Abstract
A policy action by the Fed consists of using any one of various instruments, such as the federal funds rate and different measures of money, to pursue its multiple objectives. This chapter discusses dynamic multivariate modeling in general and reviews other approaches to forecasting. Dynamic multivariate modeling has complex structures in the sense that it allows both contemporaneous and dynamic interactions among the macroeconomic variables. More important, dynamic multivariate modeling provides empirically coherent ways to assess the uncertainty about forecasts. The dynamic multivariate model used in this article employs monthly data with the six key macroeconomic variables often used in the literature: the commodity prices, the federal funds rate, the stock of M2, the consumer price index, the real gross domestic product and the unemployment. The dynamic multivariate model discussed here is transparent enough to be reproduced and improved. At the same time, it is sufficiently complex to capture dynamic interplay between policymakers and the private sector.
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