Determinants of vietnam’s rice exports

Nội dung text: Determinants of vietnam’s rice exports

1. DETERMINANTS OF VIETNAM’S RICE EXPORTS Huynh Thi Dieu Linh*1 ABSTRACT: The main purpose of this study is to examine the major factors affecting Vietnam’s rice export values to 20 major import partners by employing a gravity model. A generalized least squares (GLS) estimation method is employed on panel data over a ten-year period from 2007 to 2016. Apart from importers’ GDP, all other remaining independent variables show expected signs. The findings indicate that Vietnamese rice exports have positive relationship with Vietnam’s GDP, importers’ population, depreciation of Vietnam’s currency, average export price, members of ASEAN and importers sharing the same border with Vietnam, whereas its rice exports have adverse relationship with importers’ GDP. Keywords: determinant of rice export value; Vietnam; Gravity model; panel data; GLS 1. INTRODUCTION 1.1. Research Background Currently, Vietnam is one of the top largest rice exporters in the world market. In 2016, Vietnam was ranked the fourth biggest country that exports rice, which reduce from the second largest rice exporting country in the last few years. In Vietnam, rice plays an important role both in earning export turnover, with export value approximately 2.2 billion USD, and in the most consequential crop production of agricultural sector. In recent years, the market share of Vietnam’s rice exports has witnessed an impressive downward trend since Vietnam’s rice exports deals with potential competition from other rice leading exporters like Thailand, India and other emerging markets such as Cambodia. It is more likely that the decreasing rice export may has an adverse impact on Vietnam’s economy because rice is one of the most dominant export commodities of Vietnam, making up for 1.13 per cent of Vietnam’s export values and contributing a crucial role to the export income. Beside facing increasing competition, the reduction of Vietnam’s rice exports might be because the demand for rice in global market has been experienced a downward trend. Timmer, Block, and Dawe (2010) indicated that consumers these days tend to use substitute products containing more protein and vitamin due to the rise in their per capita income. Moreover, many countries begin to expand their rice planting area and number of rice crops for domestic demand. 1.2. Research problems and objectives Because of the importance of rice exports in earning export turnover in Vietnam, the decrease in rice export values from the country should be taken into considerations. Moreover, it should be noticed while rice export volume of Vietnam is larger than its major competitors, export values of the country is lower than its counterpart. Therefore, it does not bring good income for Vietnamese rice farmers in recent years, * University of Economics, The University of Da Nang, Viet Nam
2. 526 HỘI THẢO KHOA HỌC QUỐC TẾ KHỞI NGHIỆP ĐỔI MỚI SÁNG TẠO QUỐC GIA which might contribute to declining rice export value of the country. Thus, it is vital to find out which factors affecting significantly to Vietnam’s rice export to have appropriate policies to encourage rice exports. While previous studies have indicated several insights concerning the determinants of exports in general, there are still relatively few of those regarding to factors affecting rice exports. In addition, there has not been consistence in the conclusion regarding the significant factors impacting on rice export. Especially in Vietnam, to the best of my knowledge, there is few or no impressive research which can reliably measure the relationship between rice export and its determinant. Furthermore, Vietnam’s rice export performance has declined over recent years but there is no efficient policy to solve the reduction in rice export value. Considering this, the study intends to fill the gap by evaluating the determinant of Vietnam’s rice exports. Understanding factors impact on rice export performance to enable policy makers issue appropriate policies to encourage export flows in rice sector and to develop situation economic inV ietnam. The main purpose of this study is to identify factors affecting Vietnam’s rice export performance with its main trading partners. To do this, the study uses the annual data during the period 2007-2016 with gravity model approach to figure out what factors that determine the flow of rice exported from Vietnam to twenty trading countries which contribute major share in imports of rice from Vietnam. The paper was organized to four sections. Section 1 concerns the introduction with research background, as well as research problems and objectives. Section 2 discusses the methodology with briefly review previous papers and descripts data used in this study. Then, section 3 documents and discusses the estimation results. Finally, section 4 presents the conclusions and policy implication of this study. 2. METHODOLOGY 2.1. Model specification When examining the factors impact on rice exports, the most popular model used is gravity model as it used in may research such as Ahmad and Garcia (2012), Bui and Chen (2017), Hatab et al. (2010), Muhammad Abdullah et al. (2015), Thuong (2017), Vu and Doan (2013). In this study, the model is augmented from McCallum (1995) and Linnemann (1966). The changes of some additional explanatory variables to the basic gravity model helps to provide better understanding the factors influencing Vietnam’s rice export. The model estimated is as follow: ln(EXit) = β0 + β1ln(GDPVNt) + β2ln(GDPit) + β3ln(PROit) + β4ln(DISi) + β5ln(ERit) + β6ln(POPit) + β7ln(PRt) + β8ASEANt + β9BORDER + EXit is the total value of Vietnam rice export to country i in year t, which is measured in US dollar. GDPVNt is the GDP of Vietnam in year t, which is measured in US dollar. GDPit the GDP of country i in year t, which is measured in US dollar. PROit denotes the rice production of country i in year t, which is measured in ton. DISi is the distance between capital cities between Vietnam and country i, which is measured in kilometer. ERit is bilateral exchange rate between Vietnam and country i in year t. POPit denotes the population of country i in year t. PRt is the average price of Vietnam’s export rice in year t, which is measured in US dollar per ton. ASEAN is a dummy variable equal to 1 if country i is member of ASEAN and zero otherwise.
3. INTERNATIONAL CONFERENCE STARTUP AND INNOVATION NATION 527 BORDER is a dummy variable equal to 1 if country i shares the same border with Vietnam and zero otherwise. is error term of export equation. All the quantitative variables will apply the natural logarithm (ln) apart from dummy variables in the model. 2.2. Description of variables and data sources To analyze factors affecting the Vietnam’s rice export within the framework of gravity model, this study employs panel dataset of yearly observations of twenty most important import partners of Vietnam’s rice over the period of ten years between 2007 and 2016. The importing trading partners chosen in this study are top rice importers from Vietnam based on their average annual import value during the researched period. They are The Philippines, China, Indonesia, Malaysia, Cote d’Ivoire, Ghana, Singapore, Hong Kong, Angola, Cameroon, Mozambique, Russian, Papua New Guinea, Guinea, Algeria, The United States of America, Tanzania, South Africa, Gabon and Korea. The choice of the sample period and importing countries in this study is based on the availability of data on all the variables utilized in the study and the relative importance of each country in Vietnam’s total value of rice export over the sample period. These twenty partners represented over 80 percent of the total value of Vietnam rice export in the 2007-2016 periods. Three set of explanatory variables are employed as determinants of Vietnam’s rice export values (EX). The first group of variables represents internal supply conditions in the exporting country and the external market conditions in the importing country, namely, gross domestic product (GDP), population (POP), bilateral exchange rate (ER), export price (PR), and rice production of importers (PRO). The second group of variables is a trade resistance factor, particularly the geographical distance between the capital city of Vietnam and its trading partners (DIS). The last set of variables is trade preferential factors namely, ASEAN members (ASEAN) and common border (BORDER). Outlined below is a brief description of all variables used in this study: 2.2.1. Dependent variable EXt is the total values of Vietnam’s rice exports to country i in year t (from 2007 to 2016). Data of the dependent variable was retrieved from United Nations Comtrade online database. 2.2.2. Independent variables GDP of exporter (GDPVNt): Gross domestic product of exporter is the market value of entire production of goods and services in exporting country. GDP is one of standard variables of gravity equation. In this study, GDP is considered as a proxy of rice supply capacity. When gross domestic product of exporter increase, the supply of rice will rise along with more potential export opportunities. On the contrary, when GDP of exporter decreases, the export value of goods and services will reduce as a result. GDP of exporting country was also taken into consideration about the determinants of rice export in preceding researches such as Ahmad and Garcia (2012), Bui and Chen (2017), Hatab et al. (2010), Muhammad Abdullah et al. (2015), Thuong (2017), Vu and Doan (2013). It is expected that the indicator of exporter’s GDP has positive effect on rice export value. Data was obtained from World Development Indicator online database in the World Bank. GDP of importer (GDPit): Gross domestic product of trading partner is regarded as one of the primary indicators that are likely to impact the demand for imports in these importers. GDP reflects the ability of a country to pay for goods, hence GDP and import value of that country ties a close relationship in the same way. GDP of importing country are considered into the set of factors affecting rice exports in earlier empirical researches like Ahmad and Garcia (2012), Bui and Chen (2017), Hatab et al. (2010), Leelawattanapan and Chaiboonsri (2014), Muhammad Abdullah et al. (2015), Thuong (2017). These studies argued that if GDP of importing country increase, value of rice import from this country will increase as a result. Hence, the
4. 528 HỘI THẢO KHOA HỌC QUỐC TẾ KHỞI NGHIỆP ĐỔI MỚI SÁNG TẠO QUỐC GIA relationship between importer’s GDP and value of rice export is anticipated to be positive. Data is collected from World Bank’s World Development Indicator online database. Population of importer (POPit): An importing country with a huge population size is denotative of potentially larger market size and is anticipated to import more. As a result, population of importing country can cause various effects to the export of commodity especially rice. Several previous studies determine the importer’s population as consideration about one of indicators of rice export (Bui & Chen, 2017; Hatab et al., 2010; Muhammad Abdullah et al., 2015; Thuong, 2017; Vu & Doan, 2013). It is expected that the relationship between importer’s population and rice export value is positive. Data on population of importing countries is retrieved from World Development Indicators data from World Bank. Exchange rate (ERit): The bilateral exchange rate is the price of exporter’s currency expressed in terms of currency of trading partners. Because there is no direct exchange rate between Vietnam dong (VND) and some currencies of trading partners. In these situations, exchange rate is calculated by dividing the Vietnam Dong/USD rate and importing country’s currency/USD ratio. In this study, an increase in exchange rate denotes a depreciation of VND. Thus, when exchange rate increase cause Vietnam’s rice become cheaper in importing countries, which lead to importers are likely to buy more Vietnam’s rice. Hence, the exchange rate is expected to be positively signed. Many previous researches have taken exchange rate into consideration the factors effect on rice export (Adhikari, 2014; Ahmad & Garcia, 2012; Bui & Chen, 2017; Hatab et al., 2010; Leelawattanapan & Chaiboonsri, 2014; Maneejuk et al., 2016; Molina et al., 2013; Muhammad Abdullah et al., 2015; Shane et al., 2008; Vu & Doan, 2013). Data on exchange rate was sourced from the World Bank, Global Economic Monitor online database. Export price (PRt): Price is considered as one of the leading factors determining the competitiveness of products in the international market. It is argued that when price increase the producers want to produce more and the exporters want to export more. Vietnam’s rice has represented a strong brand name in the world market, therefore, rice is preferred by global consumers and they are willing to pay for that product. This could be explained by the fact that rice exporter in Vietnam tend to export more in those markets where they can obtain a higher price. Therefore, this variable is anticipated to have a positive effect on value of rice export (Adhikari, 2014; Ahmad & Garcia, 2012; Bui & Chen, 2017; Javed et al., 2015; Maneejuk et al., 2016). Data on export price is retrieved from Global Economic Monitor Commodities available on World Bank, International Monetary Fund and reports on United States Department of Agriculture. Importer’s rice production (PROit): Volume of rice production from importing country represents the domestic production capability to meet the domestic demand. If a trading partner experiences rice production less than rice consumption, this country tends to import from global market. Therefore, this lead to the increase in the rice export from Vietnam and vice versa. In this study, the coefficient of importer’ rice production is expected to be negatively signed. Some earlier studies added rice output of importing country to their estimation model (Adhikari, 2014; Bui & Chen, 2017; Leelawattanapan & Chaiboonsri, 2014; Thuong, 2017). Data on this variable is sourced from Food and Agriculture Organization of the United Nations online database. Distance (DISi): Distance between exporter and importer is the basic variable of gravity model. As a proxy for transaction cost, the bilateral distance is used by calculating geographical distance between two capital cities of Vietnam and its trading partner. Since the bilateral distance determines the transportation cost, the more transportation cost will lead to the reduction in the trade between two countries and vice versa. Thus, distance is expected to be negative. Data on distance is obtained from General Statistic Office of Vietnam (GSO). ASEAN is a dummy variable means that whether importers of Vietnam’s rice is a member of ASEAN. If partner is member of ASEAN, this country will experience comparative advantages in favor of tax reduction
5. INTERNATIONAL CONFERENCE STARTUP AND INNOVATION NATION 529 as well as transportation cost reduction in enhancing the rice import from Vietnam. Therefore, the relationship between ASEAN variable and rice exports is expected to be positive (Bui & Chen, 2017; Vu & Doan, 2013). BORDER is a dummy variable whether the trading partner shares the same border with Vietnam or not. When trading with neighboring countries, the transportation costs are relatively low, resulting in higher import from Vietnam. Thus, this variable is anticipated to be positively signed (Bui & Chen, 2017; Hatab et al., 2010; Muhammad Abdullah, 2015). 3. RESULTS AND DISCUSSION Table 1: Summary statistic Variable Observation Mean Standard Minimum Maximum Deviation lnEX 200 17.26148 1.82979 10.1309 20.88711 lnGDPvn 200 25.65109 0.3115702 25.07244 26.04762 lnGDPim 200 25.78311 2.094794 22.56091 30.5555 lnPRO 200 11.57358 5.307113 0 19.1678 lnDIS 200 8.631156 0.8119578 6.7663 9.49899 lnER 200 5.882321 2.801019 0.49305 10.01524 lnPOPim 200 17.19659 1.641252 14.21374 21.04438 lnPR 200 6.022329 0.1705507 5.731391 6.341549 Asean 200 0.2 0.4010038 0 1 border 200 0.05 0.2184919 0 1 Source: Compiled by authors. 3.1. Diagnostic Tests 3.1.1. Pearson’s correlation analysis Pearson’s correlation analysis is the most commonly used to examine the strengths of the correlation between each pair of variables in regression model to determine whether there would be multicollinearity or not. Multicollinearity must be checked because it leads to the increase of variance of the coefficient estimates and make the estimates becomes sensitive to minor changes in the model, therefore reduces the accuracy of the estimate coefficients which weakens the statistical power of the regression model. In this test, two independent variables may obtain multicollinearity in case that the Pearson correlation between them is larger than 0.6. Table 2: Pearson’s correlation coefficient between the variables lnEX lnGDPvn lnGDPim lnPRO lnDIS lnER lnPOPim lnPR asean border lnEX 1 lnGDPvn 0.1486 1 lnGDPim 0.1117 0.079 1 lnPRO 0.1245 0.0249 0.287 1 lnDIS -0.3138 0 -0.3754 0.1375 1 lnER 0.2237 0.0034 0.3291 -0.3385 -0.2067 1 lnPOPim 0.223 0.0341 0.6501 0.7318 -0.1685 -0.0296 1 lnPR 0.1064 -0.1451 0.0002 -0.0027 0 0.0138 -0.0092 1 Asean 0.5038 0 0.1753 0.0721 -0.5763 0.064 0.1191 0 1 Border 0.1723 0 0.4207 0.3271 -0.2489 0.1736 0.536 0 -0.1147 1 Source: Compiled by authors
6. 530 HỘI THẢO KHOA HỌC QUỐC TẾ KHỞI NGHIỆP ĐỔI MỚI SÁNG TẠO QUỐC GIA Table 2 shows the Pearson’s correlation analysis for the variables presented in this study. The correlation coefficient’s matrix demonstrates most of independent variables had positive relationship with the dependent variable apart from Distance which had negative correlation with total value of rice export. It can be seen that most of the variables have low correlations (less than 0.6) apart from population of importers and these production (0.7318), and population of importers and these GDP (0.6501). The presence of relatively high relationship between these variables indicates that there might be multicollinearity problems. Therefore, there is a need to carry out another test to check the multicollinearity. 3.1.2. Variance inflation factor (VIF) test To make certain about the multicollinearity, the Variance Inflation Factor (VIF) should be tested. Particularly, VIF greater than 10 is a problem, nevertheless, VIF less than 10 can be tolerated. Table 3: Variance inflation factor (VIF) test Variable VIF 1/VIF lnPOPim 4.44 0.225367 lnPRO 3.42 0.292096 lnGDPim 2.46 0.406178 lnDIS 2.38 0.419542 Asean 1.96 0.509154 Border 1.84 0.542734 lnEX 1.55 0.644051 lnGDPvn 1.03 0.969448 lnPR 1.02 0.978214 Mean VIF 2.24 Source: Compiled by authors. Results for VIF test can be seen below in the Table 3. Because all the VIF coefficients of all explanatory variables are less than 10, it is concluded that the multicollinearity does not exist among variables. As a result, the dataset used is appropriate for further estimation. 3.2. Empirical Results The most common estimation method using in this research area is ordinary least squares (OLS), however OLS estimation may face problems of heteroskedasticity and autocorrelation, which may cause inaccurate results. The study, therefore, uses generalized least squares (GLS) to avoid these econometric problems. Table 4: Gravity model estimation results based on GLS regression Rice export value (lnEX) GLS Regression Vietnam’s GDP (lnGDPvn) 1.083955 (0.3838948) Importers’ GDP (lnGDPim) -0.3096992 (0.0639216) Importers’ production (lnPRO) -0.0016461 (0.0280917) Distance between Vietnam and importers (lnDIS) 0.0508843 (0.2149877) Exchange rate between Vietnam and importers (lnER) 0.185437 (0.0402179)
7. INTERNATIONAL CONFERENCE STARTUP AND INNOVATION NATION 531 Importers’ population (lnPOPim) 0.3376779 (0.0906924) Export price (lnPR) 1.417292 (0.6710353) Asean 2.489678 (0.3831779) Border 1.504184* (0.8032676) Observation 200 Source: Compiled by authors. Notes: The figures in parentheses are standard errors. , , and * in the table denote statistical significant coefficient at 1 per cent, 5 per cent and 10 per cent level respectively. The estimation results from GLS estimation indicate that most coefficients are statistically significant at 1 per cent, and most of the significant variables experience the positive relationship with Vietnam’s rice export value. The indicator of GDP of Vietnam is significant at 1 per cent. Vietnamese rice export values will raise by 108 per cent when Vietnam’s GDP increase 1 per cent. This finding is consistence with theory as when GDP increases, the supply of rice will go up which exposes the host country more potential export opportunities. In addition to this, Vietnam is an export – oriented country, the increase in GDP will potentially enhance the total export value of rice. Ahmad and Garcia (2012) argued that this positive and elastic coefficient denoted that rice exports are sensitive to domestic supply (production capacity); therefore, economic growth and greater production of rice can stimulate rice exports. The similar results have been pointed out by various studies such as Ahmad and Garcia (2012), Hatab et al. (2010), and Muhammad Abdullah et al. (2015). However, the estimation results show that importers’ GDP have a negative effect on rice export values from Vietnam. The coefficient is significant at 1 per cent andhe t magnitude of the effect is -0. 31, which indicate that 1 per cent increase in GDP of import partners lead to a reduction in Vietnam’s rice exports by 31 per cent. The possible explanation of this adverse relationship might be because rice is inferior goods, that rise in living standards in trading partners along with rise in income so that people in these countries, which will decrease demand of that goods. As a result, when GDP of importers increase, the demand of rice declines which cause a reduction in rice imported from Vietnam to these countries. In contrast, the estimation results of main import partners’ population indicate an expected sign when this variable has a positive impact on rice exports of Vietnam. The estimated coefficient is 0.338. Given the population variables are expressed in logarithms, it can be interpreted as a 1 per cent increase in population of major trading partners will lead to a 33.8 per cent increase in rice exports of Vietnam. The positive relationship is completely consistent with the theoretical predictions of the gravity model. Bilateral exchange rate is significant at 1 per cent. The estimation results suggest that 1 per cent depreciation in the value of Vietnam Dong leads to an increase in total value of rice export of 18.5 per cent. This outcome is similar with expectation and consistent with economic theory. When Vietnam Dong devaluate, the relative cost of rice from Vietnam become lower with importers resulting in larger Vietnam’s rice import demand of trading partners. As a result, the increase in depreciation of VND enhance the value of rice export from Vietnam. This findingappears to be quite similar to the findings of previous papers, such as Ahmad and Garcia (2012), Hatab et al., (2010), and Muhammad Abdullah et al. (2015). Mentioned in Table 4, the indicator of average export price is significant at 1 percent. The results indicate that an increase by 1 per cent in the average export price causes the value of rice export from Vietnam grow
8. 532 HỘI THẢO KHOA HỌC QUỐC TẾ KHỞI NGHIỆP ĐỔI MỚI SÁNG TẠO QUỐC GIA up by 141.7 per cent. The possible explanation of the finding because when the price increase, the exporters are likely to export more. In addition to this, the increase in price consequently results in the increase in the value of rice export. Ahmad and Garcia (2012) argued that the exporter’s decision regarding the choice of an export market responds closely to price. It means that exporters export more to markets where a higher price is obtained. This finding is in line with findings of Ahmad and Garcia (2012) and Thuong (2017). The estimation results show that the coefficient of ASEAN has the expected signs and is statistically significant at 90 per cent level of confidence. The positive relationship between the ASEAN variable and Vietnam’s rice exports indicates that if importers are members of ASEAN, these countries have comparative advantages in favor of tax reduction due to enforcing free trade agreements when intra-trade between members. The coefficient is 2.49 which reflect that when importers are ASEAN members, rice exports of Vietnam to its trading partners are enhanced by 249 per cent. The indicator of Border coefficient is positive and significant at 10 per cent.he T magnitude of the effect is 1.50 which shows that when trading with neighboring countries, rice import value from Vietnam increase by 150 per cent. The estimation results confirm the preliminary expectations that trading between nations with same border, transportation costs are relatively low, resulting in higher trade flows between these countries. The estimation results of distance and export price variables are not statistically significant. Despite their insignificance, these variables are left in model, as their removal may distort the signs and explanatory power of the other variables. 4. CONCLUSIONS AND POLICY IMPLICATION 4.1. Summary The main purpose of this study is to examine what factors affecting export performance of rice industry in Vietnam during the period 2007-2016. In the study, the gravity model approach was employed to explore factors that have impact on Vietnam’s rice export as this model is considered as one of the most efficient models in explaining bilateral trade. The period of 2007-2016 was chosen because the research targets to provide the most updated results. Twenty major trading partners were chosen because they accounted for more than 80 percent of the total value of Vietnam’s rice export in the 2007-2016 periods. The estimated results indicate that GDP of Vietnam is found to be a significant and positive determinant of Vietnam’ rice export in two models. The rise in Vietnam’s GDP results in the increase in Vietnam’s rice export. Other significant factors affecting rice export from Vietnam found are population and GDP of importing countries. The positive and significant of population variable indicates that increasing in population of major importers enhances the demand of rice resulting in increase in the value of rice export from Vietnam. However, GDP of importers have a harmful effect on Vietnam’s rice exports since people in import countries have higher income, they are more likely to choose other substitute products than rice as mentioned above. Average export price is found to be positively and significantly affecting rice export from Vietnam. Increasing price of rice export help increase the value of rice export from Vietnam. Bilateral exchange rate is found significantly in the model, indicating that depreciation in Vietnam Dong against the currencies of its trading partners stimulates rice export. Being members of ASEAN countries and sharing the same border are also concluded to be positively and significantly impacting Vietnam’s rice export values. These positive and significant relationship indicates that an increase in rice exports from Vietnam resulting from trading with ASEAN and neighbour countries.
9. INTERNATIONAL CONFERENCE STARTUP AND INNOVATION NATION 533 4.2. Policy recommendations The key findings of this research have important implications for export policies in Vietnam’s rice exports. Based on these findings, the following recommendations are for policy makers issuing trade policies which aim at expanding the value of Vietnam’s rice exports to main import partners to maximize revenues from export and enhance the pace of the national economic growth. Firstly, the positive relationship between GDP of Vietnam and value of rice exports from Vietnam indicates that rice export is sensitive to domestic supply and economic growth and greater production of rice can boost the rice exports. Consequently, Vietnam’s production capability should be enhanced to utilize export potential. Particularly in rice sector, the government should devote attention to technological improvement by encouraging research and development for new types of rice with high quality and good productivity. Moreover, the government should encourage rice farmers to apply technical advances into production, harvesting, processing and post-harvest preservation to increase productivity and product quality, reduce costs and improve competitiveness. Large-scale rice farming should be encouraged to enhance the product quantity therefore boost the product capability. Secondly, while importers ’population have positive effects on Vietnam’s rice exports, its impacts of importers’ GDP are negative. Vietnamese government and rice exporters, therefore, should pay more attention to markets with large population rather than markets with high income. Hence, to increase rice export performance to major trading partners, the policy makers should issue appropriate trade policies targeting to populated countries. Thirdly, the positive relationship between average rice export price and value of rice export from Vietnam indicates the importance of price in determining the value of rice export. Since Vietnam has exported more types of rice with high value such as basmati and sticky rice, resulting in the rising value of rice export in recent years. Therefore, the government should encourage to export the high value rice varieties which contribute significantly to export price of Vietnam’s rice. Next, exchange rate plays vital role in rice export, so the central bank of Vietnam should effectively manage the exchange rate because a depression in Vietnam Dong would stimulate the rice export from Vietnam, but it would also have other negative consequences on economy. For example, the depression in Vietnam Dong should increase the inflation. Therefore, the State Bank of Vietnam need to have policy in a flexible way that is suitable to situation as well as different objects of economic development in different periods. Lastly, positive relationship between trading with ASEAN members as well as neighbour countries and Vietnam’s rice export values indicate the important role of participating in free trade agreement and trading with neighbour countries. Therefore, policy makers should issue policies which encourage joining to global associations and free trade agreements to enjoy advantages from reducing tariff and transportation costs. REFERENCE: Adhikari, A. (2014). Export of rice from India: Performance and determinants. Punjab Agricultural University, Ludhiana. Ahmad, B., & Garcia, R. J. (2012). Measuring Commodity-Specific Trade Determinants and Export Potential: A Gravity Model of Pakistan’s Rice Exports. Journal of International Agricultural Trade and Development, 8(2), 125. Bui, T. H. H., & Chen, Q. (2017). An Analysis of Factors Influencing Rice Export in Vietnam Based on Gravity Model. Journal of the Knowledge Economy, 8(3), 830-844. Hatab, A. A., Romstad, E., & Huo, X. (2010). Determinants of Egyptian agricultural exports: A Gravity model approach. Modern Economy, 1(03), 134. 63
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