• Journal of Distribution Science
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• v.16 no.11
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• pp.37-45
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• 2018

Purpose - Recently, large quantities of factors have affected the signing of the Free Trade Agreement between two countries. Due to this background, this paper selects South Korea as an example to explore the determinants of Free Trade Agreement from Asian countries. Research design, data, and methodology - A cross sectional data of 2016 will be employed and some variables such as real income and GDP will be used to run an empirical analysis under the linear probability model, probit model and logit model. Results - The findings show that the Asian countries' exchange rate regime, real income, GDP and so forth can increase the probability of signing the Free Trade Agreement with Asian countries. Conversely, the distance can lower the probability of signing the Free Trade Agreement with Asian countries. Meanwhile, although the Asian countries' import, consumer price index and population also can affect the probability of signing the Free Trade Agreement with Asian countries, the estimated coefficients are not statistically significant at 5% level. Conclusions - According to the empirical results, this paper provides a new scope for South Korea's government to sign the Free Trade Agreement with other Asian countries.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.4
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• pp.83-92
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• 2022

Due to the uncertainty in the order of the integrated model, the SARIMA-LSTM model, SARIMA-SVR model, LSTM-SARIMA model, and SVR-SARIMA model are constructed respectively to determine the best-combined model for forecasting the China-Russia trade turnover. Meanwhile, the effect of the order of the combined models on the prediction results is analyzed. Using indicators such as MAPE and RMSE, we compare and evaluate the predictive effects of different models. The results show that the SARIMA-LSTM model combines the SARIMA model's short-term forecasting advantage with the LSTM model's long-term forecasting advantage, which has the highest forecast accuracy of all models and can accurately predict the trend of China-Russia trade turnover in the post-epidemic period. Furthermore, the SARIMA - LSTM model has a higher forecast accuracy than the LSTM-ARIMA model. Nevertheless, the SARIMA-SVR model's forecast accuracy is lower than the SVR-SARIMA model's. As a result, the combined models' order has no bearing on the predicting outcomes for the China-Russia trade turnover time series.

• Korea Trade Review
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• v.46 no.5
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• pp.83-98
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• 2021

This study aims to examine the effects of international trade in intermediate input on the implications of international business cycle properties in Korea. To do this, I have extended standard one goods New Keynesian international business cycle model to incorporate the role of intermediate inputs. After constructing the DSGE model, I have analysed the impulse response function and varian decomposition results. The results show that the model could introduce a new channel, that is, "cost channel" like Eyquem and Kamber (2014). In other words, the model has changed the dynamics of aggregate inflation by the cost channel. When the trade in intermediate goods increase, which is measured by openness of foreign input, the volatility of output, consumption and inflation increase two or three times. However, the model itself fails to explain the full account of cycle behavior of historical data, but the results imply that the trade in intermediate input assumption can help to improve the forecasting ability of international business cycle models.

• Korea Trade Review
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• v.44 no.2
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• pp.51-62
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• 2019

This study predicts the future world seaborne trade volume with econometrics methods using 23-year time series data provided by Clarksons. For this purpose, this study uses simple regression analysis, exponential smoothing method and seemingly unrelated regression model (SUR Model). This study is meaningful in that it predicts worldwide total seaborne trade volume and seaborne traffic in four major items (container, bulk, crude oil, and LNG) from 2019 to 2023 as there are few prior studies that predict future seaborne traffic using recent data. It is expected that more useful references can be provided to trade related workers if the analysis period was increased and additional variables could be included in future studies.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.77
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• pp.195-214
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• 2018

In order to analyze the current status of trade with Korea and FTA partner countries, the Trade Intensity Index and the Market Comparative Advantage index were calculated and analyzed using panel gravity model. In the case of trade, trade intensity index has been strengthened according to each FTA enforecement, and in some cases, trade inensity has been weakened. In the case of the comparative advantage index, there was a case in which the comparative advantage was strengthened or the comparative advantage was not significantly changed according to each Chapter of HS code. This means that the Korea's FTA enforcement effect has not directly affected the increase of the trade intensity and the increase of the market comparative advantage index. The panel gravity model using the trade intensity and the comparative advantage index as the dependent variable and the trade volume between the two countries as the dependent variable was analyzed.

• Journal of Korea Trade
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• v.25 no.4
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• pp.88-107
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• 2021

Purpose - Using a model that highlights Ricardian comparative advantage and Cournot competition, I derive theoretical predictions on how bilateral measures of trade intensity, specialization, and intra-industry are interrelated, and how Ricardian productivity differences affect these measures. We test the predictions using trade and production data, and confirm them. Design/methodology - A simple two-country general equilibrium model is constructed to derive theory-based bilateral indexes. We then test the relationships among them using panel data for 35 countries and 14 industries between 1996 and 2008. Findings - Bilateral trade intensity is increasing in specialization, as in the classical trade theory, and in intra-industry trade, as in the new trade theory. However, productivity differences positively affect specialization, and negatively affect intra-industry trade. These effects cancel each other; thus productivity differences have little impact on trade intensity. Originality/value - This paper provides a comprehensive conceptual framework for understanding the relationship among trade intensity, specialization, intra-industry trade, and productivity differences. We derive theory-consistent measures of specialization, intra-industry trade, and productivity differences. Moreover, we reevaluate the empirical relevance of these variables for the study of gravity equations. This paper is also an effort to capture oligopolistic competition in a general equilibrium framework, interests in which recently resurged.

• Korea Trade Review
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• v.45 no.3
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• pp.119-132
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• 2020

In this paper we explore the two analyses to know the urbanization effect on trade. First, the granger causality test to examine the relationship between trade and urbanization. The Granger causality test is a statistical hypothesis test for determining whether one time series is useful for forecasting another. The results indicated that the existence of a bidirectional causality running from trade to urbanization when six lags were applied. When eight lags were applied, we found unidirectional causality running from urbanization to trade. Second, gravity models were used to investigate the urbanization effect on trade. The production cost and specification are affected by the economies of scale, and the economies of scale increased as the greater geographically agglomeration. However, the gravity model to explain the bilateral trade flows ignores the urbanization variables. Therefore we added the urbanization variable represented as the geographically agglomeration into gravity model. The results show that the degree of urbanization of both countries has statistically positive effect on trade (export and import) and the bigger coefficients of trade partner's urbanization. The reason is that the trade share of industrial supplies, intermediate goods and capital goods is much higher than finished consumer goods. The urbanization is more important the improved the efficiency of production than demand market.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.3
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• pp.43-50
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• 2018

The paper aims to investigate the impact of trade cost on export: A Case Study Vietnam. The study conducts a static linear panel data analysis on annual data covering bilateral export between Vietnam and 70 major importers of Vietnam from 2001 to 2013. The gravity model has been one of the most successful applications in empirical trade. In this paper we apply the gravity model to estimate the impact of trade cost on Vietnamese bilateral export value. The paper uses gravity model to estimate the impact of trade cost on Vietnamese bilateral export value. The empirical results derive from a static linear panel data analysis (fixed effects model) indicates that trade cost plays a crucial role in determining the export value that occurs between Vietnam and trading partners. Besides, population of importing country, trade openness of importing country, gross domestic product of importing country and gross domestic product of Vietnam are also significant determinants of Vietnamese bilateral export value. The main findings indicates that trade cost plays a very important role in the Vietnamese bilateral export performance. This suggests that the Vietnamese government should attempt to improve domestic trade costs to enhance competitiveness and increase export growth sustainably.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.403-411
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• 2021

This study discusses the influence of economic factors on the clothing exports from China and 15 South and Southeast Asian countries to the United States. A basic gravity trade model with three predictors, including the GDP value produced by exporting and importing countries and their geographical distance was established to explain the bilateral trade patterns. The conventional approach of multiple regression and the novel approach of Artificial Neural Networks (ANNs) were developed based on the value of clothing exports from 2012 to 2018 and applied to the trade pattern prediction of 2019. The results showed that ANNs can achieve a more accurate prediction in bilateral trade patterns than the commonly-used econometric analysis of the basic gravity trade model. Future studies can examine the predictive power of ANNs on an extended gravity model of trade that includes explanatory variables in social and environmental areas, such as policy, initiative, agreement, and infrastructure for trade facilitation, which are crucial for policymaking and managerial consideration. More research should be conducted for the examination of the balance between developing countries' economic growth and their social and environmental sustainability and for the application of more advanced machine-learning algorithms of global trade flow examination.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.72
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• pp.139-160
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• 2016

Using the gravity model, this paper analyzes empirically how the world trade in goods is affected by regional trade agreements(RTAs) which have been spreading rapidly since the mid-1990s. This paper attempt to do the panel data analysis about 174 countries during the period of 1994-2008. These panel data include 157 RTAs. It is meaningful that this paper uses comprehensive data to analyze the net effect of regional trade agreements on the global trade volume. This provides a clue as to the answer to the stumbling block debate raised early in the regional trade agreement. Also, confirming how the participation of the WTO affected the trade volume among the member countries, the WTO-related dummy variables are additionally introduced to this gravity model. And as far as we know, the state system-related variables is first considered in this model. This variable reflects the social and cultural environments of countries as the proxy variable representing the sociocultural homogeneity. In all regressions, joining to the WTO and consistency of the state system have a positive effect on increasing the trade volumes between countries. According to the analysis of RTA trade effects, RTAs, on average, increase the volume of trade within the RTA region by 27%~37%, and decrease the volume of trade between the regional and the non-regional nation by 1.2%~3.4%.Therefore, the net effect of regional trade agreements on the promotion of global welfare is positive. For robustness check, we also introduce the interaction term of the dummy variable which reflects the RTA tightening and the continuous variable which reflects the distance effect. As a result, the RTAs alleviate the trade-decreasing effect which is caused by the distance between the countries.