• Korea Trade Review
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• v.47 no.4
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• pp.293-309
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• 2022

The purpose of this paper is to analyze the import and export volume of Jeollabuk-do to establish a plan to activiation Saemangeum New Port. To this end, this study utilized the HHI(Herfindahl-Hirschman Index), LQ(Location Quotient) analysis using the annual data set from the Korea Trade Statistics Promotion Institution between 2015 to 2020. As a result, it has been confirmed that the degree of export volume concentration (HHI (Herfindahl-Hirschman Index)) in Jeollabuk-do has been increasing over the past 5 years. According to results of LQ(Location Quotient) analysis, Brazil had the highest index in the case of exporting countries, and Meat, edible meat offal (HS 2) had the highest index in the case of export items. This paper is meaningful in analyzing the export structure using import and export volumes and proposing a plan to improve the competitiveness of Saemangeum New Port.

• Journal of Navigation and Port Research
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• v.33 no.4
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• pp.277-282
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• 2009

This paper estimated the container volumes for the Incheon port with univariate time series. As best suited models Winters' additive model, ARIMA model,and Winters' additive model were selected by import-export, coastal, and transshipment volume respectively, based on the data of monthly volume by October 2008 since January 2001. This study supposed the import-export container volumes would be decreased by 14% against that in 2008 and would have been recovered to the increasing trend of the volumes beyond the fourth quarter of 2010. The future import-export and transshipment volumes showed the increasing trend beyond 2011, while the coastal volumes would be on the stagnation. The yearly container volumes were finally forecasted as 1,705, 2,432, and 3,341 thousand TEU in 2011, 2015, and 2020 respectively.

• Journal of Korea Port Economic Association
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• v.32 no.3
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• pp.35-46
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• 2016

This study investigates the export behavior of Busan, Gwangyang and Incheon Port. The monthly data cover the period from January 2000 to December 2015. We employ six export functions composed of various exchange rates and industrial production index. This paper finds that the nominal effective exchange rate is more appropriate for explaining the export behaviors of the three ports, regardless of the narrow and wide indices which comprise 26 and 61 economies for the nominal and real indices respectively. This paper tests whether exchange rate and industrial production are stationary or not, rejecting the null hypothesis of a unit root in each of the level variables and of a unit root for the residuals from the cointegration at the 5 percent significance level. The error-correction model is estimated to find that both Gwangyang and Incheon ports are much slower than Busan port in adjusting the short-run disequilibrium and Gwangyang port is a little slower than Incheon port. The rolling regressions show that the influence of exchange rate as well as industrial production tends to decrease in all of three ports. The variance decomposition, however, shows that the export variables are very exogenous and the export of Busan Port is the least exogenous and that of Gwangyang Port the most. This result indicates that the economic variables such as exchange rate and economic activity affect the export of Busan Port more strongly than that of Gwangyang and Incheon Port.

• Journal of Korea Port Economic Association
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• v.31 no.3
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• pp.141-153
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• 2015

This paper is an attempt to analyze the comparative advantage of Busan Port to China. For this, we use the market comparative advantage index, which is a version of the revealed comparative advantage index. The market comparative advantage index (MCA) uses trade patterns to identify the sectors in which a region has a comparative advantage, in this case by comparing Busan Port's trade profile with the world average (China). The indices are calculated at the commodity level of the HS four-digit classification. The export data used in this study are obtained from the Korea International Trade Association. Exports to China accounted for almost one third of Korean exports in 2014. There are, however, structural differences among the main export items of Busan Port. This paper, therefore, employs MCA indices to reveal the behaviors of the ten main export items, which are "HS3920-other plates/sheets/film/foil of plastics," "HS7606-aluminum plates/sheets/strip," "HS8479-unspecified machines/medical appliances," "HS8486-machines for semiconductor devices or wafers," "HS8529-parts for transmission apparatus for television," "HS8703-motor vehicles for the transport of persons," "HS8708-parts of motor vehicles," "HS9001-optical fibers," and "HS9013-liquid crystal devices." The study shows that export competitiveness of nine items increases, the exception being HS8703. However, China's import ratios of seven of the nine items for which the MCA indices go up are on the decrease, which means that it would be hard to expand the export market for these seven items, despite the higher MCA indices. Since the shares of the port's total exports to China of HS3907, HS8486, HS8529, HS9001, and HS9013 in total exports to China increase together with China's import ratio decreasing, these items may have promising export markets. MCA increases of HS7606 and HS8479 are attributable to China's lower import ratio, rather than a higher export share, so higher MCA indices do not guarantee higher export competitiveness for these items.

• Journal of Korean Port Research
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• v.11 no.2
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• pp.145-156
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• 1997

The purpose in this study is development of model for the Container Terminals of Pusan Port, First of all, Quantitive and Qualititve factors are characterized which effects on Physical Distribution System in Container Terminals. The System Dynamics method is used to develope the model by using these factor. This model is able to present the timinig of investment in Container Terminals of Pusan Port. Six models are showed by change of parameters in System Dynamics, in this paper. In the model, Five feedback loop were found. Loop 1 : Number of Liners$\rightarrow$Number of Congested ships$\rightarrow$Port's Charges$\rightarrow$Export & Import Cargo Volumes$\rightarrow$Number of Liners$\rightarrow$The will to investment of government$\rightarrow$Length of berth→Number of Liners. Negative loop was acquired. Loop 2 : Port's Charge$\rightarrow$Economic of Port$\rightarrow$The will to Private management$\rightarrow$Efficiency for Port's Operation$\rightarrow$Port's Charges. Positive loop was acquired. Loop 3 : Number of Congested ships$\rightarrow$Planning for future development$\rightarrow$Information Service$\rightarrow$Support service for port's user$\rightarrow$Number of Congested ships. Negative loop was acquired. Loop 4 : Number of Congested ships$\rightarrow$Planning for future development$\rightarrow$Extent of stacking area$\rightarrow$Number of handling equipmint$\rightarrow$Number of Congested ships. Negative loop was acquired. Loop 5 : Export & Import Cargo Volumes$\rightarrow$Number of Liners$\rightarrow$Econmic of Port$\rightarrow$Support service for port's user$\rightarrow$Export & Import Cargo Volumes. Positive loop was acquired. System's level variables were selected as followings ; Number of Liners, Number of Congested ships, Export & Import Carge Volumes, Length of berth, and Port's Charges. As result of simmulation of model, fluctuation of respective year was found in level variables. This fluctuation can be used properly to present timing of investment.

• Journal of Korea Port Economic Association
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• v.30 no.2
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• pp.133-143
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• 2014

The paper uses a panel gravity model to analyse the determinants of export via Gwangyang port for the period from 2000-2012. The gravity model includes export via Gwangyang port, GDP and population of trading partners, the distances between Korea and its partners, and Korea-ASEAN FTA dummy. Hausman test shows up which one is exactly appropriate between random effect estimation and fixed effect estimation to use panel dataset. It depends on whether or not existence or nonexistence of the correlation between unobserved omitted factors and variables. Fixed effect estimation is suitable for this paper by the rejection of null hypothesis. An Empirical analysis of this paper shows GDP influences positive effects and distance influences negative effects to Gwangyang port trading partners. In addition, the results strongly supported the effects of Korea-ASEAN FTA on the growth of Gwangyang port export.

• Korea Trade Review
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• v.46 no.1
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• pp.83-111
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• 2021

This paper conducts a Structural Dcomposition Analysis on the structure of factors contributing to the output growth of Korean Maritime and Port Industry during year 2000~ year 2017. Some of results are as follows. The output growth rates of the industry (yearly average 4.3%) was far lower than the average growth rates of Service as well as of Manufacturing Industries (yearly average 9% and 6.8%, respectively) due to the lower output growth of Maritime Industry. Among the growth contributing factors, change in domestic demand for final goods is the first contributing factor, and then change in technology, change in export and import substitution for intermediate goods are followed in order, but import substitution for final goods decreased its output. However, in each respective sub-periods of pre-global financial crisis and post-global financial crisis, change in the export, especially change in the export of Maritime Industry is the dominant determinant of output change in the Maritime and Port Industry in opposite ways. In the periods of the former the increase in the export of Maritime Industry overwhelmingly led the output growth of the Maritime and Port industry, but in the periods of the latter the decrease in its export was the culprit of lower output growth of the industry. On the other hand, among all industries of service and manufacturing sectors, Wholesale and Retail industry is the leading industry in contributing to the output growth of the Maritime and Port Industry, and Transportation Equipment industry is the leading industry among all manufacturing industries.

• Journal of Korea Port Economic Association
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• v.29 no.2
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• pp.239-253
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• 2013

Changes of a port's market share in the exports of domestic ports result from many interrelated factors. Therefore, the analysis of the export performance of a port should be put in perspective by analysing long periods to identify trends. This paper aims to show the development of competitiveness, product and geographical structure of the Busan Port's merchandise exports from 1995 to 2012 using constant-market shares (CMS) analysis. This article is relevant for Busan port because its export market shares have been showing disappointing path. The dynamic consideration of the CMS analysis, which the static indicators have been replaced by time series, helps to track all changes in the export structure and competitiveness of the Busan port over time. The long-term trend of the indicators suggests that it may be very hard for the Busan port to maintain its market share in the global environment. The advantage in competitiveness of the Busan port has vanished and the product and geographical structure effects show negative trends after 1995, pointing to vulnerability in the Busan port's exports.

• Journal of Korea Port Economic Association
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• v.25 no.1
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• pp.1-14
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• 2009

This study predicted Port trade volume by considering Korea's export to China and import Com China separately using ARIMA model (Multiplicative Seasonal ARIMA Model). We predicted monthly Port trade volumes for 27 months from October 2008 to December 2010 using monthly data from September 2008 to January 2001 using monthly data. As a result of prediction, we found that the export volume decreased in January, February, August and September while the import volume decreased in February, March, August and September. As the decrease period was clearly differentiated, it was possible to predict export and import volumes. Therefore, it is believed that the results of this study will generate useful basic data for policy makers or those working for export and import enterprises when they set up policies and management plans. And to improve competitive power of Port trade, this study suggests privatization of Port, improvement of information capability, improvement of competitive power of Port management companies, support for Port distribution companies, plans for active encouragement of transshipment, and management of added value creation policy.

• Journal of Korea Port Economic Association
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• v.25 no.2
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• pp.115-128
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• 2009

This study aims to identify the influence of exchange rate and national economy on Export through container ports (Busan Port, Incheon Port, Gwangyang Port, and Pyeongtaek Port) from January 2001 to October 2007. This study carried a unit root test on the results of the analysis and failed to reject the null hypothesis that level variables have a unit root at the level of 1%. However, it carried out a unit root test on the variables by the first order difference and succeeded in rejecting the null hypothesis aforementioned at the level of 1%. As a result of the cointegration test, it was found that the model is stable. When this study carried out a variance decomposition on the prediction error of export at container various container ports, it found 89% for Busan Port, 83% for Incheon Port, 86% for Gwangyang Port, and 84% for Pyeongtaek Port. These figures indicate that such variables significantly account for export at container ports. For Busan Port, Step 2 of exchange rate showed negative (-) effect, and Step 3 shows an extreme transition into a positive (+) effect. The national economy showed an extreme change from Steps 2 to Step 7, and then a positive effect has been maintained. The Incheon Port, Gwangyang Port and Pyeongtaek Port showed similar trends to Busan Port. From Step 7, it seems that they have Shifted to more stable trends.