NEXUS BETWEEN CAPITAL FLOWS AND ECONOMIC GROWTH: AN EVIDENCE FROM SOUTH ASIAN COUNTRIES

This study aims to look at how capital inflows affect economic growth in South Asian countries. Gross Domestic Savings (GDS), Foreign Direct Investment (FDI), Foreign Portfolio Equity Investment (FPEI), Foreign Debts (F.Debts), and Foreign Aids (F.Aids) are the study's independent variables, while Gross Domestic Product Growth (GDPG) is the dependent variable. Data has been collected from World development Indicator and Quandl from 1980 to 2018. To analyse the data Panel ARDL (PMG) model was utilised. Gross domestic savings, foreign direct investment, and foreign aid, all exhibit positive and strong long-term connections with GDP growth. Results also revealed that there are negative and strong long-run links between GDP, Foreign Portfolio Equity Investment, and Foreign Aids. There are negative and insignificant links between GDP growth, Foreign Direct Investment, and Foreign Aids. Results also reveal the positive and insignificant connections between GDP and GDS, FPEI, and foreign debt. The data imply that institutional improvement has an impact on capital inflows and economic growth. The study has policy implications for government and policymakers in the sense that capital flows and economic growth can improve the institutional environment.


INTRODUCTION
Several countries lack sufficient internal revenue to support economic development. Low savings and persistent budget deficits have exacerbated the need for foreign financing (Ndikumana, 2014;Feltenstein and Iwata, 2002). Many countries loosened restrictions and gave tax cuts and subsidies to attract foreign capital as bank funding to developing economies dried up in the 1980s (Aitken & Harrison, 1999;World Bank, 1997). Inflows of foreign capital are an important source of finance for investments in host countries, and as a result, they are thought to support a faster rate of economic growth. Investment capital flows, according to economic theory, help recipient countries improve their economic growth by contributing considerably to capital growth and bringing technology, expertise, and efficiency (Agbloyor et al., 2016). Ndiweni and Bonga (2021) studied the link of capital inflows and Sub-Saharan African economic growth. There are threshold effects linking capital inflows and economic growth. Results also reveal the positive and significant link of capital inflows on economic growth. Consequently, there has been an increase in the amount of capital moving into the region. More crucially, the sourcing and composition of capital flows have changed over time, besides with non-OECD countries' overseas investments and remittances supporting the growing trend. In developing countries, the FDI has been increased in 2013 by 6%, according to the World Bank (2015), with total net financial flows of $1,185 billion, up 10% from 2012. Despite 29% reduction in portfolio equity flows in 2013, net private capital flows to Sub-Saharan Africa (SSA) increased by 3.3 percent to a record high of $54.5 billion. In 2013, official development aid (ODA) to LDCs increased by 1.3 percent, reaching $42.3 billion. This leads to the conventional believe that higher domestic savings are directed to higher economic development in a country. Due to the crises in 2008, the effect of capital inflows on gross domestic product development has gained a more debatable topic (Macias and Massa, 2009). Despite these arguments, the empirical evidence has produced inconclusive findings. In fact, empirical studies have repeatedly failed to answer the widely held belief that capital flows (inherent spillovers and productivity) and growth are linked. While some studies have found a negative link between capital flows and economic growth, others have found the opposite (Djankov and Hoekman, 2000;Coulibaly et al., 2018;Van Bon, 2019 andKonings, 2001).
Foreign Direct Investment (FDI) and Portfolio Equity Investment (PEI) are two distinct types of investment. PEI is tied to ownership, but FDI is not. Both FDI and Portfolio Equity Investment created foreign debts. As a result, capital flows have the same impact on economic development. FDI is the most important element for economic development compared to other capital flow considerations. On the other hand, many economists believe that foreign debts are the primary source of aggravating financial crises in developing countries' growing economies. A well-developed financial market is critical in transforming the negative effects of capital flows into positive ones. Past studies have shown that capital flows are unable to recover a country's economic development in the absence of a well-organised financial industry. The findings also show that nations with sophisticated financial markets can benefit from EFPI and debt flows. The favorable impact of capital flows on economic development is highly dependent on the level of development of financial markets in the receiving country. Baharumshah and Thanoon (2006) explored that short-term capital flows can stifle development in emerging Asian economies due to the rush and abrupt reversals of inflows. These studies also show that short-and long-term capital flows can have different effects on industrialised and developing countries' economic development. Capital flows can boost investment and GDP development in both developed and developing countries, allowing these countries' living standards and consumption levels to rise dramatically. It is a fact that emerging countries have large profit margins and numerous prospects for successful investment. The effect of capital flows on GDP development varies depending on a country's economic development; Edwards (2001) found that capital flows have a positive and significant effect on Economic Development in developing countries. The financial systems and stock markets of developed countries are more active and efficient. Furthermore, countries that received large amounts of capital have risen at a higher rate. Capital inflows are more likely to benefit developed countries with better domestic institutional qualities (Soto, 2003). Policymakers and Economists hunt to step up economic development and maintain macroeconomic permanence. This means that exploring the catalysts of development is important for the design of proper development policies. Researchers stress the role of savings in economic development. They maintain that a high savings rate allows a high rate of investment, leading to higher economic development through capital accumulation. Even though the causal relationship between savings & economic development has been broadly studied in literature. The primary goal of this research is to look at the effect of capital inflow on economic development using these variables: "gross domestic saving, foreign portfolio equity investment, foreign direct investment, foreign debts, and foreign aid". Gocer et al. (2016) explored the impact of saving investment on GDP. Results show that savings have a positive and momentous effect on economic development in developing countries. The effect of savings on investment is negative and insignificant in these countries. Finally, it is concluded from this study that developing countries put a lot of effort into increasing their saving rates to boost their economic development and debt structure. Hailu (2016) considered the association between domestic saving (GDS) and gross domestic product development (GDP) in Ethiopia. The finding suggests that there is a negative association and unimportant contact between gross domestic saving and GDP development (economic development). Patra et al. (2017) investigated the long-term association between gross domestic savings and economic development and also found the causality issues in India during the period 1950 to 2012. Initially, this study investigates the structural breakdown during the period 1980 by using the Bi-Perron test. Furthermore, this study also explored the causality relationship between gross savings and economic development. Findings of the study reveal that "Gross Domestic Saving" liver up the real activity before and after the break-up period in the long term. Moreover, in the pre-break period GDP development caused gross saving in the short period. The current research supports exogenous neoclassical and endogenous post-neoclassical popular development theories. Findings recommend that both incentive-based and productivity-based methods are effective in increasing savings and strengthening the rate of income and development. Opschoor (2015) investigated the link of economic development and gross domestic saving by using the panel data studies and Granger causality study. Results reveal that most of the countries have causal association among the two above variables, but the direction of association is unclear; finding also shows that there are chances of causality direction is reliant on the income level of the country. Jagadeesh (2015) explored the association between GDP Development and Gross Domestic Saving (GDS) in Botswana. Botswana Time series data is used which is 33 years from 1980 to 2013. The technique used for analysis was the ARDL model to see the existence of a long term association between Gross Domestic Savings (GDS) and Economic Development (GDP Development). In this study, the DOLS model is used to investigate the dynamic long-term integration among Economic Development (GDP Development) and Gross Domestic Saving (GDS). The finding shows a positive and significant association between GDS and GDP Development. Tsaurai (2017) showed the influence of equity portfolio investment on gross domestic product development (economic development) of fourteen European and Asian rising markets. The finding also indicates that they must also focus on overseas portfolio bond investment if they want long-term sustainability in economic development. Ibrahim and Akinbobola (2017) asserted the association between gross domestic product development (economic development) and overseas portfolio equity investment in Nigeria. The finding indicates that there is a positive association between overseas PEI and GDP development. In the long run, the finding indicates that there is an important and positive impact of democracy on gross domestic product development. Albulescu (2015) explored the impact of FDI on the GDP development of the country. Moreover, in this study, two independent variables are used, i.e. FPI and FDI, to check the long-term impact of these variables on the GDP development of the European countries. The technique used to find out the results is the GMM test in Panel Data. Moreover, in this study, different control variables are used to correct the endogeneity issues among Economic Development and Investment. Results suggest that direct and portfolio investments have a significant effect on economic development. Moreover, these results are consistent for both inward and outward investments. Anyanwu et al. (2017) explored the influence of bank offering on GDP development (when the private sector borrows money from a commercial bank). Ordinary least squares analysis shows that bank lending has a moderate and negative impact on GDP development. The result of the Johansen co-integration test shows that GDP development and bank lending have a long-term relationship. Tahir et al. (2015) explored the link of bank lending to the private sector and GDP development. The outcomes of regression analysis showed that bank lending to the private sector has a negative link with economic development. The data also revealed that, in both the short and long run, there is a robust link between bank lending to the private sector and GDP development. The discovery also suggests that private-sector bank lending has a causal effect on GDP development. Rateiwa and Aziakpono (2017) discussed the root and long-run association between other lendings (non-bank financial institutions) and gross domestic product development of South Africa, Egypt, and Nigeria. The results in Egypt suggested there is a positive and lasting relationship between other lending and development in the economy. The findings from South Africa suggest that there is a significant, positive, and long-term relationship between other lending and GDP development. The conclusion in Nigeria implies that there is an insignificant relationship between other loans and GDP development, but it also indicates mixed and weak results.

Research Hypothesis
H1: There is an insignificant relationship between GDS and EG in South Asian nations. H2: FDI and EG have an insignificant relationship in South Asian nations. H3: There is an insignificant relationship between FPEI and EG in South Asian nations. H4: There is an insignificant association between foreign debts and economic development in South Asian nations. H4: There is an insignificant association between foreign aids and economic development in South Asian nations.

METHODOLOGY
Data for the period 1980 to 2018 was collected from WDI and Quandl. The dependent variable of the study is Gross Domestic Product Development, and independent variables are Gross Domestic Saving (GDS), FPEI, FDI, Foreign Debts (F.Debts), Foreign Aids (F.Aids). Description of variables in given in Table  1. For analysing the data, the Panel ARDL (PMG) model was used by using the following equation (Pesaran et al., 2001).

RESULT AND ANALYSIS
This study consists of 6 variables which are "gross domestic saving, foreign debts, foreign portfolio equity investment, FDI, foreign Aids, and economic development". The data were collected from the period 1980 to 2018. Kurtosis results reveal that the FPEI variable is leptokurtic; in simple terms, it indicates that it has a higher peak / long tail. Finally, Jarque-Bera statistics show that the surplus of the FPEI variable is not normally distributed, and the probability value of portfolio equity investment is 0.00, which is less than 5%, so we accept the alternative hypothesis that the surplus/residual is not normally distributed. However, even if the surplus is not normally distributed, we still accept the model (Enders and Lee, 2004 The skewness for the F.Aids variable proves that the distribution is extremely skewed, while the kurtosis results suggest that the F.Aids variable is leptokurtic. Simply said, it indicates that it has a higher peak and a longer tail. Finally, Jarque-Bera statistics prove that the surplus of the F.Aids variable is not normally distributed; the probability value of FAids is 0.00, which is less than 5%, so we accept the alternative hypothesis that the surplus residual is not normally distributed; however, even if the surplus is not normally distributed, we still accept the model (Enders and Lee, 2004). There are lots of methods available to check unit root in data, but in the present study, only two-unit root test is applied first one is the IPS test, and the second one used in this study was the LLC test. The LLC test is not good in small sample size due to their serial correlation, but their forte is in a large sample; their results are accurate in large samples. To overcome their disadvantage, we used the IPS test. IPS test is good in small sample size because this test minimises the serial correlation and this is their forte but this test is not good for the large sample size and this is their disadvantage. Both tests have one advantage and one disadvantage; this is why in this study, we chose both of them to enhance the accuracy of the results (Wang et al., 2011;Im et al., 2003;Levin et al., 2002). If the pvalue is less than 5%, it means there is no unit root; in simple words, if the p-value is less than 0.05 in both tests (LLC & IPS), then the data is called stationary, and in Table 3, the p-value is less than 5%. The results from the Table 3 are extracted by using the EViews 9, and based on LLC and IPS test, the four variables (Foreign Portfolio equity investment, Foreign Debts, Foreign Aids and Economic development) are found stationary at the level, and the remaining two variables (Gross domestic saving and Foreign Direct Investment) is found stationary at first difference. In Table 3, the results of the correlation are extracted by using EViews 9. Correlation describes the degree of the relation among the variables of the study. If the values of the correlation coefficient are greater than 0.90, it means there is a problem of multicollinearity among the variables. In the above results, all the values of the correlation coefficient are below the threshold of 0.90 therefore it is established that data.

PMG Analysis
The PMG (pooled mean group) evaluator allows short-run coefficients, as well as the cutoff and speed of change to the longrun equilibrium, to differ between countries. Im et al. (1999) used the MLE (pooled maximum likelihood estimate) to examine the long and short-run coefficients, and the results are as follows. Table 6 shows the average for all four nations. Long-run results show that there is a positive and significant long-run link among GDP Development and Foreign Direct Investment, Gross Domestic Savings, and Foreign Aids. Secondly, there are negative and significant relations among GDP and Foreign Portfolio Equity Investment as well as Foreign Debts among the leading South Asian Countries in the long run. In the short run, there is a negative and insignificant relationship between GDP Development and Foreign Direct Investment as well as Foreign Aids. Secondly, there are positive and insignificant relations among GDP and GDS, FPEI, and Foreign debts among the leading South Asian Countries.

Results Related to Short-Run Relationship for Each Economy
Following are the short-run results of each nation. The results in the Table 7 are related to Bangladesh's short-run relationship. Because the probability value in Table 7 is 0.075 and it is greater than 5%, there is a non-significant link in these variables, and the coefficient value of FDI is 0.799, there is a positive and non-significant short-run relationship present between FDI and GDP. Because the probability value in the Table 7 is 0.990 and it is more than 5%, there is a nonsignificant relationship present in these variables, and the coefficient value of FPEI is 19.846 which indicate that there is a positive and non-significant short-run relationship present between FPEI and GDP development.   The results for Bangladesh GDS show that there is a negative and significant short-run relationship between GDP development and GDS because the probability value is 0.0006 and it is less than 5%, indicating that there is a significant relationship between these variables, and the coefficient value of GDS is -0.110, indicating a negative relationship between GDS and GDP. Because the probability value in Table 7 is 0.706 and it is more than 5%, there is a non-significant relationship present in these variables, and the coefficient value of F.Debts is 0.202, there is a positive and non-significant short-run relationship present between foreign debts & GDP gross domestic product development in Bangladesh. Because the probability value in Table 7 is 0.003 and less than 5%, there is a significant relationship present in these variables, and the coefficient value of F.Aids is -1.258, there is a negative and significant short-run relationship present between F.Aids and GDP. The result for India FDI indicates that there is a negative and non-significant short-run relationship between gross domestic product development and foreign direct investment because the probability value is 0.241 and it is greater than 5%, indicating that there is a non-significant relationship between these variables, and the coefficient value of FDI is -1.863, indicating a negative relationship between FDI and GDPG. The result for India FPEI indicates that there is a negative and nonsignificant short-run relationship between PEI and GDP development because the probability value in Table 7 is 0.987, which is greater than 5%, indicating that there is a nonsignificant relationship between these variables, and the coefficient value of FPEI is -104.467, indicating that there is a negative relationship between FPEI and GDPG. The outcome for India GDS indicates that there is a positive and significant short-run relationship between GDS and GDP development because the probability value in Table 7 is 0.001 and it is greater than 5%, indicating that there is a non-significant relationship in these variables & the coefficient value of GDS is 0.624, indicating a positive relationship between GDS and GDPG. The result for India F.Debts indicates that there is a negative and non-significant short-run relationship between gross domestic product development and foreign debts because the probability value in Table 7 is 0.922, which is greater than 5%, indicating that there is a non-significant relationship between these variables, and the coefficient value for F.Debts is -0.114, indicating that there is a negative relationship between F.Debts and GDPG. The result for India F.Aids indicates that there is a negative and non-significant short-run relationship between GDP development and foreign aids because the probability value in Table 7 is 0.783, which is greater than 5%, indicating that there is a non-significant relationship between these variables, and the coefficient value for F.Aids is -1.87"indicating that there is a negative link of F.Aids and GDPG.
The result for Pakistan FDI shows that there is a positive and "insignificant short-run relationship between GDP development and foreign direct investment because the probability value is 0.275, which is greater than 5%, indicating that there is a non-significant relationship between these variables, and the coefficient value of FDI is 0.448, indicating that there is a positive relationship between FDI and GDPG. Because the probability value in Table 9 is 0.993 and it is greater than 5%, there is a non-significant relationship present in these variables, and the coefficient value of FPEI is 109.249" there is a positive and non-significant short-run relationship present between foreign portfolio equity investment and gross domestic product development in Pakistan.  The result for Pakistan GDS indicates that there is a positive and significant short-run relationship between gross domestic saving and gross domestic product development because the probability value is 0.0001 and it is less than 5%, indicating that there is a significant relationship between these variables, and the coefficient value of GDS is 0.454, indicating that GDS and GDPG have a positive relationship. The result for Pakistan F.Debts indicates that there is a positive and significant shortrun relationship between foreign debts and GDP development because the probability value is 0.01 and less than 5% in Table  9, indicating that there is a significant relationship between these variables, and the coefficient value of F.Debts is 0.582, indicating that there is a positive relationship between F.Debts and GDPG. The result for Pakistan F.Aids indicates that there is a negative and significant short-run relationship between foreign debts and gross domestic product development because the probability value in Table 9 is 0.008 and it is less than 5%, indicating that there is a significant relationship between these variables, and the coefficient value of F.Aids is -0.972, indicating that there is a positive relationship between F.Aids and GDPG. The result for Sri Lanka FDI indicates that there is a negative and insignificant short-run relationship between foreign DFI & GDP development because the probability value in Table 9 is 0.490, which is greater than 5%, indicating that there is a non-significant relationship between these variables, and the coefficient value for FDI is -0.131, indicating that there is a negative relationship between FDI and GDPG. Because the probability value in Table 9 is 0.921 and it is greater than 5%, there is a non-significant relationship present in these variables, and the coefficient value of FPEI is 11.205, there is a positive and insignificant short-run relationship present between PEI and"GDP development.
The result for Sri Lanka GDS indicates that there is a negative and significant short-run relationship between GDS and GDP development because the probability value is 0.000 and less than 5% in Table 10, indicating that there is a significant relationship between these variables, and the coefficient value of GDS is -0.421, indicating that there is a negative relationship between GDS and GDPG. The result for Sri Lanka F.Debts indicates that there is a positive and significant short-run relationship between GDP development and foreign debts because the probability value in Table 10 is 0.0014, which is less than 5%, indicating that there is a significant relationship between these variables, and the coefficient value for F.Debts is 1.999, indicating that there is a positive relationship between F.Debts and GDPG. The result for Sri Lanka F.Aids indicates that there is a positive and significant short-run relationship between GDP development and foreign aids because the probability value is 0.0062, which is less than 5%, indicating that there is a significant relationship between these variables, and the coefficient value of F.Aids is 0.310, indicating that F.Aids"and GDPG have a positive relationship.

CONCLUSIONS
For the enhancement of the living standards of the citizens, they require a sustainable inflow of capital for maintaining the saving and foreign exchange gap, which will increase the development rate and capital accumulation. Another resource is capital inflow. Macias and Massa (2009) explained that during the 2008 crisis, the effect of capital inflows on gross domestic product development was more debatable. Empirical research linked the capital flow and gross domestic product results favoured and opposed the theoretical debate concerning the influence of capital inflow. "The results of this study reveal that the outcomes of the LLC & IPS tests show that the two variables (Foreign Portfolio Equity Investment, Foreign Debts, and Foreign Aids) are found stationary at the level, while the remaining two variables (Gross domestic saving and Foreign Direct Investment) are found stationary at the first difference, leading to the selection of the panel ARDL model. Gross domestic savings, foreign direct investment, and foreign aid all exhibit positive and strong long-term relationships with GDP growth, according to the findings. Second, there are negative and strong long-run links between GDP, Foreign Portfolio Equity Investment, and Foreign Aids. In the short run, there are negative and weak links between GDP growth, Foreign Direct Investment, and Foreign Aids". Second, there are both positive and insignificant links between GDP and GDS, FPEI, and foreign debt.