Figuring Out the Fed-Beliefs about Policymakers and Gains from Transparency

In this paper, I use a Markov chain Monte Carlo algorithm to estimate a model of private-sector behavior that does not feature private-sector knowledge of the monetary policymaking process and, instead, leaves firms and households uncertain about how monetary policy is set. The private sector entertains two competing views of monetary policymaking, which I estimate. Firms and households use Bayes' law on a rolling data sample to distinguish between those two models. I use this setup to study the evolution of beliefs about the Federal Reserve and the possible gains from transparency.