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Output Growth and its Volatility: The Gold Standard through the Great Moderation

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  • WenShwo Fang

    () (Department of Economics, Feng Chia University, 100 WenHwa Road, Taichung, Taiwan;)

  • Stephen M. Miller

    () (Department of Economics, University of Nevada, Las Vegas, 4505 Maryland Parkway, Las Vegas, NV 89154-6005, USA; corresponding author)

Abstract

This study examines the relationship between U.S. output growth and its volatility over the period 1876:I to 2012:II. We adjust the data for outliers and structural breaks. We employ generalized autoregressive conditional heteroskedasticity (GARCH) and exponential GARCH (EGARCH) specifications. Normality and homoskedasticity appear only in the GARCH or EGARCH model that corrects for the outliers. When including the break in the mean equation, high volatility persistence remains. After also accommodating the breaks in the variance equation, the integrated GARCH effect proves spurious, either for the symmetric or the asymmetric model. Finally, our empirical results suggest that the finding of higher output growth volatility stimulating output growth and higher output growth reducing its volatility obtained from the symmetric GARCH-in-mean (GARCH-M) model also proves spurious as a result of the emergence of an asymmetric effect. Our more appropriately specified asymmetric EGARCH-M model suggests positive volatility-in-mean and level effects in the long-period real gross national product series.

Suggested Citation

  • WenShwo Fang & Stephen M. Miller, 2014. "Output Growth and its Volatility: The Gold Standard through the Great Moderation," Southern Economic Journal, Southern Economic Association, vol. 80(3), pages 728-751, January.
  • Handle: RePEc:sej:ancoec:v:80:3:y:2014:p:728-751
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    File URL: http://dx.doi.org/10.4284/0038-4038-2012.161
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    References listed on IDEAS

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    Cited by:

    1. Huang, Ho-Chuan (River) & Fang, WenShwo & Miller, Stephen M. & Yeh, Chih-Chuan, 2015. "The effect of growth volatility on income inequality," Economic Modelling, Elsevier, vol. 45(C), pages 212-222.
    2. Cecilia Bermúdez & Carlos D. Dabús & Germán H. González, 2015. "Reexamining the link between instability and growth in Latin America: A dynamic panel data estimation using k-median clusters," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 52(1), pages 1-23, May.
    3. Akhand Akhtar Hossain, 2014. "Inflation and Inflation Volatility in Australia," Economic Papers, The Economic Society of Australia, vol. 33(2), pages 163-185, June.
    4. repec:eee:riibaf:v:42:y:2017:i:c:p:61-74 is not listed on IDEAS
    5. Trypsteen, Steven, 2017. "The growth-volatility nexus: New evidence from an augmented GARCH-M model," Economic Modelling, Elsevier, vol. 63(C), pages 15-25.

    More about this item

    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
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General

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