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Keywords:signal extraction OR Signal extraction 

Working Paper
Mechanics of Linear Quadratic Gaussian Rational Inattention Tracking Problems

This paper presents a general framework for constructing and solving the multivariate static linear quadratic Gaussian (LQG) rational inattention tracking problem. We interpret the nature of the solution and the implied action of the agent, and we construct representations that formalize how the agent processes data. We apply this infrastructure to the rational inattention price-setting problem, confirming the result that a conditional response to economics shocks is possible, but casting doubt on a common assumption made in the literature. We show that multiple equilibria and a social cost ...
Finance and Economics Discussion Series , Paper 2017-109

Report
Aggregate Output Measurements: A Common Trend Approach

We analyze a model for N different measurements of a persistent latent time series when measurement errors are mean-reverting, which implies a common trend among measurements. We study the consequences of overdifferencing, finding potentially large biases in maximum likelihood estimators of the dynamics parameters and reductions in the precision of smoothed estimates of the latent variable, especially for multiperiod objects such as quinquennial growth rates. We also develop an R2 measure of common trend observability that determines the severity of misspecification. Finally, we apply our ...
Staff Reports , Paper 962

Working Paper
Introducing Trimmed Imports and Exports

Trade flows are volatile and notoriously difficult to predict. This paper introduces trimmed import and export growth rates for the United States to help improve trade forecasts. We calculate the growth rates as a trimmed mean that strips out subcomponents with less predictive power. By separating the signal from the noise, our trimmed growth rates provide a better perspective on where aggregate imports or exports are heading, particularly at horizons four to 12 months ahead. Consequently, out-of-sample forecasts based on our trimmed growth rates reduce forecast errors by up to 15 percent ...
Research Working Paper , Paper RWP 26-08

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