Working Paper
VAR estimation and forecasting when data are subject to revision
Abstract: Conventional VAR estimation and forecasting ignores the fact that economic data are often subject to revision many months or years after their initial release. This paper shows how VAR analysis can be modified to account for such revisions. The proposed approach assumes that government statistical releases are efficient with a finite lag. It takes no stand on whether earlier revisions are ?noise? or ?news.? The technique is illustrated using data on employment and the unemployment rate, real GDP and the unemployment rate, and real GDP and the GDP/consumption ratio. In each case, the proposed procedure outperforms conventional VAR analysis and the more-restrictive methods for handling the data-revision problem that are found in the existing literature.
Access Documents
File(s):
File format is application/pdf
https://www.dallasfed.org/~/media/documents/research/papers/2005/wp0501.pdf
Description: Full text
Authors
Bibliographic Information
Provider: Federal Reserve Bank of Dallas
Part of Series: Working Papers
Publication Date: 2005
Number: 0501
Note: Published as: Kishor, N. Kundan and Evan F. Koenig (2012), "VAR Estimation and Forecasting When Data Are Subject to Revision," Journal of Business and Economic Statistics 30 (2): 181-190.