Bayesian Inference, Modeling and Forecasting Techniques in Econometrics

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This project extends past and current research on Bayesian inference, econometric modelling and forecasting techniques. In particular, in the area of Bayesian inference further research will be done: (1) to assess the properties of estimates and predictions relative to asymmetric loss functions; (2) to extend and elaborate work on optimal information processing and Bayes' Theorem; (3) to report and extend results on invariant maximal data information prior distributions; and (4) to continue research on minimum expected loss estimates for structural coefficients. In the area of econometric modeling and forecasting techniques, work on Bayesian state-space models have been developed and applied in forecasting annual and quarterly data for the U.S. and eight European countries. These models will be further refined and applied to data from nine additional countries.