  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.
