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  <http://purl.org/dc/terms/title> "Forecasting and conditional projection using realistic prior distributions";
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  <http://purl.org/dc/elements/1.1/creator> "Litterman, Robert B.",
    "Sims, Christopher A.",
    "Doan, Thomas";
  <http://purl.org/dc/elements/1.1/publisher> "Federal Reserve Bank of Minneapolis";
  <http://purl.org/dc/elements/1.1/relation> "Forecasting",
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  <http://purl.org/dc/elements/1.1/subject> "E27 - Macroeconomics: Consumption, Saving, Production, Employment, and Investment: Forecasting and Simulation: Models and Applications",
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  <http://purl.org/dc/terms/abstract> "This paper develops a forecasting procedure based on a Bayesian method for estimating vector autoregressions. The procedure  is applied to ten macroeconomic variables and is shown to improve out-of-sample forecasts relative to univariate equations.  Although cross-variables responses are damped by the prior, considerable interaction among the variables is shown to be captured by the estimates.  We provide unconditional forecasts as of 1982:12 and 1963:3* We also describe how a model such as this can be used to make conditional projections and to analyse policy alternatives. As an example, we analyze a Congressional Budget Office forecast made in 1982:12.  While no automatic causal interpretations arise from models like ours, they provide a detailed characterization of the dynamic statistical interdependence of a set of economic variables,  which may help in evaluating causal hypotheses, without containing any such hypotheses themselves."^^<http://ns.ontowiki.net/SysOnt/Markdown>;
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