Abstract
AbstractThe purpose of central bank minutes is to give an account of monetary policy meeting discussions to outside observers, thereby enabling them to draw informed conclusions about future policy. However, minutes are by necessity a shortened and edited representation of a broader discussion. Consequently, they may omit information that is predictive of future policy decisions. To investigate this, we compare the predictive content of the Federal Open Market Committee's (FOMC) minutes and transcripts, focusing on dimensions that are likely to be excluded from the minutes, such as the committee's degree of hawkishness, the chairperson's degree of hawkishness, and the level of agreement between committee members. We measure committee and chairperson hawkishness with a new dictionary that is constructed using the FOMC's minutes and transcripts. Agreement is measured using a technique we import from the machine learning literature. We also show that transcripts contain predictive content that is not included in FOMC minutes, macroeconomic variables, financial variables, forecasts, or federal funds rate futures.
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