AU - Schulhoff, Sander
AU - Stewart, Brandon M.
N1 - Publisher Copyright:
© 2023 Association for Computational Linguistics.
PY - 2023
Y1 - 2023
N2 - Markets and policymakers around the world hang on the consequential monetary policy decisions made by the Federal Open Market Committee (FOMC). Publicly available textual documentation of their meetings provides insight into members' attitudes about the economy. We use GPT-4 to quantify dissent among members on the topic of inflation. We find that transcripts and minutes reflect the diversity of member views about the macroeconomic outlook in a way that is lost or omitted from the public statements. In fact, diverging opinions that shed light upon the committee's “true” attitudes are almost entirely omitted from the final statements. Hence, we argue that forecasting FOMC sentiment based solely on statements will not sufficiently reflect dissent among the hawks and doves.
AB - Markets and policymakers around the world hang on the consequential monetary policy decisions made by the Federal Open Market Committee (FOMC). Publicly available textual documentation of their meetings provides insight into members' attitudes about the economy. We use GPT-4 to quantify dissent among members on the topic of inflation. We find that transcripts and minutes reflect the diversity of member views about the macroeconomic outlook in a way that is lost or omitted from the public statements. In fact, diverging opinions that shed light upon the committee's “true” attitudes are almost entirely omitted from the final statements. Hence, we argue that forecasting FOMC sentiment based solely on statements will not sufficiently reflect dissent among the hawks and doves.
UR - http://www.scopus.com/inward/record.url?scp=85183309946&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85183309946&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85183309946
T3 - Findings of the Association for Computational Linguistics: EMNLP 2023
SP - 6529
EP - 6539
BT - Findings of the Association for Computational Linguistics
PB - Association for Computational Linguistics (ACL)
Y2 - 6 December 2023 through 10 December 2023
ER -