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Cross-Country Evidence On Output Growth Volatility: Nonstationary Variance And Garch Models

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  • WenShwo Fang
  • Stephen M. Miller
  • ChunShen Lee

Abstract

This paper revisits the issue of conditional volatility in real GDP growth rates for Canada, Germany, Italy, Japan, the United Kingdom, and the United States. Previous studies find high persistence in the volatility. This paper shows that this finding largely reflects a nonstationary variance. Output growth in the six countries became noticeably less volatile over the past few decades. In this paper, we employ the modified ICSS algorithm to detect structural change in the variance of output growth. One structural break exists in each of the six countries after identifying outliers and mean shifts in the growth rates. We then use generalized autoregressive conditional heteroskedasticity ( GARCH) specifications, modeling output growth and its volatility with and without the break in volatility. The evidence shows that the time-varying variance falls sharply in Canada and Japan, and disappears entirely in Germany, Italy, the U.K. and the U.S., once we incorporate the break in the variance equation of output for the six countries. That is, the integrated GARCH (IGARCH) effect proves spurious and the GARCH model demonstrates misspecification, if researchers neglect a nonstationary variance. Moreover, we also consider the possible effects of our more correct measure of output volatility on output growth as well as the reverse effect of output growth on its volatility. The conditional standard deviation possesses no statistical significance in all countries, except a significant negative effect in Japan. The lagged growth rate of output produces significant negative and positive effects on the conditional variances in Germany and Japan, respectively. No significant effects exist in Canada, Italy, the U.K., and the U.S.
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  • WenShwo Fang & Stephen M. Miller & ChunShen Lee, 2008. "Cross-Country Evidence On Output Growth Volatility: Nonstationary Variance And Garch Models," Scottish Journal of Political Economy, Scottish Economic Society, vol. 55(4), pages 509-541, September.
  • Handle: RePEc:bla:scotjp:v:55:y:2008:i:4:p:509-541
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    9. Esta Lestari, 2012. "Is Indonesia More Financially Linked To The World Since The Asian Financial Crises?," RIEBS, Economic Research Center, Indonesian Institute of Sciences (P2E-LIPI), vol. 3(2), pages 1-14, November.
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    12. Ahmad Zubaidi Baharumshah & Siew-Voon Soon, 2014. "Inflation, inflation uncertainty and output growth: what does the data say for Malaysia?," Journal of Economic Studies, Emerald Group Publishing, vol. 41(3), pages 370-386, May.

    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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