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System Priors for Econometric Time Series
Andrle, Michal ; Plašil, Miroslav
This paper introduces “system priors” into Bayesian analysis of econometric time series and provides a simple and illustrative application. Unlike priors on individual parameters, system priors offer a simple and efficient way of formulating well-defined and economically meaningful priors about model properties that determine the overall behavior of the model. The generality of system priors is illustrated using an AR(2) process with a prior that its dynamics comes mostly from business-cycle frequencies.
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