Predictable recoveries

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

Preview

PDF - Accepted Version Download (795kB) | Preview

• Author

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:	12 Dec 2024 01:07
URI:	http://eprints.lse.ac.uk/id/eprint/65188

Actions (login required)

View Item