1. Introduction
Attracting FDI inflows is a bright part of the world’s economic picture in many past years. The development of FDI enterprises has been making an important contribution to building a modern technology system, advanced management experience, and support for enterprises participating in global value chains and global distribution networks (Imansyah & Nasrudin, 2016). Moreover, at the same time, FDI inflows also createa premise for businesses to expand the market in the world. Along with that, attracting FDI inflows contributes to increasing production and consumption in the economy. It supports the economy growing more than in the short, medium, and long term as well as creates breakthrough developments for all nations in the world Yugang (2018).
In the case of Vietnam, foreign direct investment is believed to be an important element of Vietnam's economic development. FDI improves GDP and international balance of payments. FDI helps Vietnam receive and transfer modern technologies, and professional techniques, develop domestic technology capabilities, improve human resource quality, create jobs, promote import and export, as well as access to the world market (Jenkins, 2004). FDI also plays a prominent role in international economic integration, it creates links between industries all over the world (Dang & Nguyen, 2021). The rapid increase of FDI inflows into Vietnam in recent years is a great advantage for economic development. Although, some empirical studies have tried to find out the factorsaffecting the foreign direct investment in Vietnam. However, these studies still only provide the impact of traditional factors such as output, economic growth, or interest rate (Nguyen, Luong, & Hoang, 2021). Meanwhile, the openness of trade and economiccooperation – an important issue in increasing investment through attracting external resources and expanding the market has not been considered.
Therefore, the author studied factors of international trade integration such as GDP, Total Trade, Openness, Inflation, and Exchange Rate which have been identified as the set of determinants that can influence foreign direct investment in Vietnam. The study aims to assess the impact of international trade cooperation and distribution on foreign direct investment in Vietnam using the ARDL model to analyze variables. The paper includes 5 parts. The first is the introduction part. Other parts are a literature review, an overview of Vietnam’s FDI inflow, research methodology, empirical results, and the conclusion part.
2. Literature Review
The rapid FDI flows could be pushed up by international integration, as well as free trade agreements (FTAs). In the context of FDI inflows and the increasing of free trade agreements, it proved that the role of integration is very important for all nations and regions. Several studies found and analyzed the achievements of international trade cooperation on inward FDI such as Hicks (1937), Tobin (1969), Bannaga, Gangi, Abdrazak, and Fakhry (2013), Dang et al. (2021). These studies suggested that trade openness has positive signs and significance at a 5 percent level on FDI inflows. This indicates that FTAs may increase the FDI inflows of a region or a nation. As a result, the impact of trade openness on FDI is one robust factor to attract FDI in a nation or a region.
In another study by Nakagane (2002), he acknowledged that the economic process accelerates FDI inflows, probably because the expansion rate represents the prospects of China as an emerging market. The developing Chinese market also attracts many foreign investors. In addition, trade openness is also related to FDI inflows (Barker, 1977; Barro & Sala, 2004; Jayachandran & Seilan, 2010; Belloumi, 2014). Besides, some studies by Omer and Hisham (2013), and Sauvant (2021)used inflation variables to analyze. They proved that the economic and trade stability will also support increasing FDI inflows. While a high rate of inflation usually makes short terms pricing decisions costlier, it could affect the investment decisions of foreign investors. The sign was negative, which indicates that higher levels of inflation would cause fewer amounts of FDI flows. As a result, inflation is also considered a variable impacting FDI inflow in a nation or an area in the world. Besides, Barro et al. (2004) argued that the higher openness of the economy, the more tariff walls can be reduced and eliminated. And, in terms of investment, trade openness will drive investment (Shrestha & Bhatta, 2018). Besides, Joseph, Wang, and Park (2010) still stated that the foreign exchange rate also impacts FDI. A weak exchange rate in the host country can make conditions to attract more FDI inflows because it will be cheaper to buy domestic means. As a result, exchange rate volatility could support increasing or reducing investment.
There are also some studies on this issue in the ASEAN regions (Ismail, Smith, & Kugler, 2009; Masron & Kamaruddin, 2009; Imansyah et al., 2016; Jin, 2016; Yugang, 2018;Dang et al., 2021). All their studies have proved that there is an impact of trade-economic integration on foreign direct investment. Ismail et al.(2009) have proved that there are some determinants of international trade integration affecting FDI inflows into ASEAN nations such as market size, skilled labor, infrastructure, transparency, and trade policy. While Masron et al. (2009) and Pokou (2020) considered that many factors impact FDI in nations, especially factors relating to market issues. They indicated that the moreintegration nations take part in, the more FDI they can attract. Ang (2008) has obtained consistent findings with the market size hypotheses where any increase in the size of the domestic market will cause an increase in FDI inflows into Malaysia. Farhad, Alberto and Ali (2001) examined the importance of human capital in attracting FDI inflows into developing countries (26 countries from Africa, Asia, and Latin America) and found that human capital is one of the most important determinants of FDI inflows. They also found that the growth of domestic markets, stable macroeconomic environment, liberalization policies, the availability of energy, and a generally supportive business environment are significant determinants of FDI inflows.
Imansyah et al. (2016) studied the impact of economic integration and macroeconomic factors on Indonesia's Foreign Direct Investment. Their results indicated that economic integration between Indonesia and Japan, as well as other nations in ASEAN, has created an impact of investment on Indonesia's FDI. Or Jin (2016) found that there are some advantageous aspects of the free trade agreements supporting sharing the mutual resources among countries in integration, especially FDI inflows as a part of economic activities. These results were once again proved by Yugang (2018) when he examined the impact of foreign direct investment flows into the Association of Southeast Asian Nations using the bilateral foreign direct investment data from 2000 to 2009. His empirical results indicated that the Free Trade Agreements have a positive impact on foreign direct investment inflows. In the case of Vietnam, Dang et al. (2021) found that the rise of 1 percent in Vietnam’s GDP will boost approximately from 1.3 percent to 1.6 percent of inward FDI into VietnaAThe greater GDP means the better development of Vietnam’s economy as well as higher purchasing power, which will give more opportunities to enhance sales revenue and gain more profit for companies. As a result, it makes conditions to attract more foreign investors. One percent of the increase in the real exchange rate of the country induces the rise of approximately 1.8 percent to 2 percent in Vietnam’s FDI inflows. This affects FDI inflow because investors will tend to look to other markets when rates change, therefore making opposite influences.
3. Research Methods and Materials
Since 2007, Vietnam joined the World Trade Organization, FDI inflows into Vietnam increased sharply. Table 1. indicates that FDI inflows in 2007 reached 6.700 billion USD. In 2008, it continued to increase, up to $ 9.579 million, up 42.9% over the previous year. However, since 2009, after the 2008 global financial crisis took place, followed by the European public debt crisis, FDI into Vietnam declined significantly. Specifically, FDI in Vietnam in 2009 decreased by 20.7% compared to 2008. However, along with achieving the goal of macroeconomic stability of the Vietnamese government since 2011, FDI into Vietnam has also grown sharply again. And at present, the total FDI inflow reaches 28.50 billion USD (Nguyen, et al., 2021).
Table 1. FDI Inflow in Vietnam from 2006 to 2020
Source: Nguyen, et al. (2021)
There are more than 125 countries and territories investing in Vietnam. Data from 2020 in table 2. shows that South Korea leads total capital is 7.92 billion USD, accounting for 20.8% of total registered investment in Vietnam. Hong Kong ranked second with 7.87 billion USD. Singapore ranked third with 4.5 billion USD, accounting for 11.8% of total investment capital. It is followed by Japan and China. Besides, investment from China and Hong Kong also increase in that period. Investment from China increased by nearly 1.65 times, and Hong Kong by 2.4 times compared with that 2019 (Nguyenet al., 2021).
Table 2. Main FDI Investors in Vietnam 2020
Source: Nguyen, et al. (2021)
4. Data, Methodology, and Hypothetical Issues
4.1. Data and Variables
This study uses quarterly data in Vietnam in the period from 2006 to 2020 to analyze the impact of international trade cooperation on foreign direct investment.
Table 3. Variables
Total trade (TRADE) is the first estimated variable, it reflects the level of trade integration. When TRADE increases, it makes conditions to attract more FDI inflows. Or the more the total trade of the country is, the more efficient the country’s trade is, and this is a good sign for foreign investors.
The next variable is the trade openness of the economy. Trade openness is highly associated with FDI inflows (Tembe & Xu, 2012). That is to say, the more widely the economy is opened, the more foreign capital flows come to the nation. In general, the estimate of OPEN shows that FDI inflows are significantly positively affected by the trade openness of partner countries (Yong, 2013; Majidi, 2017).
The exchange rate is also thought to affect FDI inflows. The increase in the exchange rate means the domestic currency is depreciated against the foreign currencies (Malik, 2019). Investors will find the foreign market in which their value of the investment is valued larger. As a result, they have a trend to seek potential markets to invest their capital. Therefore, countries with low currency value still seem to have more chances to attract FDI inflows.
On the other hand, high levels of inflation would cause fewer amounts of FDI flows. The reason is that a high rate of inflation is a sign of economic instability as well as a government’s inability to remain monetary policies. Foreign companies often avoid investing in countries where governments are weak institutionally or their capabilities in economic governance are low. As a result, high inflation can cause barriers to attracting FDI inflows to a nation (Wang, Hong, Kafouros, & Wright, 2012).
GDP is the final estimated variable, when GDP increases, it makes more opportunities to attract more FDI to the economy because its potential development can increase in the future. Therefore, GDP is expected to be a good sign contributing to FDI attraction (Sahu, 2014; Dritsaki & Dritsaki, 2020).
4.2. Research Model
ARDL (Autoregressive Distributed Lag) model is applied to analyze the impact of international trade cooperation on foreign direct investment in Vietnam in the period from 2006 to 2020. The ARDL model is a combination of the Vector Autoregressions model (VAR) and the Ordinary Least Squares model (OLS). According to Pesaran (1997), Farhad et al. (2001), and Shrestha et al. (2018), using ARDL has many advantages compared with other cointegration methods: (1) The ARDL model is a more statistically significant approach to cointegration testing, whereas Johansen's cointegration technique requires a larger sample size for cointegrationto gain the results; (2) Contrary to the conventional system of long-term relationships, the ARDL does not estimate the equations, it seems to estimate only a single equation; (3) Some other cointegration techniques require the same lagging variables, butusing ARDL the regression variables can contain different optimal delays; (4) In case, variables don’t guarantee the unit root or the stationary of the data system, applying the ARDL procedure is the most suitable.
Based on that, we propose a regressionmodel in which all independent variables will be taken as logarithm or percentage format:
FDI = βo + β1TRADE + β2OPEN + β3EXR + β4INF+ β5GDP (1)
5. Results and Discussion
Based on table 4, we estimate that between FDI and TRADE, FDI and EXR, TRADE and EXR had a high positive correlation. Other variables were not highly correlated within the acceptable range, without affecting the accuracy of the model.
Table 4. Degree of Autocorrelation Between the Independent Variables in the Model
In table 5, the result from the Johansen test shows the cointegration with a significance level of 5%. The results indicate that the trace statistical value is 155.3089 and the critical value is 94.15. Therefore, at the significance level of 5%, there exists a cointegration relationship among the variables in the model.
Table 5. Cointegration Test Using Johansen’s Methodology
Table 6 conducts regression with the VAR model and uses the AIC (Akaike information criterion) as the primary standard. The results show that according to the AIC
standard, the lowest value is when the lag is 4. Therefore, the maximum lag of the model is 4.
Table 6. Choosing the Optimal Lag Length
Moreover, in table 7, FDI quarterly (lag 1, lag 2, and lag 3) has a negative relationship with FDI at the 1% significance level. TRADE without lag has a positive effect on FDI, while TRADE (lag 1 and lag 2) has a negative relationship on FDI at the significant level of 5% and level of 1%. The OPEN is not statistically significant. In addition, EXR (lag 2) has a positive impact on FDI, but EXR (lag 4) still negative impact on FDI. Both EXR is at the significant level of 5%. INF has a negative impact on FDI at all lag variables (lag 1, lag 2, and lag 3) at the significant level of 1% and 10%. Besides, GDP without lag has a negative effect, and GDP (lag 1) has still a positive impact at a significant of 5% and 10%. The R-square of the model is 0.8973, as a result, the ARDL model can explain 89.73% of the change in the FDI by chosen independent variables. It means that the 11.27% remaining influence is considered by other factors. By using the ARDL model, the study proved that international trade cooperation, as well as international distribution, will make more conditions to move international sources more effectively.
Table 7. Regression Expresses the Impact of International Trade Cooperation on FDI
Note: *, **, and *** indicates significant at 10%, 5% and 1% level of significance
Moreover, the research results also show that the ARDL model is a suitable and reliable tool to evaluate the impact of international trade cooperation on inward FDI. The resultsagain test the reliability and relevance of the research model in the case of Vietnam’s FDI inflows. The findings indicate that, out of five chosen factors, there are only four factors that have a clear impact on attracting foreign direct investment to Vietnam. The factor OPEN shows an unclear effect on the ability to attract FDI.
Findings also indicate that when the FDI (lag 1) variable increases 1 percent, FDI will increase 0.5005 units. This was entirely relevant to the practice because the amount of FDI in the previous years increased, the future FDI would be positively influenced, and the economy seems to become more developed. However, FDI (lag 2 and lag 3) has a negative relationship with FDI inflows. When FDI (lag 2 and lag 3) increases by 1 percent, the real FDI will decrease by 0.4528 and 0.4653 respectively. Or the change of FDI (lag 2 and lag 3) has a negative relationship in attracting FDI in the future.
In terms of TRADE, the result shows that there is a significant positive impact on the change of total trade on FDI. When the TRADE increases by 1 percent or when the total import and export value increase, the FDI will increase by 4.5324 units. The reason explains for this situation is that the total trade increases and the economy shows signs of opening and becoming more active. And this issue makes the bases for increasing the investment attractiveness of foreign investors. However, TRADE (lag 1 and lag 2) has a negative influence. When total trade in the past 2 or 3 quarters increases by 1%, the FDI inflows decline by 1.7696 and 2.4754 respectively. It means that the change in TRADE (lag 1) and TRADE (lag 2) will cause a decrease in FDI inflows in the future.
However, the trade openness variable (OPEN) shows an unclear impact on FDI inflows. This result seems different from economists’ opinions. Besides, with the exchange rate variable (lag 2), if EXR (lag 2) increased 1 percent, FDI will increase by 12.7824 units. However, the value of EXR (lag 4) is different, when EXR (lag 4) increases by 1 percent, FDI still decreases by 8.1476 units. The reason explaining is that if the exchange rate increases so much over a long time, it will express an instability of the economy, and it can cause harm to the value of the investment. As a result, in short term, increasing EXR can increase FDI inflows, but in long term, it causes a contrast result.
The two remaining variables are INF and GDP. Results indicate that if INF (lag 1 and lag 3) increases by 1 percent, FDI will decline by 0.0842 and 0.0364 units. However, the positive result of INF (lag 2) indicates that FDI increases by 0.1089 units. It means that inflation has a different impact on FDI inflows in different periods. The final variable is GDP. When GDP increases 1 percent, the FDI would decline by 0.2278 units. Besides GDP (lag 1) has still a positive impact on FDI. When GDP (lag 1) increases 1 percent, FDI will increase by 0.4811 units.
5. Conclusions
The study aims to assess the impact of international trade integration and distribution on Vietnam's foreign direct investment in the period from 2006 to 2020. The study used the ARDL model to estimate the impact of variables such as total trade, trade openness, exchange rate, inflation, and gross domestic growth on foreign direct investment inflows. The findings proved that FDI inflows are influenced by international trade cooperation and distribution. In general, all chosen variables and their lags have statistics significant at 1 and 5 percent levels.
Vietnam's economy is still in the first stage of development according to the World Economic Forum classification. At this stage, the economic development is mainly based on production factors, and investment capital is one of those important sources. Therefore, these research results suggest that governments and managers should have some adjustments relating to trade cooperation as well as international distribution such as signing more free trade agreements with nations and regions, issuing attractive tariff policies, building a friendly investment environment, remaining economic environment stably, and making many attractive conditions for foreign investors. All the recommendations can make a base for attracting more FDI inflows in the future.
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