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Activity Number: 122
Type: Contributed
Date/Time: Monday, August 1, 2016 : 8:30 AM to 10:20 AM
Sponsor: Government Statistics Section
Abstract #320889 View Presentation
Title: Optimal Monetary Policy with Noisy Information
Author(s): Jacob Orchard* and James McDonald and Kerk Phillips
Companies: Brigham Young University and Brigham Young University and Brigham Young University
Keywords: Optimal Monetary Policy ; Taylor Rule ; Data uncertainty ; Observation noise ; Policy Evaluation

This study investigates optimal Taylor Rule style monetary policy when the Central Bank's observations of the current state of the economy are subject to noise. Comparing the real-time Federal Reserve Estimates of nominal GDP growth and the inflation rate with current historical estimates we fit the data noise to the Skewed Generalized T distribution. The Skewed Generalized T is a more flexible distribution that fits the noise much better than the normal distribution, which has been used in earlier studies. Using a simple DSGE model of the US economy, we are able to estimate the parameters for the optimal Taylor Rule style monetary policy. We compare these results with optimal policy under the naive assumption that the Central Bank has perfect information, as well as the assumption that the errors are distributed normally. We then estimate the Federal Reserve's implied assumptions of the data noise's distribution using 1992-current Federal funds rate targets.

Authors who are presenting talks have a * after their name.

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