Foreign Aid,FDI and Economic Growth in South-East Asia and South Asia

Introduction

Foreign aid and foreign direct investment (FDI) are two important sources of capital for developing countries. Foreign grant-in aid mainly flows in the form of Official Development Assistance (ODA) from developed countries to developing countries to promote economic development and national welfare (OECD, 2012). Aid not only supplements to other sources of finance for development in low-income and developing countries who are unable to attract FDI, aid may also create necessary domestic and international conditions to facilitate and attract FDI flows.

Aid broadly aims at stimulating economic growth by financing health and educational infrastructure, strengthening of political institutions, providing emergency relief, and stabilizing economies that are afflicted by supply shocks. Contingent upon a sound governance structure, well-developed markets and trade-friendly policies, effective monitoring and evaluation systems, if aid helps in developing complementary social overhead capital (SOCs) such as, building roads, dams and electricity generation, it may crowd-in private investment in promoting Direct Productive Activities (DPAs). By providing access to capital and technological expertise to the capital scarce developing economies, aid can increase the marginal efficiency of capital and can create conditions conducive to private investment and FDI, and hence, can trigger dynamism for a higher sustained growth (Papanek, 1972; Rostow, 1960). However, that aid has a ‘catalyzing’ effect on FDI, or, that aid and FDI are complements, or, aid promotes growth, is by no means empirically very evident (Rajan & Subramanian, 2008).

To examine the relation between foreign aid, FDI and economic growth, we consider two groups of countries of South-East Asia (SEA) and South Asia (SA) during the 1980s to 2016 when the countries in the region gradually witnessed trade and financial openness. SEA as a region, except for low-income countries such as Cambodia, Timor Liste and Lao PDR, has relied less on foreign aid flows but more on higher FDI flows for economic growth whereas SA as a region, except for India, has relied more on foreign aid flows and less on insignificant FDI flows for economic growth. Given the varied experiences of SEA and SA in terms of foreign aid, FDI flows and growth, we empirically examine: (a) the role of foreign aid and FDI in the process of economic development and growth. Specifically, we robustly investigate, whether foreign aid and FDI played a role in sustaining higher economic growth. (b) Whether foreign aid and FDI complement or substitute? (c) Did the economies in the region benefit from trade openness especially after joining in WTO? and (d) Did domestic financial assistance to private sector for investment and industrial growth augmented FDI flows? The rest of the article is structured as follows. The second section reviews the relevant literature on the relationship between aid and FDI as well as whether aid and FDI promote economic growth. The third section highlights the trends in aid and FDI flows to the SEA and SA region. The fourth section deals with the data and empirical methodology of the article. The empirical methods include the baseline as well as several robustness econometric specifications. The concluding section of the article summarizes the findings of the article. Our empirical results from alternate empirical specifications demonstrate that while foreign aid negatively affects economic growth and is crowding out FDI, there exists positive relation between FDI and economic growth. We also find that domestic financial assistance to private sector that promotes domestic investment positively related to both FDI and economic growth in the region.

A Brief Review of Literature

A large amount of literature is devoted on how aid can positively affect economic growth (Fayissa & El-Kaissy, 1999). Aid works well in developing countries with sound institutional structure and policy environment (Burnside & Dollar, 1997; Sethi, Bhujabal, Das, & Sucharita, 2019). Aid can increase public investment, especially in infrastructure (Feyzioglu, Swaroop, & Zhu, 1998) and it can improve human capital. Morrissey (2001) and Gomanee, Girma, and Morrissey (2005) contend that aid can augment investment in physical and human capital, capacity to import capital goods and technology, and capital productivity and promotes endogenous technical change. Hansen and Tarp (2001) find that aid has a positive effect on growth via capital accumulation (investment). Foreign aid also brings the opportunity to access the up-to-date technology and managerial skills, and allows easier entry into the foreign market (Chenery & Strout, 1966; Gulati, 1975; Islam, 1995; Levy, 1988). However, examining the effects of aid on growth in cross-sectional and panel data, Rajan and Subramanian (2008) find little evidence of a positive (or negative) relationship between aid and economic growth. Furthermore, they find no evidence that aid works better in better policy or geographical environments, or that certain forms of aid work better than others. Easterly (2003) reviewed the empirical works, and worldwide evidences end in a restrained conclusion that aid only has benefited growth modestly and in few of the cases only.

Aid can have a net ambiguous effect on FDI since it can affect FDI both positively and negatively through multiple channels (Askarov & Doucouliagos, 2015; Harms & Lutz, 2006; Kimura & Todo, 2010;). Kosack and Tobin (2006) argue that aid and FDI are essentially unrelated as aid is to support budget finances to invest in human capital, whereas FDI is invested in private sector and more connected to physical capital. Only middle-income developing countries with a relatively high level of human capital benefit from local knowledge spillovers that FDI may create because of skilled job creation. Low income developing countries with relatively low human capital, in general, do not benefit from knowledge spillovers created by FDI as the investments are mostly aimed towards low-skill labour intensive production. Foreign aid and FDI in these countries are, therefore, neither substitutes nor complements to human capital development.

Selaya and Sunesen (2012) distinguish aid into two broad types: (a) ‘aid invested in complementary inputs’ such as education, health, energy, transport and communication, and (b) ‘aid invested in physical capital’ including transfers to directly productive sectors such as, agriculture, industry, trade and banking. While the former type of aid is expected to have a positive effect to the extent that aid increases productivity of private investment by improving supply of SOCs, that is, economic and social infrastructure, the later type of aid crowds out FDI. Aid can also have a negative effect by encouraging firms to indulge in unproductive rent-seeking activity (Economides, Kalyvitis, & Philippopoulos, 2008) and can affect resource allocation between tradable and non-tradable sectors by crowding out private foreign activity in the tradable goods sector (Oladi & Beladi, 2007). Indeed, Sahoo and Sethi (2017) find neither aid nor FDI positively affects economic growth in India. Furthermore, aid can only have ‘vanguard effect’, that is, aid can only encourage FDI from the same donor country.

Harms and Lutz (2006) conclude that aid overall has no significant effect on FDI. Asiedu, Jin, and Nandwa (2009) find a negative effect of aid on FDI in low-income recipient countries; although it tends to reduce the adverse effect of country risk on FDI. Therefore, one strand of literature views that foreign aid-funded infrastructure investment in building roads, schools, electricity and telecommunications attracts FDI at the later stage of development, but the other argues that investment projects financed by foreign aid from multilateral financial institutions crowds out foreign capital in the long run.

The later literature on aid provides a mixed evidence on possible transmission mechanisms through which aid helps to remove bottlenecks to higher FDI inflows. Vijil and Wagner (2012) provide cross-country evidence on how a well-targeted aid improves recipient country’s infrastructure. Mishra and Newhouse (2009) find that health aid reduces infant mortality in the recipient countries. Dreher, Nunnenkamp, and Thiele (2008), and D’Aiglepierre and Wagner (2013) find educational aid to be effective in improving educational outcomes. Karakaplan and Neyapti (2005) although find an insignificant negative direct effect of aid on FDI, but good governance and well-developed financial markets improve the impact of aid on subsequent FDI flows.

Foreign Aid and FDI Flows in South-East Asia and South Asia

Although, SEA and SA region have been experiencing foreign private capital flows in recent decades, after a greater degree of integration to world economy (Bhavan, Xu, & Zhong, 2011), by and large, they have remained less attractive to FDI due to structural bottlenecks: poor quality of infrastructure and insufficient domestic savings (WEF, 2011, 2012). Besides Singapore, Malaysia, Thailand, Bangladesh and India, rest of the region has exhibited macroeconomic instability: volatile economic growth, bouts of higher inflation and higher fiscal deficit (Crowley & Lee, 2003; Cushman, 1988; Julio & Yook, 2016; Lemi & Asefa, 2003).

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Figure 1.

Source: World Development Indicators, World Bank.

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Figure 2.

Source: World Development Indicators, World Bank.

In order to accelerate regional economic development, many economies in the region thrived upon foreign aid especially from the developed west. Quazi (2014) find a positive and significant association between foreign aid and FDI in East Asian and South Asian economies during 1995 -2012. Similarly, Bhavan et al. (2011) and Carro and Larru ́ (2010) find that aid attracts FDI in Bangladesh, Sri Lanka, Pakistan and India. Chinese aid to several poor SEA and SA economies might have had a positive impact on FDI inflows at a later stage of development through a positive infrastructure effect and so as foreign aid from USA and several European countries to the region later translated into FDI from these economies.

Figures 1 and 2 present 5-year annual average foreign aid and FDI flows as a percentage of GDP during 1980–2015 of SEA. Only low developing economies like Timor Leste, Lao PDR and Cambodia received substantial foreign aid followed by Vietnam and Philippines in the region to promote economic development. Only three out of nine economies have obtained more foreign aid compared to FDI flows. Among SEAs, Singapore has received the highest amount of FDI followed by Vietnam, Cambodia, Malaysia, Lao PDR, Timor Leste, Thailand and Myanmar. Opening up of economies by Malaysia, Cambodia, Thailand and Vietnam witnessed higher FDI inflows post 1995. Interestingly, for Vietnam, Cambodia, Lao PDR and Timor Leste, a declining foreign aid is substituted by increasing FDI over time. Indonesia, Myanmar and Philippines and Brunei have undergone several macroeconomic challenges which have impeded FDI flows. Similarly, we provide a 5-year annual average foreign aid and FDI flows as a percentage of GDP of SA economies during 1980–2015.

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Figure 3.

Source: World Development Indicators, World Bank.

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Figure 4.

Source: World Development Indicators, World Bank.

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Figure 5.

Source: World Development Indicators, World Bank.

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Figure 6.

Source: World Development Indicators, World Bank.

In contrast to SEAs, it can be observed that since most of the economies in the SA region are low-income countries, they depend exclusively on foreign aid for growth except for India. Afghanistan, Bhutan, Maldives and Nepal received a higher portion of foreign aid in the region. While most of these economies started receiving increasing FDI flows with the decline in foreign aid flows except for Maldives, SA as a region has received a pitiful FDI. Besides lower levels of growth, most of the region mainly characterized by weak political and institutions and corruption, structural deficiencies, instability, lack of policy coordination at federal and local government levels, bureaucratic red-tapism and infrastructure bottlenecks, and significant regional differences (WEF, 2011, 2012). This makes the region unattractive for private capital flows. Maldives and India are the two economies in the region received substantially higher FDI compared to foreign aid. Not only that SEA and SA economies in the region exhibited varied experiences in terms of aid and FDI flows, they do also exhibit varied economic growth experiences (see Table 3 and Table 4).

As can be seen from Figures 5 and 6, except for, Philippines, Cambodia and Lao PDR, countries in SEA have experienced either falling or fluctuating economic growth. However, Bangladesh, Bhutan, India, Nepal and Sri Lanka in SA have sustained economic growth. Therefore, these trends in aid and FDI flows do suggest that both in SEA and SA low income countries receiving relatively higher aid flows during the initial decades of 1980s and early 1990s, and relatively higher FDI flows in the post-1990s exhibit sustained higher economic growth. We also observe that despite economic development and increased capital flows, foreign aid has not been completely dissipated from low-income countries such as, Afghanistan, Bhutan, Nepal, Maldives, Timor Leste and Lao PDR. Therefore, as pointed out earlier, given the varied experiences of SEA and SA in terms of foreign aid, FDI flows and growth, we empirically examine the relationship between foreign aid and FDI flows in the process of economic development and growth of the countries in these two regions.

Data and Empirical Model

The major aim of this article is to empirically examine the impact of foreign aid and FDI on the economic growth. The article simply delves into the empirical examination of impacts of aid and FDI on economic growth in SEA and SA region. The article does not look into any development issues of the region. Due to the macroeconomic diversities, changes in economic and political conditions, trade and financial openness, this article seeks to look into certain financing channels of fuelling economic growth. Hence, we identify the role of both FDI and foreign aid in the growth process.

In the early literature based on Harrod–Domar models and on standard ‘two-gap’ models of Chenery and Strout (1966), the first gap is investment-saving gap for a desired growth, while the second gap is between import requirements and foreign exchange earnings (Easterly, 2003). Foreign aid filling-in one binding gap at any time helps in overcoming the domestic savings constraint. As Hansen and Tarp (2000) argue, aid accelerates economic growth by supplementing domestic capital accumulation, that is, aid impacts on investment and in turn impacts on growth. Furthermore, Obstfeld (1999) shows that an increase in aid raises both consumption and investment as well as the growth rate of an economy, which is initially below the steady state. Therefore, we examine the relationship between aid, FDI and economic growth. This is to understand: (a) whether foreign aid and FDI flows influence economic growth in the region as well as does (b) higher sustained growth results in higher capital flows. For example, India and Bangladesh has been able to attract more foreign capital flows post-liberalization of the 1990s during the periods of higher growth and macroeconomic stability. Similarly, Singapore, Malaysia, Indonesia and Thailand have experienced FDI-led growth over the years (Pradhan, 2009). While Febiyansah (2017) finds that FDI and trade (exports) conjointly promote economic growth in Indonesia and improve export competitiveness in the short run, Kulkarni and Sun (2004) argue that international trade meeting domestic demand sustain growth. In the light of these findings, our objective of specifying a two-way casual relation between economic growth and FDI is also to see whether FDI and economic growth influence each other in the presence of foreign aid flows, joining WTO, greater trade openness and domestic financial assistance to private sector.

We derive the following empirically estimable equation:

F D I i t = α 0 + α 1 g G D P i t + α 2 A I D i t + α 3 F D i t + α 4 T R O P i t + α 5 W T O D i t + ε i + ε t + ε i t

(1)

where FDI_it is the FDI flows of the year t of the country i. α 1 denotes the parameter for the GDP growth of the country i of the year t. gGDP_it denotes the gross domestic product of the country i of the year t. α 2 denotes the parameter associated with the WTO dummy of the country i of the year t. WTOD_it denotes the WTO dummy, that is, joining of the country to WTO as a member. Similarly, α 3 and α 4 denote the parameters associated with the domestic financial assistance (FD) and foreign aid (AID) for country i of the year t respectively. α 5 denote the parameter associated with the trade openness (TROP) for country i of the year t. ε i t is the error term of the above empirical model. The empirical model specified in Equation (1) is of a simple regression model specification by considering both the time- and country-specific fixed effects. In the cases where we employ regression techniques to cross-country panel, we apply both the year and the country fixed effects to make our analysis more robust.

The next empirical model is structured as follows:

g G D P i t = α 0 + α 1 F D I i t + α 2 A I D i t + α 3 F D i t + α 4 T R O P i t + α 5 W T O D i t + ε i + ε t + ε 2 t

(2)

FDI and AID are considered in terms of net inflows. We measure FDI as the net FDI flows in US dollars. Data regarding net FDI flows are taken from World Development Indicator (WDI) database of World Bank. For empirical simplification, we further convert FDI flows into logarithm of FDI. In order to measure domestic financial assistance provided by the government with an aim to finance and revive industrial sector, we consider domestic credit provided by government to private sector (FD) as a percentage of GDP. We believe domestic financial assistance to private sector for investment purpose is important to sustain higher economic growth as well as in attracting complementary capital flows. It may be noted that foreign aid may increase the ability of government finances yet it is not to say that aid flows were used as a complement to the domestic financial assistance since there is no guarantee that countries utilize aid exclusively for financing domestic investment for industrialization. Therefore, domestic financial assistance may be seen as country’s quest for economic development via higher domestic investments. The data have been collected from WDI database of World Bank. For empirical specification, we convert FD into natural log.

We measure economic growth in terms of gross domestic product in constant prices and the data has been sourced from WDI. We also consider the specific year in which each of these countries joined WTO by constructing WTO dummy. WTO dummy in the empirical analysis presents the year of joining of the economies in the region to WTO. WTO dummies are represented in forms of 0 and 1. For each country, the years with having values 0 present the years prior to joining WTO and the years with values 1 present the subsequent years to joining WTO. This is to examine whether joining WTO improves trade and capital flows. We have obtained the data on WTO membership of different economies of South Asian and South-East Asian region from World Trade Organization (WTO) database.

Foreign aid refers to the total aid flows from the official donors to countries and territories in part (ii) of Development Assistance Committee (DAC) list of recipients; more advanced countries, countries of former Soviet Unions and some developing economies. It is measured as a percentage of gross national income. The data regarding foreign aid are also taken from WDI database. The degree of trade integration of countries is measured by trade openness which is an aggregate of exports and imports to GDP ratio. The data on exports and imports of SEA and SA are taken from WDI database. Based on this data, we compile trade openness of all 18 economies of the region wherein trade openness is measured as the summation of imports and exports as a percentage of GDP.

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Table 1.

Baseline Regression Model 1: FDI as a Function of GDP Growth

FDI	I	II	III	IV
gGDP	−0.004 (0.005)	0.230* (0.049)	0.289* (0.046)	−0.040 (0.041)
AID	−0.487*** (0.307)	0.352 (0.352)	0.101 (0.112)	−1.216* (0.339)
FD	2.203* (0.286)	0.583* (0.261)	0.933* (0.270)	2.287* (0.287)
TROP	0.161 (0.162)	0.008 (0.008)	0.020 (0.018)	0.082 (0.084)
WTO dummy	0.445 (0.319)	0.759* (0.375)	1.266* (0.213)	−1.605* (0.513)
Constant	−0.238 (0.195)	−1.210* (0.591)	−0.916* (0.378)	−0.402 (0.401)
Region	SEA & SA	SEA & SA	SEA & SA	SEA & SA
Time effect	No	Yes	Yes	No
Country effect	No	Yes	No	Yes
No. of observations	684	684	684	684
R 2	0.166	0.754	0.731	0.219
F-test	27.01*	33.06*	78.20*	14.53*

Source: World Development Indicators, World Bank and WTO.

Notes: All variables are converted into natural logarithm. p-values are reported in parentheses under the values of coefficients. * and *** denote the estimates significantly different from 0 at 1% and 10% levels of significance respectively.

Baseline Specifications

Our baseline specifications consider simple regression analysis among the variables considered for the study to examine the mutual relationship. The model takes into account the fuller panels (SEA and SA), where FDI is a function of GDP given other control variables such as foreign aid, domestic financial assistance, trade openness and country specific WTO joining year in order to examine the temporal relationship between FDI and GDP. The country-specific fixed effects consider country-related macroeconomic heterogeneity in terms of differences in macroeconomic policies, such as inflation, fiscal deficit, trade structure, exchange rate, governance structure and other socio-political conditions. Similarly, year specific effects are used to capture the time specific heterogeneities at the country level, which can also take care of the year specific macroeconomic policy changes in the concerned economies. Table 1 presents ordinary least square (OLS) regressions results from four alternate specifications: (a) without time and country fixed effects, (b) with both time and country effects, (c) only time effects and (d) only country effects. In order to ensure stationarity and long-run co-integration among all the variables considered in the model, we have performed panel unit root tests as well as Fisher-Johansen co-integration tests and Pedroni co-integration tests. ¹ We find from the unit root tests that all variables are stationary at first difference and Fisher-Johansen co-integration test suggest that all variables are co-integrated in the long run. Furthermore, the Pedroni co-integration test suggests that there exists a long run co-integration relation among all the variables. Our empirical results for the entire region (SEA and SA) presented in Table 1 suggest that coefficients of GDP growth are positive and significant at the conventional level of significance (see columns II and III, Table 1).

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Table 2

. Baseline Regression Model 2: GDP Growth as a Function of FDI

gGDP	I	II	III	IV
FDI	−0.003 (0.003)	0.147* (0.031)	0.190* (0.030)	−0.031 (0.032)
AID	0.069 (0.067)	3.644* (0.238)	4.037* (0.228)	−0.628* (0.301)
FD	3.439* (0.228)	0.444* (0.206)	1.075* (0.200)	3.472* (0.227)
TROP	0.159 (0.158)	0.053 (0.054)	0.080 (0.086)	0.111 (0.112)
WTO dummy	0.113 (0.118)	−0.791* (0.296)	0.891* (0.174)	−1.212* (0.453)
Constant	4.754* (0.251)	−0.357 (0.359)	0.855* (0.306)	4.104* (0.741)
Region	SEA & SA	SEA & SA	SEA & SA	SEA & SA
Time effect	No	Yes	No	Yes
Country effect	No	Yes	Yes	No
No. of observations	684	684	684	684
R 2	0.346	0.840	0.817	0.370
F-test	72.00*	56.75*	128.24*	79.47*

Source: World Development Indicators, World Bank and WTO.

Notes: All variables are converted into natural logarithm. p-values are reported in parentheses under the values of coefficients. * denotes the estimates significantly different from 0 at 1% level of significance.

The coefficients of foreign aid are negative and significant when country-specific effects are considered (see column IV, Table 1). We find positive and significant relations between domestic financial assistance and FDI flows. This further confirms that an increase in domestic financial assistance to the private sector, an uptick to investment cycle and a boost to indigenous efforts for rapid industrialization are complemented by FDI flows. We find that for every 1 per cent increase in domestic financial assistance, the FDI increases by 0.58 per cent to 2.29 per cent (see columns I–IV).

Table 2 reports the basic regression results of entire region, where the GDP growth is the function of FDI and other control variables, such as foreign aid, domestic financial assistance, trade openness and WTO dummy. The empirical results indicate that coefficients of FDI are positive and statistically significant at the conventional level of significance (see columns II and III, Table 2). Every 1 per cent increase in FDI leads to 0.15 per cent increase in GDP growth in the region annually. The impact of joining WTO found to be having mixed response on GDP during the period. Our empirical results reveal that there exists positive and significant association between WTO dummy and GDP growth when country specific effects are incorporated. This suggests that joining WTO and the subsequent impact on GDP growth are exclusively country specific. The results further reveal that after joining WTO, countries following WTO clauses may be able to restructure and abide by global trade standard. Singapore, India, Malaysia, Thailand, Philippines and some other developing economies from the region have joined WTO by 1995, thus opening up their economies substantially to global trade. However, on the contrary, we find a negative association between joining WTO and GDP growth when both the time and country effects are considered (see column II, Table 2). This indicates that joining WTO has not had a positive impact on growth for some of the economies in the region. For instance, trade and foreign capital follows could have hurt domestic investors and dampened uncompetitive domestic markets. Similarly, we find the negative impact of foreign aid on GDP growth, while considering time-specific effects (see columns IV, Table 2). Given the weak institutional and corrupt political and governance structure, most of the received foreign aid in the region is often misappropriated, diverted and underutilized for their original purposes except for economies such as Bhutan and Maldives. Our empirical specifications show that every 1 per cent increase in foreign aid leads to 3.6 per cent increase in GDP growth when time and country specific effects are considered. The positive coefficients of domestic financial assistance to annual GDP growth rate indicate that improvements in domestic investment cycle also leads to higher economic growth. We find no significant association between growth and trade openness in the region (see columns I–IV, Table 2). This does indicate that trade liberalization has not bolstered growth for most of the SEA and SA economies except for Singapore, India, Vietnam, Maldives and Malaysia. While most of the economies in the region have joined WTO after 1995, but from our regression results it can be observed that joining WTO has been negatively impacted on GDP growth. Except few economies such as, India, Singapore, Maldives and Malaysia, the rest of the economies have not been able to reap the benefits of trade liberalization due to lack of institutional reforms, corruption, infrastructures bottlenecks, civil war and the absence of well-developed financial market.

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Table 3.

System GMM Analysis at Regional Perspective 1

FDI	I	II	III
FDI (−1)	0.632* (0.059)	0.736* (0.029)	0.724* (0.018)
gGDP	2.809* (1.320)	−0.166 (0.157)	0.050 (0.051)
AID	1.322 (1.301)	−1.677* (0.656)	−1.653* (0.425)
FD	−1.270 (1.091)	1.537* (0.478)	0.455 (0.452)
TROP	−0.235* (0.053)	−0.196* (0.057)
WTO Dummy	1.706(1.481)		0.297(0.270)
Constant	−2.554*(1.967)	0.822(0.820)	0.237(0.229)
Region	SEA & SA	SEA & SA	SEA & SA
No. of instruments	64	63	63
No. of observations	665	665	665
Sargan p-value	0.999	0.998	0.994
AR (1) test p-value	0.135	0.058	0.082
AR (2) test p-value	0.383	0.449	0.412

Source: World Development Indicators, World Bank and WTO.

Notes: All variables are converted into natural logarithm. p-values are reported in parentheses under the values of coefficients. * denotes level of significance.

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Table 4.

System GMM Analysis at Regional Perspective-2

gGDP	I	II	III	IV
gGDP (−1)	1.044*(0.083)	0.982*(0.058)	1.022*(0.075)	0.946*(0.069)
gGDP (−2)				0.008***(0.005)
FDI	0.010*(0.003)	0.004*(0.001)	0.005**(0.002)	0.006**(0.003)
AID	−0.097**(0.058)	−0.106*(0.046)	−0.135*(0.061)	−0.079**(0.046)
FD	0.118**(0.060)	0.058**(0.030)	0.053(0.052)	0.059***(0.036)
TROP	−0.003***(0.002)	−0.004*(0.001)		−0.003*(0.001)
WTO dummy	−0.118***(0.072)		−0.058(0.056)	−0.019(0.013)
Constant	−0.362(0.363)	0.224(0.208)	−0.101(0.100)	0.611(0.604)
Region	SEA & SA	SEA & SA	SEA & SA	SEA & SA
No. of observations	665	665	665	665
Sargan p-value	0.991	0.981	0.983	0.974
AR (1) test p-value	0.016	0.011	0.014	0.017
AR (2) test p-value	0.566	0.673	0.752	0.286

Source: World Development Indicators, World Bank and WTO.

Notes: All variables are converted into natural logarithm. p-values are reported in parentheses under the values of coefficients. *, ** and *** denote the estimates significantly different from 0 at 1%, 5% and 10% levels of significance respectively.

Conclusion

We examine the relationship among foreign aid, FDI and economic growth in SEA and SA countries during the 1980s to 2015. Our empirical results from alternate empirical estimations suggest that FDI flows positively impact economic growth in the region. However, GDP growth attracts FDI only when entire SEA and SA region as a whole is considered; underlying the importance of trade integration to benefit from foreign capital. In this regard, our findings also suggest that being a member of WTO have shown a mixed impact on FDI and economic growth in the region. This clearly indicates that mere compliance of WTO norms might not work well for most of these economies due to their macroeconomic constraints and structural bottlenecks.

We find that foreign aid flows have contemporaneous negative relation with FDI flows as well as with economic growth indicating the negative impact of excessive dependence on foreign aid on FDI in the long run. The economies such as, Afghanistan, Pakistan, Thailand, Malaysia, Philippines and PDR have experienced substantial decline in capital flows despite receiving significant amount of foreign aid. Foreign aid may increase the ability of budget finances and in turn that may enable governments to allocate funds to finance physical capital and channel direct transfers to the productive sectors; thus foreign aid may end up in crowding out FDI flows. However, our empirical results also show that domestic financial assistance by government to private sector for investment significantly and positively affects FDI flows and growth. Therefore, it could be inferred that while low-income countries of the SEA and SA relied on foreign aid flows for economic growth, but they have not efficiently utilized aid flows for building human and physical capital. An increased reliance on foreign aid assistance but having potentially declining marginal returns of aid flows may have resulted in sustained lower economic growth. Subsequently, this may have indirectly and negatively had an impact on foreign capital flows.

The overall key findings of our empirical analysis is that developing economies of SEA and SA region need to channel funds to domestic private sector and invest in human and physical capital, stabilize their macroeconomic conditions, pursue greater degree of trade integration and increase the utilization efficiency of foreign aid flows in order to attract, absorb and reap the benefits of complementing FDI flows and sustaining higher economic growth.