Institutions are considered the primary driver of long-term growth, a crucial compone nt of economic progress, facilitated by the implementation of policies that influence investm ent and human capital (Acemoglu et al., 2005). Institutions provide incentives for economic activity, which ultimately influences economic progress. Institutions create optimal conditio ns that can enhance various components of production, including capital investment, huma n capital, and innovation and technological progress (Eslamloueyan & Jafari, 2019). (North, 2016) states that institutions are the "rules of the game," limiting human behaviour and in fluencing economic activity through transaction costs. In addition to transaction costs, inves tment, human capital, and savings, institutions can influence various macroeconomic activi ties, including exports, imports, and foreign capital flows, by improving efficiency in resourc e allocation, ensuring property rights stability, and promoting freedom of choice, including e conomic growth, all of which are crucial for sustainable economic development (Nguyen et al., 2018).

Institutional quality and foreign direct investment are crucial foundations of sustaina ble economic growth. In this context, Foreign Direct Investment (FDI) is essential for a nati on's economic development, and institutional quality, including political stability, regulatory framework, and law enforcement, is pivotal in attracting and maintaining foreign investmen t (Bhujabal et al., 2024). (Acemoglu et al., 2005) initially investigated the influence of institu tions on economic growth by analyzing the economic disparities between North Korea and S outh Korea. North and South Korea attained independence from Japan simultaneously and exhibit parallels in some aspects, including geographical and cultural situations. Neverthele ss, disparities exist in the operational governance of institutions inside each country, leadin g to divergent economic conditions, with South Korea exhibiting greater development than North Korea.

World Bank classifies seven country regions: South Asia, East Asia and Pacific, North America, Europe and Central Asia, Sub-Saharan Africa, Middle East and North Africa, and Latin America and the Caribbean. There are interesting facts about the development of FDI flows in the seven regions where East Asia Pacific countries have a positive and relatively stable trend of increasing from 2011-2020 (Bank, 2021). That is consistent with findings from (Yerrabati & Hawkes, 2014), where the rate of economic growth and FDI in the East Asia and Pacific region had a positive trend from 1980 to 2012. The development of FDI in 2011-2020 can be seen in Figure 1.

From Figure 1, the development of net inflows of FDI indicates that the East Asia and Pacific region is the first destination for foreign investors to invest. That is consistent with research by findings from (McNulty et al., 2013), which states that the East Asia and Pacific region is an emerging market. The development trend of FDI net inflows in the East Asia and Pacific region tends to be more stable and positive when compared to the other six regions (Yerrabati & Hawkes, 2014). One of the reasons for the significant net inflow of FDI in the East Asia and Pacific region is the substantial net inflow of FDI in East Asian countries. The three largest countries contributing FDI for the last ten years on average (2011-2020) in East Asian countries are China USD229.86 billion, Hongkong USD 109.05 billion, and Japan USD22.32. However, when viewed from the net inflow FDI in the Southeast Asian region, that are part of East Asia and Pacific region, they have only contributed an average of USD138.43 billion or 24.39% of total net inflow FDI East Asia & Pacific over the past ten years (2011-2020) (Bank, 2021). This is reinforced by findings from (Petri, 2012), which indicates that overall, Asian countries receive 25% of inflows and 13% of world FDI outflows, whereas countries in East Asia, such as China and Japan, are in the top two, while ASEAN was still low in 2002-2006.

(Masron, 2013) also stated that in 2005-2007, ASEAN countries only obtained 12% of the total FDI to developing countries, indicating ASEAN's decreasing attractiveness as an FDI location. Furthermore, it is known that the average ASEAN net inflows of FDI (2011-2020) as measured by the percentage of GDP did not experience an increase or even decrease except for Singapore, which experienced a significant increase (Bank, 2021). According to (Rao et al., 2020), the Southeast Asian region has received foreign private capital inflows in recent decades. However, the region remains less attractive for FDI inflows due to structural bottlenecks, poor infrastructure quality, and insufficient domestic savings. (Jude & Levieuge, 2017) stated that institutions that have low quality are associated with low levels of investment and per capita income, stunted productivity growth, and overall slowing output growth. According to (Acemoglu et al., 2005), the quality of institutions is divided into two types: political and economic. Previous publications published six indicators in evaluating political institutions in each country. The six indicators are political stability, rule of law, government, effectiveness, control of corruption, regulatory quality, and accountability (Santiso, 2001). (Kaufmann et al., 2009) states that the size of political institutions issued by the world governance indicator is between -2.5 and +2.5. The greater the value, the better the quality level of institutions in that country and vice versa. Figure 2 shows the average quality index of political institutions in ASEAN countries in 2011-2020.

Figure 2 shows only three countries that have an average positive value of institutional quality, namely Brunei (0.62), Malaysia (0.35) and Singapore (1.58). This indicates that these three countries have good institutional quality because the value is positive or in the range of 0 to 2.5 (Kaufmann et al., 2009). Meanwhile, seven other countries had negative average institutional quality, namely Cambodia (-0.76), Indonesia (-0.24), Myanmar (-1.13), Philippines (-0.30), Thailand (-0.31), Vietnam (-0.42), Laos (-0.78). This indicates that seven countries have poor institutional quality because the value is negative or in the 0 to -2.5 (Kaufmann et al., 2009). Various bad phenomena in the ASEAN region include the corruption case in the procurement of Rolls Royce jet engines in 2017, which involved three countries in ASEAN, namely Thailand, Indonesia, and Malaysia (Prakasa, 2019). Furthermore, there is the Rohingya ethnic conflict in Myanmar, which culminated in a dispute between military forces and the Rohingya community in 2016 (Burke et al., 2017). Another phenomenon that shocked the world was that in 2014, there was a coup case carried out by the military in Thailand (Kawaura, 2018). Then, there were cases of terrorism by the Abu Sayyaf group in the Philippines in the Philippines in 2017 (Database, 2018). These phenomena can affect investors' decisions to invest in ASEAN countries because many previous studies have concluded that bad or inefficient institutions will make other people reluctant to invest (Asiedu & Lien, 2011).

Economic institutions play a role in regulating policies in the form of property rights and economic freedom. These property rights indirectly incentivize individuals who invest, especially in the technology development sector and production efficiency. (Haini, 2019) stated that economic institutions can cut information and transaction costs so that market failures do not occur and maintain market performance stability. In addition, economic institutions also ensure that the allocation of limited resources can be used efficiently to avoid exploitation by certain parties. The following is Figure 3, which shows the quality of economic institutions measured using the economic freedom index indicator.

The annual publication issued by the(Institute, 2022) measures the economic freedom of every country in the world based on five categories: the size of government, legal system and property rights, sound money, freedom to trade internationally, and regulation. The index score is between 0 and 10, where the closer to 10, the freedom of economic activity will encourage markets to function efficiently, thereby increasing a sense of trust, especially in companies, reducing uncertainty, and creating high levels of economic growth. As seen in Figure 3 above, the highest average index of economic freedom is Singapore, while the lowest is Myanmar. In total, ASEAN gets an average of 6.94 for 2011-2020. This means that the ASEAN region is in the second-ranking qualification or second quartile (score 6.83 to 7.42) according to the rating scale set by the (Institute, 2022). The ASEAN index value is still below the expected condition, namely the most free ranking (the highest rank with a value of 7.43 and above) According to (Khan, 2018), in general, countries in Asia generally have the same problem, which tends to have weak institutional conditions due to a lack of economic freedom in that country. This occurs due to excessive intervention in the market, which creates inefficiencies and has the potential for practices detrimental to fair competition.

Past studies have been conducted in various countries to study the relationship betwe en institutions and economic growth. (Nisa & Farah, 2021) stated that the political stabilit y indicators set by the WGI significantly and positively affected economic growth. In that co ntext, if a country achieves higher political stability, it can be perceived with the possibility of higher economic growth. (Akin et al., 2014) and (Panahi et al., 2014) stated that economic i nstitutions that use the economic freedom index indicator from the Fraser Institute have a s ignificant and positive impact on economic growth. Furthermore, (Uddin et al., 2017) found i ndividual institutional effects that were measured using political and economic institutions, providing positive and significant economic growth results. (Muja & Gunar, 2019) state that there is a strong causal relationship between the quality of government and economic perfor mance in the Western Balkans, where countries with better governance have enjoyed a high er standard of living. The increase in GDP per capita in the West Balkan is strongly related to the country's success in increasing citizen participation in the political system, guarantee ing political stability, providing effective governance, rule of law, quality regulations, and co ntrolling corruption. (Asamoah et al., 2016) stated that macroeconomic uncertainty in sub-S aharan Africa affected FDI flows, while the quality of institutions also increased FDI flows i n the presence of other control variables. The interaction between institutional quality and macroeconomic uncertainty reduces the initial negative effect exerted on FDI flows by econo mic uncertainty. This is consistent with findings from (Buchanan et al., 2012) that state that political institution indicators set by WGI have a positive and significant effect on FDI. How ever, there are differences from previous studies, where (Mauro, 1995) states that corruption as a measure of institutional quality negatively impacts investment, resulting in decreased economic growth. (Klomp & Haan, 2009) also state that democratic institutions had a n egative impact on economic volatility in the 116 countries studied. (Gurgul & Lach, 2013) sta ted that institutions in the form of a trend towards change of government in the Central & Eastern European region have a negative impact on economic growth.

Historical trends indicate that net FDI inflows in the ASEAN region are subdued due to inadequate institutional conditions stemming from insufficient economic freedom. This re sults from excessive market involvement, which generates inefficiencies and may lead to acti ons harmful to robust competition. Moreover, prior research suggests that the influence of i nstitutions and foreign direct investment (FDI) on economic growth produces disparate or in consistent outcomes. This study will investigate the impact of foreign direct investment (FD I) and the quality of political and economic institutions on economic growth in ASEAN natio ns from 2011 to 2020. This article aims to deliver substantial empirical insights about the i nfluence of Foreign Direct Investment, Institutional Quality, and Economic Growth: Empiri cal Evidence from ASEAN. The distinctiveness of research on foreign direct investment (FD I), institutional quality, and economic growth in ASEAN is rooted in the understanding that the efficacy of FDI is contingent not solely on capital inflows but also on the capacity of insti tutions to effectively absorb and utilize these capital flows.

This study uses secondary data from panel data from ten ASEAN member countries, namely Indonesia, Malaysia, the Philippines, Thailand, Singapore, Cambodia, Myanmar, La os, Brunei, Darussalam, and Vietnam. These countries were selected because net FDI inflo ws in the ASEAN region are still below East Asian countries (Bank, 2021). This stud y covers data from 2011-2020, justified by a phenomenon that reflects the poor quality of in stitutions in the ASEAN region, which can hinder net FDI inflows into the country. These p henomena include the Rolls Royce jet corruption cases in Thailand, Indonesia, and Malaysi a (Prakasa, 2019) the Rohingya ethnic conflict in Myanmar (Burke et al., 2017), the coup ca se in Thailand, (Kawaura, 2018) and the terrorism in the Philippines (Database, 2018).

Economic institutions are measured using the Economic Freedom Index obtained fro m The Heritage Foundation, as used in (Uddin et al., 2020). It comprises four main pillars: r ule of law (legal conditions in a country), government size (government size and behavior), r egulatory efficiency (legal effectiveness in a country), and open market (barriers to economic activity). The overall value of these four pillars is used to assess the degree of market freedo m in a country. The greater the level of individual freedom in carrying out economic activiti es, the greater the level of investment, per capita income, and economic growth of a country. Meanwhile, political institutions refer to studies by (Uddin et al., 2020), (Benayed et al., 2020), and (Mahaini et al., 2019), using political stability and absence of violence/terrorism obta ined from the World Governance Indicator (WGI), which is used to assess political stability, including politically motivated violence and terrorism (Kaufmann et al., 2009). Other variab les believed to influence economic growth are obtained from the World Bank, such as invest ment, using the gross capital formation measure (Alexiou et al., 2020). Foreign direct invest ment is used to measure investment inflows from abroad (Olaoye & Aderajo, 2020). Inflation is calculated using the Consumer Price Index (Saha & Zhang, 2017). Trade openness refers to the extent to which a country is oupen to international trade, as measured by the ratio of exports and imports to a country's Gross Domestic Product (GDP). This openness can be ac hieved through various policies, including reducing trade barriers, implementing fiscal polic ies, and ensuring adequate infrastructure to facilitate trade (Adams & Opoku, 2015).

The main variables in this study are FDI, political institutions (INST_POLT), econom ic institutions (INST_ECO), and economic growth (GDP), including control variables such a s inflation (INFL) and trade openness (TRA). The model used as a reference for this study re fers to a study by (Adams & Opoku, 2015). Several modifications in this study used the six political institution indicators variables derived from the Worldwide Governance Indicator (Asamoah et al., 2016) and the economic freedom index variable, which is an indicator of eco nomic institutions (Uddin et al., 2017). Moreover, to simplify the econometric model, the poli tical institution variables, which consist of six indicators, can be summarized into one instit utional quality index (INST_POLT) using the principal component analysis (PCA). (Kelechi, 2012) states that using PCA can reduce independent variables without reducing the interp retation of results and avoiding high multicollinearity between independent variables. The empirical equation model in this study is as follows:

(1)

Subscripts i in the model above are countries in ASEAN, and t represents the year of research, uit while is the error term of the research model. The model was estimated using a static panel data regression, by determining the selection of the best model between common, fixed and random effects, as well as testing classical assumptions (Parks et al., 2010). Operational variable definitions and data sources for this study can be seen in the Table 1.

Before conducting panel data regression analysis, a test is first carried out to determi ne which model approach is better between common, fixed, or random effects. After the initi al testing, it was determined which approach was better in this research. The following are the results of the Chow Test used to test and choose which method is better between the Co mmon Effects Model (CEM) and the Fixed Effects Model (FEM) (Wooldridge, 2013), where H 0 is not rejected (CEM is selected) if the F-statistical probability value is > α; and is rejecte d (FEM is selected) if the F-statistical probability value is < α.

Based on the Chow test results in Table 2, the probability value is 0.000. Therefore, it can be concluded that FEM is better for this study. Next, to ensure the research model, a retest was conducted to find out which model is better between the Fixed and Random Effects using the Hausman test, where H0 is not rejected (REM is selected) if the χ2 statistical probability value is > α; and is rejected (FEM is selected) if the χ2 statistical probability value is < α. The results of the Hausman test are presented in Table 3.

The Hausman test results in Table 3 show that this model has a χ2 probability of 0,000. Therefore, it can be concluded that the Random Effects Model is rejected, and the Fixed Effects Model (FEM) is better used in this study. The estimation thus uses the FEM approach based on the test results. Before obtaining the results from the FEM approach, the classical assumption tests, which consists of the heteroscedasticity, multicollinearity, and autocorrelation tests, are first carried out. Multicollinearity test was conducted to see whether there is a correlation between the independent variables in the regression model (Wooldridge, 2013). The results of multicollinearity testing with a partial correlation matrix between independent variables is presented in Table 4.

Table 4 shows that the correlation value for each independent variable is not greater than 0.8. Therefore, it can be concluded that there is no multicollinearity problem in this model (Parks et al., 2010). Furthermore, heteroscedasticity testing was carried out for the FEM results using the modified Wald test technique for groupwise heteroscedasticity in Stata 17. The results of the test show that the χ2 probability value is 0,000; which indicates that there is a heteroscedasticity problem in the model. Then, the autocorrelation test was carried out using the Wooldridge test for autocorrelation technique in panel data in Stata 17. The results show that the prob. F value is 0.000; indicating the existence of autocorrelation in the model.

Based on the tests carried out above, the model has two problems: heteroscedasticity and autocorrelation. The right technique to overcome these two problems is to use robust regression (Rousseeuw & Leroy, 1987). The results of the estimation of the robust regression are shown in Table 5.

The estimation results of the robust FEM regression in Table 5 show that four independent variables significantly influence economic growth partially in the ASEAN region, which consist of foreign direct investment (lnFDI), political institutions (INST_POLT), economic institutions (INST_ECO), and Inflation (INFL). However, trade openness (TRA) does not significantly influence economic growth in the ASEAN region. When viewed simultaneously, all the independent variables significantly affect economic growth in the ASEAN region. This can be seen from the F test where prob. F is 0.000. The goodness of fit (R2) in this study is 0.667, meaning that the combination of independent variables can explain as much as 66.7% of the variation in the economic growth. After estimating the model and performing various tests, an economic analysis is performed to see the relationship between the independent and dependent variables through the coefficients on each independent variable.

FDI, as measured by the net inflow of foreign direct investment current, has a positive effect at a significance level of 10% and a coefficient value of 0.083. This means that for every 1% increase in net inflow of FDI, economic growth will increase by 0.08% (ceteris paribus). This is similar to research by (Adams & Opoku, 2015) which states that the relationship between FDI and regulatory quality significantly and positively impacts economic growth. (Bashier & Khan, 2019) also provide similar results where net inflow of FDI significantly and positively impacts Asian countries. From the results of this study, the net inflow of FDI can drive the wheels of economic growth in the ASEAN region. However, the development of net inflow in the ASEAN region is still far below that of other East Asian countries such as China, Japan, and Hong Kong.

In this study, the quality of political institutions (INST_POLT), as measured by the w orldwide governance indicator, has a positive effect at a significance level of 10% with a coe fficient value of 0.189. This shows that an increase of 1 point in the political institution inde x will increase economic growth by 0,18%. This is in line with the findings of (Muja & Gunar, 2019) which state that countries with better governance have enjoyed a higher standard of living due to increased GDP per capita in Western Balkan countries. Political institutions consisting of six indicators (political stability, rule of law, effective governance, control of cor ruption, regulatory quality, and accountability) also significantly and positively impact econ omic growth in 11 developing Asian countries (Sabir, 2019). Likewise, (Nawaz, 2015) states t hat good institutional factors can be the main driver of economic growth in his research on high-income countries. Furthermore, (Jude & Levieuge, 2017) find a positive relationship between institutions and economic growth, where when the quality of institutions is low, it will harm the country's economy and development, and vice versa. Chairman's statement of the 42 nd (Summit, 2023) in Indonesia was to encourage the creation of sustainable g rowth, where ASEAN economic focus is expected to achieve economic growth of 4.7% in 202 3 and 5% in 2024. In this context, one of the factors that is very important is strengthening the system of government governance, where political stability, compliance with regulations accountability, and prevention of corruption in a country are indicators that must be impro ved in ASEAN countries. Governments in ASEAN countries need quick and targeted impro vements in improving the quality of political institutions because, in general, political instit utions in ASEAN (2011ASEAN ( -2020) ) are still weak where only three countries have positive scores (Singapore, Malaysia, Brunei Darussalam) and seven countries with negative values (Indon esia, Thailand, Myanmar, Laos, Vietnam, Cambodia, the Philippines).

The quality of economic institutions, as measured by the economic freedom index (IN ST_ECO), has a positive effect at a significance level of 5% with a coefficient of 0.190. This s hows that with an increase of 1 point in economic institutions, economic growth will increas e by 0.19%, ceteris paribus. This is in line with the findings by (Akin et al., 2014), (Panahi et al., 2014),(Wanjuu & Roux, 2017), which explain that the quality of economic instit utions can trigger economic growth by providing guarantees as well as improving quality of private property rights so that it will encourage the level of investment in research and deve lopment (R&D), development of production technology to human capital, as well as providin g an environment that triggers savings to maintain the availability of loan funds. Another s tudy that gave similar results was conducted by (Uddin et al., 2017) using the economic free dom index variable as an indicator of economic institutions. The security provided by econo mic institutions in maintaining stability, especially property rights issues, will increase eco nomic growth. Chairman's statement of the 42 nd (Summit, 2023) in Indonesia state stated that in order to create an epicenter of growth in ASEAN countries, one of the import ant factors is the existence of clear rules for conducting business activities and reduction of tariffs in the Regional Comprehensive Economic Partnership (RCEP) agreement.

Other control variables, such as inflation and trade openness, are important macroeco nomic indicators in economic growth (Mankiw, 2007). From the FEM estimation results, it c an be seen that inflation (INFL) has a negative impact with a significance of 5% and a coeffi cient of -0,003. This means that if inflation increases by 1%, economic growth will decrease by 0.003%. Similar results are also found by (Adams & Opoku, 2015), (Nawaz, 2015),(Aisen & Veiga, 2011), where inflation will decrease economic growth. (Mankiw, 2007) states that inflation can reduce people's purchasing power, hence reducing consumption levels and ultimately hampering economic growth.

However, no significant effect was found on the variable trade openness (TRA), which is proxied by the number of exports and imports of goods and services divided by GDP, wher e the results are in line with research by (Wanjuu & Roux, 2017), which states that trad e openness has not boosted economic growth in economic community of West African states.

Several conclusions can be drawn from the regression results. First, FDI can significantly contribute to economic growth in ASEAN countries. This indicates that net inflows of FDI in ASEAN countries as host countries have a role in economic development in a country because they are relatively stable and long-term. Net inflow of FDI can drive economic growth in the ASEAN region, even though the average contribution of net inflow in the ASEAN region is only 24.39% of the total net inflow of FDI in East Asia and the Pacific. Second, the quality political institutions have a positive and significant impact on economic growth in ASEAN countries. A good and effective system of political stability, freedom of expression, effective government, the rule of law, quality regulations, and corruption control can create a conducive environment for incoming foreign direct investment and increase economic growth. Third, the quality of economic institutions, measured using the economic freedom index indicator, positively and significantly influence economic growth in ASEAN countries. Economic freedom provides convenience, especially regarding access to and from the market, so foreign investors are interested in investing in destination countries. This economic freedom is supported by property rights policies that can guarantee investors' assets, thereby triggering the process of technological advancement and increasing human capital. Combining these policies will ultimately boost domestic productivity, followed by increased economic growth.

Based on the analysis results and conclusions, the policy implications that can be applied are as follows: firstly, ASEAN countries must increase high levels of trust betwe en the home country and the host country to increase net FDI inflows in the ASEAN reg ion. High trust can provide guarantees and confidence for foreign investors in investing. The way to increase foreign investor confidence is by providing ease of doing business in investment destination countries. Ease in the process of obtaining business permits will be able to attract foreign investors to invest in the host country. Relaxing regulations o n foreign investment is very important because, in general, many foreign companies wa nt to be able to invest in the host country. After all, the bureaucracy is very complex. Se condly, good governance, such as clear legal regulations, control of corruption, and politi cal stability, are the main indicators governments in ASEAN countries must improve to attract foreign investors. Along with improving the quality of these political institutions , economic growth in ASEAN countries will undoubtedly develop rapidly. Lastly, econom ic institutions are important in maintaining and controlling market activities in ASEA N countries. Effective economic institutions also have an important role in controlling fr aud in market activities. Economic freedom is one of the important factors in attracting investment into the country, where the government is expected to give business people, especially foreign investors, freedom to operate with few obstacles. In addition, strict su pervision is needed to prevent practices that harm fair competition and only benefit cert ain groups.