Forecasting and Conditional Projection Using Realistic Prior Distributions / Thomas Doan, Robert B. Litterman, Christopher A. Sims.

Format:

Book

Author/Creator:

Doan, Thomas.

Contributor:

National Bureau of Economic Research.

Litterman, Robert B.

Sims, Christopher A.

Series:

Working Paper Series (National Bureau of Economic Research) no. w1202.

NBER working paper series no. w1202

Language:

English

Subjects (All):

Distribution (Economic theory).

Physical Description:

1 online resource: illustrations (black and white);

Place of Publication:

Cambridge, Mass. National Bureau of Economic Research 1983.

Cambridge, Massachussetts : National Bureau of Economic Research, 1983.

Summary:

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.

Notes:

Print version record

September 1983.