In terms of maritime logistics amount in Northeast Asia, China has sustained a high-speed growth of more than 8% per year. This is in stark contrast to Japan, which has suffered from sustained recession for more than 10 years. China’s production has increased quickly compared to what the marine cargo handling volume around the world has shown. In particular, transshipment cargo handling amount has rapidly progressed, compared to the increase in container volume.

The economic development of these Northeast Asian countries has led to the increase of each region’s maritime cargo handling volume. Because of this, the shape of port networks has changed to a polynuclear system hub port, which is the centrality and intermediacy of the large ports.

There are limits to these studies. For example, most studies of time series analysis were analyzed except that of China and Asian related variables. In particular, there are limitations because most of the studies of transshipment volume are estimated and forecasted using Chinese and Japanese economic growth outlook.

There are hardly any studies concerning the changes in the competitive port development projects of the Northeast Asian countries' ports, and port call strategy of shipping companies to port call in the North China port, especially using China-related variables which have the greatest impact on container cargo volume in Korean port. Therefore, in this study, by using the time-series data and China-related variables, the container throughput of Korean ports has been estimated.

By using the time series data to respond to changes in the port environment, it estimated the handling volume of the entire container associated with centrality, and the transshipment container volume associated with intermediacy. In addition, the container throughput of Busan port was also estimated together as a Korean representative port.

However, this port throughput situation has changed since the 2008 financial crisis in the US. Port throughput has plummeted. The disparity of large ports and small ports became larger, and liner routes of shipping companies were also changed. It is necessary to correctly estimate port throughput after the 2008 financial crisis in a new light.

This study will discuss the estimated container throughput in Korean ports, and assurance that the proper port facilities corresponding to the maritime cargo (which is handling the amount of increase) and the suggestions to the port policy of the Korean government after the 2008 financial crisis.

Because of the equipment expansion of the port logistics industry is based on port volume prediction, port volume prediction has important implications that have a significant influence on port development in the position of the individual ports. Therefore, it is necessary to perform prediction in consideration of the various domestic and international environmental uncertainties, and it can be displayed with different results based on the prediction model that is always present.

OSC (2003) studied that there is increase in customer demand and raw materials and intermediate goods of industry demand due to the economic growth of the last 10 years. The port environment has drastically changed, due to a variety of factors. For one, radical containerization of general cargo, bulk cargo and intermediate goods occurred. Second, there was an increase in the size of vessels due to greater trade volume. Third, there was significant port ownership of large shipping companies. Finally, port productivity improved. All of these factors were taken into account while predicting port throughput. Also, they were predicted by mixing two values: the long-term GDP growth rate of positive-negative, and the short-term GDP rate of IMF for container throughput prediction. In particular, the global uncertainty (i.e. double-dip fear of US economy, Europe long-term recession of Japan and Western, diffusion of the Iraq War, and terrorism etc.) acted as a negative scenario in GDP growth rate. On the other hand, in the US economic recovery, stabilization of the East Asian economies and currencies, and diffusion of FTA applied to the positive scenario have been utilized for prediction.

Drewry (2010) was a ″Container Market 2010 / 11″ report, and presented a regional medium term prediction about port throughput between 2010 and 2015 in the world. For their prediction, they referred to the data published in the IMF of 2010. They forecasted port throughput using trading volume of the world's goods and services, and took advantage of the predictive index of consumer prices in major industrialized countries (US, EU, Germany, Japan and England etc.) and BRICs (Brazil, Russia, India and China) which are also the major developing countries. In particular, they emphasized the surprising rise of major economic indicators of China, which caused an increase in the container handling amount over the past few decades.

Zhao et al. (2011) implied that these are dominated by quantitative methods such as regression forecasting method (particularly ARIMA) because most of the existing methods deduce future trends or pattern based on changing time sequences of the past. Among existing studies, auto regressive integrated moving average (ARIMA) models are being applied most frequently. Then, exponential smoothing class of time-series models is applied less frequently (Coshall and Charlesworth, 2011). However, one class of existing forecasting models does not continuously dominate others and many disputes are currently progressing about choosing the method. For instance, it was demonstrated by some researchers that the autoregressive integrated moving average (ARIMA) model outperforms error collection models (ECM) (Gonzalez and moral, 1995), dynamic harmonic regression (DHR) (Garcia-Ferrer and Queralt, 1997), Winters models (Lee et al., 2008), artificial neural network (ANN) and multivariate adaptive regression splines (MARS) (Lin et al., 2011).

In the previous studies, they estimated port throughput using terminal facilities (total area, berth, number of C/C and length etc.), economic variables (GDP, REER and economic index etc.) and time series data (ARIMA amd GARCH etc.).

Based on these studies, we estimated China′s trade scale as an explanatory variable for estimating the transshipment cargo volume, and we also estimated the index representing the economy of the world (including Korean economy) and real effective exchange rate of Korea Won as an explanatory variable for estimating the port throughput.

The growth of Northeast Asian trade has been supported by China's economic development and the recovery of the Japanese economy. However, regional growth has not been the only factor in this increase of trade. There has also been an expansion of Northeast Asian-North American trade.

Port development policy that was started by the competition of hub port of Asia countries is based on medium-long term plan. Because it needs such large government funding, accurate estimation is required for the evaluation of the proper port facilities.

This port throughput situation has changed after the 2008 financial crisis from US. Port throughput has plummeted. The disparity between large ports and small ports became larger, and liner routes of shipping companies were also changed. It is necessary to take these new factors into account to correctly estimate port throughput after the 2008 financial crisis.

Therefore, in this study, we estimated port traffic in 2008 to 2013 using time-series data.

First, port throughput; 1 % increase of Korean GDP were found to increase the container throughput about 1.1 to 1.5 %, and the rise of the real effective exchange rate of Korean Won of 1 % were found to increase the container throughput from 0.5 to 0.8 %.

Second, the port transshipment cargo volume; Trade volume with China accounted for a large proportion. 1% increase of trade volume of China was found to increase the container transshipment volume from about 0.6 to 0.7 %.

In these results, because based on studies of Rose (1991) and Coto-Millan et al. (2005) we just considered about 3 variables for estimating port traffic, there are low significance relation each variables. It needs to study at some length in the future.

Also, we made several seasonally multiplicative ARIMA models using monthly data in 2001 to 2014 for validity of data because data of transshipment cargo volume were systemized after 2000.

Based on the model, we forecasted port throughput and port transshipment cargo volume for the next six years (72 months) from 2015 to 2020. As a result, the port throughput of Korean and Busan ports were forecasted by increasing the annual average from about 3.5% to 3.9%. The transshipment cargo volume was forecasted by increasing the annual average about 4.5%. Therefore, because of the increase of the transshipment cargo volume and despite the facility expansion in Busan port of 14 million TEU in 2011, it is likely to face a shortage of facilities soon. In particular, the case of transshipment cargo volume in Korea port has higher increase of transshipment cargo volume than the rate of increase in port throughput. This is interpreted as a phenomenon associated with the development of Chinese ports, such as the growth of Shanghai port.

In these results, port transshipment cargo volume in Korean port and Busan port are falling short of real port transshipment cargo volume of Korean port 7% to 16% since 2000. Because of property of time series analysis, especially ARIMA, it can not consider about another variables (rapidly changing world situation, Chinese economy as a related country of transshipment and variety variables etc.). Therefore it needs to study and supplement with the methods of estimate port throughput and port transshipment cargo volume in-depth in the future.

This study that port throughput estimation using quantitative methods has significant meaning for establishing port policy in the future.

In order to efficiently establish and implement a master plan of ports, in preparation for the demand of port traffic, it is necessary to establish long-term and overall development plan based on the estimated port traffic. And, in order to increase port traffic in the future, it needs (1) the industry and corporate policy to increase the manufacturing industry and trade value, (2) the port facilities improvement and customs clearance, system improvement and attraction of port hinterland and domestic and foreign companies for the increasing transshipment cargo volume, (3) to establish multimodal transport system, (4) and to implement the active utilization strategies in Korea-US FTA, Korea-EU FTA, and Korea-China FTA.

In this study, we analyzed and forecasted port throughput for the port development and port development plan through the prediction and estimation of port throughput demand of Korea and Busan port. It is necessary to take into consideration some of the previously described improvement policies and institutions to increase the port throughput more accurately, as well as to analyze the activation strategy. Also, there are too many studies about port throughput estimation. however these studies need to consider about various methods about port throughput estimation by supplement with limits of previous methods.

Finally, based on this study, it needs to estimate port traffic other ports in Korea using various methods for establishing a port policy.