A Textual Taylor Rule: Estimating Central Bank Preferences Combining Topic and Scaling Methods
(with Will Lowe) (Last Updated April 2017)
Scholars often use voting data to estimate central bankers' policy preferences but consensus voting is common. To get around this, we combine topic-based text analysis and scaling methods to generate theoretically motivated comparative and dynamic measures of central bank preferences on the U.S. Federal Open Market Committee leading up to the financial crisis (2005 - 2008) in a way that does not depend on voting. We apply these measures to a number of applications in the literature. We confirm that committee members on schedule to vote are more likely to express consensus opinion than their off schedule voting counterparts and show that it is Dovish rather than Hawkish members who are more likely to want to amend the official policy statement.