TY - JOUR
AU - Doan, Thomas
AU - Litterman, Robert B
AU - Sims, Christopher A
TI - Forecasting and Conditional Projection Using Realistic Prior Distributions
JF - National Bureau of Economic Research Working Paper Series
VL - No. 1202
PY - 1983
Y2 - September 1983
DO - 10.3386/w1202
UR - http://www.nber.org/papers/w1202
L1 - http://www.nber.org/papers/w1202.pdf
N1 - Author contact info:
Christopher A. Sims
Department of Economics
Princeton University
104 Fisher Hall
Princeton, NJ 08544
Tel: 609/258-4033
Fax: 609/258-6419
E-Mail: sims@princeton.edu
AB - 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 1983:3.We also describe how a model such as this can be used to make conditional projections and to analyze 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 inevaluating causal hypotheses, without containing any such hypotheses themselves.
ER -