• Journal of Environmental Policy
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• v.12 no.3
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• pp.97-122
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• 2013

The ARDL(Autoregressive Distributed Lag) method is employed analyzes the long-run equilibrium relationships among environmental pollution($CO_2$ emissions) per capita, income levels per capita, and energy consumption per capita. The error correction model is employed to analyze the short-term effects of income and energy consumption on $CO_2$ emissions. The Toda-Yammamoto method is employed for causal analysis among the three variables. The results show that income levels, energy consumption, and $CO_2$ emissions are cointegrated. We found the N type relationship between income and $CO_2$ emissions. Long-term elasticities of income and energy consumption with respect to $CO_2$ emission were greater than their short-term elasticities. There were a bilateral causality between energy consumption and $CO_2$ emissions. There was a unilateral causality from $CO_2$ emissions to income and from energy consumption to income not vice versa. Energy consumption can be an important variable to contribute to forecasting $CO_2$ emissions.

• Culinary science and hospitality research
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• v.23 no.2
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• pp.126-134
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• 2017

The purpose of this paper was to examine the dynamics of the price discovery function between lean hog futures and spot markets using the vector error correction model (VECM). The researcher also investigated the existence of the long-run equilibrium relationship between the lean hog futures and spot markets. Daily time series data of lean hog futures and spot observed in the Korean market during the period from 5 Jan. 2011 to 28 Dec. 2012 were analyzed. To examine the price discovery, this study employed the Gonzalo and Granger's (1995) information ratio and Hasbrock's (1995) information ratio measurement method. The significant findings of the study are summarized as follows. First, lean hog futures and spot market are significantly correlated. Secondly, the lean hog future market plays a more dominant role in price discovery than the spot market. Finally, price discovery measures based on the VECM suggested that the lean hog future market plays a more dominant role in price discovery than the lean hog spot market. This is the important systematic empirical work to find the relationship between the lean hog future and spot market.

• The Korean Journal of Financial Management
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• v.23 no.1
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• pp.49-67
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• 2006

This study examines whether won/dollar futures have price discovery function and volatility spillover effect or not, using intraday won/dollar futures prices, volumes, and spot rates for the interval from March 2, 2005 through May 30, 2005. Futures prices and spot rates are non-stationary, but there is the cointegration relationship between two time series. Futures returns, spot returns, and volumes are stationary. Asymmetric effects on volatility in futures returns and spot returns does not exist. Analytical results of mean equations of the BGARCH-EC (bivariate GARCH-error correction) model show that the increase of futures returns raise spot returns after 5 minutes, which implies that futures returns lead spot returns and won/dollar futures have price discovery function. In addition, the long-run equilibrium relationship between the two returns could help forecast spot returns. Analytical results of variance equations indicate that short-run innovations in the futures market positively affect the conditional variances of spot returns, that is, there is the volatility spillover effect in the won/dollar futures market. A dummy variable of volumes does not have an effect on two returns but influences significantly on two conditional variances.

• 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.