Impacts of enonomic growth, trade openness, financial development and energy security on fdi into vietnam

Nội dung text: Impacts of enonomic growth, trade openness, financial development and energy security on fdi into vietnam

1. IMPACTS OF ENONOMIC GROWTH, TRADE OPENNESS, FINANCIAL DEVELOPMENT AND ENERGY SECURITY ON FDI INTO VIETNAM Nguyen Thu Thuy, Le Van Tuan, Ngo Duy Do1 Abstract: In this paper, we tested the effect of integration after Vietnam joined the WTO by applying the theory of Autoregressive Distributed Lagged model combined with interaction variables to measure the influence of some economic factors on foreign direct investment (FDI), including GDP growth, trade openness, financial development and energy security after the event in which Vietnam joined WTO in 2007. The annual data collected from 1992 to 2019 covered the periods before and after Vietnam joined the WTO, respectively, called pre-WTO and post-WTO. The empirical results proved the integration of Vietnam to the WTO had led to a relevant impact of aforementioned macroeconomic variables on FDI. Concretely, FDI itself had a positive impact after 2 years during pre-WTO. GDP growth immediately improved FDI in the pre-WTO year, but seemed to decreased FDI in a year of joining WTO, and then quickly increased FDI in a year later. Trade openness this year showed an inversed impact on FDI in the following year. However, thanks to joining WTO event, trade openness enhanced FDI. Financial development in pre-WTO year had a positive impact on FDI. WTO joining had made the degree of influence almost disappear, but still positive. Energy security revealed a negative impact on FDI, without evidence of effect after WTO entering. Keywords: Energy security, FDI, financial development, GDP growth, trade openness, Vietnam, WTO. 1. INTRODUCTION National economies all around the world have emerged as the major channel for economic integration of emerging market economies amid globalization. Simultaneously, linkages among economic variables can promote economic development. The event that Vietnam joined the WTO in 2007 is one of channels which makes Vietnamese economic integrate with the international economic. It is obvious that the Vietnamese economy is now being influenced by many different factors which result from both internal causes and the international economic integration process, such as WTO entry in particular. One can find many benefits of WTO admission, such as the same import tariffs as other WTO members; fewer non-tariff barriers; increase continually of Vietnam’s export; benefit from a wider variety of products and services; increase significantly of foreign direct investment; higher position on the international arena. However, WTO accession also poses some challenges. For example, growing competitive pressure is the biggest challenge. As we can see, Vietnam is now in tight correlation with the world economy, hence Vietnam will be stronger and quicker global impacted. To exist and gain more benefit, every economic sector should be aware and understand deeply the integration process and its mechanism. Stock market is one of the fastest channels that the volatility of international economy influences on Vietnam economy. 1 Thuongmai University; Email: nguyenthuthuy@tmu.edu.vn 612
2. INTERNATIONAL CONFERENCE PROCEEDINGS: GLOBAL FDI AND RESPONSES OF FDI ENTERPRISES IN VIETNAM IN THE NEW CONTEXT 613 Foreign direct investment is a form of business of one economy enterprise operating in the territory of another economy in order to gain long-term benefits and gain real management rights over the enterprise. FDI capital is the capital flow of individuals and organizations of this economy to invest in production and business activities in the territory of another economy for the purpose of generating profits or other benefits for investors. Although appearing several decades later than other external economic activities, FDI has quickly established its position in international relations. Theoretically, economic growth means more profits for investors, so it will attract FDI by increasing the investor’s expected return (Toulaboe et al., 2009). Trade openness is an indispensable factor paving the way for the process of attracting FDI into each country (Pravin, 2012). Financial development is one of the factors affecting the attraction of FDI, through the efficient allocation of resources of the economy. Thereby it helps to better absorb the benefits from FDI capital. Consequently, when FDI comes into economic growth promotion, the stimulation of FDI inflows continues to be enhanced into the country (Mollah et al., 2020). Furthermore, the attraction and development of the FDI sector must always be associated with the sustainable development strategy. One aspect of sustainable development is the issue of resource use and environmental protection, which needs to take into account the requirements of ensuring energy security, food security and in the context of global climate change. Therefore, when energy security is ensured, it will help to reduce the burden in the process of attracting and effectively using FDI capital (Rabindra, 2021). Gradually becoming an inevitable trend of history, an indispensable need of every country in the world. For empirical situation, FDI has been improved by some macroeconomic factors in developed countries (see Lipsey, 2001) as well as developing countries (see Alam et al., 2013). Such as Vo Thi Ngoc Trinh et al. (2020) investigated some Southeast Asia, including Vietnam, showed that those variables that were statistically significant and had a positive effect on FDI included GDP growth, total population, inflationary, mobile phone registration, labor force participation rate, domestic credit for the private sector and economic integration. The variable that had a negative effect on FDI was the final general government expenditure. With a similar idea of studying the impact of some macroeconomic variables on FDI under the WTO environment in a developing country of Vietnam, the authors changed the set of variables with a different econometric methodology of Autoregressive Distributed Lagged model to fill the gap in the empirical literature. With a hope of inspiring researchers and market practitioners to further conduct research on the potential of the emerging economic of Vietnam, in this article the authors seek to answer the following questions: Does the WTO joining event increase the impact of GDP growth, trade openness, financial development and energy security on FDI? The paper is organized as follows. The literature on the effects of some macroeconomic variables on FDI during the integration of Vietnamese economic is presented in Section 2. Section 3 is devoted to describe the research data and methodology. Section 4 presents empirical results and discussions. Conclusion is in Section 5. 2. LITERATURE REVIEW The relation between economic and uncertainty manner has already been investigated numerously. Hassett and Sullivan (2015) reviewed the literature on the effects of policy
3. 614 KỶ YẾU HỘI THẢO KHOA HỌC QUỐC TẾ FDI TOÀN CẦU VÀ ỨNG BIẾN CỦA DOANH NGHIỆP FDI TẠI VIỆT NAM TRONG BỐI CẢNH MỚI uncertainty on governments as well as enterprises’ manner. Hassett and Sullivan focused on the linkage between investment and uncertainty, and explained economic variables including domestic FDI, investment and economic growth. Dunning (1988) studied the determinants of FDI through the theoretical model of OLI (Ownership-Location-Internalization) including 3 groups of advantages: advantage of ownership (O), advantage of location advantage (L) and advantage of internalization (I). With the goal of FDI is to reduce the cost of market research, tariff and non-tariff barriers. Nunnenkamp (2002) studied the determinants of FDI in developing countries in the context of globalization. The results showed that globalization had an effect on FDI. In addition, non-traditional factors such as cost, additional factors of production and openness of the economy were gradually becoming more important, and traditional factors such as market size and growth were on the decline. However, traditional factors were still the dominant factors shaping the allocation of FDI. There are many empirical studies related to factors affecting FDI by different methods. Demirhan et al. (2008) identified factors affecting FDI of 38 developing countries in the period from 2000 to 2004, using a cross-data analysis model, including: size market, inflation rate, the infrastructure, labor costs, openness of the economy, political and tax risks. The results showed that the above factors all had a positive influence on FDI attraction, in addition to labor costs and political risks. Jayasekara (2014) studied the determinants of FDI in Sri Lanka, India, Bangladesh and Pakistan for the period 1975-2012, using a modified minimum regression model (FM-OLS). Factors included in the analysis model were GDP growth rate representing the market size, inflation rate, government consumer spending, exchange rate representing macroeconomic stability, lending rates representing financial development, total import and export value representing the openness of the economy, workforce. The number of phone lines per 100 people in the country represented the infrastructure. The results showed that there was a positive effect of GDP growth rate, government spending, total export and import value, labor force, and infrastructure. However, inflation rate, exchange rate, interest rate negatively affected FDI attraction and competition among countries. In addition, the study had shown that tariffs on international trade and the country’s socio-economic conditions also affected FDI inflows. Some economic uncertainty come from events such as crises, wars and trade tensions generate shocks to FDI inflows. Joining WTO is one of those meaningfull events.The negative nexus between domestic uncertainty and FDI inflows, and the positive influence of world uncertainty on FDI inflows was found (Nguyen et al. 2019). Related to the situation of Vietnam, Vo Thi Ngoc Trinh et al. (2020) analyzed the factors affecting FDI in Southeast Asian countries in the context of global economic integration during the period between 2000 and 2018, using panel data of Southeast Asian countries with the GMM estimation method. This paper investigates the influence of some economic factors on foreign direct investment (FDI), including GDP growth, trade openness, financial development and energy
4. INTERNATIONAL CONFERENCE PROCEEDINGS: GLOBAL FDI AND RESPONSES OF FDI ENTERPRISES IN VIETNAM IN THE NEW CONTEXT 615 security after the event in which Vietnam joined WTO in 2007, thanks to combination of Autoregressive Distributed Lagged model combined with interaction variables. 3. DATA AND METHODOLOGY This study uses annual time series data of Vietnam from 1992 to 2019, including FDI, GDP growth, trade openness, financial development and energy security. The set of data was extracted from a study of Ho et al. (2021). Data was collected from the World Bank’s World Development Indicators to discover the effect of GDP growth, trade openness, financial development and energy security on FDI inflows. Table 1 below reports the description of the variables used in the study. Table 1. Variables, Measurement, and Data Sources Variables name Symbols Variables measurement Foreign direct investment FDI Foreign direct investment, net inflows (% of GDP) Gross domestic product growth GDP Gross domestic product growth (annual %) Financial development FINANCE Domestic credit to private sector (% of GDP) Trade openness TRADE Sum of exports and imports of goods and services (% of GDP) Energy security ENERGY Total natural resource rents (% of GDP) Dummy variable WTO WTO = 0, from 1992 to 2006 WTO = 1, from 2007 to 2019 Source: Authors’ summary. Followed by Persaran et al. (1996), in this study, we are doing an estimated regression based on Autoregressive Distributed Lag - ARDL model, the functional form of ARDL model can be shown as follows: whereαi, βi, γi, δi, θi, ϑi, μi, ρi, τi are, respectively, the regression coefficients, ut is the residuals, that have a simultaneous association, and without association with explanatory variables and lags of residuals, and. In this study, it is evident that the ARDL model can be analyzed in the following steps: Step 1, the stationarity of time series should be checked Step 2, the optimal lag length of the model could be found Step 3, the bounds test cointegration Step 4, the estimated results of ARDL model. In order to find out the best model, the study needs to check diagnostics such as using Ramsey Reset test to verify the conditional mean is correctly specified, the stability test of the ARDL model according to the cumulative
5. 616 KỶ YẾU HỘI THẢO KHOA HỌC QUỐC TẾ FDI TOÀN CẦU VÀ ỨNG BIẾN CỦA DOANH NGHIỆP FDI TẠI VIỆT NAM TRONG BỐI CẢNH MỚI sum of recursive residuals (CUSUM) and the test of the residuals without autocorrelation based on Lagrange Multiplier test (LM test). 4. RESULTS AND DISCUSSIONS 4.1. Descriptive statistics Table 2 below presents the descriptive statistics of all variables used in this study, it shows that FDI, GDP, TRADE, ENERGY and FINANCE are all normally distributed according to Jarque-Bera test. Table 2. Descriptive summary and correlation matrix Items FDI GDP TRADE ENERGY FINANCE Mean 5.933823 6.809344 137.0474 8.034836 70.51503 Median 6.106361 6.787316 134.7063 7.842112 65.35954 Maximum 9.713081 9.540480 210.4002 14.18276 137.9121 Minimum 3.390404 4.773587 66.21227 3.355316 13.65691 Std. Dev. 1.860135 1.193273 40.96535 3.011423 41.77317 Skewness 0.505047 0.606914 0.068593 0.176351 0.078156 Kurtosis 2.364233 2.936761 2.130689 2.114842 1.585327 Jarque-Bera 1.602549 1.662047 0.871337 1.021391 2.278950 Probability 0.448757 0.435603 0.646832 0.600078 0.319987 Sum 160.2132 183.8523 3700.281 216.9406 1903.906 Sum Sq. Dev. 89.96264 37.02138 43632.15 235.7853 45369.94 Observations 27 27 27 27 27 Source: Authors’ analysis. 4.2. Unit Root Tests For time-series data, it should be checked for stationarity. Theoretically, if the studied variable is integrated in the order of both I(0) and I(1), the ARDL should be applied. In this study, we check the stationarity based on advanced methods, for example, Augmented Dickey Fuller (ADF), Phillips-Perron (PP). Table 3 below depicts the results of the unit root tests and indicates that variables in this study are stationary in the both I(0) and I(1). In the study of Persaran et al. (2001), the ARDL and especially the ARDL bounds test approach should be focused. Table 3. Results of unit root tests Intercept/trend Variables Augmented Dickey-Fuller Phillips-Perron At level FDI -3.145462 -2.37445 GDP -2.433431 -2.353645 Intercept TRADE 0.239393 0.764259 ENERGY -1.545818 -1.513297 FINANCE 0.027474 0.032954 FDI -3.044176 -2.365952 GDP -2.29853 -2.210794 Intercept and trend TRADE -3.30238* -3.335932* ENERGY -1.595224 -1.551878 FINANCE -2.458524 -2.458524
6. 4.3. Optimal Lag,4.3. Optimal andCointegration Bounds Test INTERNATIONAL CONFERENCE PROCEEDINGS:GLOBAL FDIANDRESPONSESOFENTERPRISESIN VIETNAM IN CONTEXT THE NEW that thebestmodelisARDL(2,1,1,1,1,1,1,1,1). shows 1 Figure models, leading twenty the for value criterion Hannan-Quin demonstrating image the addition, In value. criterion information Hannan-Quin select smallest the can with one study the the models, ARDL estimated some Among zero. to descending lags with optimal lag length will affect the ARDL model, and the selection will follow a number of times model. Theoretically,best in ordertoselectthe will beused traditional waytochoosethe the Significant at1%,5%and10%levels,respectively. At firstdifference Intercept andtrend Notes: To evaluate the optimal lag length in this study, Hannan-Quin information criterion value Intercept ADF; PP indicate the Augmented Dickey–Fuller test; the Phillips–Perron test, respectively. , and * 1.5 1.6 1.7 1.8 1.9 2.0 2.1 TRADE GDP FDI FINANCE ENERGY TRADE GDP FDI FINANCE ENERGY ARDL(2, 1, 1, 1, 1, 1, 1, 1, 1) Figure 1.Hann-Quin’s Criteria for thetwenty BestModels ARDL(2, 1, 1, 0, 1, 1, 1, 1, 1) ARDL(2, 0, 1, 1, 1, 1, 1, 1, 1) ARDL(2, 0, 1, 1, 1, 1, 1, 1, 0) ARDL(2, 0, 1, 0, 1, 1, 1, 1, 1) H a n ARDL(2, 0, 1, 1, 0, 1, 1, 1, 0) n a n ARDL(2, 0, 1, 1, 0, 1, 1, 1, 1) - Q u ARDL(2, 1, 1, 1, 0, 1, 1, 1, 0) i n n ARDL(2, 0, 1, 0, 1, 1, 0, 1, 0) C r i t ARDL(2, 0, 1, 0, 1, 1, 1, 1, 0) e r i a ARDL(2, 1, 1, 1, 0, 1, 1, 1, 1) ( -4.461853 -7.114202 -4.557649 -4.527914 -5.803759 -7.252229 -4.595521 -3.781244 t -5.84757 -3.69387 o ARDL(2, 1, 1, 0, 1, 1, 0, 1, 1) p 2 ARDL(2, 1, 1, 1, 1, 1, 1, 1, 0) 0 m ARDL(2, 0, 1, 1, 1, 1, 0, 1, 0) o d e ARDL(2, 1, 1, 0, 1, 1, 0, 1, 0) l s ) ARDL(2, 0, 1, 0, 1, 1, 0, 1, 1) Source: Results from EVIEWS9 Source: Results ARDL(2, 1, 1, 0, 1, 1, 1, 1, 0) ARDL(2, 1, 1, 1, 1, 1, 0, 1, 1) ARDL(2, 1, 1, 1, 1, 1, 0, 1, 0) Source: Authors’ analysis. ARDL(2, 0, 1, 1, 1, 1, 0, 1, 1) -4.441097 -6.354185 -8.256167 -5.726965 -4.511064 -5.936409 -8.632211 -4.856654 -3.612609 -3.712164 617
7. 618 KỶ YẾU HỘI THẢO KHOA HỌC QUỐC TẾ FDI TOÀN CẦU VÀ ỨNG BIẾN CỦA DOANH NGHIỆP FDI TẠI VIỆT NAM TRONG BỐI CẢNH MỚI 4.4. ARDL Estimation The selected ARDL model is shown in the short run relationship between FDI and economic growth, trade openness, finance development and energy security. Table 4. ARDL (2,1,1,1,1,1,1,1,1) Estimation with Dependence Variable of d(FDI) Variable Coefficient Std. Error t-Statistic Prob.* Short-Run Coefficients D(FDI(-1)) 0.233030 0.207513 1.122966 0.3125 D(FDI(-1)) 0.790199 0.192765 4.099288 0.0094 D(GDP) 0.879645 0.257534 3.415647 0.0189 D(GDP(-1)) -0.283444 0.266282 -1.064453 0.3358 D(TRADE) 0.047143 0.041080 1.147574 0.3031 D(TRADE(-1)) -0.119447 0.040685 -2.935926 0.0324 D(FINANCE) 0.242854 0.039386 6.165926 0.0016 D(FINANCE(-1)) 0.065188 0.070371 0.926356 0.3968 D(ENERGY) -0.593914 0.128303 -4.629012 0.0057 D(ENERGY(-1)) 0.344910 0.205334 1.679753 0.1538 WTO*D(GDP) -1.816096 0.531803 -3.414981 0.0189 WTO(-1)*D(GDP(-1)) 1.964050 0.696563 2.819631 0.0371 WTO* D(TRADE) 0.185819 0.056305 3.300204 0.0215 WTO(-1)* D(TRADE(-1)) 0.085699 0.044885 1.909300 0.1145 WTO* D(FINANCE) -0.244219 0.080345 -3.039627 0.0288 WTO(-1)* D(FINANCE(-1)) -0.239528 0.061007 -3.926212 0.0111 WTO* D(ENERGY) 0.496251 0.329387 1.506588 0.1923 WTO(-1)* D(ENERGY(-1)) -0.438079 0.255391 -1.715325 0.1469 C -0.788013 0.570468 -1.381344 0.2257 Source: Results from Eviews 9 4.4.1. Autocorrelation test According to Breusch-Godfrey Serial Correlation LM test, one can consider: The Null hypothesis: there is no autocorrelation The Alternative hypothesis: There is an autocorrelation Table 5 indicates that the p-value of the ARDL (2,1,1,1,1,1,1,1,1) model is much larger than zero. It is greater than 0.05, therefore, one cannot reject the null hypothesis, indicating that there does not exist autocorrelation between variables in this model. Table 5. LM test for the residual of the ARDL model F-statistic 0.673243 Prob. F (2,3) 0.5734 Source: Results from EVIEWS 9 4.4.2. Model specification test In order to test model specification of ARDL (2,1,1,1,1,1,1,1,1), the Ramsey Reset test can be carried out. Theoretically, if the corresponding probability value is over 0.05, the model
8. INTERNATIONAL CONFERENCE PROCEEDINGS: GLOBAL FDI AND RESPONSES OF FDI ENTERPRISES IN VIETNAM IN THE NEW CONTEXT 619 will be well-specified at the level of significance of 5%. Table 6, in which all probability values are all greater than 0.05, shows that the model is well-specified. Table 6. Model specification Test Value Degree of freedom Probability t-statistic 0.051814 4 0.9612 F-statistic 0.002685 (1, 4) 0.9612 Source: Results from EVIEWS 9 4.4.3. Stability test The stability of the long-run coefficients along with the short-run relationship are evaluated by using CUSUM. In fact, CUSUM checks for the cumulative sum of recursive residuals. Moreover, the cumulative sum of the residuals is inside the standard range. It could be induced that the model residual is stable and therefore the model is also stable. Figure 2 indicates that plots of CUSUM statistics is within the critical bounds of 5 percent significant level or within the pairs of the red straight lines. Accordingly, the results of the study are stable. 6 4 2 0 -2 -4 -6 2015 2016 2017 2018 CUSUM 5% Significance Figure 2. The cumulative sum of recursive and square residuals of the ARDL model at a 5% significance level Source: Results from EVIEWS 9 4.5. Discussion Table 4 indicates that, the empirical results of the short-run relationship are presented as follows: d(FDIt) = - 0.788013 + 0.23302 * d(FDI(t-1)) + 0.790199*d(FDI(t-2)) + 0.879645 * d(GDPt) -0.283444 * d(GDP(t-1)) + 0.047143*d(TRADEt) - 0.119447 * d(TRADE(t-1)) + 0.242854 *
9. 620 KỶ YẾU HỘI THẢO KHOA HỌC QUỐC TẾ FDI TOÀN CẦU VÀ ỨNG BIẾN CỦA DOANH NGHIỆP FDI TẠI VIỆT NAM TRONG BỐI CẢNH MỚI d(FINANCEt) + 0.065188 * d(FINANCE(t-1)) - 0.593914 * d(ENERGYt ) + 0.34491 * d(ENERGY(t-1)) - 1.816096 * WTOt * d(GDPt) + 1.96405 * WTO(t-1)* d(GDP(t-1)) + 0.185819 * WTOt * d(TRADEt) + 0.085699*WTO(t-1) * d(TRADE(t-1)) - 0.244219 * WTOt * d(FINANCEt) - 0.239528WTO(t-1) * d(FINANCE(t-1)) + 0.496251 * WTOt * d(ENERGYt) - 0.438079*WTO(t-1)* d(ENERGY(t-1))+ut The estimate results indicate that variables as FDI itself, GDP growth, trade openness, financial development could significantly explain the volatility of FDI at the 5% level of significance. Further, the event in which Vietnam joined WTO in 2007 had made a significant effect on the relationship among these variables. The estimated coefficient of D(FDIt-2) is 0.790199, indicating that a one percent of GDP increase in FDI inflow could increase itself by about 0.79 percent in two years after, during the time before 2007. This shows that Vietnam’s FDI growth rate is still on the rise in long run. The estimated coefficient of GDP is 0.879645, indicating that a one percent increase in GDP growth could significantly raise the FDI inflow by about 0.88 percent during the pre- WTO period. This result is consistent with Khamis et al. (2015) from considering the influence of GDP per capita and inflation rate on FDI inflows into United Arab Emirates (UAE), in which GDP per capita is used as proxy of market size has a statistically positive effect on FDI inflows. This result is consistent with expectation in economic theory as referred in Toulaboe et al., 2009 The estimated coefficient of D(TRADEt-1) is -0.119447, indicating that a greater trade openness could significantly decrease FDI inflows in the pre-entering-WTO period. Trade openness is meaningful for investigating the import-export balance of each country, and is regarded to be one of critical determinants of FDI inflows. Globalization and liberalized trade policies impact the degree of output and economic activitớe and enhance foreign investors. A quantity of economies have encouraged to increase more FDI thanks to opening their country. The impact of trade openness on FDI inflows is found to be various. In economic theory, trade openness can generate effect on FDI negatively or positively, which is decided greatly by the trade policies of the host country’s (Liargovas and Skandalis, 2012). Firstly, a great of previous research has showed a positive nexus between FDI inflows and trade openness, for example as presented by the empirical results found by Makoni (2018). The author revealed the positive nexus between trade openness and FDI. Concretely, a country with fewer restrictions on exports and imports has a greater opportunity of increading FDI. Secondly, some other studies have discovered that there existed a negative nexus between FDI inflows and trade openness (Adow and Tahmad, 2018). Thirdly, Wickramarachchi (2019) showed that trade openness had no influence on FDI in BRICS countries. Our results is consistent with Adow and Tahmad (2018). However, after Vietnam joined the WTO the impact of trade openness has become positive with the estimated coefficient of be of 0.185819. This has made the aggregate impact of trade openness on FDI be 0.066372. Now the result is similar to Makoni (2018). Interstingly, this supports the great advantage of globalization to enhance FDI inflows. The estimated coefficient of D(FINANCEt) is 0.242854, indicating that a greater financial development could significantly increase FDI inflows before Vietnam joined WTO. In contrast, after Vietnam joined the WTO the impact of financial development has become negative with the estimated coefficient of and , respectively, be -0.244219 and -0.239528. This has made the
10. INTERNATIONAL CONFERENCE PROCEEDINGS: GLOBAL FDI AND RESPONSES OF FDI ENTERPRISES IN VIETNAM IN THE NEW CONTEXT 621 aggregate impact of financial development on FDI be -0.001365 and 0.003326. It means that, after joining WTO, financial development of Vietnam may negative impact on the first year but become positive on the following year. This empirical result is consistent with and follows the theorical principle mentioned in Mollah et al. (2020). The estimated coefficient of D(ENERGYt) is -0.593914, indicating that a greater energy security could significantly decrease FDI inflows before Vietnam joined WTO. Whereas, after Vietnam joined the WTO, the author could not found the effect of energy security on FDI inflows. Our results are specific to the situation of Vietnam, in the line of research of Inglesi- Lotz et al. (2021), in which the authors demonstrated that electricity supply is a positive contributor to inward FDI, ceteris paribus, and electricity prices are a negative contributor to inward FDI, ceteris paribus. The resutl in the paper comes inversely to Inglesi-Lotz et al. (2021) and economic theory, which needs more other empirical evidences. 5. CONCLUSIONS This study discovers the influence of economic growth, trade openness, financial development and energy security on FDI inflows of Vietnam between 1992 and 2019. The Augmented Dickey-Fuller (ADF), Phillips-Perron (PP) unit root test; the ARDL model are employed. It is found that FDI itself had a positive impact after 2 years during pre-WTO. GDP growth immediately improved FDI in the pre-WTO year, but seemed to decreased FDI in a year of joining WTO, and then quickly increased FDI in a year later. Trade openness this year showed an inversed impact on FDI in the following year. However, thanks to joining WTO event, trade openness enhanced FDI. Financial development in pre-WTO year had a positive impact on FDI. WTO joining had made the degree of influence almost disappear, but still positive. Energy security revealed a negative impact on FDI, without evidence of effect after WTO entering. The government should keep enhancing the GDP growth, trade openness and financial development as they showed positive impacts on FDI inflows. Future studies could be deployed to investigate other determinants of FDI inflows in Vietnam related to many other variables, except for those in this paper, which have been theoretically hypothesized to impact FDI inflows into a host country. For instance, variables could be included as political stability, infrastructure, country risk, and others, as suggested in Khamis et al. (2015). REFERENCES 1. Adow, Anass Hamedelneel, and Abdel Mahmoud Ibrahim Tahmad. 2018. The impact of trade openness on foreign direct invest-ment in Sudan by sector in the 1990–2017 period: An empirical analysis. Economic Annals-XXI 172: 14–21. 2. Alam, A., & Zulfiqar Ali Shah, S. 2013. Determinants of foreign direct investment in OECD member countries. Journal of Economic Studies, 40(4), 515-527. 3. Demirhan, E., & Masca, M. 2008. Determinants of foreign direct investment flows to developing countries: a cross-sectional analysis. Prague economic papers, 4(4), 356-369. 4. Dunning, J. 1988. The Eclectic Paradigm of International Production: A Restatement and Some Possible Extensions. Journal of International Business Studies, 19(1), 1-31.
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