| Title: | Conditional Forecasts in Dynamic Multivariate Models |
| Author: | Waggoner, Daniel F.; Zha, Tao |
| Author Affiliation: | Federal Reserve Bank of Atlanta |
| Source: | Review of Economics and Statistics, November 1999, v. 81, iss. 4, pp. 639-51 |
| Publication Date: | November 1999 |
| Abstract: | In the existing literature, conditional forecasts in the vector autoregressive (VAR) framework have not been commonly presented with probability distributions. This paper develops Bayesian methods for computing the exact finite-sample distribution of conditional forecasts. It broadens the class of conditional forecasts to which the methods can be applied. The methods work for both structural and reduced-form VAR models and, in contrast to common practices, account for parameter uncertainty in finite samples. Empirical examples under both a flat prior and a reference prior are provided to show the use of these methods. |
| Descriptors: | Forecasting and Other Model Applications Econometric Methods: Multiple/Simultaneous Equation Models: Time-Series Models |
| Geographic Descriptors: | Global |
| ISSN: | 00346535 |
| Publication Type: | Journal Article |
| Availability: | http://mitpress.mit.edu/catalog/item/default.asp?ttype=4&tid =17 |