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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)

  • Stephen M. Miller

    () (Department of Economics, University of Nevada, Las Vegas)

Abstract

This study examines the relationship between U.S. output growth and its volatility over the period 1875:Q1 to 2008:Q2. We examine the data for outliers and apply corrections when found. Next, we search for possible effects of structural breaks in the growth rate and its volatility. In so doing, we employ autoregressive generalized conditional heteroskedasticity and autoregressive exponential general conditional heteroskedasticity specifications of the process describing output growth rate and its volatility with and without structural breaks in the mean and volatility processes. We discover one break in the mean process – 1936:Q2 – and three breaks in the volatility process – 1916:Q4, 1950:Q3, and 1983:Q4 (or 1984:Q3). After accommodating the breaks in the mean and volatility processes, the integrated generalized autoregressive conditional heteroskedasticity effect proves spurious. Finally, our data analyses and empirical results suggest that higher output-growth volatility stimulates output growth and that higher output growth reduces its volatility. Moreover, the evidence shows that the time-varying variance falls sharply once we incorporate the three structural breaks in the unconditional variance of output.

Suggested Citation

  • WenShwo Fang & Stephen M. Miller, 2012. "Output Growth and Its Volatility: The Gold Standard through the Great Moderation," Working Papers 1205, University of Nevada, Las Vegas , Department of Economics.
  • Handle: RePEc:nlv:wpaper:1205
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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. repec:eee:riibaf:v:42:y:2017:i:c:p:61-74 is not listed on IDEAS
    3. Trypsteen, Steven, 2017. "The growth-volatility nexus: New evidence from an augmented GARCH-M model," Economic Modelling, Elsevier, vol. 63(C), pages 15-25.
    4. 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.
    5. Akhand Akhtar Hossain, 2014. "Inflation and Inflation Volatility in Australia," Economic Papers, The Economic Society of Australia, vol. 33(2), pages 163-185, June.

    More about this item

    Keywords

    economic growth and volatility; structural change; IGARCH;

    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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