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Long Memory in UK Real GDP, 1851-2013: An ARFIMA-FIGARCH Analysis

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  • 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), implying that aggregate output is not an I(1) process. The presence of long memory in output volatility (d = 0.80) is also confirmed.

Suggested Citation

  • Guglielmo Maria Caporale & Marinko Skare, 2014. "Long Memory in UK Real GDP, 1851-2013: An ARFIMA-FIGARCH Analysis," Discussion Papers of DIW Berlin 1395, DIW Berlin, German Institute for Economic Research.
  • Handle: RePEc:diw:diwwpp:dp1395
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    Cited by:

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    2. Guglielmo Maria Caporale & Luis Alberiko Gil‐Alana, 2022. "Trends and cycles in macro series: The case of US real GDP," Bulletin of Economic Research, Wiley Blackwell, vol. 74(1), pages 123-134, January.

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    More about this item

    Keywords

    ARFIMA-(FI)GARCH; Dual long memory; Volatility; Fractional impulse-response; Unemployment; Inflation;
    All these keywords.

    JEL classification:

    • B23 - Schools of Economic Thought and Methodology - - History of Economic Thought since 1925 - - - Econometrics; Quantitative and Mathematical Studies
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling

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