A Bayesian interpretation of the Federal Reserve's dual mandate and the Taylor Rule

When the Federal Reserve was established by the US Congress in 1913, its charter mandated that the new central bank “promote an elastic currency” and the institution was given extraordinary powers to serve as a lender of last resort to the banking system. Congress was reacting to the cycle of financial panics that had beset the country since the Civil War and had worsened with the Panic of 1907. Congress sought to find a remedy to prevent runs on banks turning into full-fledged financial crises. The term “elastic” in the opening words of the charter was intended to underscore the need for a robust banking system that could withstand shocks and not collapse upon itself. There was no mention whatsoever of a dual mandate of promoting price stability and encouraging full employment. With prodding from the US Congress, the Federal Reserve became highly involved in the management of the economy of the United States after WWII, focusing on inflation and full employment objectives. In 1993 Professor John Taylor set forth an elegant and simple framework (aka, the Taylor Rule) for analyzing the interest rate policy of the Federal Reserve in terms of its dual mandate. This paper examines Federal Reserve behavior from the mid-1950s to 2011 through the lens of the Taylor Rule. Our contribution is to use a dynamic linear model with Bayesian inference to update the evolution through time of the key parameters surrounding the inflation and full employment mandates, using only the information available to the Federal Reserve at each point in time. Our findings provide a more nuanced quantitative view than is previously available in the literature of how the Federal Reserve shifted its management of its dual mandate over time and in response to different economic challenges. Moreover, our research leads to serious questions of how Federal Reserve decision making may change in the future, following the financial panic of 2008, pointing toward numerous avenues for new research.