We all see headlines about Federal Reserve Open Market Committee members debating the merits and demerits of raising the federal funds rate. Changes to the rate have a powerful effect on economic activity as it influences interest rates across the economy. While the Fed may or may not take action after a particular meeting, the conversations that take place during the meeting may give insight to their next step. Because of this, FOMC transcripts are widely read and analyzed by the financial industry.

San Cannon applies text-mining techniques to FOMC transcripts to identify patterns in Committee discourse over time as well as changes in the relationship between participants’ tone and economic activity. 

Sandra “San” Cannon is an Assistant Vice President and Economist in, as well as an Associate Director of, the Center for the Advancement for Data and Research in Economics (CADRE) at the Federal Reserve Bank of Kansas City.   She develops and oversees data and content curation services in support of data and computationally intensive economic research. She holds a bachelors of arts in economics from the University of California, Irvine, a master of science in economics from the London School of Economics, and a Ph.D. in economics from the University of Wisconsin-Madison. Her research focuses on data organization and dissemination, research support processes, and applications of data science techniques. San is also an adjunct professor in the data science program at Rockhurst University.