Specifying Vector Autoregressions for Macroeconomic Forecasting

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Creator Series Issue number
  • 092
Date created
  • 1984-03
Abstract
  • This paper describes a Bayesian specification procedure used to generate a vector autoregressive model for forecasting macroeconomic variables. The specification search is over parameters of a prior. This quasi-Bayesian approach is viewed as a flexible tool for constructing a filter which optimally extracts information about the future from a set of macroeconomic data. The procedure is applied to a set of data and a consistent improvement in forecasting performance is documented.

Corporate Author
  • Federal Reserve Bank of Minneapolis. Research Department
Publisher
  • Federal Reserve Bank of Minneapolis
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