We use a Bayesian Markov Chain Monte Carlo algorithm to estimate the parameters
of a true data-generating mechanism and those of a sequence of approximating
models that a monetary authority uses to guide its decisions. Gaps between
a true expectational Phillips curve and the monetary authoritys approximating
nonexpectational Phillips curve models unleash inflation that a monetary authority
that knows the true model would avoid. A sequence of dynamic programming
problems implies that the monetary authoritys inflation target evolves as its
estimated Phillips curve moves. Our estimates attribute the rise and fall of post-
WWII inflation in the United States to an intricate interaction between the monetary
authoritys beliefs and economic shocks. Shocks in the 1970s made the monetary
authority perceive a tradeoff between inflation and unemployment which ignited big
inflation. The monetary authoritys beliefs about the Phillips curve changed in ways
that account for former Federal Reserve Chairman Paul Volckers conquest of U.S.
inflation. (JEL E24, E31, E52, N12)
Sargent, Thomas, Noah Williams, and Tao Zha.
2006."Shocks and Government Beliefs: The Rise and Fall of American Inflation."American Economic Review,