• Communications for Statistical Applications and Methods
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• v.29 no.1
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• pp.41-51
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• 2022

We forecast the US oil consumption level taking advantage of google trends. The google trends are the search volumes of the specific search terms that people search on google. We focus on whether proper selection of google trend terms leads to an improvement in forecast performance for oil consumption. As the forecast models, we consider the least absolute shrinkage and selection operator (LASSO) regression and the structured regularization method for large vector autoregressive (VAR-L) model of Nicholson et al. (2017), which select automatically the google trend terms and the lags of the predictors. An out-of-sample forecast comparison reveals that reducing the high dimensional google trend data set to a low-dimensional data set by the LASSO and the VAR-L models produces better forecast performance for oil consumption compared to the frequently-used forecast models such as the autoregressive model, the autoregressive distributed lag model and the vector error correction model.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.27 no.1
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• pp.43-50
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• 2019

The aviation demand forecast field has been actively studied along with the recent growth of the aviation market. In this study, the demand for domestic passenger demand and freight demand was estimated through cross-validation method. As a result, passenger demand is influenced by private consumption growth rate, oil price, and exchange rate. Freight demand is affected by GDP per capita, private consumption growth rate, and oil price. In particular, passenger demand is characterized by temporary external shocks, and freight demand is more affected by economic variables than temporary shocks.

• Environmental and Resource Economics Review
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• v.26 no.4
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• pp.519-547
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• 2017

This paper explores whether it is better to forecast city gas demand in Korea using national level data directly or, alternatively, construct forecasts from regional demand models and then aggregate these regional forecasts. In the regional model, we consider gas demand for Seoul metropolitan and the other local areas. Our forecast evaluation exercise for 2013-2016 shows the regional forecast model generally outperforms the national forecasting model. This result comes from the fact that the dynamic properties of each region's gas demands can be better taken into account in the regional demand model. More specifically, the share of residential gas demand in the Seoul metropolitan area is above 50%, and subsequently this demand is heavily influenced by temperature fluctuations. Conversely, the dominant portion of regional gas demand is due to industrial gas consumption. Moreover, electricity is regarded as a substitute for city gas in the residential sector, and industrial gas competes with certain oil products. Our empirical results show that a regional demand forecast model can be an effective alternative to the demand model based on nation-wide gas consumption and that regional information about gas demand is also useful for analyzing sectoral gas consumption.

• Journal of Korea Port Economic Association
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• v.33 no.1
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• pp.75-87
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• 2017

The purpose of this study is to utilize the system dynamics to carry out a medium and long-term forecasting analysis of the bunker price. In order to secure accurate bunker price forecast, a quantitative analysis was established based on the casual loop diagram between various variables that affects bunker price. Based on various configuration variables such as crude oil price which affects crude oil consumption & production, GDP and exchange rate which influences economic changes and freight rate which is decided by supply and demand in shipping and logistic market were used in accordance with System Dynamics to forecast bunker price and then objectivity was verified through MAPEs. Based on the result of this study, bunker price is expected to rise until 2029 compared to 2016 but it will not be near the surge sighted in 2012. This study holds value in two ways. First, it supports shipping companies to efficiently manage its fleet, offering comprehensive bunker price risk management by presenting structural relationship between various variables affecting bunker price. Second, rational result derived from bunker price forecast by utilizing dynamic casual loop between various variables.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.360-365
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• 2003

In this paper, GMDH(Croup Method of Data Handling) algorithm which is proved to be more excellent in efficiency and accuracy of practical use of data is applied to electric power demand forecasting. As a result, it became much easier to make a choice of input data and make an exact prediction based on a lot of data. Also, we considered both economy factors(GDP, export, import, number of employee, number of economically active population and consumption of oil) and climate factors(average temperature) when forecasting. We assumed target forecast period from first quarter 1999 to first quarter 2001, and suggested more accurate forecasting method of electric power demand by using 3-step computer simulation processes(first process for selecting optimum input period, second for analyzing time relation of input data and forecast value, and third for optimizing input data) for improvement of forecast precision. The proposed method can get 0.96 percent of mean error rate at target forecast period.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.27 no.3
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• pp.98-105
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• 2019

In the past 30 years, our aviation demand has been growing continuously. As such, the importance of the demand forecasting field is increasing. In this study, the factors influencing Korea's international air demand were selected, and the international air demand was analyzed, forecasted and reviewed through OLS multiple regression analysis. As a result, passenger demand was affected by GDP per capita, oil price and exchange rate, while cargo demand was affected by GDP per capita and private consumption growth rate. In particular, passenger demand was analyzed to be sensitive to temporary external shocks, and cargo demand was more affected by economic variables than temporary external shocks. Demand forecasting, OLS multiple regression analysis, passenger demand, cargo demand, transient external shocks, economic variables.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2006.06a
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• pp.189-192
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• 2006

For the safety and efficiency of voyage, the demand for decision support system in route planning has been increasing with the advance of information technology and the increase of oil price. According to the needs, the authors developed an optimum route assessment system. The system assists an navigator to make an optimum route plan with respect to sailing time and fuel consumption using weather forecast data. Also, the system provides the quantitative estimation for the various safety indexes including parametric roll and etc. Using these functions, a navigator is able to design the safe and efficient voyage plan. The effectiveness of system were verified by the operation during actual voyages and the simulation studies.

• International Commerce and Information Review
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• v.15 no.3
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• pp.313-332
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• 2013

Large tundra of the Russian Empire, has rich resources and science and technology, and a huge domestic market potential is rapidly changing. Based on the abundant energy resources such as oil, gas, and minerals, as foreign trade is active, the huge capital is moving. And commitment the active SOC by improving laws and regulations and changes in the structure of the Russian economy. One of them pushed the WTO since 1993, 19 years to see fruition join the WTO (World Trade Organization). As the official entry into force August 22, Russia, July 10, 2012, Congress passed the treaty after joining the WTO and of the 156th WTO member countries, was officially join. As the WTO, Russia has the world's 11th-largest economy in the steel tariffs from 30% to 15% are exported to Russia, South Korea Car TV parts from 10% to 0%, reduced from 20% to 5% Korean export companies to export to Russia, etc., is expected to become the new land of opportunity. Russia hopes the changes improve the investment environment, the service industry, manufacturing revitalization the macroeconomic sectors of the economy through the WTO, and forecast, but the consumption increased revenue due to tariff cuts, falling import prices and the real economy, and weak manufacturing base. On the one hand, the perspective of concern. In conclusion, Russia joining the WTO, and the feed to improve the fairness and transparency of the market opening, the Russian advance in Korean companies be facilitated and strong complementary cooperation, especially in manufacturing is expected. In this paper, after Russia joining the WTO, trade liberalization, and ready for a new era of economic cooperation between Korea and Russia, at the point of expanding openness to propose strategies to analyze the problems of Korean companies during the Russian advance.