• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 1993.05a
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• pp.101-105
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• 1993

국내 천연가스 공급가격을 산정하기 위해 천연가스 가격책정 모형을 이용하여 한국가스공사 공급가격과 도시가스회사 공급가격을 구하고 도출된 결과를 분석하였다. 분석결과에 의하면 LNG를 전량 수입하는 국내 상황에서 천연가스가격은 외부조건과 기술여건에 상당히 민감하다는 것을 알 수 있었다. 또한 모형에서 구한 가격을 현행 소비자가격과 비교하였을 때 모형에 의해서 도출된 가격이 다소 높이 책정되었으며, Peak 기간과 Off Peak 기간에 뚜렷한 가격격차를 나타내었다.

• Environmental and Resource Economics Review
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• v.17 no.2
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• pp.313-326
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• 2008

This paper is concerned with the effect of an increase in the import price of LNG on the Korean economy and industries. A computable general equilibrium analysis is applied to compute the comparative-statical effect of 10% rise of LNG price. The price increase places relatively heavy burden on the city gas, oil products and thermal power, decreasing their outputs and domestic sales by relatively larger percentages than other industries. The 10% increase in the LNG price reduces GDP by 0.4% and raises the general price level by 0.08%. The increase in oil price resulting in the same decreasing rate of GDP caused by the 10% LNG price rise turns out to raise the general price level and reduce the consumer's welfare in terms of equivalent variation by less percentage than the increase in LNG price.

• Journal of the Korean Data and Information Science Society
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• v.22 no.3
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• pp.401-412
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• 2011

This study uses a vector error correction model to analyze the daily time series data of the spot price of EUA (European Union Allowance). As endogenous variables, five variables are considered for the analysis, including prices of crude oil, natural gas, electricity and coal in addition to carbon price. Data period is Phase 2 period (April 21, 2008 to March 31, 2010) to avoid Phase 1 period (2005-2007) where the EUA prices were distorted. Unit-root and cointegration test results reveal that all variables have a unit root and cointegration vectors exist, so a vector error correction model is adopted instead of a vector autoregressive model.

• LP가스
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• v.20 no.4
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• pp.38-46
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• 2008

최근 경유, LPG 등 유류가격 급등으로 상대적으로 저렴한 천연가스를 연료로 하는 천연가스자동차에 대한 관심이 높아지고 있다. 정부 또한 천연가스자동차 보급 확대를 위한 정책을 속속 내놓고 있다. 이에 천연가스자동차에 대한 전반적인 현황을 요약 정리하여 게재한다.

• Journal of Energy Engineering
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• v.8 no.1
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• pp.166-173
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• 1999

본 연구는 램지가격결정방식과 효율적요소가격결정방식을 이용하여 향후 국내 가스산업의 배관망공동이용시 발전용 천연가스의 가격 및 이용료 수준을 파악할 수 있는 천연가스 가격 결정의 이론적 모형을 도출하였다. 또한 사례분석을 통하여 램지가격결정방식(RCPR)과 효율적요소가격결정방식(ECPR)하에서 도출된 최적 가격 및 최적 이용료를 비교·분석하였고 결정변수들이 가격과 이용료에 미치는 영향에 대해서 분석하였다. 그 결과 RCPR에 의한 최적 이용료는 쿠르노 불완전 경쟁하에서 한계직접비용 보다 낮게 도출된데 반해서 ECPR에서는 한계직접비용보다 높게 도출됨으로써 가격결정방식에 따라 최적 이용료의 수준이 상이함을 보였다. 또한 도시가스용 및 발전용 가격은 RCPR 하에서 신규사업자 수가 증가할수록 하락하였고 이용료는 증가하여 한계비용에 접근하였다. 한편 최적 발전용 가격과 최적 이용료는 한계직접비용이 클수록 증가되었고, 역가격탄력성이 클수록 최적 발전용 가격은 증가하는 반면에 최적 이용료는 감소하였다.

• Environmental and Resource Economics Review
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• v.15 no.5
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• pp.799-826
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• 2006

Combining recent advances in causal flows with time series analysis, relationships among eight North American natural gas spot market prices are examined. Results indicate that price discovery tends to occur in excess demand regions and move to excess supply regions. Across North America, the U.S. Midwest region represented by Chicago spot market is the most important market for price discovery. The Ellisburg-Leidy Hub in Pennsylvania is important in price discovery, especially for markets in the eastern two-thirds of the U.S. Malin Hub in Oregon is important for the western markets including the AECO Hub in Alberta, Canada.

• Environmental and Resource Economics Review
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• v.8 no.2
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• pp.245-269
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• 1999

향후 기후변화협약과 같은 환경규제의 강화가 예견되는 상황에서 에너지산업은 상당한 정책변화를 겪게 될 것으로 예상된다. 이러한 정책수립과 결정과정에서 본 연구는 천연가스산업에 대한 정책변화 효과를 분석할 수 있는 일반균형 분석모형을 제시함으로써 천연가스산업에 관한 유용한 정보를 제공할 수 있을 것으로 기대된다. 소국경제를 가정한 연산가능 일반균형모형(CGE)을 통해 분석된 천연가스산업의 거시경제적 파급효과를 살펴보면 다음과 같다. 먼저, 천연가스 가격이 5% 상승하였을 경우에는 실질GDP가 0.031% 감소하고, 생산자 물가지수는 0.051% 상승하였다. 가계수요가 10% 증가한 경우와 투자가 10% 증가한 경우에는 실질 GDP가 각각 0.002%씩 상승하고 생산자 물가지수는 0.008%와 0.004% 상승하는 것으로 나타났다. 이러한 분석결과는 천연가스산업이 비교적 거시경제에 미치는 영향이 적은 것을 보여 주고 있다.

• Environmental and Resource Economics Review
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• v.17 no.4
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• pp.751-774
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• 2008

In this paper, we examine the institutional prices differences in the electricity and natural gas industries using unbalanced panel data from 1999 to 2001. The changing market structures following deregulation in both markets allow us to examine the institutional prices differences by ownership type, market structure and merger activities. Estimating the reduced form, after controlling both intrinsic characteristic (marginal costs) and external factors (demand), allows us to identify the extent to which specific factors are correlated with the price. Furthermore it allows us to identify systematic institutional price differences in both electricity and natural gas markets. Our estimation results suggest that the private firms in electricity markets are associated with higher prices than public firms after controlling for demand and cost. We further find that dual-product firms in the natural gas industry and the electricity industry are associated with lower rates than single product firms. These results provide a weak evidence of economies of scope in the dual-product firms. Our results finally suggest that merger activities in natural gas markets are associated with higher rates.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.453-459
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• 2021

The system marginal price of electricity is the amount paid to all the generating units, which is an important decision-making factor for the construction and maintenance of an electrical power unit. In this paper, we suggest a long-term forecasting model for calculating the system marginal price based on prices of natural gas and oil. As most variables used in the analysis are nonstationary time series, the long run relationship among the variables should be examined by cointegration tests. The forecasting model is similar to an error correction model which consists of a long run cointegrating equation and another equation for short run dynamics. To mitigate the robustness issue arising from the relatively small data sample, this study employs various testing and estimating methods. Compared to previous studies, this paper considers multiple fuel prices in the forecasting model of system marginal price, and provides greater emphasis on the robustness of analysis. As none of the cointegrating relations associated with system marginal price, natural gas price and oil price are excluded, three error correction models are estimated. Considering the root mean squared error and mean absolute error, the model based on the cointegrating relation between system marginal price and natural gas price performs best in the out-of-sample forecast.

• Environmental and Resource Economics Review
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• v.29 no.2
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• pp.145-170
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• 2020

This study analyzes the dependence structure between energy (crude oil, natural gas, coal) prices and economic (real and financial) uncertainty. Summary of the results of the dependence structure between energy prices and economic uncertainty analysis is as follows. First, the results of model selection show that the BB7 copula model for the pair of crude oil price and economic uncertainty, the Joe copula model for the pair of natural gas price and economic uncertainty, and the Clayton copula model for the pair of coal price and economic uncertainty were chosen. Second, looking at the dependency structure, it showed that the pair of energy (crude oil, natural gas, coal) prices and real market uncertainty show positive dependence. Whereas, the only pair of financial market uncertainty-crude oil price shows positive dependency. In particular, crude oil price was found to have the greatest dependence on economic uncertainty. Third, looking at the results of tail dependency, the pair of real market uncertainty-crude oil price and pair of real market uncertainty-natural gas price have an asymmetric relationship with the upper tail dependency. It can be seen that the only pair of financial market uncertainty-crude oil represents asymmetric relationships with the upper tail dependencies. In other words, combinations with asymmetric relationships have shown strong dependence when negative extreme events occur. On the other hand, tail dependence between economic uncertainty and coal price be not found.