A comparison of the executive leadership of Mikhail Gorbachev and Ronald Reagan

Abstract

This article estimates firm mark-ups to evaluate market competition in Korean manufacturing industries for the period of 1982–2004 and analyzes how the mark-ups differ across industry sectors. For the manufacturing sector as a whole, our results lead us to reject the null hypothesis of a competitive market, although market imperfection varies across industry sectors. Meanwhile, the parameter for union bargaining power over firm profit was much smaller than those found in the previous studies and insignificant in some industry sectors. Our firm-level results indicate that intra-industry variation in mark-ups and returns to scale is greater than inter-industry variation as shown in the sector analysis. Also, we find that mark-ups respond counter-cyclically to aggregate demand shocks and that the magnitudes of responses differ from industry to industry.     

The threshold effect in expected volatility: a model based on asymmetric information

This article develops theoretical insight into the thresholdeffect in expected volatility, which means that large shocksare less persistent in volatility than small shocks. The modeluses the Kyle-Admati-Pfleiderer setup with liquidity traders,informed traders, and a market maker. Information is modeledas a GARCH process. It is shown that the GARCH process for informationis transformed into a TARCH process (for 'threshold GARCH')for the market price changes. Working with information flowsallows one to derive implications for trading volume and marketliquidity which provide the basis for a more complete test ofthe model.     

Extreme Correlation of International Equity Markets

Testing the hypothesis that international equity market correlation increases in volatile times is a difficult exercise and misleading results have often been reported in the past because of a spurious relationship between correlation and volatility. Using "extreme value theory" to model the multivariate distribution tails, we derive the distribution of extreme correlation for a wide class of return distributions. Empirically, we reject the null hypothesis of multivariate normality for the negative tail, but not for the positive tail. We also find that correlation is not related to market volatility per se but to the market trend. Correlation increases in bear markets, but not in bull markets.