Multivariate Filter Estimation of Potential Output for the United States
Author/Editor: Ali Alichi, Olivier Bizimana, Douglas Laxton, Kadir Tanyeri, Hou Wang, Jiaxiong Yao, Fan Zhang
Release Date: © May, 2017
ISBN
: 978-1-47559-860-5
Stock #: WPIET2017106
English
Languages and formats available
| English | French | Spanish | Arabic | Russian | Chinese | Portuguese | |
| Paperback | Yes | ||||||
| Yes | |||||||
| ePub | Yes | ||||||
| Mobipocket | Yes |
Description
Estimates of potential output are an important component of a structured forecasting and policy analysis system. Using information on capacity utilization, this paper extends the multivariate filter developed by Laxton and Tetlow (1992) and modified by Benes and others (2010), Blagrave and others (2015), and Alichi and others (2015). We show that, although still fairly uncertain, the real-time estimates from this approach are more accurate than estimates constructed from naïve univariate statistical filters. The paper presents illustrative estimates for the United States and discusses how the end-of-sample estimates can be improved with additional information.
More publications in this series: Working Papers
More publications by: Ali Alichi ; Olivier Bizimana ; Douglas Laxton ; Kadir Tanyeri ; Hou Wang ; Jiaxiong Yao ; Fan Zhang
