  This paper introduces a transparent framework to identify the informational
content of FOMC announcements. We do so by modelling the expectations of the
FOMC and private sector agents using state of the art computational linguistic
tools on both FOMC statements and New York Times articles. We identify the
informational content of FOMC announcements as the projection of high frequency
movements in financial assets onto differences in expectations. Our recovered
series is intuitively reasonable and shows that information disclosure has a
significant impact on the yields of short-term government bonds.
