Specifying vector autoregressions for macroeconomic forecasting

Robert Litterman

No 92, Staff Report from Federal Reserve Bank of Minneapolis

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.

Date: 1984
New Economics Papers: this item is included in nep-ets
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