Cai, Xiaoming, Den Haan, Wouter J. ORCID: 0000-0001-6214-8156 and Pinder, Jonathan (2016) Predictable recoveries. Economica, 83 (330). 307 - 337. ISSN 0013-0427
|
PDF
- Accepted Version
Download (795kB) | Preview |
Abstract
A random walk with drift is a good univariate representation of US GDP. This paper shows, however, that US economic downturns have been associated with pre- dictable short-term recoveries and with changes in long-term GDP forecasts that are substantially smaller than the initial drop. To detect these predictable changes, it is important to use a multivariate time series model. We discuss reasons why univariate representations can miss key characteristics of the underlying variable such as predictability, especially during recessions.
Item Type: | Article |
---|---|
Official URL: | https://onlinelibrary.wiley.com/journal/14680335 |
Additional Information: | © 2016 The London School of Economics and Political Science |
Divisions: | LSE |
Subjects: | H Social Sciences > HB Economic Theory Q Science > QA Mathematics |
JEL classification: | C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Other Model Applications E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E32 - Business Fluctuations; Cycles E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E37 - Forecasting and Simulation |
Date Deposited: | 01 Feb 2016 10:16 |
Last Modified: | 01 Oct 2024 03:43 |
URI: | http://eprints.lse.ac.uk/id/eprint/65188 |
Actions (login required)
View Item |