SYMMETRIC AND ASYMMETRIC ASSOCIATION BETWEEN FOREIGN DIRECT INVESTMENTS AND MACROECONOMIC VARIABLES: AN ARDL APPROACH

Objectives: The main objective of the study is to investigating the dynamic relationship between FDI and different Macro Economic Variables (MEVs) using the ARDL procedure, providing a more comprehensive understanding of the association between FDI and MEVs and to evaluate their relative importance for FDI. Methods: This study utilizes annual data from 1991 to 2021 from the World Bank (2021) and the Reserve Bank of India (2021). Data on GDP, Export, Inflation and interest rate, and FDI are collected from the World Bank. Autoregressive Distributive lag Model procedure has been used for the study in order to establish relationship between Macro economic variables and FDI. Results: Our methodological approach using ARDL model and finds: (a) a positive correlation between exports and FDI, (b) a negative impact of inflation and exchange rates on FDI in the long run. Non-linear ARDL analysis reveals the asymmetric impact of inflation and interest rate on FDI, which includes the effect of positive and negative shock of interest rate and inflation on FDI. d) 1% increase in inflation reduces FDI by 0.4% and if Inflation is reduced by 1%, FDI is increased by 0.2%. At the same time, the non-linear estimation of interest rates concludes that there is an asymmetric and significant association between interest rates and FDI. e) If Interest rate has increased by 1% FDI is decreased by 0.9% and if interest rate has reduced by 1% FDI has deceased by 1.63%. f) The causality analysis reveals that exports, GDP, and exchange rates are the significant economic variables that affect FDI. Conclusion: The study's findings have practical implications for policymakers and investors looking to attract more FDI in India. The results indicate that exports play a critical role in attracting FDI and that the government should focus on improving export performance to increase FDI inflows. Additionally, the study highlights the importance of controlling inflation and exchange rates to attract more foreign investment. The finding that interest rates have an asymmetric relationship with FDI suggests that policymakers should be cautious when implementing monetary policies that may impact interest rates. Overall, the study provides valuable insights for policymakers and investors looking to attract more FDI in India and highlights the importance of considering the country's macroeconomic conditions when making investment decisions.


INTRODUCTION
Foreign Direct Investment (FDI) inflows are the investment made by foreign-owned companies in another country in the form of controlling ownership.FDI may be in horizontal or vertical mode, or it can be in the nature of efficiency-seeking or market-seeking.Horizontal FDI is when a company invests in the same business in a foreign nation, while vertical FDI is when a business invests in a complementary business in a foreign nation.An investment to cut input costs would mean an efficiency-seeking FDI, and an investment to capture a foreign market means a market-seeking FDI.The World Bank defines "foreign direct investment" as "net inflows of investment for the acquisition of a long-term management interest (10 percent or more of voting stock) in an enterprise operating in a country other than the investor's."The entire equity capital, earnings reinvested, other long-term capital, and short-term capital make up the balance of payments.
Developing countries have many constraints that ultimately create hindrances in economic development.Political constrain such as corruption is also one of the othe major concern for promoting economic development since corruption can distort market competition and reduce foreign investment.By examining the factors influencing corruption control and implementing effective reforms, the government can establish a business-friendly environment that attracts investment and drives economic growth (Hoa & Thanh, 2023).When financing their investments, most emerging nations encounter financial and technical difficulties they also do not have modern technology.They consequently work hard to draw in as much FDI as possible to satisfy these monetary and technological needs.FDI helps governments generate tax revenue and new jobs.
The planned economy in India is transitioning to an open market economy.The transition began explicitly after 1995 but more generally in 1991.Three methods are available for the Indian economy to expand: loans or commercial borrowings, official development assistance (ODA), and FDI (Alam Iqbal, 2006).Inviting more FDI is the best and most appropriate course of action.Considering its importance, several factors made it necessary to 4 renovate the FDI policy after 1991, specifically after 1995.India signed the Uruguay agreement in 1995, making it a member of the WTO and an automatic signatory to the TRIMS.TRIMS assures that pre-export obligation or minimum domestic employment cannot be applied to foreign firms.It confirms that the regulation imposed by India on foreign investment could not be applied (Pant & Mondal, 2010).
India is now among the most alluring countries for foreign investors.India's FDI inflows have tremendously risen, with an average annual growth rate of approximately 38 percent between 1991 and 2018 (Nayak & Sahoo, 2020).From 2014 onwards, the Indian government has adopted several policy reforms to attract huge foreign inflows in different sectors, particularly manufacturing and service sectors.Higher FDI volumes have been seen in the pharma, hardware, cars, and electronics industries.The "Make in India" initiative, launched in 2014, aims to make India a leading destination for manufacturing, research, and innovation.
The government identified ten critical sectors with high growth potential to achieve this goal and implemented changes to the FDI policy regime in 2017 to attract foreign investment.These changes included the liberalization of traditionally restricted sectors such as rail infrastructure and defense and the removal of various restrictions and policy hurdles faced by foreign investors.In 2016-17, the Indian agriculture sector received FDI worth Rs.515.49crores (S.Singh, 2019).The government's ongoing efforts to liberalize the FDI framework in India are expected to attract more FDI and drive economic growth in the future.
One of the key trends in the global economy is FDI.As discussed earlier, to attract more FDI, the policy framework should be eased and attractive to foreign investors.Other macroeconomic variables (MEVs) like exchange rate, inflation, interest rate, export, and trade openness are the indicators that affects the FDI.Vasconcellos and Kish (1998) contend that to understand aggregate FDI trends over time, MEVs must be examined.The exchange rate has a negative impact on FDI (Nayak & Sahoo, 2020).Another critical factor that affects FDI is the country's economical, and political stability.Investors opt to invest in countries with a stable political climate and a well-functioning legal system.
Additionally, a country's infrastructure and level of development also play a role in attracting foreign investment.Countries with well-developed transportation networks and efficient communication systems are more attractive to investors than those with poor infrastructure.Another key trend in FDI is the increasing importance of emerging markets.In recent years, developing countries have become increasingly attractive destinations for foreign investment, as they offer a large and growing consumer market and a lower labor cost.Due to their large populations and rapidly growing economies, China and India are two of the most popular destinations for foreign investment in emerging markets.As these countries continue to develop, they are expected to attract even more FDI.Hence, it is essential to note that the impact of FDI on a country's economy is not always positive.While FDI can bring in muchneeded capital and technology, it can also lead to adverse effects, such as increased competition for domestic firms and a loss of control over key industries.Therefore, countries must weight the pros and cons of foreign investment before making policy decisions that may impact their ability to attract it.
The motivation for this study stems from the growing importance of FDI in the global economy and its potential impact on the economic growth of a country.Despite the increasing interest in the subject, the association between FDI and MEVs remains an ongoing research and debate area.Using the Autoregressive Distributed Lag (ARDL) procedure, this study provides a more comprehensive understanding of the association between FDI and MEVs.The key motivation for this study is to investigate the symmetric and asymmetric association between  6 variables that are stationary at level I (0) or first difference I (1) or even fractionally integrated (Pesaran & Pesaran, 1997).However, the limitation of the technique is that it cannot be applied if any of the variables under the study in a given model is I (2).This study employed Non-linear ARDL approach because of its ability to examine short-run and long-run asymmetries among explanatory variables.Overall, this study contributes to the extant literature by investigating the symmetric and asymmetric association between FDI and different MEVs using the ARDL procedure, providing a more comprehensive understanding of the association between FDI and MEVs and its potential impact on economic growth.
The rest of the paper proceeds as follows: Section 2 discusses the theoretical framework, Section 3 presents a brief review of previous literature, Section 4 introduces the data and methods, Section 5 presents the results of the analyses, and Section 6, while providing recommendations, concludes the study.

THEORETICAL FRAMEWORK & EMPIRICAL REVIEW
The Heckscher-Ohlin model, a fundamental component of neoclassical trade theory, was the first to explain the determinants of FDI and their significance.The model is based on a 2x2x2 general equilibrium framework and the assumption that differing relative factor endowments and intensities among nations and commodities lead to variations in international factor prices.The model posits that nations abundant in the capital will either export capitalintensive goods or invest abroad in pursuit of higher returns on capital and lower returns on labor until factor prices equalize across countries (Leamer & Levinsohn, 1995).The essential core of FDI is that local firms are more advantageous because of familiarity with local conditions.In order to meet these local advantages, foreign firms should meet with compensating advantages.This can exist with the presence of market imperfection.Kindleberger (1969) was one of the first economists to critique the neoclassical approach to FDI.While arguing that the assumption of perfect competition could not adequately explain FDI, he outlined four key market imperfections that could influence FDI: product differentiation in the goods market, access to patent knowledge in the factor market, internal and external economies of scale, and government intervention in the form of tax structures, tariffs, and other legal systems to compete with local firms (Calvet, 1983).These market imperfections, according to Kindleberger, would have a significant impact on the FDI.Caves (1974) focused on product differentiation as a key driver of FDI in the context of monopolistic advantage and argued that imperfect competition in the market encourages multinational 7 enterprises to differentiate their products and engage in horizontal FDI.He contends that FDI is preferable to licensing or exporting if knowledge is applied to product differentiation rather than managerial abilities.This is because product differentiation allows multinational enterprises to gain a competitive advantage over other firms in the market.Hennart (1986) proposed the idea that internalization advantages, which are the benefits of performing a certain activity within the firm rather than through external market transactions, can be attributed to two factors: know-how and goodwill (reputation).He suggested that these internalization advantages can lead to horizontal integration when a firm acquires or merges with another firm in the same industry, or vertical integration, when a firm expands its operations to include activities at different stages of production in the supply chain (Faeth, 2009).This theory suggests that internalization advantages are the major driving force behind FDI, as firms seek to internalize activities to gain competitiveness in the market.Lunn (1980) agreed that internalization advantages drive FDI but arrived at different conclusions.He found that market size and growth are important factors influencing FDI.Empirical evidence highlights "market size," "market growth," and "trade barriers" as significant factors driving FDI, warranting their inclusion in FDI theoretical models.This highlights the importance of considering the external market conditions and their potential impact on the decision of firms to invest in foreign markets.Dunning's (1979) Eclectic Paradigm integrates internalization and entry mode theories to explain multinational enterprises' motivations for international operation and choice of entry modes (FDI, export, licensing).Three advantages drive FDI: ownership (e.g., patents, tech knowledge, management skills), location (e.g., access to protected markets, favorable taxes), and internalization (e.g., lower transaction costs, improved reputation).The theory emphasizes that firms undertake FDI to exploit these advantages for a competitive edge in the global market.
It is also known as the OLI paradigm (ownership, location, and internalization), and it emphasizes that FDI is a result of a complex interaction of various factors, such as the company's specific resources and capabilities, external market conditions, and government policies.This theory is widely accepted as a comprehensive explanation for the motives behind FDI.
In conclusion, the Heckscher-Ohlin model was one of the first theories to explain the determinants and importance of FDI.However, it was criticized for its assumption of perfect competition and its inability to explain FDI.Subsequent theories, such as the product differentiation theory and the internalization theory, have built upon the neoclassical model and have highlighted the importance of market imperfections, market size, market growth, trade barriers, and special advantages such as ownership, location, and internalization in explaining 8 FDI.The proposed study aims to investigate the symmetric and asymmetric association between FDI and different MEVs using the ARDL procedure, which will help to further our understanding of the factors that drive FDI.

EMPIRICAL REVIEW
Various factors, including GDP per capita, trade and FDI openness, and availability of skilled labor significantly influence FDI inflows.Studies have shown that GDP and FDI are inversely correlated, meaning that FDI inflows are efficiency-seeking rather than marketcapturing (Bhasin & Gupta, 2017).Shah (2013) found that labor costsignificantly impact FDI decisions, suggesting that policies should focus on reducing labor costs to attract more FDI.Boateng et al. (2015) found a significant impact of "real GDP," "exchange rate," and "trade openness" on FDI inflows, with a negative effect on "inflation," "unemployment," and "interest rates."Iqbal et al. (2018) found that market size is not a significant factor for FDI in India, but it does play a role in Sri Lanka.Inflation and exports are not significant for either country, but the current account balance affects FDI inflows in India.Prakash and Abraham (2005) studied the factors that affect India's attractiveness as a destination for FDI.They found several factors limit India's ability to attract FDI, particularly in export-oriented sectors.These factors include a shortage of skilled workers, inadequate infrastructure, and a lack of effective policies to promote openness and encourage the use of bilateral investment treaties.These issues impede India's ability to compete with other countries in attracting FDI, and addressing them is crucial for India to increase its competitiveness as a destination for FDI.According to Pradhan et al. (2017), opening Eurozone countries to trade and promoting financial and economic development casignificantly increase FDI in the long term.Studies have also found that exchange rate and FDI are related when there is an imperfection in the global market, with the depreciation of the host country's currency leading to an increase in inward FDI due to decreased investment costs (Bénassy-Quéré et al., 2001;Zhang & Song, 2001).Kiymaz (2009) found that investors consider market potential and risk when making foreign investment decisions, and MEVs such as GDP, capital market indicators, exchange rate, interest rate, and inflation can be used to assess these factors.Fedderke and Romm (2004) and Moosa and Cardak (2006) discovered that positively influences FDI inflows.These findings support Dunning's (1977) eclectic paradigm, which states that one of the primary reasons for firms investing abroad is to gain better access to the host country's market and that the volume of FDI inflows into a country is determined by the size of its host country's market (Uddin & Boateng, 2011).9 Agarwal (2013) analyzed the association between FDI and GDP in the BRICS countries from 1989-2012 using panel-level cointegration and causality analysis, finding a long-run causal link between FDI to economic growth in these economies.The study also found that factors such as "GDP per capita," "infrastructure development," "trade openness," and "control of corruption" impact FDI inflows.Similarly, Chaudhary et al. (2012) investigated the impact of exchange rate volatility on FDI in Pakistan, India, Sri Lanka, and South Korea.However, their research did not find any correlation between the two variables in Bangladesh, China, Malaysia, Indonesia, Thailand, Singapore, and Iran.On the other hand, Okafor et al. (2017) found that while inflation has a negative impact on FDI inflows, rents from natural resources have no significant influence on FDI.Bano et al. (2019) investigated the decline in FDI inflows in Pakistan and found energy shortages, financial instability, and political instability to have long-term negative effects.Post-financial crisis, terrorism, and energy shortages were the main drivers of FDI decline."Market size," "inflation," and "favorable exchange rates" were found to impact FDI inflows positively.Similarly, Şiklar and Kocaman (2018) examine the association between FDI and macroeconomic indicators in Turkey and found a negative and significant impact of inflation and real exchange rate fluctuations on FDI.The authors recommend Turkey maintain stability in its macroeconomic indicators to increase FDI inflows.
These studies suggest that stability in macroeconomic indicators is crucial for attracting FDI.
Mishra and Jena (2019) find "market size," "inflation rate," and "real interest rate" as key drivers of FDI, with institutional and infrastructural factors such as "telecommunications," "degree of openness," "globalization index," and "economic freedom index" also influencing FDI attraction in Asian countries.Ho and Rashid (2011) confirmed that FDI flows in most countries are affected by economic growth and degree of openness.Alkathiri and Soliman (2022) used an ARDL model to examine the dynamics between "trade openness," "FDI," and "economic growth" in India.They found that trade openness negatively affect economic growth in the long-run, but that appropriate policies can help extract the benefits of FDI inflow.
Additionally, they found that "market size" positively affects FDI attractiveness in Egypt, while in Oman, FDI is directed towards resource-seeking purposes rather than market-seeking purposes.
Liu and Dejphanomporn (2021) found that factors such as trade openness, research, and development intensity, and bilateral trade agreements positively influence FDI decisions for both inflows and outflows in Thailand, while relative wages and geographic distance have a negative impact.They found that "market size" is the most significant determinant of inward FDI, and bilateral trade agreements are the most important determinant of outward FDI.In 10 contrast, Mishra et al. (2013) discovered that infrastructure has no significant effect on FDI inflows in India, but rather, the profitability of existing firms significantly impacts the level and variability of FDI inflows.Mohanty and Sethi (2019) found that FDI has a negative and insignificant impact on real exports in the long run, but there is a unidirectional causal association between FDI and export.In contrast, Jahanger (2021) found that FDI positively affects high-quality economic development in eastern provinces of China by promoting export capacity, while in central provinces, the technical level of FDI promotes high-quality economic development.However, the actual size of FDI has a negative impact on economic development in central provinces.Tsitouras et al. (2020) found that "market size," "trade openness," "the quality of labor," "infrastructure facilities," and "technological skills" are crucial in attracting FDI.They also discovered that technological capabilities play an increasingly important role in attracting FDI, particularly after the Greek economic crisis.This emphasizes how critical it is for Greece to be able to transfer, adapt, and develop technology resources in order to increase its attractiveness to multinational corporations in the cutthroat global business environment.Forign policy is major concern for policy making in order to facilitates foreign investment and coperation in a country and as well as major economic intergaration like ASEAN (Mamentu et al., 2024).Dang and Nguyen (2021) used panel data and different econometric models to examine the factors that attract FDI in their study.They discovered that while "population increase" and the "quality of political institutions" negatively affect FDI inflows, "economic growth," "tax burden," "the quality of economic institutions," and "inflation" are favorably associated with FDI.Kamal et al. (2022) used a long-term association approach to investigate the association between FDI inflows and trade openness in India.They found that a more open trade policy positively and significantly impacts FDI in India, meaning that a country with greater trade openness is likely to have more FDI.Additionally, they found that while "trade openness" and "inflation" are positively correlated with FDI inflows, only "trade openness" had a statistically significant impact, and "inflation" was not found to be a significant factor.Chattopadhyay et al. (2022) studied the motives behind FDI inflows to the BRICS nations and found that different motives were dominant in each country.Horizontal and vertical motives were significant for India and Russia, while only horizontal motives were significant for China.None of the motives were found to be significant for Brazil and South Africa.They also found that the COVID-19 pandemic significantly impacted FDI in Brazil but not in the other BRICS countries, suggesting that determinants of FDI are country-specific and that BRICS countries should frame appropriate FDI policies and adopt more reforms to attract FDI.In conclusion, various studies have found that different factors can influence FDI inflows, including GDP per capita, labor costs, trade, and FDI openness, availability of skilled labor, exchange rate, inflation, interest rates, market size, and macroeconomic stability.Some studies have found that FDI is efficiency-seeking rather than market-capturing, while others have found that "market size" plays a significant role in attracting FDI.Additionally, some studies have found that "trade openness" and "bilateral trade agreements" can positively impact FDI decisions, while others have found that they can negatively impact economic growth in the long run.Factors such as "telecommunications," "degree of openness," "index of globalization," and "index of economic freedom" have also been found to play a role in attracting international investors.
Overall, The contributions of the paper to exisisting literature are: first, the paper contribute additional insight on the puzzling evidence from existing empirical works on MEVs -FDI nexus by specifically examining the asymmetric effects in the form of positive and negative changes in MEVs on FDI inflow in India; Second, the time-series analysis provide specific results unlike panel data approach used by most of the previous studies, on the relationship of MEVS and FDI inflow in the Indian context; and lastly, the non-linear autoregressive distributed lag (ARDL) model used for this study is dynamic and robust to the issue of endogeneity bias, therefore ensuring the consistency as well as reliability of the empirical findings.The findings suggest that policymakers should focus on creating a stable macroeconomic environment and improving infrastructure and institutions to attract more FDI.
One potential research gap in the literature is the lack of studies investigating the positive and negative shock of MEVs on FDI using the ARDL procedure.Therefore, this study aims to fill this gap by using the ARDL procedure to investigate the symmetric and asymmetric association between FDI and different MEVs in a specific country or region.

METHODOLOGY
This study utilizes annual data from 1991 to 2021 from the World Bank (2021) and the Reserve Bank of India (2021).Data on GDP, Export, Inflation and interest rate, and FDI are collected from the World Bank.Variables are defined in Table 1.Data on exchange rates was collected as an annual average with respect to USD from the Reserve Bank of India.The ARDL modeling approach was selected for this study because to its advantages over similar techniques, such as the Engle and Granger (1987) two-stage cointegration approaches.Firstly, the ARDL technique is applicable to integrated variables of a different order: I (0), I (1), or a combination of both.Secondly, it is robust when a single long-run relationship exists between the underlying variables in a small sample size.The bounds test, proposed by Pesaran et al. (2001), estimating a conditional ARDL model for the variables under consideration to establish the long-run association among them.
Conducting an extensive unit root analysis is the first step in a cointegration and causality analysis.To ensure the validity of the results, it is important to confirm that the variables are stationary at either 1(1) or 1(0) level of integration.Once this requirement is met, we perform both linear and non-linear cointegration analyses to establish long-run relationships among variables.For a better understanding, refer to Figure 1.The symmetric ARDL model is specified as in Equation (1).

𝛥 𝑙𝑛 𝐹 𝐷𝐼
Based on the regression result of Equation ( 1), the bounded F-statistic test has been Where: The coefficient of error correction term θ indicates the speed of adjustment towards the long-run equilibrium.

SUMMARY STATISTICS
Table 2 presents the mean and other fundamental properties of the macroeconomic determinants of FDI used in the study, including lnFDI, lnEXP, lnER, lnGDP, lnINF, and lnINT.The mean values of all the variables suggest that the average levels of FDI, exports, exchange rate, GDP, inflation, and interest rate are relatively high.However, the standard deviation values show that the data for these variables are relatively less dispersed, except lnFDI, which has a higher standard deviation, indicating greater dispersion in the data.The minimum and maximum values of all the variables also provide an overview of the range of values of these macroeconomic determinants of FDI.

UNIT ROOT TEST
Determining the stationarity level of the variable unit root test has been conducted (see Table 3).The variables in ARDL are either stationary at a level or first difference or a combination of both.The ADF and PP tests show that FDI, GDP, and interest rates are stationary at I(0), whereas inflation, exports, and exchange rates are stationary at I(1).

BOUND TEST FOR LINEAR COINTEGRATION
A bound test is a statistical method used to determine whether a series of variables are cointegrated.The test involves testing the null hypothesis that the series of variables are not cointegrated and the alternative hypothesis that they are cointegrated.The test is used to identify whether there is a long-term equilibrium relationship between the variables and whether the variables move together over time.The test typically involves estimating a regression equation and testing the significance of the coefficients.If the coefficients are found to be statistically significant, then it is concluded that the variables are cointegrated.The bound test is commonly used in econometrics and finance to analyze the relationship between different economic variables.
The ARDL method is used for the cointegration test to determine the long-run association between the considered variables.The optimal lag length is decided through VAR lag length criteria, AIC and SIC.The lag length is 2, and the model for cointegration is selected as (2, 2, 1, 2, 2, 0) for the dependent variable FDI with other economic variables.As shown in the bound test results reported in Table 4, the computed F-statistics is 5.4748, which exceeds the lower and upper bounds critical values of 2.39 and 3.38 at the 5% significance level.The results indicate the rejection of the null hypothesis of no cointegration.Hence, there is a cointegration between FDI and other MEVs.

LONG RUN AND SHORT RUN FINDINGS OF SYMMETRIC ARDL
The value of the F-test gave evidence for a long-run association between FDI and considered MEVs.Long-run estimates in Table 5 indicate that exchange rates and inflation have adversely affected the inflow of FDI.The result is supported by Caves (1974) and Kenneth A. Froot (1991), who have found a positive correlation between dollar depreciations and increased FDI.Coskun (2001) concluded that low inflation is good for MNCs working in the host country and thus encourages inward FDI flows.The long run results indicate that exports facilitate the inflow of FDI (Grossman & Helpman, 1991;X. Liu et al., 2001).Long-run results indicate that exports facilitate the inflow of FDI and are in line with Grossman and Helpman (1991), X. Liu et al. (2001), and Mina (2007).There is no effect of GDP and interest rates on FDI.indicates the valid short-run relationship between variables.In the short run, the coefficient of export, GDP, and the first lag of FDI is negatively associated with FDI, whereas the first lag of inflation positively affects the FDI.In the short run, the exchange rate does not affect FDI.   7, there is no evidence of serial autocorrelation and heteroscedasticity.The Jarque-Bera test of normality confirmed that the error terms are normally distributed, and Ramsey's RESET test for model specification validates that the functional form is correctly specified.Further, the results of the CUSUM test in Figure 2 explain that at a 5 percent significant level, there is no structural instability in the long-run export model.The Nonlinear Autoregressive Distributed Lag (NARDL) model allows for the inclusion of the potential for asymmetric effects of both positive and negative changes in explanatory variables on the dependent variable.According to ARDL estimates, there is no significant association between interest rates and FDI, which requires further clarification.Non-linear ARDL estimation concluded that there is an asymmetric relation, and it segregates the effects of positive and negative interest rates and inflation on FDI.
The value of the F-test gives evidence for a long-run association between FDI and considered macro-economic Variable.The F-statistics is 9.022430 (see Table 8), which is more than the upper bound at the 5% level, which means F-statistics reject the null hypothesis of noco-integration.The result confirms that there is non-linear cointegration between FDI and another macroeconomic variable.9) and short-run (see Table 10) estimates of non-linear ARDL segregate the effect of inflation and interest rates into two parts of positive and negative effects.
The result of positive changes in inflation on FDI is significant at 10%.While results of Negative changes in inflation is insignificant at 5% and 10% as well.1% increase in inflation .reduces FDI by 0.4% and if Inflation is reduced by 1% FDI is Increased by 0.2%.At the same time, the non-linear estimation of interest rates concludes that there is an asymmetric and significant association between interest rates and FDI.If Interest rate has increased by 1% FDI is decreased by 0.9% and if interest rate has reduced by 1% FDI has deceased by 1.63%.It means the effect of interest rates is not the same for all time.Further, the results of the CUSUM test in Figure 3 explain that at a 5 percent significant level, there is no structural instability in the long-run export model.22

RECOMMENDATIONS AND CONCLUSIONS
India is a growing country with a large space for consumer and capital goods but suffers from financial and technological challenges.As a result, they constantly seek as much FDI as possible to meet these financial and technological requirements.Thus, this study focused on the factors responsible for attracting more FDI.The study investigates the relationship between FDI and various MEVs in India using the auto-regressive distributive lag (ARDL) procedure.
The research gap identified in this study is the lack of examination of asymmetric relationships between FDI and MEVs.The study finds that exports have a positive and significant impact on FDI inflows, while in line with Caves (1974) and Froot and Stein (1991), inflation and exchange rates have an adverse effect in the long run.However, the study also finds that the association between interest rates and FDI is asymmetric, meaning that the effect of interest rates on FDI is not the same at all times.The causality analysis reveals that export, GDP, and exchange rate are the significant economic variables that affect FDI.The study suggests that to increase FDI, the government should focus on improving export performance and controlling inflation and exchange rates.Additionally, the study suggests that the government should be aware of the asymmetric association between interest rates and FDI and take appropriate measures to attract more FDI.Overall, this study highlights the importance of considering asymmetric relationships when analyzing the association between FDI and MEVs.
FDI plays a crucial role in the economic development of a country.It brings in capital, technology, and new jobs, which ultimately helps to boost growth and development.India has made significant progress in attracting FDI in recent years, thanks to various policy changes and structural reforms.However, there are still several factors that need to be addressed in order to continue to attract more FDI in the future.These include easing policy frameworks, improving macroeconomic stability, and investing in infrastructure and development.
Additionally, as the global economy shifts towards emerging markets, it will be important for India to continue positioning itself as an attractive destination for foreign investment.This can be done by continuing to implement policy changes and structural reforms that make the country more attractive to foreign investors and by investing in areas that are likely to be of interest to foreign investors in the future.
The study's findings have practical implications for policymakers and investors looking to attract more FDI in India.The results indicate that exports play a critical role in attracting FDI and that the government should focus on improving export performance to increase FDI inflows.Additionally, the study highlights the importance of controlling inflation and exchange 23 rates to attract more foreign investment.The finding that interest rates have an asymmetric relationship with FDI suggests that policymakers should be cautious when implementing monetary policies that may impact interest rates.Overall, the study provides valuable insights for policymakers and investors looking to attract more FDI in India and highlights the importance of considering the country's macroeconomic conditions when making investment decisions.
Since the study only focuses on a specific country, India, the findings may not be generalized to other countries.Additionally, the study only uses a small number of MEVs to explain FDI inflows and may not capture the complexity of the association between FDI and MEVs.Future research avenues include expanding the study to cover a longer period, including more countries, and incorporating additional MEVs to explain FDI inflows.Future research could also explore the effects of other factors, such as political instability and corruption, on FDI inflows.Furthermore, the study could be extended to other sectors and industries to see if the results are consistent across different sectors.Additionally, it would be interesting to see how the results change when using different econometric techniques, such as panel data analysis or structural equation modeling.

FDI
and MEVs.While previous literature does examine the association between FDI and MEVs, they have primarily focused on symmetric relationships.However, it is important to consider the possibility of asymmetric relationships as well, as this could have important implications for policy-making.Another motivation is to investigate the association between FDI and different MEVs.While previous studies have examined the association between FDI and MEVs, such as exchange rate, inflation, and interest rate, this study aims to expand upon this research by including other variables, such as export and trade openness.This will provide a more comprehensive understanding of the association between FDI and MEVs and the potential impact of different policy measures.Finally, the use of the ARDL procedure in this study is motivated by its ability to provide a more robust and accurate examination of the association between FDI and MEVs.Unlike other methods, the ARDL procedure allows for the simultaneous examination of long-run and short-run interactions, providing a more comprehensive understanding of the association between FDI and MEVs.ARDL procedure developed by Peasaran can work with data set integrated at I(0) or I(1), I(0) and I(1) but not at I(2), has more advantegous over other method of cointegration like VECM.For the purpose of identifying asymmetric relationShin et al. (2014)  have extended the ARDL procedure and recently developed the asymmetric ARDL model using negative and positive partial sum decompositions that allow to identify the asymmetric effect in short term and long run.NARDL model has some advantages over classical cointegration models.First, NARDL model works efficiently even in small sample size(Romilly, Song, & Liu, 2001 Symmetric and Asymmetric Association Between Foreign Direct Investments and Macroeconomic Variables: An Ardl Approach ___________________________________________________________________________ Rev. Gest.Soc.Ambient.| Miami | v.18.n.1 | p.1-27 | e06697 | 2024.
Symmetric and Asymmetric Association Between Foreign Direct Investments and Macroeconomic Variables: An Ardl Approach ___________________________________________________________________________ Rev. Gest.Soc.Ambient.| Miami | v.18.n.1 | p.1-27 | e06697 | 2024.11 Al-Khouri (2015) found evidence of the agglomeration effect, i.e., countries with already high levels of FDI entice more future FDI."Economic risk" was found to negatively impact FDI inflows, while "trade openness" had a positive impact.Batschauer da Cruz et al. (2022) found that both Eclectic and OLI Paradigms can be applied to analyze the influence of institutional and political factors on sub-national level location strategies and determinants for a more comprehensive understanding of FDI dynamics in a country.Singh et al. (2020) conducted a review study on the determinants of spillover effects of FDI and found that most studies are based on empirical data and use industry-specific variables.The study also inferred that domestic firms benefit from foreign technology that has been transferred from foreign-owned companies.
Figure 1Flow of methodology adopted for the co-integration test, a long-run relationship among the model variables.The null hypothesis of "no cointegration" in the long run is H0: β1 = β2 = β3 = β4 = 0.The computed Fstatistic is compared with critical values.When cointegration among the variables in the model is confirmed based on the bound test, the long-run and short-run elasticity coefficients are Symmetric and Asymmetric Association Between Foreign Direct Investments and Macroeconomic Variables: An Ardl Approach ___________________________________________________________________________ Rev. Gest.Soc.Ambient.| Miami | v.18.n.1 | p.1-27 | e06697 | 2024.14 estimated using ARDL-restricted error correction models.After establishing the evidence of the cointegration between variables, an error correction model is developed.The error correction equation is reflected in Equation (2).     =  0 + ∑  1  − +  −1 +   (2) 4.5 DIAGNOSTIC TESTS FOR SYMMETRIC ARDL Finally, diagnostic tests for the ARDL model, such as autocorrelation tests, normality tests, and stability tests, were employed, and all the tests indicated the suitability of the estimated model.As shown in Table

Figure 2
Figure 2Cusum test and cusum of square test for ARDL cointegration

Table 1
Definitions of the macroeconomic variables used in the study

Table 2
Results of mean and other fundamental properties of macroeconomic determinants of FDI

Table 3
Unit root test

Table 4
Bound Test

Table 5
Long-term coefficient

Table 6
defines the short-run association between FDI and MEVs.The ECT term

Table 6
Short run coefficient

Table 7
Diagnostic test

Table 8
Bound test for cointegration

Table 9
Long run Coefficient

Table 10
Short run coefficientNotes: * and ** indicate 5 percent and 1 percent levels of significance, respectively 4.8 DIAGNOSTIC TESTS FOR ASYMMETRIC ARDL Diagnostic tests for the NARDL model, such as autocorrelation, normality, and stability tests, were employed, and all the tests indicated the suitability of the estimated model.As shown in Table11, there is no serial autocorrelation, and the model has homoscedasticity.For normality confirmation of the model, the Jarque-Bera test of normality confirmed that the error terms are normally distributed.Ramsey's RESET test has been applied to validate the model and confirms that the functional form is correctly specified.

Table 11
Diagnostic test

Table 12
presents the results of the Granger causality test.There is a bi-direction causal relationship between export and FDI at a 10% significance level.A unidirectional causal relationship has been confirmed between GDP and FDI, and the direction is from GDP to FDI.It means that the GDP or the market size attracts foreign investors.There is no causal relationship between FDI and inflation and interest rate and FDI.A unidirectional causal relation is confirmed between the exchange rate and FDI at a 10% significance level, and the direction is from exchange rate to FDI.Therefore, based on causality analysis, it can be concluded that export, GDP, and exchange rate are the significant economic variables that affect FDI.