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An Assessment of UK Macroeconomic Volatility: Historical Evidence Using Over Seven Centuries of Data

Author

Listed:
  • Vasilios Plakandaras

    (Department of Economics, Democritus University of Thrace, Greece)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Pretoria, South Africa)

  • Mark E. Wohar

    (College of Business Administration, University of Nebraska at Omaha USA, and School of Business and Economics, Loughborough University)

Abstract

Breaking ground from all previous studies, we estimate a time-varying Vector Autoregression model that examines the time-period 1270-2016 - the entire economic history of the U.K. Focusing on permanent and transitory shocks in the economy, we study the fluctuation in conditional volatilities and time-varying long-run responses of output growth and inflation. Unlike all previous studies that use time invariant linear models, our approach reveals that the pre 1600 period is a turbulent economic period of high volatility that is only repeated in the 20th century. The repeating patterns in the conditional volatilities follow the approach of aggregate supply shocks, while most of the inflation responses follow from aggregate demand shocks. Thus, we uncover that despite the technological growth and the various changes in the structure of the U.K. economy in the last century, the recurring patterns call for an examination of the true impact of the various policies to the economy.

Suggested Citation

  • Vasilios Plakandaras & Rangan Gupta & Mark E. Wohar, 2017. "An Assessment of UK Macroeconomic Volatility: Historical Evidence Using Over Seven Centuries of Data," Working Papers 201779, University of Pretoria, Department of Economics.
  • Handle: RePEc:pre:wpaper:201779
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    References listed on IDEAS

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    More about this item

    Keywords

    Time-Varying VAR; Macroeconomic Shocks;

    JEL classification:

    • 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

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