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The growth-volatility nexus: New evidence from an augmented GARCH-M model

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  • Trypsteen, Steven

Abstract

The paper examines the growth-volatility nexus for 13 OECD countries using an augmented GARCH-M model. The model is able to simultaneously account for country interactions, structural breaks, heterogeneous effects, dynamics in the volatility effect and particular nonlinearities. To take country interactions into account, the model includes cross-country weighted averages of growth and volatility. This makes it possible to distinguish between domestic and external volatility. The paper shows that i) accounting for dynamics in the volatility effect, country interactions, structural breaks and heterogeneous effects is important and ii) domestic volatility is positively associated and external volatility is negatively associated with growth.

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  • Trypsteen, Steven, 2017. "The growth-volatility nexus: New evidence from an augmented GARCH-M model," Economic Modelling, Elsevier, vol. 63(C), pages 15-25.
    • Handle: RePEc:eee:ecmode:v:63:y:2017:i:c:p:15-25
    DOI: 10.1016/j.econmod.2017.01.012
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    Cited by:

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    2. Amélie Charles & Olivier Darné, 2021. "Econometric history of the growth–volatility relationship in the USA: 1919–2017," Cliometrica, Journal of Historical Economics and Econometric History, Association Française de Cliométrie (AFC), vol. 15(2), pages 419-442, May.
    3. Jiang, Yong & Zhou, Zhongbao & Liu, Qing & Lin, Ling & Xiao, Helu, 2020. "How do oil price shocks affect the output volatility of the U.S. energy mining industry? The roles of structural oil price shocks," Energy Economics, Elsevier, vol. 87(C).
    4. Pinar Deniz & Thanasis Stengos & M. Ege Yazgan, 2021. "Revisiting the link between output growth and volatility: panel GARCH analysis," Empirical Economics, Springer, vol. 61(2), pages 743-771, August.
    5. Aykut Ekinci, 2022. "Relationship Between Output Volatility and Output in OECD Countries Revisited," Prague Economic Papers, Prague University of Economics and Business, vol. 2022(6), pages 509-537.
    6. Abosedra, Salah & Arayssi, Mahmoud & Ben Sita, Bernard & Mutshinda, Crispin, 2020. "Exploring GDP growth volatility spillovers across countries," Economic Modelling, Elsevier, vol. 89(C), pages 577-589.

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    More about this item

    Keywords

    GARCH-M; Global VAR; Structural breaks; Bounce back effect;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • 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
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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