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

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.


Issue Date:
2002
Publication Type:
Conference Paper/ Presentation
Record Identifier:
http://ageconsearch.umn.edu/record/19706
PURL Identifier:
http://purl.umn.edu/19706
Total Pages:
11
Series Statement:
Selected Paper




 Record created 2017-04-01, last modified 2018-01-21

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