Regional Economic Integration, Logistics Performance and Bilateral Trade: Empirical Evidence from Vietnam

Regional Economic Integration, Logistics Performance and Bilateral Trade: Empirical Evidence from Vietnam Duc-Nha Le Ton Duc Thang University, Vietnam Abstract In the age of flourishing regional economic integration, export-oriented economies tend to be more easily approached which is synonymous with subsequent increases in bilateral trade volume Nations have paid much attention to determining the key drivers of export growth In accordance with technological advancements of transportation and logistics industries, international trade has been dramatically affected by this trend Thus, this research exploits an integration- and logistics-driven Gravity Model of trade as the analytical framework by including measurement of logistics performance and regional economic integration into the fixed effect and random effect estimation A panel data set of Vietnam and its importing partners is selected as sample for the analysis Findings confirm the validity of Trade Gravity Model However, geographic disadvantages significantly seem to exist which could be simultaneously mitigated by either trade openness or logistics performance as they statistically appear to be conducive to trade flows This implicitly indicates the active role of trade and logistics policies in the contemporary period Most strikingly, from the perspective of the exporting country, trade agreements signed by a trading block to which the exporting country is a party and a single economy might facilitate “intra-block” competition for foreign markets, which ultimately hampers the export growth of each individual member, specifically in trading relations with importing countries of improved logistics performance Keywords: Bilateral trade; Gravity model; Logistics performance; Regional economic integration JEL Classification: F1; F13; F14; F15 Introduction For decades, export-oriented economy has been a prevailing economic model which has been constantly deeply rooted in the mind of national policy-makers (Suzuki, Y., 2012; Yang, C., 2014; Hong, C Y., & Li, J F., 2015) In the most recent years, it has been constantly being observed that export of developing countries have kept growing at a steady pace, especially those which are located in Asia (WTO, 2017) The growing participation of developing economies in the global trading system has been statistically confirmed by the volume of exported merchandise and its share in the world export pie which has reached the value of 6.6 trillion US Dollars in 2016 (WTO, 2017) accounting for approximately 42.4% of the entire world The similar figures of developing Asian countries are 4.4 trillion US Dollars and 28.4% respectively (WTO, 2017) As can be seen in Figure 1, the export of developing regions has been steadily accounted for about 40% of the world’s total export in which the share of Asian countries has kept almost unchanged at the rate of 33.51% the world’s total share on average with a promising signal of a slight annual increase in the portion thereof 210 150 Developing Asia Developing economies World 100 50 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Source: World Bank Statistics Figure 1: Share of export value by region (%), 2007 – 2016 In 2016, Vietnam’s export was among few ones’ which maintained a positive growth in comparison with the statistics of 2015 (WTO, 2017) which achieved the increasing rate of 9.0% (Vietnamese MOIT, 2016) This has marked a continued augmentation of Vietnam’s export value in the series of seven consecutive years since the global economic crisis in 2009 with the average growth rate of the entire selected period is 17.83% As can be seen in Figure 2, the upward-sloping longitudinal trend of export value has been at a dramatic pace over the past eight years since the global economic downturn 200,000,000 150,000,000 100,000,000 50,000,000 2009 2010 2011 2012 2013 2014 2015 2016 Source:UN COMTRADE Statistics Figure 2: Vietnam's export value (US Dollar thousand), 2009 – 2016 Export value is calculated as the aggregate of those generated by all firms within one nation in a certain period of time Therefore, the exporting macro-achievements could be largely built from the corporate microfoundations (Hoekman, B., & Nicita, A., 2010; Persson, M., 2013) At the firm level, one of the key things determining export performance of an exporting firm is the trading costs it has to pay to successfully deliver the goods to the importer which can be reversely considered as the impediments to trade when these costs are extremely high (Hausman, W H et al., 2005; Persson, M., 2013; Martí, L et al., 2014; Martí, L., & Puertas, R., 2017) In the overall breakdown of most international business transactions, the costs of transportation and logistics account for a considerable proportion thereof (Saslavsky, D., & Shepherd, B., 2014; Feenstra, R C., & Ma, H., 2014; Martí, L., & Puertas, R., 2017), which ultimately determines the business competitiveness at both firm and national levels (Mustra, M A., 2011; Martí, L et al., 2014) At the macro-level, logistics has been reportedly one of the core pillars of national and sub-national economic development and competitiveness and conversely the growing demand for logistics services resulted from economic wealth facilitates the expansion 211 of logistics capacity (Sánchez, R J et al., 2014; Lean, H H et al., 2014; Xuejiao, W., 2015; World Bank, 2016; Qiao, H., 2017; Lan, S et al., 2017) Over the last few decades, logistical capacity of Vietnam has been improved dramatically The performance of logistics is characterized by the quality of institutional environment and supply chain performance which consequently enables the cross-comparison among various economic groups at different levels (World Bank, 2016) The synthetic indicator of logistics performance allows the evaluation of logistics development of the entire nation It is called the Logistics Performance Index (LPI) which is constituted by the six components including Customs, Infrastructure, International Shipments, Logistics Quality and Competence, Tracking and Tracing, Timeliness which represent main aspects of national logistical competitiveness This indicator is constructed in the effort of providing national governments with a closer and multi-dimensional look at how logistics and trade facilitation policies have been being improved to satisfy the demand for international trade flourishing and economic growth 3.20 3.15 3.10 3.05 3.00 2.95 2.90 2.85 2.80 2.75 3.15 3.00 2.98 2.96 2.89 2007 2010 2012 2014 2016 Source: World Bank Statistics Figure 3: LPI of Vietnam, 2007 – 2016 As can be seen in Figure 3, the aggregate LPI increased significantly in the period 2007 – 2014 and sharply declined in 2016 to the value even less than that of 2012 This poses a warning for Vietnam’s policy-makers to enhance the performance of national logistics as this is a key driver of global value chain participation of the nation In terms of ranking position, the constant status of the 53 th was recorded in the period of 2007 – 2012 which then increased to the 48th position in 2014 before plunging to the 64 th in 2016 (World Bank, 2016) In terms of the absolute LPI scores, there has been only some slight changes in these values over the abovementioned period (World Bank, 2016), the decreasing value of ranking position in 2016 accordingly indicates the backward development of Vietnam’s logistics performance when compared to those of other nations The increase of other nations’ logistical capacity has arguably led to the comparative degradation of that of Vietnam This marks a negative and worrisome sign in the race of boosting cross-border trade volume of the economy and the resultant inflow of foreign direct investment or the competition among host countries for external engines of growth The concern for logistics performance was also actualized by the first annual publication reported by Vietnamese Ministry of Industry and Trade in 2017 entitled “Logistics Report of Vietnam 2017: From plan to action” This marked a raising policy-leveled awareness of the contribution of logistics to export growth and economic development 212 Literature Review A large mosaic of contemporary academic work has employed the Gravity Model to scrutinize the drivers of export growth (Babri et al., 2017; Baltagi et al., 2017; Krugman, 2008), which confirms the superiority of this model in international trade research area Krugman (2008, p 12) formulated the traditional version of this model which was primarily proposed by Tinbergen & Hekscher (1962) as follows: Tij = A * Yi * Yj/Dij in which A is a constant value, Tij is the bilateral trade volume between country i and country j, Yi is country i’s GDP, Yj is country j’s GDP, and Dij is the distance between the two countries Various studies has subsequently integrated different variables into the traditional version of Gravity Model to test whether and how significantly contextual determinants strengthen the metaphorical “gravitational force”, measured by bilateral trade volume, between focal economies In other words, variants of this model could be created by adding different factors, in most cases, they could be linguistic similarity (Bensassi et al., 2015; Gani, 2017; Kahouli & Maktouf, 2015b; Kahouli & Omri, 2017; Martí et al., 2014; Martí & Puertas, 2017; Puertas et al., 2014; Saslavsky & Shepherd, 2014), continental backgrounds (Kahouli & Maktouf, 2015b; Martí et al., 2014; Martí & Puertas, 2017; Puertas et al., 2014; Saslavsky & Shepherd, 2014), exchange market fluctuations (Bui & Chen, 2017; Kahouli & Maktouf, 2015b; Kahouli & Omri, 2017; Narayan & Nguyen 2016), geographic advantages and proximity (Bensassi et al., 2015; Gani, 2017; Kahouli & Maktouf, 2015b; Kahouli & Omri, 2017; Martí et al., 2014; Martí & Puertas, 2017; Puertas et al., 2014; Saslavsky & Shepherd, 2014), market access (Bensassi et al., 2015; Besedeš & Cole, 2017; Gani, 2017; Kahouli & Maktouf, 2015b; Narayan & Nguyen 2016), trade barriers (Bensassi et al., 2015; Besedeš & Cole, 2017; Gani, 2017), population (Bui & Chen, 2017; Kahouli & Omri, 2017; Kahouli & Maktouf, 2015b; Liu et al., 2016; Martí et al., 2014), environmental deterioration (Duarte et al., 2018; Kahouli & Omri, 2017), regional economic integration (Carrere, 2006; Gani, 2017; Kahouli & Maktouf, 2015b; Kahouli & Omri, 2017; Narayan & Nguyen 2016), foreign investment (Kahouli & Omri, 2017; Liu et al., 2016), logistical capacity (Bensassi et al., 2015; Bottasso et al., 2018; Gani, 2017; Martí et al., 2014; Martí & Puertas, 2017; Puertas et al., 2014; Saslavsky & Shepherd, 2014), factor endowments like labour and technology (Liu et al., 2016) Those factors reflect a holistic and multi-aspect approach to the study of bilateral trade between countries Some extended models could be generated from the original version by replacing its dependent variable of international trade and inserting new ones like migration (Czaika & Parsons, 2017; Poprawe, 2015; Ramos & Suriñach, 2017), foreign direct investment (Falk, 2016; Kahouli & Maktouf, 2015a; Leibrecht & Riedl, 2014) Nevertheless, previous studies have disproportionately focused only on emerging economies in various regions other than Vietnam (Bui & Chen, 2017; Narayan & Nguyen 2016) Few scholarly concerns have been received in response to this situation of Vietnam (Griffin, 2016; Hai & Hung, 2018) This seems to be contrary to the growing demand for deeper insights into underlying contextual drivers of Vietnam’s export growth Most recently, Bui & Chen (2017) have revisited this model by conducting analysis on Vietnam’s rice export to 15 strategic trading partners in the period of 2000-2013 thus limiting the applicability to a solely industryspecific level Also, this study summarized relevant literature whose sampling was based on Vietnam’s statistics However, all of those studies appeared to be conducted more than ten years ago, just few years after Vietnam’s accession to WTO, which may restrained the validity of the findings Some macro-variables were also disregarded in this study such as whether the partners had participated in the free trade agreements to which Vietnam is a party (regional economic integration), the extent to which logistical advantages contributed to the overall trade growth (logistics performance), whether a coastal position enabled a larger amount of trade volume to flow across nations (landlockedness), etc Findings of this study confirmed the significant impacts of economic growth, price, demographic characteristics, and foreign exchange fluctuations on rice export volume which validated the sectoral Gravity Model in the situation of Vietnam’s economy 213 Based on a similar approach but focusing on a broader scope, Narayan & Nguyen (2016) have investigated the causality among the bilateral trade, openness, distance and international economic integration In this study, much attention has been paid to the effect of selected trading blocks to which Vietnam was a signatory, specifically ASEAN (Association of Southeast Asian Nations), APEC (Asia-Pacific Economic Cooperation) and WTO (World Trade Organization) In this logic, other traditional variables were not included in the study, which apparently exposes the findings to the risk of endogeneity (Baltagi, 2008) Despite those limited scholar albeit primary concerns for Vietnam’s situation, research gaps still exist As presented in the Introduction section, logistical capacity has been playing an increasing role in boosting trade flows, especially in the situation of economies in transition like Vietnam (Bensassi et al., 2015; Bottasso et al., 2018; Gani, 2017; Martí et al., 2014; Martí & Puertas, 2017; Puertas et al., 2014; Saslavsky & Shepherd, 2014) Logistics costs which were previously reflected by the geographic distance variable in traditional Gravity Model have not provided a multi-dimensional and comprehensive view about how logistics affect export growth Additionally, distance variable does not indicate the active role of policies in shaping and strengthening national logistics competitiveness, instead it solely represents an “inborn” advantage which nations could not affect Hence, this research aims at examining whether the two mainstream trends in Vietnam, specifically logistics development and regional economic integration, significantly affect the export growth of the country To analyze the causality between export growth and other economic phenomena, the study exploits an integration- and logistics-driven Gravity Model which includes trade openness, regional economic integration, landlockedness and logistics performance Also, the aggregate effects of integration and logistics on export have been considered by adding combined variables of logistics performance, regional economic integration and landlockedness Thus, the proposed model of this study is presented as follows: Equation: lnEXPij,t = β1 + β2*lnGDPi,t + β3*lnGDPj,t + β4*laglnGDPi,t + β5*laglnGDPj,t β6*lnDISTij + β7*lnTOIi,t + β8*lnTOIj,t + β9*lnOLPIi,t + β10*lnOLPIj,t + β11*LANDj + β12*RTAij + β13*MODRTAi,t + β14*MODRTAj,t + i,t Where the prefix “ln” represents the natural logarithm of attached variables’ values, i is the export country (Vietnam) and j is the importer (Vietnam’s trading partners), t is the year of observation (t = 1-2007, 2-2010, 32012, 4-2014, 5-2016), prefix “lag” means the regressors’ data is extracted from the year t-1, i,t is the error term of the estimation, EXPij,t is the annual bilateral export volume (in thousand US Dollars) from country i to country j in year t, GDPi,t is the gross domestic product value (in thousand US Dollars) of country i in year t, GDPj,t is the gross domestic product value (in thousand US Dollars) of country j in year t, the research also includes the lagged values of those indicators of economic size, specifically laglnGDPi,t and laglnGDPj,t, as the possibility of significant bidirectional causality between export growth and economic performance (Goh et al., 2017; Rahman, 2017; Sunde, 2017) may cause the lag effect, endogeneity and residual autocorrelation of the estimation (Bellemare et al., 2017; Wilkins, 2018), DISTij is the time-invariant geographic distance (Kilometers) from country i to country j, TOIi,t and TOIj,t are the trade openness indexes (the sum of exports and imports of goods and services measured as a share of GDP) of country i and j in year t respectively, OLPIi,t and OLPIj,t are the overall logistics performance indexes of country i and j in year t respectively, LANDj (landlockedness) equals if country j is landlocked (not a coastal country) and equals if country j has the seashore in certain regions, RTAij (Regional Trade Agreement) equals if country i and country j are both signatories to at least one regional trade agreement in year t and equals if the two countries have not yet signed any regional economic agreements, MODRTAi,t and MODRTAj,t are combined variables which equal lnOLPIi,t and lnOLPIj,t respectively multiplied by the dummy variable named RTAij to examine the moderating effects of regional economic integration on the “gravitational force” between Vietnam and its trading partners Additionally, this aims at testing whether regional economic integration and logistics development could simultaneously affect the export growth 214 Research Methodology As the panel or longitudinal data delineates both spatial and time-variant aspects of the selected sample, this characteristic makes them more superior to the cross-sectional or time series data set when used separately (Baltagi, 2008; Hsiao, 2014), thus the findings of this research are concluded based on a panel data set of selected countries Furthermore, cross-country or cross-industry analysis frequently requires this type of data set as it could reflect the time-variant changes of economic phenomena in the selected countries as well as assess the long-term impacts of policies on economic issues (Askenazy et al., 2018; Baltagi, 2008; Cerutti et al., 2017; Joshi et al., 2017; Shahbaz et al., 2018; Zhang et al., 2017) The quantitative method of this research benefits the advantages of the Fixed Effect Model (FEM) and Random Effect Model over those of Pooled OLS (Ordinary Least Square) in panel data set (Baltagi, 2008; Hsiao, 2014) as the latter could lead to the omitted variable bias (OVB) (Fraser et al., 2006) and some frequently-detected flaws of estimation models like autocorrelation and multicollinearity (Baltagi, 2008; Hsiao, 2014) Additionally, the Pooled OLS appears not to be appropriate for panel data analysis as it disregards the national variations in different aspects of their economies (Cerutti et al., 2017; Fraser et al., 2006; Joshi et al., 2017) Despite the fact that FEM allows estimating specific y-intercepts of each individual observation (Baltagi, 2008; Bui & Chen, 2017; Hsiao, 2014) which instead could turn the coefficient β1 in the proposed Equation to βj (j represents each individual trading partner of Vietnam), it could not incorporate the effects of time-invariant variables like geographic distance and landlocked status of nations (Baltagi, 2008; Bell & Jones, 2015; Bui & Chen, 2017; Hsiao, 2014) while those variables are unremovable components of the prototypical Gravity Model for international trade Alternatively, the REM could be employed as a complement to the estimation by enabling the presence of time-invariant variables’ parameters (Baltagi, 2008; Hsiao, 2014) Nevertheless, the heterogeneity of the selected sample could not be considered in the REM (Baltagi, 2008; Hsiao, 2014) as the y-intercept is a random average value which does not vary across the nations in this model Hence, to determine whether model is statistically valid to be applied to the data set, the Hausman test is exploited to solve this problem (Baltagi, 2008; Hsiao, 2014) which designed to test the correlation between explanatory variables and the cross-sectional error term Sampling And Data Collection Selected countries are 112 Vietnam’s trading partners which include countries in different regions around the world The bilateral export volume from Vietnam to those countries is collected in the five years, specifically 2007, 2010, 2012, 2014 and 2016 due to the fact that OLPI statistics were only reported in those years by World Bank All of the data sources and calculation units of included variables of this research are presented in Table as follows Table 1: Data sources and intepretation Variables EXPij,t GDPi,t GDPj,t DISTij TOIi,t Data measurement Annual Bilateral export volume (in thousand US Dollars) between Vietnam and 112 importing countries Annual Gross Domestic Product of Vietnam (in thousand US Dollars) Annual Gross Domestic Product of Vietnam’s trading partners (in thousand US Dollars) Geographic distance between Vietnam and each trading partner (Kilometers) Annual Trade Opennes Index of Vietnam (the sum of exports and imports of goods and services measured as a share of GDP) 215 Sources International Trade (ITC), trademap.org Center World Bank World Bank FreeMapTools freemaptools.com World Bank website, TOIj,t OLPIi,t OLPIj,t LANDj RTAij Annual Trade Opennes Index of Vietnam (the sum of exports and imports of goods and services measured as a share of GDP) Annual Overall Logistics Performance Index of Vietnam Annual Overall Logistics Performance Index of Vietnam’s trading partner Landlockedness (equals if the trading partner does not seashore in its sovereign territory and equals if it has at least one coastal region within its territory) Regional Trade Agreement (equals if the trading partner and Vietnam are both signatories to at least one bilateral/multilateral trade agreement in a specific year and equals if they have not yet entered such agreements) WTO membership is disregarded as almost all Vietnam’s trading partners have already integrated into this global mulitlateral trading system World Bank World Bank World Bank Google Map WTO Regional Trade Agreements Information System (RTA-IS), rtais.wto.org Source: Conducted by the Author In the next section, the research presents analytical results which reveal the impacts of logistics performance and regional economic integration on export growth of Vietnam and also unveil how they simultaneously affect the trade volume of Vietnam Analytical Results Table demonstrates the mean, minimum, maximum and standard deviation values of the panel data set In terms of logistics performance and economic size, as could be seen from Table 2, Vietnam has exported to a wide range of countries of different logistical competitiveness and economic size This increases the generability of the findings as it takes the logistical and economic heterogeneity into analytical account Similarly, the extent to which trading partners differ in trade openness is considerable as the maximum value appears to be four times higher than the minimum one Table 2: Descriptive Statistics Variables mean max Std N EXPij 988592.41 420 38450000 3009702.5 560 GDPi 1.476e+08 77414426 2.026e+08 45896267 560 GDPj 6.094e+08 739027.2 1.857e+10 1.854e+09 560 DISTij 9187.4424 392.848 19387.52 4523.8328 560 TOIi 151.80515 135.48939 173.24206 13.336841 560 TOIj 72.202076 17.724777 398.42979 47.227941 560 OLPIi 2.9978657 2.8888546 3.154763 08737181 560 OLPIj 3.0222047 1.716096 4.225967 58121862 560 Source: Analyzed by the Author Table 3: Regression Results VARIABLES lnGDPi,t lnGDPj,t 216 FEM lnEXPij,t REM lnEXPij,t 1.135*** (0.009) 0.426** 0.841** (0.037) 0.734*** laglnGDPi,t laglnGDPj,t o.lnDISTij lnTOIi,t lnTOIj,t lnOLPIi,t lnOLPIj,t o.LANDj RTAij MODRTAi MODRTAj (0.024) -0.220 (0.468) 0.008 (0.766) - (0.000) -0.341 (0.238) 0.025 (0.312) 1.246 (0.527) 0.043 (0.848) 1.218 (0.467) 0.895 (0.119) - 2.214 (0.233) 0.283* (0.050) 0.858 (0.606) 1.312*** (0.004) 0.405 (0.859) -0.074 (0.970) -0.697 (0.475) 1.886 (0.367) -0.342 (0.857) -1.149* (0.084) -0.791*** (0.000) -0.969*** (0.000) 19.302*** (0.000) 0.7974 lnDISTij LANDj Constant 22.160*** (0.000) 0.5728 R-sq overall Hausman Test Prob>chi2 = ***, **, * significant at the levels of 1%, 5% and 10% respectively 217 0.4345 The regression results of FEM and REM are presented in Table (see Appendix) Based on the empirical results, REM appears to be more appropriate than FEM for the estimation as the p-value of the Hausman test is greater than 0.05 (Prob.>chi2 = 0.4345) As could be seen in Table 3, gross domestic product of both Vietnam and its trading partners is positively associated with Vietnam’s export growth while geographic distance appears to be negatively associated with it This validates the gravity model for trade in the situation of Vietnam Additionally, importing country’s landlockedness empirically restrains their exporting partner from expanding its current market share thus reducing its export growth, which is also supported by previous studies Nevertheless, national geographic disadvantage could be alleviated when domestic markets of importing countries are more easily to be accessed as importer’s trade openness positively affects export growth It seems that in the case of an economy in transition like Vietnam maintaining a roughly stable and substantially open market with openness index greater than 130 (see Table 2), the problem of market access lie in its partners Similarly, the positive causality running from importing countries’ logistics performance to bilateral trade is statistically confirmed However, most strikingly when both exporting and importing countries are parties to a regional trade agreement, the positive impact of logistics performance of importing countries on export growth would be offset considerably This may come from the fact that most regional trade agreements with key partners in which Vietnam participated are plurilateral not bilateral agreements (bilateral agreement signed between a trading block and a single country is equivalent to a plurilateral one) like ACFTA (ASEAN-Chine Free Trade Agreement), AANZFTA (ASEAN-Australia-New Zealand Free Trade Agreement), AKFTA (ASEAN-Korean Free Trade Agreement), ATIGA (ASEAN Trade in Goods Agreement), etc This means that regional economic integration facilitates the competition among exporting countries in seeking foreign markets and reversely differentiates the choices of exporters made by importing countries of improved logistics performance, which ultimately restrains export growth to be further boosted In other words, an importing country may obtain stronger “bargaining power” when joining a trading block by improving its own logistics performance From the specific perspective of Vietnam as an exporting country, this poses a warning that regional economic integration with the participation of more advanced economies, which have frequently already achieved higher logistics performance, would hamper subsequent export growth instead of enabling it due to a common market access commitment made by the parties as a result of MFN (MostFavoured Nation) rule The insignificant effect of exporting country’ logistics performance may come from the fact that Vietnam’s logistical activities and infrastructure have not been well-developed which keeps its logistics performance almost unchanged in the research period (see Table as the maximum-minimum margin is not significant) Conclusions This research has exploited fixed effect and random effect models for the quantitative analysis on a panel data set of Vietnam and its trading partners in an effort of examining which drivers are significant to the export growth of Vietnam in particular and bilateral trade of economies in transition in general An integration- and logistics-intensive Gravity Model is applied to this situation Findings confirm the validity of Gravity Model for trade Also, they advocate the active roles of trade and logistics polices in shaping export competitiveness in the age of international economic integration Geographic disadvantages are empirically the most challenging issues facing export-oriented economies hence implicitly proposing both public and private further investment in logistics development and more attention paid to logistics policy-making Meanwhile, greater market openness is a valid antecedent of increasing export Most importantly, the research validates the effect of logistics performance on international trade Additionally, regional economic integration must be 218 accelerated simultaneously with enhancing logistics performance and implementing other measures to consolidate export competitiveness otherwise the export growth may not increase as expected Limitations And Future Research Directions The fixed effect and random effect models are not sufficient enough to examine the causality among variables especially in cases of existing bidirectionality between economic phenomena in the long run In those situations, Granger causality test appears to be a reliable complement to the analysis Also, the OLPI variable is only reported in 2007, 2010, 2012, 2014 and 2016 which makes it seem to be a biennial indicator Thus, involving this variable in the estimation would limit the number of observations of the entire panel data set and may restrict the meaning of lagged variables in the estimation Alternatively, another annual wellreported albeit sea mode-inclined indicator, namely LSPI (Liner Shipping Connectivity Index) could be worth being considered Future research could expand the scope of selected sample to other emerging economies to enhance the applicability and generability of the findings The separation between North-South and SouthSouth trade is necessary thus prospective as this may better clarify the role of logistics performance in boosting export More contextual variables should be added to the estimation such as tariff and non-tariff barriers, six component indexes of OLPI, exchange rates, economic distance, etc which provides more comprehensive understanding of drivers of international trade ACKNOWLEDGEMENT The author is immensely thankful to Mr Pham Tien Thanh who has provided his precious academic advice and econometric support that greatly assisted the research Also, the author is thankful to Ms Nguyen Thi Hong for her assistance in sending paper to her colleagues for further comments and instructions Finally, the author expresses the sincere appreciation to his colleagues in the Faculty of Business Administration, Ton Duc Thang University, Ho Chi Minh City, Vietnam, for sharing paperwork which helps the author have more time to conduct the research References Askenazy, P., Cette, G., & Maarek, P (2018) Rent‐Sharing and Workers' Bargaining Power: An Empirical Cross‐Country/Cross‐Industry Panel Analysis The Scandinavian Journal of Economics, 120(2), 563-596 Babri, S., Jørnsten, K and Viertel, M (2017) Application of gravity models with a fixed 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A cross-country panel data analysis Energy Policy, 107, 678-687 220 ... integration- and logistics- driven Gravity Model which includes trade openness, regional economic integration, landlockedness and logistics performance Also, the aggregate effects of integration and logistics. .. Vietnam, specifically logistics development and regional economic integration, significantly affect the export growth of the country To analyze the causality between export growth and other economic. .. OLPIi,t and OLPIj,t are the overall logistics performance indexes of country i and j in year t respectively, LANDj (landlockedness) equals if country j is landlocked (not a coastal country) and equals