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

Abstract

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.Demand and Price Analysis,

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