Specifying vector autoregressions for macroeconomic forecasting
AbstractThis 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.
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Bibliographic InfoPaper provided by Federal Reserve Bank of Minneapolis in its series Staff Report with number 92.
Date of creation: 1984
Date of revision:
This paper has been announced in the following NEP Reports:
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