• The Journal of shipping and logistics
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• v.35 no.1
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• pp.93-109
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• 2019

This study applied the statistically significant factors to the short-run model in the existing nonlinear long-run equilibrium relation analysis for the forecasting of maritime economy using the mixed cycle model. The most common univariate AR(1) model and out-of-sample forecasting are compared with the root mean squared forecasting error from the mixed-frequency model, and the prediction power of the mixed-frequency approach is confirmed to be better than the AR(1) model. The empirical results from the analysis suggest that the new approach of high-level mixed frequency model is a useful for forecasting marine industry. It is consistent that the inclusion of more information, such as higher frequency, in the analysis of long-run equilibrium framework is likely to improve the forecasting power of short-run models in multivariate time series analysis.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.07a
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• pp.208-210
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• 2015

항만의 연결기능이 확대됨에 따라 해운 항만산업은 전문화 및 고도화되었으며, 이에 따른 인적자원의 양적 질적 경쟁력 향상도 무엇보다 중요해졌다. 하지만 이를 육성하고 발전시키기 위한 인적자원의 수급에 대해서는 시장기능이 원활이 작동하지 못하고 있으며, 이러한 연구도 부족한 실정이다. 따라서 본 연구에서는 해당산업통계자료를 바탕으로 회귀모형에 의한 해운 항만물류산업에 필요한 전문인력에 대한 정확한 예측을 제시하고자 한다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.63-65
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• 2023

한국 경제에 근간이 되는 산업은 제조업이고, 그중 석유화학산업은 전량 원유를 수입하여 우리나라의 기술력으로 가공하여 재수출하는 전략적 성장 산업이다. 수많은 제조업의 원료가 되는 원유를 전량 해상운송을 통해 수입하는 우리나라는 변동성이 심한 유조선 운임 시장에 대해 기민하게 대응해야 한다. 유조선 운임 시장의 위기는 관련 해운회사의 위기에서 끝나지 않고 원유를 사용하는 산업에서부터 국민의 생활까지 영향을 미칠 수 있으므로, 본 연구에서 신호접근법을 활용한 조기경보모형을 제시했다. BDTI 운임지수를 활용하여 유조선 해운시장 위기를 정의하고, 38개의 거시경제, 금융, 원자재 지표 그리고 해운시장 데이터를 활용해 시차상관관계를 분석하여 유조선 해운시장 위기에 선행적으로 반응하는 종합선행지수를 도출했다. 연구 결과, 종합선행지수는 두 달 전 가장 높은 0.499의 시차상관계수 값을 가졌으며, 5개월 전부터 유의미한 상관계수 값을 나타냈다. 더불어 QPS 값은 0.13으로 위기 예측에 대해 높은 정확성을 지니는 것으로 검증됐다.

• Journal of Korea Port Economic Association
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• v.29 no.1
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• pp.67-76
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• 2013

It has been more than four years since the outbreak of global financial crisis. However, the world economy continues to be challenged with new crisis such as the European debt crisis and the fiscal cliff issue of the U.S. The global economic environment remains fragile and prone to further disappointment, although the balance of risks is now less skewed to the downside than it has been in recent years. It's no wonder that maritime business will be bearish since the global business affects the maritime business directly as well as indirectly. This paper, hence, aims to predict the Baltic Dry Index representing the shipping business using the ARIMA-type models and Hodrick-Prescott filtering technique. The monthly data cover the period January 2000 through January 2013. The out-of-sample forecasting performance is measured by three summary statistics: root mean squared percent error, mean absolute percent error and mean percent error. These forecasting performances are also compared with those of the random walk model. This study shows that the ARIMA models including Intervention-ARIMA have lower rmse than random walk model. This means that it's appropriate to forecast BDI using the ARIMA models. This paper predicts that the shipping market will be more bearish in 2013 than the year 2012. These pessimistic ex-ante forecasts are supported by the Hodrick-Prescott filtering technique.

• Journal of Korea Port Economic Association
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• v.39 no.2
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• pp.97-110
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• 2023

This study examines the effect of macroeconomic shocks on the financial stability of the Korean shipping industry. Using Firth logistic regression model, this study estimates the default probability of a shipping company. The results from a default prediction model suggest that total assets are negatively correlated with default probability, while total debt is positively correlated with default probability. Based on the results from a default prediction model, this study investigates the effect of macroeconomic shocks, namely total assets, sales, and total debt shocks, on a shipping company's default probability. The stress test results indicate that a decrease in sales and total assets significantly deteriorates the financial stability of a shipping company.

• Journal of Korea Port Economic Association
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• v.26 no.4
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• pp.207-218
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• 2010

The purpose of the study is to predict the shipping business during the period of 2011 using the ARIMA-type models. This include the ARIMA and Intervention-ARIMA models. The multivariate cause-effect econometric model is not employed for not assuring a higher degree of forecasting accuracy than the univariate variable model. Such a cause-effect econometric model also fails in adjusting itself for the post-sample. This article introduces the four ARIMA models and six Intervention-ARIMA models. The monthly data cover the period January 2000 through October 2010. The out-of-sample forecasting performance is compared between the ARIMA-type models and the random walk model. Forecasting performance is measured by three summary statistics: root mean squared percent error, mean absolute percent error and mean percent error. The root mean squared percent errors of all the ARIMA-type models are somewhat higher than normally expected. Furthermore, the random walk model outperforms all the ARIMA-type models. This reveals that the BDI is just a random walk phenomenon and it's meaningless to predict the BDI using various econometric techniques. The ARIMA-type models show that the shipping market is expected to be bearish in 2011. These pessimistic ex-ante forecasts are supported by the Hodrick-Prescott filtering technique.

• Journal of Navigation and Port Research
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• v.47 no.3
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• pp.155-166
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• 2023

Trend analysis and time series analysis were conducted to predict the demand of manpower under the smartization of shipping and port logistics with transportation survey data of Statistic Korea during the period from 2000 to 2020 and Statistical Yearbook data of Korean Seafarers from 2004 to 2021. A linear regression model was adopted since the validity of the model was evaluated as the highest in forecasting manpower demand in the shipping and port logistics industry. As a result of forecasting the demand of manpower in autonomous ship, remote ship management, smart shipping business, smart port, smart warehouse, and port logistics service from 2021 to 2035, the demand for smart shipping and port logistics personnel was predicted to increase to 8,953 in 2023, 20,688 in 2030, and 26,557 in 2035. This study aimed to increase the predictability of manpower demand through objective estimation analysis, which has been rarely conducted in the smart shipping and port logistics industry. Finally, the result of this research may help establish future strategies for human resource development for professionals in smart shipping and port logistics by utilizing the demand forecasting model described in this paper.

• 해운
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• s.102
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• pp.8-19
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• 2013

현재 해운시장은 유럽 재정위기 장기화 신흥국 실물경기 둔화 확대 등으로 인해 회복이 지연되고 있으며, 주요 해운시황 예측기관들은 시장 회복시기를 2014년~2015년 이후로 예상되고 있다. 2013년 해운시황은 전년에 비해 소폭 개선될 전망이나 공급과잉 부담으로 2015년 이후 L자형의 완만한 회복세를 보일 전망이다. 또한, 시황 회복 시 선종별 상위선사들을 중심으로 수익이 집중화될 가능성이 언급되고 있으며, 상위 선사들을 중심으로 승자독식 체제가 형성이 우려되고 있다. 다음은 KDB산업은행 경제연구소에서 발표한 "컨테이너선 시장의 변화요인 점검 및 향후 전망"의 주요 내용을 요약 정리한 것이다.

• Journal of Korea Port Economic Association
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• v.27 no.4
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• pp.1-11
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• 2011

In much the same way as the US Lehman crisis of 2008-2009 severely impacted the European economy through financial market dislocation, a European banking crisis would materially impact the US economy through a generalized increase in global risk aversion. A deepening of the European crisis could very well derail the US economic recovery and have a harmful impact on the Asian economies. This kind of vicious circle could be a bad news to the shipping companies. The purpose of the study is to predict the Baltic Dry Index representing the shipping business during the period of 2012 using the ARIMA-type models. This include the ARIMA and Intervention-ARIMA models. This article introduces the four ARIMA models and six Intervention-ARIMA models. The monthly data cover the period January 2000 through October 2011. The out-of-sample forecasting performance is also calculated. Forecasting performance is measured by three summary statistics: root mean squared percent error, mean absolute percent error and mean percent error. The root mean squared percent errors, however, are somewhat higher than normally expected. This reveals that it is very difficult to predict the BDI The ARIMA-type models show that the shipping market will be bearish in 2012. These pessimistic ex-ante forecasts are supported by the Hodrick-Prescott filtering technique.

• Journal of Navigation and Port Research
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• v.36 no.3
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• pp.205-213
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• 2012

This study focused on the supply-demand and training system of the crew for domestic coastal shipping. First of all, it forecasted the prospect and effect in the future of the crew supply-demand through the analysis to the current situation of crew employment and the internal and external environment changes. Next, it suggested the specific role and alternatives of government, industry and educational institutions after the comparison and examination of the sailor policies among Korea and major shipping countries. In regard to the demand of crew manpower in coastal shipping, it figured out the bottoms and the current circumstances of sailors, and it could anticipate the future demand by the gradational approach. According to the findings, firstly the result of this simulation by the changes of the ship numbers demonstrated that the demand over the next 10 years will be 7,890~8,025 in the case of the growth 0.4%, and 7,894~8,063 in 0.5%. Secondly, assuming the growth 0.1~1%, the result illustrated that the demand will come to 7,879~8,258. This means the fact that the additional manpower has to be input to 20~430 annually from now on. To conclude, this study showed the more rational numbers about the supply-demand than the past researches and displayed the systematic approach to supply and train the crew in domestic coastal shipping.