Learning and Loss Functions: Comparing Optimal and Operational Monetary Policy Rules forthcoming in the International Journal
of Mathematical Modeling and Numerical Optimization with Srikanth Ramamurthy
Modern Bayesian tools aided by MCMC techniques allow researchers to estimate models with increasingly intricate dynamics. This paper highlights the
application of these tools with an empirical assessment of optimal versus operational monetary policy rules within a standard new Keynesian macroeconomic
model with adaptive learning. The question of interest is which of the two policy rules – contemporaneous data or expectations of current variables – better
describes the policy undertaken by the US central bank. Results for the data period 1954:III to 2007:I indicate that the data strongly favours contemporaneous
expectations over real time data.