A gravity model for trade between vietnam and korea

Nội dung text: A gravity model for trade between vietnam and korea

1. A GRAVITY MODEL FOR TRADE BETWEEN VIETNAM AND KOREA Phan Thanh Hoan Hue College of Economics Abstract This study examines the bilateral trade between Vietnam and Korea based on a gravity model and panel data for years 1992 to 2012. The results show the Vietnam-Korea bilateral trade is positively correlated with the parties’ GDP and Korea’s total trade, while it is negatively correlated with the tariffs between two countries. Overall, economic size, bilateral tariffs and partner’s trade volume are indicated as most relevant determinants of trade between Vietnam and Korea. The results of gravity model are also applied to calculate the trade potential between the two countries. It shows that that Vietnam’s exports to Korea will be potentially expanded in many sectors. Keywords: Bilateral trade, gravity model, panel data, Vietnam, Korea 1. Introduction Vietnam-Korea relation has developed considerably since the establishment of diplomatic ties in 1992. The relationship has been rapidly deepened in all fields such as political and economic, social and cultural, trade and investment, education and people-to-people exchanges. During the short period of two decades, there has been great progress in bilateral relations. Trade volumes have increased 56 folds from about US$ 500 million in 1992 to approximately US$ 29 billion in 2014. The average annual growth rate of Vietnam’s imports from Korea was about 25 percent, whereas Vietnam’s exports to Korea increased by an average growth rate of nearly 19 percent per annum during the period from 1992-20141. Korea has been one of Vietnam’s top trading partners since 1992, specifically; Korea is the second-largest import market and fourth- largest export market for Vietnam, while Vietnam is Korea’s fourth-largest export market in 2014. Vietnam is also one of Korea’s largest export markets for industrial goods. On the other hand, although Korea’s trade share declined, Korea still has maintained its position as Vietnam’s top 10 trading partner in the past over 20 years (UNSD, 2015)2. In an effort to improve on the strategic partnership established between the two countries, the trade ministers of Vietnam and Korea signed a free-trade agreement (FTA) on May 5th, 2015. Both sides hope that the bilateral trade volume will reach US$ 70 billion by 2020 (VCCI, 2016). The gravity model has been extensively used in international trade research for many years because of its considerable empirical robustness and explanatory power (see Kepaptsoglou, K., Karlaftis, M., and Tsamboulas, D., 2010). However, it appears that there are a limited number of studies applying gravity model for the case of Vietnam. There also have been limited studies of bilateral trade between Vietnam and Korea in a gravity model framework. Moreover, only few studies applied gravity model with disaggregated data at the sector level. Therefore, this paper aims to: (i) empirically test whether the bilateral trade between Vietnam and Korea would follow the traditional gravity theory; (ii) predict the trade potential between Vietnam and Korea using gravity model estimates; and (iii) fill the gaps in literature concerning Vietnam and Korea trade in utilizing gravity model. The paper is organized as follows. Section 2 summarizes the review of gravity model’s literature. Section 3 presents the hypotheses to be tested, data collection and the empirical model 1 See appendix 1 2 See appendix 2 527
2. applied for Vietnam-Korea bilateral trade. The results are discussed in Section 4, and Section 5 concludes the paper. 2. Literature Review It has been known since the seminal work of Jan Tinbergen (1962) that the size of bilateral trade flows between any two countries can be approximated by a law called the “gravity equation” by analogy with the Newtonian theory of gravitation. Since its introduction by Tinbergen, the gravity model has been widely used for explaining flows of international trade. As reported by Porojan,in the last decade gravity models have been employed innumerous studies for analyzing and assessing trade flows.A particular application of the gravity model is to explain and predict the effects of Free Trade Agreements on trade flows. Free Trade Agreements are forms of trade pacts between countries; these agreements eliminate tariffs, quotas and other barriers for a number of goods (if not for all),traded between involved partners. Initially the gravity equation was thought of merely as a representation of an empirically stable relationship between the size of economies, their distance and the amount of their trade.In practice, the gravity equation relates the natural logarithm of the monetary value of trade between two countries to the log of their respective GDPs, a composite term measuring barriers and incentives to trade between them, and terms measuring barriers to trade between each of them and the rest of the world. The formulation of the standard gravity model can be generalized as follows: where is the flow of exports from country i to country j, and are country and country GDPs, is the geographical distance between the countries’ capitals, and is represents an error term with expectation equal to 1. The linear form of the model is as follows:′ ′ where the are coefficients. Given the hypothesized relationships contained in the log gravity model, and are expected to be positive, while is expected to be negative. In the gravity equation, geographical distance between the importing and exporting countries is actually a proxy for trade costs, which impede bilateral trade. Other variables that capture trade costs (e.g., adjacency, common language, colonial links, common currency, or whether the importing or exporting countries are islands or landlocked) may be added to this basic equation along with other explanatory variables. The gravity model has been extensively used in international trade research for many years because of its considerable empirical robustness and explanatory power (see Kepaptsoglou, K., Karlaftis, M., and Tsamboulas, D., 2010). However, it appears that there are a limited number of studies applying gravity model for the case of Vietnam. There also have been limited studies of bilateral trade between Vietnam and Korea in a gravity model framework. Moreover, only few studies applied gravity model with disaggregated data at the sector level. Therefore, this study will fill the gaps in literature concerning Vietnam and Korea trade in utilizing gravity model. 3. The model, data and estimation method The model applied in this study is a modified version of the traditional gravity model. The model is modified by using sector exports as dependent variable; tariff, partner’s aggregate trade and GDP as explanatory variables. The estimated gravity model has the following form: This equation includes two “standard” variables of the gravity model: log β β log β log β log 528
3. - Bilateral tariffs ( ), which represents the barrier to trade. Bilateral tariffs are Korea’s sectoral effectively applied rates on Vietnam’s exports. Obviously, Vietnam’s exports are expected to increase when Korea’s tariff decrease. - Average GDP ( ), which is an indicator of the average economic size of the two countries. GDP data is expressed in current million US dollars. The average of GDP serves as a proxy for the two countries’ economic size, in terms of both production capacity and size of market. Larger countries, with a greater production capacity, are more likely to achieve economies of scale and increase their exports based on their comparative advantage. They also possess large domestic markets which are able to absorb more imports. Therefore, an increase in average GDP is expected to increase Vietnam’s exports. Beside that, Korea’s total trade ( ) with the world is additional variable which is not only to represent the partner’s economic openness but also to reflect the compatibility of trade structure between two countries. Thus, it is expected that Vietnam’s exports will increase as Korea’s total trade volume rise. The concept of trade potential has been extensively used by researchers studying international trade relations. The methodology consists of selecting a sample of countries for which trade is supposed to have reached its potential. A gravity equation is then estimated to explain bilateral trade within the sample. The estimated coefficients given by the equation are used in simulations to predict the volume of trade between any pair of countries, given that data on GDP, distance,and population,etc. are systematically available. The simulated or predicted value of bilateral trade is then compared with the observed values to infer bilateral trade potential. As noted by Helmers et al.(2005), this methodology can be applied either at the aggregate or industry level. In the present study, we will carry out our analysis at the disaggregate level. Data set contains annual export flow, bilateral tariff, foreign total trade, and GDP. Data on Vietnam’s exports to Korea and Korea’s total trade are obtained from UN comtrade database. Korea’s effective tariff rates on Vietnam’s exports are collected from TRAIN. Two countries GDP in current US dollar is taken from World Bank data. Vietnam-Korea bilateral exports are collected at HS 2 digit level. All sectors then are grouped according to UN’s HS Classification by Section. A panel framework is designed to cover trade variation between Vietnam and Koreafor a period of 1992-2012. Panel estimation reveals several advantages over cross section data and time series data as it controls for individual heterogeneity, time series and cross section.Studies do not control for this heterogeneity may give biased estimated results. Panel data offer more variability, more degree of freedom and reduce the collinearity among explanatory variables therefore improving the efficiency of the econometric estimates. More importantly, panel data can measure effects that are not detectable in cross sections and time series data. (see Baltagi, 1995). Panel data involves different models that can be estimated. These are pooled, fixed effects and random effects. The main problem of the pooled model is that since the pooled regression model neglects the heterogeneity across individuals and assumes the same coefficients for all individuals, the estimates from pooled OLS regression will be usually biased and inconsistent. A random effects model can be more appropriate when estimating the flows of trade between a randomly sample drawn of trading partners from a large population. A fixed effects model would be a better model when estimating the flows of trade between ex ante predetermined selection of countries. Since this study deals with the export flows between Vietnam and Korea, the fixed effects model will be a more appropriate model than the random effect specification. Furthermore, 529
4. we also apply the Hausman test to check whether the fixed effects model is more efficient than the random effects model (see Appendix 3). 4. Estimation Results The results of panel fixed effect regression for the proposed model are presented in table1. The overall performance of the model seems to be surprisingly good, with highR-squaredvalue of around 0.76 (for more details, see Appendix 3). All explanatory variables are found to be highly significant, indicating that the gravitymodel is appropriate and effective in explaining Vietnam- Korea’s bilateral trade flows. It alsoshows that the gravity model is applicable to a single-bilateral case. As can be seen from table 1, both Korea’s trade and GDP are of reasonable magnitude and carry the expected signs. These results mean that Vietnam’s exports to Korea will increase by 1.01 percent and 1.79 percent as Korea’s total trade and average Vietnam-Korea GDP increases by 1 percent, respectively. Likewise, the coefficient of the tariff variable implies that, when the Korea’s tariff rates increase by 1 percent on average, Vietnam’s exports will decrease by 0.26 percent. Table 1.Gravity Model Result Variable Coefficient Std. Error t-Statistic Prob. LOG(TARIFF) -0.26 0.09 -2.84 0.00 LOG(AGDP) 1.01 0.16 6.18 0.00 LOG(KTRADE) 1.79 0.12 14.84 0.00 Observation 315 R-squareed 0.76 F-statistic 54.44 Prob(F-statistic) 0.00 Notes: , and * mean significant at 1%, 5% and 10% level, respectively Figuure 1. Actual vs. Predicted Trade Ratio The gravity model is supposed to provide a long-run equilibrium view of trade flows.Thus, if there is any sort of market intervention that prevents a new market equilibrium,the gravity prediction engenders a gap between the actual trade flows and its long-runequilibrium value, the “trade potential”. The basic gravity model was estimated for Vietnam-Korea export flow for a 530
5. fairly long period (1992-2012). Now it is time to compare the trade potential with the actual trade volume. The difference betweenthe predicted and actual trade flows can be interpreted as trade potential. In this study, we use the ratio of actual trade – AT, to predicted trade – PT, which is the estimated value of the dependent variable. If the value of AT/PT ratio is less than 1, this implies that Vietnam has the potentialtoexpandtrade with Korea. For each sector, the AT/PT ratio is computed as an average of annual sector AT/PT. As shown in figure 1, most of sectors have AT/PT ratio less than 1;for instance, textiles, footwear, transportation, chemicals sectors have very low values; which indicates that Vietnam’s exports to Korea will be significantly expanded in these sectors. 5. Conclusion This paper has attempted to provide an empirical test of gravity model between Vietnam and Korea bilateral trade for the period of 1992-2012; and to predict the trade potential between Vietnam and Korea using gravity model estimates.The results show that the bilateral trade flows between Vietnam and Korea are influenced by economic size (GDP), bilateral tariffs and partner’s trade volume. Bilateral trade between Vietnam and Korea increases with GDP and Trade volume implies that economic and trade growth of each party will strongly affect trade relationship. Although Vietnam-Korea trade has grown faster for many years, trade relation, in general, is still under potential levels. The findings of this study may serve as recommendations in a way that the sector trade potentials should be considered in the process of policymaking for policy makers to exploit these trade potentials and improve bilateral trade between two countries, especially in the context ofthe Vietnam – Korea free trade agreement (VKFTA). REFERENCES Baltagi, B. H. (1995), Econometric Analysis of Panel Data, New York: John Wiley & Sons. Kepaptsoglou, K., Karlaftis, M., Tsamboulas, D., (2010), The gravity model specification for modeling international trade flows and free trade agreement effects: a 10-year review of empirical studies, Journal of Open Economics, no. 3, pp. 1-13, 2010. Helmers, C., Pasteels, J.M. (2005). TradeSim (Third Version): A Gravity Model for the Calculation of Trade Potentials for Developing Countries and Economies in Transition. Geneva: International Trade Centre. Timbergen J. (1962), Shaping the world economy, New York, NY:Twentieth Century Fund 1962. Linneman H. (1966),An econometric study of world trade flows.Amsterdam: North-Holland Publishing Co. 1966. United Nations Statistics Division (UNSD), 2016, UnitedNations Commodity Trade Statistics Database, available at Vietnam Chamber of Commerce and Industry (VCCI), 2016, Vietnam- Korea towards Shared Peace and Prosperity, available at 15, 2016). 531
6. Appendix1. Vietnam-Korea Bilateral Trade Volume and Growth: 1992-2014 Import Exxport Inc. Rate Inc. Rate (US$ (US$ mil) (%) (%) mil) 1992 57.3 39.32 436.2 119.25 1995 193.6 70.16 1,351.0 31.50 2000 322.4 22.03 1,686.0 16.67 2005 694.0 3.08 3,431.7 5.41 2010 3,330.8 40.54 9,652.1 35.00 2014 7,167.5 7.25 21,728.5 5.08 Average 24.55 19.44 Source: UN Comtrade database, 2015 Apppendix 2. Vietnam and Korea trade shares Vietnam’s Trade Shares in Korea’s Korea’s Trade Shares in Vietnam’s Trade (%) Trade (%) Source: UN Comtrade database, 2015 532
7. Appendix 3: Results of Panel Fixed and Random Effects Test Correlated Random Effects - Hausman Test Equation: Untitled Test cross-section random effects Chi-Sq. Test Summary Statistic Chi-Sq. d.f. Prob. Cross-section random 45.972353 3 0.0000 Cross-section random effects test comparisons: Variable Fixed Random Var(Diff.) Prob. LOG(TARIFF) -0.262796 -0.179470 0.000404 0.0000 LOG(AGDP) 1.011354 1.234034 0.001126 0.0000 LOG(KTRADE) 1.793755 1.497376 0.002125 0.0000 Cross-section random effects test equation: Dependent Variable: LOG(EXPORT) Method: Panel Least Squares Date: 11/01/13 Time: 19:16 Sample: 1992 2012 Periods included: 21 Cross-sections included: 15 Total panel (unbalanced) observations: 314 Variable Coefficient Std. Error t-Statistic Prob. C -40.47095 3.923554 -10.31487 0.0000 LOG(TARIFF) -0.262796 0.092620 -2.837341 0.0049 LOG(AGDP) 1.011354 0.163540 6.184128 0.0000 LOG(KTRADE) 1.793755 0.120874 14.83983 0.0000 Effects Specification Cross-section fixed (dummy variables) R-squared 0.757678 Mean dependent var 2.909379 Adjusted R-squared 0.743761 S.D. dependent var 2.005557 S.E. of regression 1.015215 Akaike info criterion 2.923693 Sum squared resid 305.0756 Schwarz criterion 3.138627 Log likelihood -441.0199 Hannan-Quinn criter. 3.009577 F-statistic 54.44204 Durbin-Watson stat 0.704144 Prob(F-statistic) 0.000000 533