• KDI Journal of Economic Policy
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• v.28 no.2
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• pp.131-177
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• 2006

This paper examines a simultaneous determination of corporate control mechanisms, and its effects on firm performance. The corporate control mechanisms considered include the following; insider shareholding, institutional shareholding, the board of directors, dividend policy, and capital structure. This paper applies a simultaneous equation methodology and investigates the interdependence among the corporate control mechanisms. In the first part, the paper finds that firm-level variations of control mechanisms are large across time although average variations are relatively small. These variations are related to one another, which is confirmed by Granger causality test based on dynamic panel autoregression model. More specifically insider shareholding, institutional shareholding and outside director ratio cause each other. With regard to interdependence among the control mechanisms, 2SLS(two stage least squares) regression results show that insider shareholding and institutional shareholding are substitutes while institutional shareholding acts as complements to the ratio of outside members in the board of directors. Then in the second part, the paper examines the relationship between firm performance and corporate governance. Firm performance, measured by Tobin's Q, has a positive association with leverage ratio while that has a negative relation to outside director ratio. This suggests that there may be a room for reforming corporate governance in Korea. Specifically it is necessary to enhance the independence of the outside directors.

• Journal of Korea Port Economic Association
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• v.38 no.4
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• pp.107-118
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• 2022

In this study, daily data from January 2002 to June 2022 were used to investigate the relationship between risk-return relationship and market fear, uncertainty, stock market, and maritime freight index for the crude oil market. For this study, the time varying EGARCH-M model was applied to the risk-return relationship, and the wavelet consistency model was used to analyze the relationship between market fear, uncertainty, stock market, and maritime freight index. The analysis results of this study are as follows. First, according to the results of the time-varying risk-return relationship, the crude oil market was found to be related to high returns and high risks. Second, the results of correlation and Granger causality test, it was found that there was a weak correlation between the risk-return relationship and VIX, EPU, S&P500, and BDI. In addition, it was found that there was no two-way causal relationship in the risk-return relationship with EPU and S&P500, but VIX and BDI were found to affect the risk-return relationship. Third, looking at the results of wavelet coherence, it was found that the degree of the risk-return relationship and the relationship between VIX, EPU, S&P500, and BDI was time-varying. In particular, it was found that the relationship between each other was high before and after the crisis period (financial crisis, COVID-19). And it was found to be highly associated with organs. In addition, the risk-return relationship was found to have a positive relationship with VIX and EPU, and a negative relationship with S&P500 and BDI. Therefore, market participants should be well aware of economic environmental changes when making decisions.

• Korea Trade Review
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• v.48 no.3
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• pp.69-88
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• 2023

This study analyzes the dynamic characteristics of cargo volume (demand), ship fleet (supply), and freight rate (price) of container, dry bulk, and tanker shipping markets by using the VAR and VECM models. This analysis is expected to enhance the statistical understanding of market dynamics, which is perceived by the actual experiences of market participants. The common statistical patterns, which are all shown in the three shipping markets, are as follows: 1) The Granger-causality test reveals that the past increase of fleet variable induces the present decrease of freight rate variable. 2) The impulse-response analysis shows that cargo shock increases the freight rate but fleet shock decreases the freight rate. 3) Among the three cargo, fleet, and freight rate shocks, the freight rate shock is overwhelmingly largest. 4) The comparison of adjR² reveals that the fleet variable is most explained by the endogenous variables, i.e., cargo, fleet, and freight rate in each of shipping markets. 5) The estimation of co-integrating vectors shows that the increase of cargo increases the freight rate but the increase of fleet decreases the freight rate. 6) The estimation of adjustment speed demonstrates that the past-period positive deviation from the long-run equilibrium freight rate induces the decrease of present freight rate.