Forecasting and conditional projection using realistic prior distribution
AbstractThis paper develops a forecasting procedure based on a Bayesian method for estimating vector autoregressions. We apply the procedure to 10 macroeconomic variables and show that it produces more accurate out-of-sample forecasts than univariate equations do. Although cross-variable responses are damped by the prior, our estimates capture considerable interaction among the variables. ; 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 analyze policy alternatives. As an example, we analyze a Congressional Budget Office forecast made in 1982:12. ; While no automatic casual interpretations arise from models like ours, such models provide a detailed characterization of the dynamic statistical interdependence of a set of economic variables. That information may help evaluate casual hypotheses without containing any such hypotheses.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Federal Reserve Bank of Minneapolis in its series Staff Report with number 93.
Date of creation: 1986
Date of revision:
Other versions of this item:
- Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1983. "Forecasting and Conditional Projection Using Realistic Prior Distributions," NBER Working Papers 1202, National Bureau of Economic Research, Inc.
- NEP-ALL-2002-03-14 (All new papers)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Chow, Gregory C & Lin, An-loh, 1971.
"Best Linear Unbiased Interpolation, Distribution, and Extrapolation of Time Series by Related Series,"
The Review of Economics and Statistics,
MIT Press, vol. 53(4), pages 372-75, November.
- Tom Doan, . "CHOWLIN: RATS procedure to distribute a series to a higher frequency using related series," Statistical Software Components RTS00036, Boston College Department of Economics.
- Tom Doan, . "DISAGGREGATE: RATS procedure to implement general disaggregation (interpolation/distribution) procedure," Statistical Software Components RTS00050, Boston College Department of Economics.
- John Geweke, 1978.
"The Temporal and Sectoral Aggregation of Seasonally Adjusted Time Series,"
in: Seasonal Analysis of Economic Time Series, pages 411-432
National Bureau of Economic Research, Inc.
- John Geweke, 1979. "The Temporal and Sectoral Aggregation of Seasonally Adjusted Time Series," NBER Chapters, in: Seasonal Analysis of Economic Time Series, pages 411-432 National Bureau of Economic Research, Inc.
- Leamer, Edward E, 1972. "A Class of Informative Priors and Distributed Lag Analysis," Econometrica, Econometric Society, vol. 40(6), pages 1059-81, November.
- Shiller, Robert J, 1973. "A Distributed Lag Estimator Derived from Smoothness Priors," Econometrica, Econometric Society, vol. 41(4), pages 775-88, July.
- Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
- Robert B. Litterman, 1979. "Techniques of forecasting using vector autoregressions," Working Papers 115, Federal Reserve Bank of Minneapolis.
This item has more than 25 citations. To prevent cluttering this page, these citations are listed on a separate page. reading lists or Wikipedia pages:
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Janelle Ruswick).
If references are entirely missing, you can add them using this form.