Monetary Policy Rules With Model And Data Uncertainty
Abstract
In this paper we examine the prevalence of data, specification, and parameter uncertainty in the formation of simple rules that mimic monetary policymaking decisions. Our approach is to build real-time data sets and simulate a real-time policy-setting environment in which we assume that policy is captured by movements in the actual federal funds rate, and then to assess what sorts of policy rule models and what sorts of data best explain what the Federal Reserve actually did. This approach allows us not only to track the performance of alternative rules over time (hence facilitating a type of model selection among competing rules), but also to more generally assess the importance of the data revision process in the formation of macroeconomic time series models. From the perspective of real-time data, our results suggest that the use of data that are erroneous, in the sense that they were not available at the time decisions could have been made based on forecasts from the rules, can lead to the selection of quantitatively different models.
- Keyword(s):
- data project 74
- finance 247
- policy 19
https://kenaninstitute.unc.edu/publication/monetary-policy-rules-with-model-and-data-uncertainty-2/
