CONDITIONAL FORECASTING FOR THE U.S. DAIRY PRICE COMPLEX WITH A BAYESIAN VECTOR AUTOREGRESSIVE MODEL

Thraen, Cameron S.; Thompson, Stanley R.; Gohout, Wolfgang

CONDITIONAL FORECASTING FOR THE U.S. DAIRY PRICE COMPLEX WITH A BAYESIAN VECTOR AUTOREGRESSIVE MODEL

Autores

Thraen, Cameron S.

Thompson, Stanley R.

Gohout, Wolfgang

Descripción

A dynamic Bayesian Vector Autoregressive model of the U.S. dairy price complex is estimated based on the Normal-Wishart distribution. The Gibbs sample technique is use with the Normal-Wishart distribution to provide conditional forecasts on the future time-paths of the model variables. The conditional forecasts for key prices are examined. Confidence intervals are calculated for the conditional forecasts.