Modeling the Volatility of Real GDP Growth: The Case of Japan Revisited

Previous studies (e.g., Hamori, 2000; Ho and Tsui, 2003; Fountas et al., 2004) find high volatility persistence of economic growth rates using generalized autoregressive conditional heteroskedasticity (GARCH) specifications. This paper reexamines the Japanese case, using the same approach and showing that this finding of high volatility persistence reflects the Great Moderation, which features a sharp decline in the variance as well as two falls in the mean of the growth rates identified by Bai and Perronâs (1998, 2003) multiple structural change test. Our empirical results provide new evidence. First, excess kurtosis drops substantially or disappears in the GARCH or exponential GARCH model that corrects for an additive outlier. Second, using the outlier-corrected data, the integrated GARCH effect or high volatility persistence remains in the specification once we introduce intercept-shift dummies into the mean equation. Third, the time-varying variance falls sharply, only when we incorporate the break in the variance equation. Fourth, the ARCH in mean model finds no effects of our more correct measure of output volatility on output growth or of output growth on its volatility.

Cross-Country Evidence on Output Growth Volatility: Nonstationary Variance and GARCH Models

This paper revisits the issue of conditional volatility in real GDP growth rates for Canada, 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 four 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 unconditional variance of output growth. One structural break exists in each of the four countries. 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, Japan, and the U.K. and disappears in the U.S., excess kurtosis vanishes in Canada, Japan, and the U.S. and drops substantially in the U.K., once we incorporate the break in the variance equation of output for the four countries. That is, the integrated GARCH (IGARCH) effect proves spurious and the GARCH model demonstrates misspecification, if researchers neglect a nonstationary unconditional variance.

Last Hired, First Fired? Black-White Unemployment and the Business Cycle

Past studies have tested the claim that blacks are the last hired during periods of economic growth and the first fired in recessions by examining the movement of relative unemployment rates over the business cycle. Any conclusion drawn from this type of analysis must be viewed as tentative because the cyclical movements in the underlying transitions into and out of unemployment are not examined. Using Current Population Survey data matched across adjacent months from 1989 to 2004, this paper examines labor market transitions for prime age males to test this hypothesis. Considerable evidence is presented that blacks are the first fired as the business cycle weakens. However, no evidence is found that blacks are the last hired. Instead, blacks are initially hired from the ranks of the unemployed early in the business cycle and later are drawn from non-participation. Narrowing of the racial unemployment gap near the peak of the business cycle is driven by a reduction in the rate of job loss for blacks rather than increases in hiring. There is also evidence that residual differences in the racial unemployment gap vary systematically over the business cycle in a manner consistent with discrimination being more evident in the economy at times when its cost is lower.