Abstract
In macroeconomic policy analysis, estimates of latent variables such as the natural rate of interest and the output gap are important inputs for policymakers. We develop reliability measures to assess the quality of estimates of latent variables in linear state space models that go beyond describing the level of uncertainty surrounding these estimates. Specifically, we propose the (conditional) correlation and the associated R2 as intuitive measures to assess the average performance of models over time, and the half-life of models as a dynamic criterion that captures how quickly the estimates pick up changes.Models that estimate the level of the hidden state very imprecisely may still have information about longer-term movements in latent variables.
Local Organizer: Giovanni Angelini