INTRODUCTION

During the past few decades, The Association of Southeast Asian Nationals (ASEAN) has attracted world attention with its steady and dynamic growth. This region is expected to become one of the world’s five biggest economies in the near future (Nguyen, 2021;Nguyen and Yang, 2020). The majority of ASEAN countries, however, are developing countries, and they have a strong demand for capital investment because of the low level of gross domestic savings (Dang and Nguyen, 2021). Hence, attracting foreign capital flows is important and the issue is always top of mind. Particularly in ASEAN, where countries are becoming more active in international trade organizations like WTO, ASEAN+6 and, TPP, attracting foreign direct investment (FDI) has become increasingly important. In developing countries, the inflows of foreign capital are essential to economic development and breakthrough. Some studies suggested that the impact of FDI on economic growth through two main mechanisms. Firstly, it is “direct impact”. This mechanism refers to the net contribution FDI makes to capital stock by increasing savings and investments and expanding goods and technologies produced in the host country. FDI is considered a direct source of foreign technology transfer and productivity increase (Bijsterbosch and Kolasa, 2010). It is also considered to have the most direct impact on industries’ productivity capacity and efficiency (Damijan et al., 2006). The second mechanism is related to the “indirect effects” of FDI. It is expected to contribute to knowledge for the host country by encouraging knowledge dissemination and innovation in the country. Through FDI, the host country receives technological transfers, human capital transfers, and generation of employment (Zeng and Zhou, 2021;Carbonell and Werner, 2018;Mehic et al., 2013;Yao, 2006). Therefore, encouraging FDI is an excellent strategy for developing and emerging countries to increase production levels.

In recent years, ASEAN remained a major destination of FDI in the developing world (second after China in 2021) and FDI is expected to play an important role in driving ASEAN’s economic recovery. Because ASEAN has integration and a large market potential that continues to drive high levels of investment (ASEAN and UNCTAD, 2022). In addition, the ASEAN Member States also attract foreign direct investment by developing strong industrial infrastructure in key areas like electric vehicles, semiconductors, digital economy, and Industry 4.0, which are major areas of FDI growth in the region and will continue to attract strong foreign investment in the future. Furthermore, ASEAN countries have a comparative advantage in cheap labor, attractive preferential policies, rich mineral resources, and abundant raw materials (Dang and Nguyen, 2021). Due to these advantages, the share of FDI in the total capital flows of ASEAN countries is constantly increasing every year and the proportion of FDI enterprises’ contribution to economic growth also increases, except in 2020 which was affected by COVID 19 pandemic (ASEAN and UNCTAD, 2022). The region’s share of global FDI inflows rose from a pre-pandemic annual average of 7.4 percent in 2011– 2017, to 11 percent in 2018–2019, to 11.7 percent in 2020 –2021 (ASEAN and UNCTAD, 2022). Specifically, in 2021, the FDI inflow into ASEAN increased by 42 percent, reaching $174 billion, a pre-pandemic record. FDI is expected to continue to play an important role in driving economic development and recovery in this post-pandemic region. By attracting FDI, ASEAN countries can improve their competitiveness and increase their exports, which can help further expand their markets (ASEAN and UNCTAD, 2020-2021). Host countries can accumulate physical capital and transfer human capital, which can increase the economic growth rate. FDI can help reduce the technological gap between national and international enterprises by technology transfer (Anwar and Nguyen, 2010).

However, the empirical literature often debates the existence of an absolute growth effect of FDI. Researchers have recently examined whether FDI promotes economic growth under certain social and economic circumstances. According to Zeng and Zhou (2021), Chinese economic development has been strongly influenced by FDI, and the spillover effect of FDI technology is one of the key factors driving China to achieve new growth milestones. As well, FDI acts as a technology transfer mechanism between developed and developing nations (Borensztein et al., 1988). Alvarado et al. (2017) found that FDI only had a positive and significant impact on products in countries with a high level of income. Khurshid et al. (2023) showed FDI tends to have a favorable effect on growth in stable economies without political uncertainty. In the case of Vietnam, Le et al. (2021) concluded that FDI and GDP were bidirectionally causal relationships, and FDI can extend Vietnamese economic growth. Mehic et al. (2013) found FDI is statistically significant and robust on economic growth if domestic investments are included. Wang and Wong (2009) believed that FDI promotes economic growth when the host country showed FDI meets the requirement related to human capital and financial development. On the other hand, a few empirical studies showed that receiving countries do not benefit from foreign direct investment. The effects of FDI on growth can be negative or nonexistent (Bende-Nabende et al., 2001;Mohd Nor et al., 2013;Smolo, 2021;Carbonell and Werner, 2018;Belloumi, 2014). The results of Carbonell and Werner (2018) showed that the favorable Spanish circumstances yield no evidence that FDI stimulates economic growth. As well, Belloumi (2014) argues that FDI does not contribute to economic growth in Tunisia. In general, authors used a variety of methods and made arguments for their research results. However, the reason why the studies gave different results may be due to the difference in research time, characteristics of countries (developed or developing), the quality of economic institutions, human capital, FDI absorption capacity of the host country, etc.

In this context, this study examines the influence of FDI on economic growth in nine ASEAN countries during the period 1998-2021 using country-level panel data. Based on our empirical model, we found that FDI has a positive effect on growth in ASEAN in all outputs. Our results suggested that FDI plays an important role in raising production levels in ASEAN countries. Hence, in making economic policy decisions, policymakers should consider the importance of FDI for the growth of ASEAN. The result also indicates that FDI inflows into ASEAN are affected by COVID-19, but the effect is non-significant. This shows that it is only a temporary shock to the economy.

The rest of the paper is structured in four sections. The second section briefly reviews the literature on the relationship between FDI and economic growth. The third section describes the data and the econometric methodology. The fourth section discusses the empirical results. Finally, the fifth section 5 presents the conclusion of the paper.

LITERATURE REVIEW

The growth impact of FDI has prompted many empirical studies focusing on both developed and developing countries. In the theoretical literature, endogenous growth models fail to explain the link between FDI and growth, which is associated with increased technological capital and infrastructure, as well as employment creation. The neoclassical model of growth considers FDI as physical capital in the production function. In general, investment contributes greatly to the accumulation of human and physical capital. When FDI is combined with local investment, the development of an enterprise is promoted (Tan and Tang, 2016). In addition, FDI can promote technology transfer, which increases the production efficiency of factors.

Several empirical studies have found contradictory effects of economic growth. There are several studies that showed FDI positively affects production levels through externalities and spillovers. For example, Zeng and Zhou (2021) showed FDI has a positive and direct impact on China’s economic growth and technological innovation and has a significant pull effect on the domestic economy as well. Le et al. (2021) confirmed that the flow of foreign direct investment can extend Vietnamese economic growth because it is more reliable and less violated. Alvarado et al. (2017) concluded the impact of FDI on products is only positive and significant in high-income countries, while it is uneven and non-significant in 19 Latin American countries with upper-middle incomes. Mehic et al. (2013) concluded FDI has a positive impact on economic growth. Combining data on domestic investment confirmed the statistical significance and robustness of the FDI effect. The study also tested endogeneity issues between FDI and economic growth. This study confirmed that FDI has an impact on economic growth, but no evidence for inverse causality. Chang (2010) showed an increase in FDI flows may stimulate domestic investment rather than crowd out capital formation in the short-term, and FDI inflows directly influence growth by stimulating domestic investment. A study by Wang and Wong (2009) found FDI to be positively correlated with economic growth under two economic conditions. A certain level of human capital and a certain level of financial development are required for FDI to promote productivity growth and capital growth, respectively. Secondly, there have been empirical investigations that show the negative influence of FDI on economic growth (Smolo, 2021;Musibah et al., 2015;Ang, 2009). These results suggest the relationship between the two variables is negative and has changed over time and according to the country’s productive structure. According to Smolo (2021), FDI negatively impacts growth when the institution factor is considered. Furthermore, institutional development has a significant negative impact on growth or has no direct impact on it at all. FDI and institution development measures become insignificant when they interact, as well as their interaction terms. Curwin and Mahutga (2014) also suggested that the penetration of FDI reduces economic growth in the short and long term in socialist countries. On the other hand, some investigations have shown that FDI affects economic growth both positively and negatively. For example, Wu et al. (2020) suggested that there is an inverse U-shaped relationship between FDI and GDP growth. When the size of FDI is small compared to the local economy, it has a positive impact on growth. Its growth effect becomes negative as the share of FDI in the local economy gets larger and crosses a certain threshold. Aziz (2020) pointed out that FDI will have a positive effect on growth when there is an interaction between FDI and institution quality. This highlights the indirect effect of an institution on growth by absorbing spillovers of FDI inflows. Likewise, Su et al. (2019) also showed there is a substitute effect between FDI and trade openness on economic growth if FDI and trade openness are combined together. However, FDI and trade openness have a positive impact taken separately. In addition, the economic institution also significantly influences the aggregate effect of FDI-trade on improving economic growth. Ramzan et al. (2019) concluded FDI has only a positive effect on GDP growth if schooling years and returns on education exceed 1.563. In contrast, FDI has a negative impact on GDP growth in countries that fall below this threshold. While Belloumi (2014) showed there is no causal relationship between FDI and growth in Tunisia. Similarly, Carbonell and Werner (2018) also confirmed there is no evidence to prove FDI stimulates economic growth in Spanish. Lastly, some several investigations found the causality between economic growth and FDI. For instance, Liu et al. (2009) found two variables had a two-way relationship. The causal relationship between FDI and economic growth is the expected result, and it is logical that the two variables strengthen each other over time. Whereas Sun (2011) showed that economic growth in China leads to increased FDI, rather than the reverse. In Vietnam, the effect of a shock on economic growth on FDI is greater than the impact of FDI on economic growth (Nguyen et al., 2017) . As well, the t rade l iberalization and financial development can enhance the positive effects of foreign capital inflows (Iamsiraroj and Ulubaşoǧlu, 2015). Liu et al. (2002) and Yao (2006) suggested FDI brings more benefits to receiving countries and increase exports. In summary, empirical studies have shown the mixed impact of FDI on economic growth. We summarized all of these views in a s ummary t able ( see appendix) . Furthermore, the control variables of previous studies were also presented in this table. The authors’ arguments were also part of the basis for our consideration of determining variables in the research model.

Hypothesis

DATA AND METHODOLOGY

With the aim of empirically examining the effect of FDI on economic growth in ASEAN countries, we used statistics compiled by the World Development Indicator (WDI) of the World Bank (2021) and UNCTAD (2021). The investigation covered nine ASEAN countries for the period 1998-2021 including Brunei Darussalam, Cambodia, Indonesia, Lao PDR, Malaysia, Myanmar, Philippines, Thailand, and Vietnam. Timor-Leste and Singapore are excluded in this study. Because Timor-Leste did not participate in the ASEAN group at the time of the study data and economy of Singapore has progressed quite far from the rest of the economies in the region. Therefore, Singapore was not included in this study in order to minimize bias in the analysis of this study. Most of the variables were collected directly from the WDI. The FDI inflows were only collected from the UNCTAD statistics database. However, some countries were missed data for many years, which also made it difficult to analyze in our study.

Figure. 1 shows the trend of the logarithm of FDI inflows and the product of the nine countries. The two variables displayed similar tendencies in the period analyzed. When we calculated the average annual economic growth rate and FDI participation as a percentage of product per country for the period of 1998-2021, we found the data has a high degree of dispersion, which implies a low degree of adjustment between the two variables in aggregated form (see Fig. 2 ) . This r esult is p artly due t o ASEAN’s productive structure of, which depends strongly rapid growth of the service sector without passing through an industrialization process. There is over 50% of the bloc’s GDP in the service sector, followed by 36% in manufacturing and 10.5% in agriculture. In Brunei Darussalam, industry and construction are the leading sectors, contributing 64.2% of the country’s GDP (ASEAN report, 2023).

Table 1 shows the description of the variables used in this study and expected impacts of each variable based on findings from the previous studies. The aggregated descriptive statistics of the variables are reported in Table 2. The GDP per capita of nine countries was over 6,000 US dollars. However, there are differences in the level of per capita income among the countries included in this research. As an example, Brunei Darussalam’s real per capita income was 32,647.5 US dollars, while Myanmar’s and Cambodia’s were 886.8 and 916 US dollars, respectively. Other countries have differences, but they are not too big. The average GDP growth rate across countries was nearly 5%. The Myanmar economy had the highest average GDP growth over the years (over 8%) with a standard deviation (SD) is 6.4%. In general, most countries in the region experienced negative growth during Covid-19, except for Lao PDR and Vietnam. In 2021, Myanmar had the largest negative growth rate of minus 17.9% in the region. The mean of aggregated real GDP was about 195,960 million US dollars, the SD was 226,336 million US dollars. For the FDI inflows, the average FDI of the nine countries during the study period was 4,409.3 million US dollars. The highest was over 23,883 million US dollars and the lowest was approximately minus 5 million US dollars (Thailand in 2020) with an SD of around 5,433.6 million US dollars. Because of the impact of Covid-19, FDI inflows into the ASEAN region have decreased in 2020 (see Fig. 1) with Thailand having the largest negative FDI inflow (-4,849 million US dollars). Indonesia is the country with the second largest share of FDI in the region after Singapore (accounted for 11.2%) while FDI flows into Brunei Darussalam were so small with 0,11% in 2021. The country attracting the lowest FDI is Lao PDR with a mean is 489.7 million US dollars. It shows there was a large difference in the level of FDI attraction among ASEAN countries. In spite of this, FDI in the region is low, not exceeding 5%, with Cambodia being the only exception (see Fig. 2). The average labor force in South East Asia was around 32 million, with a trend of increasing over the past few years. Three countries had labor forces above mean, including Vietnam, Thailand, and Philippine with 48.4, 38.6, and 37.4 million respectively. In other words, ASEAN countries have a competitive advantage in the labor market. Nevertheless, if they fail to make the most of current labor resources, they are able to face future challenges in terms of population pressure. In ASEAN, a mean GFCF of 60,345 million US dollars was recorded. The highest average level was recorded by Indonesia with 210.865 million dollars, whereas the lowest was recorded by Lao PDR, with 2.761 million dollars. Only Indonesia and Thailand had higher averages than the general average, while the rest had lower averages. In terms of trade openness, Malaysia, Vietnam, Thailand, and Cambodia exceeded 100%, while others had lower than general average (lower 88.5%).

In addition, we were applied Im-Pesaran-Shin test (Im et al., 2003) to test panel unit root before analyzing regression. The results of the panel unit root test showed that all variables had stationary at significant level of 1%.

Methodology

The neoclassical growth model provides a framework for analyzing economic growth in which physical capital and labor force determine production levels (Solow, 1956;Swan, 1956). In the literature on economic growth, this model has been discussed from both a theoretical and empirical perspective. Thus, FDI and economic growth can be explained by a Cobb-Douglas production function. If i represents the countries and t the time, the initial model can be represented as following:

Where Y_it represents the gross domestic product of the receiving country i (i = 1, 2, ..., I) in the period t (t = 1998, 1999,...,T), A is the state of technology, K_it is physical capital,1) L_it is the labor force. The parameters α and 1-α measure the participation of factors capital and labor in production, respectively. The neoclassical model, however, can be expanded to capture the effect of other factors that empirical evidence and theoretical arguments suggest affect products like trade openness, bank credit, and internal and external factors of an economy. A production function is obtained if these variables are aggregated:

In order to specify our econometric model correctly, an expanded production function is used, which is widely discussed in the theoretical and empirical literature in terms of FDI flows and economic growth (Wu et al., 2020;Aziz, 2020;Carbonell and Werner, 2018;Alvarado et al., 2017;Anwar and Sun, 2011;Wang and Wong, 2009). Based on the structure of the panel data of the previous equations, Eq. (2) incorporates the term α_i+ μ_t + ε_it in order to capture both the variability between observations and time, as well as stochastic errors, respectively. By using this strategy, we can incorporate the effects of other factors that affect economic growth.

In the econometric regressions, the dependent variables to represent the economic growth of the country are the national GDP logarithm (GDPr) and GDP per capita logarithm (GDPpc). The independent variables are the logarithms of Gross Fixed Capital Formation (GFCF), the labor force, and inflows of FDI. In addition, we also add other variables on economic growth such as trade openness, and domestic credit to private sector by banks. According to Aziz (2020), Smolo (2021), Le et al. (2021), Su et al. (2019), and Mehic et al. (2013), they found a positive relationship between trade and economic growth whereas Alvarado et al. (2017) showed the negative relationship between these two variables. On the other hand, Belloumi (2015) could not confirm the effect of trade openness on growth in the short-term. Schumperter (1911), well-developed financial intermediaries enhance technological innovation that contributes to for economic growth. Similarly, Bittencourt (2012) confirmed that financial development has a positive impact on economic growth. Ramzan et al. (2019), Carbonell and Werner (2018), and Loaysa and Ranciere (2006) also showed a positive relationship between financial development and growth. In this study, we also proposed adding a dummy variable “COVID” to the model. There is no doubt that the COVID-19 pandemic has an impact on the global economy. That is why we include the variable “COVID” in our research model. The COVID-19 pandemic occurred around the end of 2019 in China and then spread to other countries in 2020 and 2021. During these two years, the pandemic has had a serious impact on the economy of ASEAN in particular and the world in general. Therefore, the dummy variable “COVID” was taken on the value 1 if it occurs in 2020 and 2021, otherwise, it was taken on the value of zero. In addition, we include the interaction between FDI and covid (FDIxCovid) to catch any complementary between these two variables.

In panel models, a relevant aspect is the choice between fixed effects (FE) or random effects (RE) models. FE assumed that the unit specific error term is treated as fixed and estimable so FE can estimate the impact of variable of interest on outcome while controlling for those unit specific effects that remain constant across units. RE is used to account for variability and differences between different units within a larger group. For RE, we assume that the unit specific effect and explanatory variables are uncorrelated. If they are correlated, the RE estimates are inconsistent (Wooldridge, 2013). In this study, the Hausman test (1978) showed that there is a difference between the coefficients obtained by fixed effects and random effects (β_FE – β_RE) in regressions. We therefore use fixed effects to estimate, which tend to produce consistent estimators (Hausman and Taylor, 1981).

The incorporation of fixed effects by year and country captures in part the spatial and temporal heterogeneity, but if the error term e_it is not independent, the estimators may be biased. In our study, independence can be violated when errors are correlated across countries (contemporary correlation), when errors within each country are correlated over time (serial correlation), and when variance is not constant. To detect autocorrelation and heteroscedasticity in the models, we used the Wooldridge and Breusch-Pagan test, respectively. The value of Prob>chi2 = 0.0710 is lager than 5%. It is clear that there is no phenomenon of heteroscedasticity at 5%, but it is necessary to consider it at 10%. Thus, we estimated models by including fixed effects for time and country (Table 3). According to Wooldridge (2002), heteroscedasticity was eliminated by including fixed effects for time and country, and autocorrelation was corrected by a self-regressive process. The value of Wooldridge test is lager than 10% so there is no autocorrelation (Prob>F = 0.5991).

RESULTS AND DISCUSSIONS

In this section, we discuss the results found when we estimated equal (2) for all countries in ASEAN with two outputs including real GDP and GDP per capita. We used these dependent variables because they provide insight into an economy’s performance and its citizen’s standards of living. (1) Real GDP represents the total value of all goods and services produced within a country over a specific period, adjusted for inflation. It reflects accurate the economy’s size over years. A rising real GDP indicates that the economy is expanding and producing more goods and services. Additionally, it is often used to compare the economic performance of many countries in the world. (2) GDP per capita provides a per capita measure of the economic activity within a country. It allows for comparisons of economic prosperity between countries. A country with a much larger population might have a much lower GDP per capita than one with a similar real GDP, indicating a different level of economic growth. Therefore, both outputs are chosen to represent for economic growth of nations. To check the consistency of our results, we estimated separately for each model. According to neoclassical growth model (Solow, 1956;Swan, 1956), there are two key factors affecting economic growth (capital and labor force). Thus, we estimated models (1) and (3) with three independent variables, in which GFCF and FDI represent the capital factor. Many empirical studies, as we mentioned in literature review section, discovered that economic growth is also affected by other variables. In order to capture the effect of control factors on economic growth, we expanded Cobb–Douglas function like model (2) and model (4) with control variables including trade openness, credit, covid and interaction between FDI and covid (FDIxcovid), which is widely discussed in the theoretical and empirical literature.

The results show that the gross fixed capital formation and labor force have positive and highly significant effects on economic growth. In addition, our variable of interest, the inflows of FDI also has a positive and significant effect on GDP per capita and real GDP, but it is not so strong. The impact level of FDI depends on many factors in the host country. For example, if human recourse of host country meets the required educational threshold, knowledge acquisition and diffusion will have a stronger impact. In recent years, the FDI flows has focused on these nations mainly for high-tech industries so that high quality human resource is required. Although ASEAN nations have a large labor force, the labor at the advanced level accounts for a low proportion. Therefore, this may be the reason why FDI had a weak impact on economic growth in ASEAN. The results for ASEAN are consistent with results obtained by Zeng and Zhou (2021), Khurshid et al. (2023), Le et al. (2021), Mehic et al. (2013), and Wang and Wong (2009) in the transition countries. These authors indicate that FDI and economic growth have a positive relationship in developing economies. Ranzan et al. (2019) also found a similar result in a work on 70 developing countries for the period 1980–2015, five of which are ASEAN countries. The result of this study supports the hypothesis, and it is consistent with previous researches after including control variables.

The FDI coefficient has a positive impact on the economic growth of ASEAN countries, and it has statistical significance at the 1% significance level. If FDI flows are increased by 1%, economic growth increases around 0.039% with ceteris paribus. This showed that ASEAN countries have absorbed spillovers of knowledge and technology from FDI firms despite the low level of absorption. This is a sign, however, of the positive transformation ASEAN countries have undergone in taking advantage of FDI capital to develop their domestic economies. Specifically, emerging countries (ASEAN-5) including Vietnam, Thailand, Indonesia, Malaysia and the Philippines are the countries that account for the majority of FDI capital in the region. And, these countries are successfully utilizing FDI capital to boost economic growth. Our results regarding FDI and growth are similar to the studies of Zeng and Zhou (2021), Khurshid et al. (2023), Le et al. (2021), Mehic et al. (2013), Chang (2010), Wang and Wong (2009), Borensztein et al. (1988). This confirms that the effect of FDI on economic growth in the ASEAN countries covered in this research is consistent. According to Su et al. (2019) with research in Vietnam, they showed that FDI has a positive impact on economic growth when combined with trade openness if the country has high-quality economic institutes. Aziz (2020) also agrees with Su et al. (2019), FDI has a positive impact on economic growth if it is made through high-quality institutions. The studies of Borensztein et al. (1998) and Grossman and Helpman (1991) agree that FDI encourages economic growth through the diffusion of technology and knowledge in the long run, but it is also dependent on the human capital of the host country and the absorptive capacity of its enterprises.

The coefficient of the labor variable is positive and significant in all regression, except model (1). It shows that the labor force plays an important role in ASEAN countries’ economic growth. In ASEAN countries, the application of advanced technologies in production is still limited. Because of this, manual labor is still the main factor. In addition, the economies of these countries are mainly agricultural, manufacturing and services so that the labor force is very important. For example, Vietnam is given a country with a golden population ratio (the labor force accounts for over 50% of the total population) and they have performed their strengths by maintaining steady growth over the years. The results of the study are also consistent with Ramzan et al. (2019) and Aziz (2020). The size and growth rate of labor are considered key to growth because of their impact on economic activities such as creating and producing huge markets for goods and services. In addition, a country with a large workforce has many labor advantages in terms of hiring and human resource costs. However, a large workforce can be an opportunity or a burden for a country. If that country creates jobs for workers, it may promote economic development.

The parameter associated with gross fixed capital formation is positive and statistically significant, which corroborates the conclusion of Hussin et al. (2013), who concluded that GFCF has an important role in stimulating economic growth. Similarly, Le et al. (2021), Ramzan et al. (2019) and Belloumi (2014) also showed that GFCF positively affects the economic growth of developing countries. This showed that the formation of fixed capital for reinvestment in the economy is a key factor for growth. The weakness of ASEAN countries is the lack of investment capital, so that the accumulation of domestic capital is an inevitable factor to strengthen internal resources. The coefficient of the credit variable is positive and significant. This result is as expected of us about the relationship between financial development and economic growth and it is also similar to the results of Ramzan et al. (2019), and Carbonell and Werner (2018). These researches confirm that bank credit has a positive influence on economic growth. Loayza and Ranciere (2006) examined the relationship between financial development and economic growth in both the short and long run. In the long run, this relationship is positive but in the short term, it is negative. This implied the important role of the private sector in economic development. The private sector can enhance the efficiency of public projects, especially large infrastructure projects, through public-private partnerships. ASEAN countries, especially socialist countries such as Vietnam, Lao PDR are also actively promoting the role of the private sector in the economy. To promote the development of the private sector, governments have implemented many policies, such as equalization of state-owned enterprises. The COVID variable has a significant and negative impact on economic growth in ASEAN countries. The sign of the estimated coefficient is consistent with the actual situation that has occurred in the economy. As we mentioned, COVID-19 has seriously impacted ASEAN countries in 2020 and 2021 due to social distancing. Manufacturing and commercial activities have been stalled and restricted for the past two years. On the other hand, because the disease spreads quickly, most countries also have difficulties and are passive in responding to the disease. Even some countries have negative growth rates such as Cambodia, Indonesia, Malaysia, Myanmar, Philippines, and Thailand. This shows that the economies of developing countries in particular and the world in general are very vulnerable to natural disasters and pandemics. The FDIxCOVID interaction variable is statistically significant, but the impact level is very small, almost zero. This suggests that the COVID pandemic does not play a moderating role in the relationship between FDI and growth in the long run. It only is a temporary shock in the economy. When a pandemic suddenly occurred, countries had not responded to solutions on time yet, so it had a negative impact on economic activities. After that, the economy of countries has rebounded (Asian Development Bank, 2023). This is clearly shown in Figure.1 the pandemic was only a temporary disruption to the economy in 2020, and then the economy of countries has rebounded again since 2021.

In this study, trade openness is not statistically significant. This result is not as expected of us about the relationship between trade openness and economic growth, and it differs from the findings of Aziz (2020), Smolo (2021), Le et al. (2021), and Mehic et al. (2013). However, this result is partially similar to Belloumi (2014). This showed that the relationship between trade openness and economic growth is complex and can vary depending on many factors such as economic structure, policy framework, institutional quality, and external economic conditions. In ASEAN countries, there are many different types of economies, from highly industrialized nations (e.g. Singapore) to agricultural or resource-dependent economies (e.g. Myanmar or Lao PRD). Because of this diversity, trade openness affects differently economic growth in ASEAN countries. In recently years, Vietnam, Thailand, Malaysia and Cambodia have had high trade openness and their economy have benefited from it. It is, however, necessary to consider the effects of trade openness on growth over the long term to capture its impact. Trade openness can lead to economic growth if it is complemented by investments in human capital, infrastructure, and technology. While ASEAN countries do not have an advantage in this regard, and they need to take a long time for improvement. Consequently, they have not yet taken full advantage of the potential from trade openness. On the other hand, the sign of the trade openness coefficient in all the models is positive. This implies that trade openness may help ASEAN countries stimulate economic growth. They need the time to take benefits of liberalization of the economy are translated into economic growth through the diffusion of knowledge, the transfer of technology, and the strengthening of competition.

CONCLUSIONS

In this paper, we examine the relationship between economic growth and FDI in developing countries. This study used FEM estimation with two outputs including GDP per capita and real GDP. With panel data of ASEAN-9 countries during the period 1998-2021, we found strong evidence to support the hypothesis that FDI is an important driver to increase the economy of countries in ASEAN. This result is consistent with the findings of Zeng and Zhou (2021), Khurshid et al. (2023), Le et al. (2021), Mehic et al. (2013), Chang (2010), Wang and Wong (2009), Borensztein et al. (1988), Su et al. (2019), Aziz (2020), and Grossman and Helpman (1991). In addition, gross fixed capital formation and labor force also are key factors for promoting economic growth in developing countries. We also find control variables such as bank credit, and the shock of the COVID-19 pandemic influence on economic growth. From the results, we suggest three possible implications for policymakers in the ASEAN region. Firstly, developing countries should consider policies to attract FDI to create spillover effects of technology and knowledge in order to promote economic growth. Institutions and policies need to be consistent, open, and transparent to ensure the legitimate interests of foreign investors. It is necessary to balance the economic interests of FDI investors and local interests. Secondly, ASEAN countries should focus on human resource development because it is an important factor in the development of the economy. The level of human capital development plays a crucial role in absorbing knowledge from FDI based on its spillover effect of knowledge and technology in order to stimulate economic growth. Ramzan et al. (2019) and Wang and Wong (2009) demonstrated the role of human resources in economic growth when there is an interaction with FDI. Ramzan et al. (2019) and Wang and Wong (2009) argue that countries will benefit from FDI when their domestic human capital development level reaches a certain threshold. Therefore, ASEAN countries need to focus on developing knowledge and skills for human resources. Finally, ASEAN countries must strengthen their financial systems to avoid negative impacts when a crisis occurs that will hurt the financial system and negatively affect economic growth. In other words, in parallel with financial development, it is necessary to ensure the stability of the national and regional financial systems. Therefore, central banks of countries need to develop monetary policies and policymakers need to develop long-term strategies to ensure stable economic growth for many years. Policymakers may consider choosing a common currency for the transactions in the ASEAN region. In addition, ASEAN countries should focus on health development. Disease problems also seriously affect economic development. It affects not only the economy but also human resources. The lesson of the COVID-19 pandemic has shown how seriously the disease affects countries around the world. Therefore, countries also need to invest and develop healthcare systems to be able to respond quickly to emergencies if the pandemic occurs again.

The results of this paper may be of interest to many developing countries considering measures to promote economic growth. This study showed a robust result that FDI has a positive effect on economic growth in ASEAN countries. In this study, however, we cannot determine whether the effect of FDI on economic growth is short-term or long-term, and we cannot test causality between FDI and growth. For future research, we recommend to examine the causality of FDI on growth economics using better identification strategy such as instrument variable method, as well as their short-run and long-term relationships.