Baynesian Leading Indicators: Measuring and Predicting Economic Conditions
Posted: 11 Nov 1996
Date Written: October 1996
Abstract
This paper designs and implements a Baynesian dynamic latent factor model for a vector of data describing the Iowa economy. Posterior distributions of parameters and the latentfactor are analyzed by Markov Chain Monte Carlo methods, and coincident and leading indicators are given by posterior mean values of current and predictive distributions for the latent factor.
JEL Classification: C11, C15, C43, C53
Suggested Citation: Suggested Citation
Otrok, Christopher and Whiteman, Charles H., Baynesian Leading Indicators: Measuring and Predicting Economic Conditions (October 1996). Available at SSRN: https://ssrn.com/abstract=3482
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