Specifying vector autoregressions for macroeconomic forecasting
By: Robert B. Litterman.
Series: Federal Reserve Bank of Minneapolis, Research Department staff report -- 92; Staff report (Federal Reserve Bank of Minneapolis. Research Dept. : Online) -- 92.
Publisher: Federal Reserve Bank of Minneapolis
Published: 1984
Place of publication: [Minneapolis, Minn.]
Language: eng
Format: Electronic resource
Subjects: Economic forecasting -- Mathematical models.; Macroeconomics -- Mathematical models.; Bayesian statistical decision theory.
Description: "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"--Federal Reserve Bank of Minneapolis web site.
Notes: Title from PDF file as viewed on 11/9/2007.

Includes bibliographical references.

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