This paper examines which macroeconomic and financial variables are most informative for the federal funds target rate decisions made by the Federal Open Market Committee (FOMC) from a forecasting perspective. The analysis is conducted for the FOMC decision during the period January 1990 - June 2008, using dynamic ordered probit models with a Bayesian endogenous variable selection methodology and real-time data for a set of 33 candidate predictor variables. We find that indicators of economic activity and forward-looking term structure variables as well as survey measures have most predictive ability. For the full sample period, in-sample probability forecasts achieve a hitrate of 90 percent. Based on out-of-sample forecasts for the period January 2001 - June 2008, 82 percent of the FOMC decisions are predicted correctly.

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Tinbergen Institute
Tinbergen Institute Discussion Paper Series
Tinbergen Institute

van den Hauwe, S., van Dijk, D., & Paap, R. (2011). Bayesian Forecasting of Federal Funds Target Rate Decisions (No. TI 11-093/4). Tinbergen Institute Discussion Paper Series. Retrieved from