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- © Vilnius University, 2002-2018
- © Brno University of Technology, 2002-2018
- © University of Latvia, 2002-2018
Article
LONG MEMORY IN UK REAL GDP, 1851-2013: AN ARFIMA-FIGARCH ANALYSIS
Guglielmo Maria Caporale, Marinko Skare
ABSTRACT. This paper analyses the long-memory properties of both the conditional mean and variance of UK real GDP over the period 1851-2013 by estimating a multivariate ARFIMA-FIGARCH model (with the unemployment rate and inflation as explanatory variables). The results suggest that this series is non-stationary and non-mean-reverting, the null hypotheses of I(0), I(1) and I(2) being rejected in favour of fractional integration: shocks appear to have permanent effects, and therefore policy actions are required to restore equilibrium. The estimate of the long-memory parameter = 1.37 is similar to that reported by Candelon and Gil-Alana (2004) and goes against the idea that aggregate output is an I(1) process. The presence of long memory in output volatility (d = 0.80) is also confirmed.
KEYWORDS: ARFIMA-(FI)GARCH, dual long memory, volatility, fractional impulse-response, unemployment, inflation, United Kingdom.
JEL classification: B23, C14, C32, C53, C54.