Home Country Determinants of Outward FDI from Developing Countries

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2013 7: 93Margin: The Journal of Applied Economic ResearchKhanindra Ch. Das

Home Country Determinants of Outward FDI from Developing Countries

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Margin—The Journal of Applied Economic Research 7 : 1 (2013): 93–116SAGE Publications Los Angeles/London/New Delhi/Singapore/Washington DC

DOI: 10.1177/0973801012466104

Home Country Determinants of Outward FDI from Developing Countries

Khanindra Ch. Das

This article examines various home country determinants of outward FDI from develop-ing economies, which have received limited attention in empirical studies. The role of home country determinants is investigated for a large sample of developing economies, as against a handful of developing economies, for the most recent period, 1996–2010, using a panel data econometric framework. The results indicate that source country’s level of economic development, globalisation, political risk and science and technology investments contribute significantly to outward FDI from developing countries. While outward FDI might be unavoidable in the course of economic development and globalisa-tion, developing countries need to emphasise improving political governance in order to prevent capital outflow arising out of high domestic political risk. On the flip side, science and technology investments could contribute to higher outward FDI, thereby yielding complementary benefits of internationalisation in the long-run. Thus, given the evolving role of developing countries in the global economic scenario, a balance between domestic and international investments is crucial for them to harness the benefits of globalisation, which can be achieved through suitable governance and policy reforms in specific fields.

Keywords: Outward FDI, Developing Countries, Macroeconomic Factors, Research and Development JEL Classification: F21, O24, O38

1. IntroductIon

Globalisation has been characterised by significant growth in the volume of trade and foreign direct investment (FDI) across countries. Under the rubric

Khanindra Ch. Das is Doctoral Scholar, Institute for Financial Management and Research (IFMR) 24 Kothari Road, Nungambakkam, Chennai 600034, India, email: [email protected]

Acknowledgements: I would like to thank Rajeswari Sengupta, Nilanjan Banik and an anonymous referee for the useful comments and suggestions on earlier versions of this article. The usual disclaimer applies.



94 Margin—The Journal of Applied Economic Research 7 : 1 (2013): 93–116

of outward-looking and export-oriented policy, many developing countries have emerged as a source of FDI in recent times. While inward FDI is a key source of capital in capital-scarce developing countries, the rapid growth in many such economies in the last decade has been accompanied by a surge in outward FDI.

The increase in outward FDI from developing countries is noteworthy. There has been a big leap in outward FDI from developing countries since the early-2000s. Outward FDI flows from developing countries have increased from $55.23 billion in 1995 to $134.19 billion in 2000 and to $327.56 billion in 2010 (see Figure 1). Further, outward FDI stock as a percentage of gross domestic product (GDP) has also risen from 5.8 per cent in 1995 to 12.7 per cent in 2000 and 15.7 per cent in 2010.

The relative position of developing countries as a source of FDI has improved substantially. In 1990, the share of developing countries in world FDI outflows was a meagre 4.93 per cent. It increased to 15.22 per cent in 1995 and reached 24.75 per cent in 2010. The share of developed countries on the other hand, has declined from 95.07 per cent in 1990 to 88.85 per cent in 2000 and finally to 70.67 per cent in 2010. Developing countries (including south-east Europe and the Commonwealth of Independent States (CIS)) accounted for 29.33 per cent of total outward FDI flows in 2010 (see Figure 2). Although the increase in the share of developing countries in the recent years of the global financial crisis can be attributed partly to a fall in outflows from developed countries, such an increase has been steady throughout even during the pre-crisis period.

Figure 1 Developing Country FDI Flows, 1995–2010

0

100

200

300

400

500

600

700

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

$ bi

llion Outward

Inward

Source: Author’s compilation from UNCTAD, World Investment Report, 2011.



Margin—The Journal of Applied Economic Research 7 : 1 (2013): 93–116

Das DETERMINANTS OF OUTWARD FDI 95

The rise of developing countries in the arena of global FDI calls for a detailed understanding of the determinants thereof.

Not only has there been an increase in the number of transnational corporations (TNCs) from many developing countries but they have also grown in size. Many TNCs from developing countries appear in the world’s top 100 non-financial TNCs, ranked by foreign asset-holdings. Developing country TNCs, both state-owned and private, have also been successful in striking multi-billion dollar deals globally in recent times. For instance, of the total of 152 merger and acquisition (M&A) deals worth over $1 billion and above in 2010 by both developed and developing country firms, more than 30 deals were by developing country TNCs. (The details of such M&A deals by developing countries are reported in the Appendix Table A1.) It is clear that TNCs from India, Hong Kong, China, Russia, Brazil, Korea, Malaysia, Qatar, Singapore, Colombia, Thailand and Mexico have successfully completed a number of multi-billion dollar deals outside their home economies, thereby spurring overall outward FDI from developing countries. Investments are in various sectors including energy and natural resources, telecommunication, motor vehicles, services, etc. Furthermore, a considerable amount of such investments are targeted towards developed countries such as US, UK, Canada, etc.

The increase in outward FDI from developing countries raises a host of issues with regard to the determinants, particularly the home country determinants that propel the outward FDI. The literature on the determinants of FDI

Figure 2 Share in World FDI Outflows, 1990–2010

0%10%20%30%40%50%60%70%80%90%

100%

1990 1995 2000 2005 2006 2007 2008 2009 2010

Developed Economies Developing Economies South-East Europe and CIS

Source: Author’s compilation from UNCTAD, World Investment Report, 2011.




flows, both inward and outward, that involves emerging countries has dealt with various macroeconomic, institutional and firm-specific characteristics pertaining to the home and host countries (Buckley et al., 2007; di Giovanni, 2005; Dunning, 1981a; Frenkel et al., 2004; Globerman and Shapiro, 2002; Hattari and Rajan, 2010; Kyrkilis and Pantelidis, 2003; Nayyar, 2008; Song et al., 2011; Wang et al., 2012).

The increase in outward FDI from developing countries has grabbed attention in recent academic discussions. However, the empirical literature on outward FDI from developing countries has remained fairly thin and limited to the examination of the outward FDI experience of a handful of developing countries. Existing studies on the subject have specifically tried to model the outward FDI experience of individual countries or a few countries together (Athukorala, 2009; Buckley et al., 2007; Goh and Wong, 2011; Hattari and Rajan, 2010; Kalotay and Sulstarova, 2010; Kolstad and Wiig, 2012; Kumar, 2007, 2008; Mlachila and Takebe, 2011; Wang et al., 2012; Wee, 2007). Most of the studies focus on host country determinants (Buckley et al., 2007; Kolstad and Wiig, 2012) with limited attention being given to source country determinants. Further, the studies that examine the source country determinants of outward FDI from developing countries are confined to individual country-specific experiences (Goh and Wong, 2011; Wang et al., 2012). Thus the effects of home country characteristics on outward FDI for a large sample of developing countries are not clear from the existing empirical literature.

The article contributes to the literature by examining several home country determinants of aggregate outward FDI for a large sample of developing countries for the period 1996–2010. The article is based on country-level panel data, given the paucity of studies that investigate outward investment of developing countries in a panel-data econometric framework. In particular, it explores the effects of the level of economic development, globalisation, political governance, science and technology investment and currency strength. The examination of home country factors also provide important policy insights since governments and policymakers can influence only domestic factors driving outward FDI, not the host country ones.

The article finds that source country levels of economic development, openness, political governance and science and technology investment play a crucial role in spurring outward FDI from developing countries. In particular, higher GDP per capita, trade openness, political risk and investment in science and technology result in higher outward FDI. The result is robust to alternative methods of normalising outward FDI.





The results, supporting an institution escapism view, emphasise the need to improve political governance in developing countries so as to prevent outflows of capital due to higher domestic political risk. On the other hand, investments in science and technology could contribute to internationalisation through the outward FDI route, which is likely to yield complementary benefits in the long-run. Given the evolving role of developing countries in international investments, the results highlight the role of governance and policy reform in specific areas, which can strike a balance between domestic and international investments.

The rest of the article is organised as follows. The theoretical motivation and hypotheses to be tested are given in Section 2. Section 3 describes the methodology and data sources used in the article. The econometric results are discussed in Section 4. Conclusions are given in Section 5.

2. theoretIcal Framework and hypothesIs development

The dominant theoretical foundation in the area of outward FDI has been the investment development path (IDP) propounded by Dunning (1981a, 1981b), which relates the dynamics of foreign investment with a country’s stages of economic development.1 According to IDP, countries go through five stages of investment development. The first four stages of an IDP include pre-industrialisation in which no inbound and outbound investment takes place followed by attracting inward investment in resource-based and labour-intensive sectors. This investment continues to grow and expand to various sectors of the economy, changing foreign firms’ attractiveness for the domestic market due to an increase in the costs of labour and resources that makes it possible for domestic firms to develop ownership advantage and start investing abroad, engaging in outbound direct investment that tends to surpass inbound investment by foreign firms, respectively. The final stage of the IDP occurs when there is a fluctuating balance between outward and inward direct investment. The basic hypothesis of the IDP is that as a country develops, the configurations of advantages facing foreign-owned firms that might invest in that country and that of its own firms that might invest overseas, undergo changes (Dunning, 2001).

There is a burgeoning literature that tests the IDP hypothesis (see Boudier-Bensebaa, 2008; Verma and Brennan, 2011 and the references therein) and

1 The other theories in connection with outward FDI of developing countries include the Uppsala school, latecomer theory, country specific theory etc.; see Hansen (2010) for a discussion.




several criticisms have been raised against the basic hypothesis. The basic IDP hypothesis makes outward FDI dependent solely on a country’s level of economic development, measured by GDP per capita and hence restrictive in nature as it takes for granted that underlying economic forces work in a certain fashion. Straightforward regressions of outward FDI on GDP per capita constitute a potentially naive view of the development process (Liu et al., 2005). According to the critics, while a common sense interpretation of GDP per capita and outward FDI relations has some appeal, it cannot successfully explain the internationalisation of all countries. Further, every country is not likely to pass through the stages of investment development as hypothesised (Erdilek, 2003; Hansen, 2010; Verma and Brennan, 2011). Bellak (2001) emphasised that the IDP model is not a normative approach, stating that the realised path of a particular country should reflect the stylised path. He also states that in many cases, countries’ IDPs do not follow the stylised path and are idiosyncratic to a large extent.

Several modifications to IDP have been proposed in order to explain emerging countries’ outward FDI. These refinements are intended to account for emerging phenomena such as trade, institutions, technology and other macroeconomic variables (Bellak, 2001; Dunning et al., 2001; Durán and Ubeda, 2001; Liu et al., 2005; Wang et al., 2012; Witt and Lewin, 2007). Dunning et al. (2001) presents a refinement of the IDP hypothesis to incorporate trade into IDP, involving types of products and industry. One of the refinements is that both inward and outward direct investment flows in average or above-average FDI-intensive sectors will be positively correlated with their counterparts in trade. However, the basic premise of the refinement remains the same, i.e. GDP per capita determines the level of outward FDI.

Furthermore, institutional factors have been emphasised in recent literature (Boisot and Meyer, 2008; Erdilek, 2003; Le and Zak, 2006; Luo et al., 2010; Wang et al., 2012; Witt and Lewin, 2007; Wright et al., 2005). According to an institution-based view, a firm’s internationalisation is facilitated or constrained by a multitude of institutional forces including elements that promote and hinder upgrading of existing resources and capabilities (Wang et al., 2012). The institution escapism view suggests that poor institutional factors in the home country, such as regional protectionism, quota allocations, high tax rates, corruption, regulatory uncertainty, insufficient protection of intellectual property rights and governmental interference, may push firms to invest abroad in pursuit of more efficient institutions (Luo et al., 2010). Recognising the importance of institutions, Dunning and Lundan (2008) examine how an institutional dimension can be incorporated into the IDP paradigm. Durán and Ubeda (2001) suggest the inclusion of a greater number of structural





and idiosyncratic variables in the analysis. These include indicators such as technology, research and development expenditure, etc., intended to measure the degree of evolution of a country in the process of structural change. In addition, many other source country macroeconomic factors such as exchange rate and interest rate have been considered prominent in explaining outward FDI (Kimino et al., 2007).

These refinements are expected to throw light on the underlying mechanism of the IDP of developing countries. Empirical research on this front is scarce but promising. For instance, Liu et al. (2005) examined whether China’s outward FDI follows the standard pattern and sequence of IDP hypothesis (Dunning, 1981b) or a refined version. The results are quite consistent with the refined IDP hypothesis, which incorporates factors such as investments in human capital, exports and inward FDI besides the conventional variable, the GDP per capita. Therefore, extension of the basic IDP merits attention by incorporating additional explanatory variables as suggested by various authors in the literature.

This article is embedded within the ongoing debate in the theoretical literature on the determinants of outward FDI. Outward FDI from developing countries requires investigation in a generalised IDP framework that incorporates multiple factors, which in turn can provide important policy implications. Further, from the policy perspective, the identification of factors contributing to outward FDI would be more useful than identifying the stages of IDP of each country. Therefore, there is a need to extend the basic IDP theory to account for other relevant factors.

Combining the basic IDP with additional variables, outward FDI is taken to be a function of the following variables:

Outward FDI = f (GDPPC, TOPEN, POLRISK, RDGDP, REER)

Where GDPPC denotes GDP per capita, TOPEN refers to trade openness, POLRISK stands as a proxy for institutional and political factors, RDGDP represents technological factors and REER is another macroeconomic factor, namely the real effective exchange rate. The remainder of this section analyses the hypotheses that are being tested in this article.

2.1 Level of Economic Development

The first hypothesis to be tested is drawn from the IDP literature, i.e. the level of economic development contributes positively towards outward FDI, even though the net outward investment position might change at various stages. Macroeconomic factors such as the level of economic development contribute




to the ease and rapid expansion of internationalisation. The evolution of FDI in connection with developing countries (first inward and later, outward) can be viewed as a dynamic paradigm (Ozawa, 1992). The direction of FDI, both inward and outward, changes with the structural transformation of the economy. The initial condition attracts inward FDI in standard, labour-intensive manufacturing activities. With rapid expansion of the modern sector, factor endowment in the country begins to shift from low-skilled labour to relatively more physical and human capital abundance, paving the way for investment-driven industrialisation. The shift in factor abundance prompts firms to transplant their existing operations to other countries where they can produce cheaper. Outward FDI could take place to exploit various firm-specific and country-specific advantages.

Hypothesis 1: Outward FDI is positively associated with the level of economic development.

2.2 Trade Openness

The openness of a country is expected to positively influence outward FDI. Evidence suggests that an expansion of trade activities enables domestic firms to acquire knowledge about foreign markets and skills related to organising foreign operations and marketing their products internationally and hence, have the ability to establish operations abroad (see Buckley et al., 2007; Goh and Wong, 2011; Kyrkilis and Pantelidis, 2003). A higher degree of trade openness provides more exposure to foreign markets. It gives scope for the exporting firm to serve such a market by locating in the foreign markets due to cost advantage. Similarly, firms may choose to locate in the source countries of import to combat import competition. Further, importing firms can break up their production process, giving them the scope for outward FDI for the processing and intermediate stages of production. Banga (2007) suggests that trade can have two potential effects on outward FDI from developing countries, i.e. higher exports may assure existing markets and therefore lower the risks attached to such investments and higher imports into the country may have a displacement effect on investment, which may look outward into economies with lower manufacturing cost and higher access to larger markets.

Hypothesis 2: Outward FDI is positively associated with degree of trade openness.

2.3 Political Risk

Institutional and political factors have received increasing attention in research in development economics since Barro (1991) explained economic growth in a cross-section of countries using measures of political stability, among others.





According to Adam and Dercon (2009), research on economic development has thus become increasingly engaged with questions of political economy and in particular, with how political choices, institutional structures and forms of governance influence economic choices made by governments and citizens and how, in turn, these structures reflect deeper forces, such as the patterns of colonial settlement and conflict, physical geography and natural resource endowments, disease ecology of societies and ethnic diversity, as well as a host of other cultural factors.

In connection with outward FDI, the political risk of the home country contends to be an important determinant. Tallman (1988) finds that the investment activity of industrialised countries in the US is dependent on home country economic and political conditions. While examining the case of Mexico, Thomas and Grosse (2001) found that as political risk increases in the home country, firms are more likely to escape or diversify away from that political risk by investing abroad, including in Mexico. In the extreme scenario, political risk is also found to accelerate capital flight (Le and Zak, 2006).

Hypothesis 3: Higher political risk in the home country increases outward FDI.

2.4 Indigenous Innovation Efforts

Outward FDI can be affected by the technological achievements of a country. Although it may not always be possible for developing countries to come up with newly minted technology but the policies aimed at technological capacity building can produce spillover benefits.

It has been argued that technology diffusion and adoption depends on technological efforts (Lall, 2001) and absorptive capacity (Fu et al., 2011; Grima, 2005; Li, 2011; World Bank, 2008). The inappropriateness of Northern technology in developing countries calls for a greater effort to develop indigenous innovation for catching up. Fu et al. (2011) highlights that to benefit from international technology diffusion spurred by globalisation, developing countries need to exert parallel indigenous innovation efforts, i.e. ‘walking on two legs’, in assimilating and augmenting their technological learning and capacity building. Further, only in the presence of local innovation capacity will multinational enterprises (MNEs) adopt a more integrated innovation practice, which has greater linkage with the local economy and thereby enable greater opportunities for knowledge transfer (Franco et al., 2011). Without proactive indigenous innovation efforts, foreign technology remains static and does not turn into real technological capacity.

This suggests that developing countries that exert greater effort in technological innovation are likely to benefit from international technological diffusion,




augmenting the country-specific advantages, which could help a greater level of internationalisation through outward investment. The evidence of technological capacity on outward FDI has been mixed. For instance, Tolentino (2008) finds that the national technological capacity of India Granger causes the level of outward FDI from India, but this is not true in the case of China. Nevertheless, it would be interesting to see if there is a positive effect at the cross-country level.

Hypothesis 4: Outward FDI is positively associated with home country’s technological efforts.

2.5 Currency Strength

Increase in currency strength tends to favour outward investment, as a strong currency can buy more in real terms. The appreciation of home country currency lowers the capital requirements of foreign investments in domestic currency units, making it easier to raise capital than in the case of a depreciating currency. Besides, home currency appreciation reduces the nominal competitiveness of exports, increasing that way the motive for choosing FDI as a mode of serving foreign markets (Kyrkilis and Pantelidis, 2003). Direct investment outflow is also found to have a cointegrating relationship with the real exchange rate of industrialised countries (Choi and Jeon, 2007). However, according to Kyrkilis and Pantelidis (2003), if currency depreciation compensates for deteriorating productivity and labour costs, export-oriented FDI may be used as a long-term effective measure for securing market shares abroad. This type of FDI is directed towards countries with a more favourable cost structure, mainly other developing countries.

Hypothesis 5: An appreciation of real effective exchange rate increases outward FDI.

In the following section the econometric model, along with variable definition and data sources, is provided for testing the above hypotheses.

3. methodology and data

We use annual data for a sample of 56 developing economies (listed in Appendix) to understand the home country determinants of outward FDI. The analysis covers the time period from 1996 to 2010, chosen primarily on the basis of data availability. The sample accounts for more than 78 per cent of FDI outflows from developing countries during this period. The outward FDI is investigated using the following baseline regression model:

OFDIGDPit = α + β

1 GDPPC

it + β

2 TOPEN

it + β

3 POLRISK

it +

β4 RDGDP

it + β

5 REER

it + u

it





Where i denotes economy, and t denotes time. The dependent variable (OFDIGDP) is FDI outflows normalised by GDP of economy i at time t, which also facilitates comparison of economies of varying sizes. It is constructed using data from the World Investment Report (2011) and World Development Indicators (WDI). The empirical specification assumes a linear form. In the panel estimation, the explanatory variables are introduced sequentially in order to judge their explanatory power.

The explanatory variables, pertaining to the home country include:

• macroeconomic factors such as the level of development captured by the GDP per capita (GDPPC)

• globalisation captured by trade openness measured by exports and imports of goods and services as a percentage of GDP (TOPEN)

• political governance represented by a political risk index (POLRISK) • science and technology investments, a proxy for indigenous innovation

efforts, captured by research and development (R&D) expenditure as percentage of GDP (RDGDP), and

• currency strength denoted by real effective exchange rate (REER) index.

The political risk index is based on several institutional parameters namely: government stability, socioeconomic conditions, investment profile, internal conflict, external conflict, corruption, military in politics, religious tensions, law and order, ethnic tensions, democratic accountability and bureaucratic quality.2 The REER index of home currency with respect to a basket of foreign currency is used as a measure of currency strength.3 Data on GDPPC, TOPEN and RDGDP are obtained from World Development Indicators. POLRISK is sourced from International Country Risk Guide, and REER from International Financial Statistics.4

In the empirical estimation, as hypothesised above, the expected signs of the coefficients of GDPPC, TOPEN, RDGDP and REER are positive. The sign of POLRISK will be negative in the empirical estimation in order to support the

2 The political risk index lies between 0–100, 0 implying higher political risk. 3 An increase in the index reflects an appreciation of the currency in real terms; appreciation of home currency is postulated to have a positive effect on outward FDI. 4 It is to be noted that data availability on POLRISK and RDGDP restricts the sample period, i.e. 1996 to 2007 in the case of Model 3 and Model 4 in the empirical estimation, whereas the sample period for first two models are 1996 to 2010. Further, data on REER is available for fewer than half the countries in the sample. Although REER data is available for the entire period, in order to avoid a loss of country information, the model including REER (Model 5) is also estimated for the period 1996–2007.




hypothesis stated above. This is because of the way POLRISK is measured, i.e. a lower value of the index represents higher political risk at home. All the variables are normalised, which is required for comparison across countries given their heterogeneity. In order to deal with endogeneity, the independent variables are lagged by a year in the estimation. Further, it is unrealistic to assume that the drivers of outward FDI are the same across all developing countries—the panel estimation helps to overcome this limitation as it allows for country and time effects.

We also augment the specification by including region dummies in all the models. (Classification of the countries by regions is explained in the Appendix.) The region dummies are: for Africa (DAF), for Latin America and Caribbean (DLAC), for West Asia (DWA), for South, East and South-East Asia (DSESEA), and the dummy for the transition economies of southeast Europe and CIS is the excluded category. The regional dummies can be significant because of the presence of regional trade and investment agreements and other factors that can influence FDI outflows at the regional level.5

4. estImatIon results and dIscussIon

Descriptive statistics and the correlation matrix of the variables used for estimation are presented in the appendix (Tables A2 and A3). The results of the random effects panel regressions based on the baseline model are presented in Table 1, where the explanatory variables are introduced sequentially. The Breusch and Pagan Lagrangian multiplier (LM) test (Breusch and Pagan, 1980) and Hausman test (Hausman, 1978) indicate the appropriateness of the random effects generalised least-square results compared to pool OLS and fixed effects respectively.6

The baseline estimation in Table 1 shows that GDP per capita, trade openness, political risk and research and development expenditure are statistically significant at conventional levels with expected signs. In particular, outward FDI rises with GDPPC, TOPEN, POLRISK and RDGDP. Therefore, the source country’s level of economic development, globalisation, political risk and

5 The regional contribution to total FDI outflows from developing countries reveals that Asian countries have been the dominant players (81.03 per cent in 1995 and 74.67 per cent in 2010) followed by Latin America and the Caribbean (13.61 per cent in 1990 and 23.28 per cent in 2010). The share of Africa is rather meager. In particular, the special role of south, east and south-east Asian countries is worth mentioning. In 1995, 82.13 per cent and in 2010, 70.70 per cent of FDI outflows from developing countries were from the south, east and south-east Asian countries. 6 The appropriateness of random effects is ambiguous in the case of model 5. Nevertheless, random effects are used across all models, as the number of cross-section units is larger than the number of years in the sample.





investments in research and development result in higher outward FDI.7 The estimated parameters are higher for RDGDP followed by POLRISK, TOPEN and GDPPC. These estimates are statistically significant and economically meaningful. However, the real effective exchange rate does not yield a statistically significant coefficient.8 The explanatory power has improved consistently from model 1 to model 5 in Table 1, justifying the inclusion of each of the additional variables in a sequential manner. Overall, the five explanatory variables included in the estimation explain 67.58 per cent of the variation in the outward FDI of the sample countries. The results also show that the region dummies are significant in a few cases, i.e. with positive coefficients for Latin America and Caribbean, and south, east and south-east Asia.

These findings suggest that outward FDI is encouraged by the economic development and globalisation of developing countries. For example, the variable capturing the level of development of the home country (GDPPC) is positive and highly significant. Therefore, the level of development seems to matter for internationalisation in our estimation.9 Further, a 1 percentage point increase in TOPEN results in a 0.0125 percentage point increase in outward FDI from developing countries relative to their GDP (Model 5, Table 1). The positive effect of trade openness is found to support previous studies (Buckley et al., 2007; Goh and Wong, 2011; Kyrkilis and Pantelidis, 2003). This suggests that in the long-run, outward-oriented policies are crucial for the promotion of trade openness which in turn could facilitate outward investment.

The results of political risk is in accordance with the institution escapism view, and supports the findings of Thomas and Grosse (2001) and Le and Zak (2006) in which, as political risk increases in the home country, firms are more likely to escape from that political risk by investing abroad. The significance of political risk implies that developing countries need to place greater emphasis on reducing political instability by improving governance standards so as to prevent capital outflows arising out of higher domestic political risk. Interestingly,

7 We also performed a number of iterations by including additional variables such as value-added in the service sector, foreign exchange reserves, domestic credit to private sector, capital account openness, the interest rate and secondary enrollment, but none of these were found to have sta-tistically significant explanatory power.8 Note that RDGDP, which was insignificant in model 4, turns significant with the inclusion of REER. We calculate the correlation between the two variables to check if there can be any serious multicollinearity. It is found that correlation between the two variables is low (-0.101) though negative (Table A3). Therefore, multicollinearity is less likely to be the case. Also, this is not a case in where a significant variable turns insignificant with the inclusion of an additional variable, as in the case of serious multicollinearity. 9 This is in line with the predictions of basic IDP theory in which there is a positive effect of GDPPC on outward FDI in the early stages of IDP.



Tabl

e 1

Ran

dom

Eff

ects

Mod

el, 1

996–

2010

Dep

ende

nt V

aria

ble:

ou

twar

d FD

I p

er c

ent

of G

DP

Mod

el 1

Mod

el 2

Mod

el 3

Mod

el 4

M

odel

5

GD

P p

er c

apit

a 0.

0001

6∗∗∗

0.00

014∗∗∗

0.00

024∗∗∗

0.00

026∗∗∗

0.00

02∗∗∗

(0.0

0005

)(0

.000

05)

(0.0

0009

)(0

.000

10)

(0.0

0007

)Tr

ade

open

nes

s 0.

0307∗∗∗

0.03

39∗∗∗

0.03

56∗∗∗

0.01

25∗∗∗

(0.0

090)

(0.0

091)

(0.0

087)

(0.0

039)

Polit

ical

ris

k (I

nde

x)

–0.0

614∗

–0.0

970∗∗

–0.0

393∗∗

(0.0

354)

(0.0

428)

(0.0

180)

R&

D e

xpen

ditu

re

–0.1

669

1.17

45∗∗∗

(0.6

604)

(0.4

228)

RE

ER

(In

dex)

–0

.008

0(0

.007

7)C

onst

ant

0.22

98–2

.678

3∗∗∗

1.01

123.

1061

0.99

96(0

.588

6)(0

.897

2)(2

.559

3)(3

.051

7)(1

.443

4)D

AF

–0.3

816

–0.2

796

0.57

200.

7210

0.51

87(0

.579

6)(0

.537

4)(0

.806

4)(0

.736

3)(0

.319

7)D

LAC

0.30

581.

0997

1.10

171.

4194

0.90

96∗∗

(0.7

589)

(0.7

000)

(0.9

055)

(0.9

574)

(0.3

974)

DW

A–1

.516

6–1

.048

8–1

.872

7–2

.331

1–1

.373

1(1

.455

0)(1

.248

5)(1

.297

8)(1

.604

8)(0

.890

7)D

SESE

A0.

9376

–0.1

034

–0.4

547

–0.3

726

0.69

46∗∗∗

(0.9

591)

(0.6

963)

(0.8

014)

(0.7

275)

(0.2

472)

Tim

e du

mm

y Ye

sYe

sYe

sYe

sYe

sN

um

ber

of o

bser

vati

ons

777

732

487

338

173

Nu

mbe

r of

cou

ntr

ies

5655

4747

24R

2 ove

rall

0.21

490.

3913

0.42

13

0.44

610.

6758

F37

.79∗∗∗

48.4

8∗∗∗

54.8

8∗∗∗

69.2

2∗∗∗

134.

23∗∗∗

LM te

st

1518

.93∗∗∗

841.

92∗∗∗

280.

06∗∗∗

193.

81∗∗∗

0.00

Hau

sman

test

0.

893.

62

6.45

0.07

2.54

Sou

rce:

Au

thor

’s c

alcu

lati

ons.

Not

es: F

igu

res

in t

he

pare

nth

esis

rep

rese

nt

robu

st s

tan

dard

err

ors;

∗p<

0.10

; ∗∗p

<0.

05; ∗∗∗

p<0.

01.





the RDGDP has a positive effect on aggregate outward FDI supporting the hypothesis of a positive effect of indigenous innovation efforts. The result is in accordance with Tolentino (2008), in which the national technological capacity of India Granger causes the level of outward FDI from India. The positive effect is expected, as higher R&D effort enables developing countries to develop technological capacity which in turn can be explored by domestic firms investing abroad.

4.1 Robustness Check

Additional robustness checks are also performed by normalising outward FDI with gross fixed capital formation (OFDIGFCF).10 This helps to assess FDI outflows in relation to domestic capital formation, which gives important implications about whether outward FDI substitutes domestic investments and the contributory factors. The robustness check results are reported in this sub-section in order to validate the above findings.

The results of the random effects are reported in Table 2. The results are largely in consonance with the baseline regressions presented in Table 1. The only difference is the significance of REER with an opposite sign (Model 5, Table 2), but only at the 10 per cent level. This kind of effect could arise if the relative disadvantage of currency depreciation is compensated by factor cost advantages associated with outward investments. Kyrkilis and Pantelidis (2003) have also found mixed results of the effects of the REER on outward FDI. Furthermore, there could be strategic investments, which are undertaken despite adverse currency movements or due to deterioration of domestic investment climate. Overall, the robustness check validates the baseline findings.

5. conclusIons

The article examines various home country determinants of outward FDI for a large sample of developing countries between 1996 and 2010. Over the last decade, developing countries have been actively investing abroad, in order to become part of the global supply chain and remain competitive. Outward investment might be unavoidable as an economy progresses and experiences structural transformation. Further, the expansion of trade would promote outward FDI as it enables domestic firms to acquire knowledge about foreign markets and learn the skills of organising foreign operations and marketing their products internationally. The empirical finding of this article suggests that the home country’s level of economic development, globalisation, political

10 Data on FDI outflows as percentage of gross fixed capital formation is obtained from UNCTAD, World Investment Report (2011).



Tabl

e 2

Ran

dom

Eff

ects

Mod

el, 1

996–

2010

Dep

ende

nt V

aria

ble:

Ou

twar

d FD

I Pe

r ce

nt

of G

ross

Fix

ed C

apit

al F

orm

atio

n

Mod

el 1

Mod

el 2

Mod

el 3

Mod

el 4

M

odel

5

GD

P p

er c

apit

a 0.

0009∗∗∗

0.00

07∗∗∗

0.00

12∗∗∗

0.00

13∗∗∗

0.00

07∗∗∗

(0.0

003)

(0.0

002)

(0.0

004)

(0.0

004)

(0.0

003)

Trad

e op

enn

ess

0.13

84∗∗∗

0.15

49∗∗∗

0.16

00∗∗∗

0.05

18∗∗∗

(0.0

404)

(0.0

473)

(0.0

448)

(0.0

167)

Polit

ical

ris

k (I

nde

x)

–0.2

544

–0.4

347∗∗

–0.1

772∗∗

(0.1

606)

(0.2

012)

(0.0

834)

R&

D e

xpen

ditu

re

–0.2

891

5.68

69∗∗∗

(2.9

119)

(1.8

336)

RE

ER

(In

dex)

–0

.064

8∗(0

.035

5)C

onst

ant

–1.1

578

–13.

1510∗∗∗

0.89

5511

.013

68.

4095

(2.4

348)

(4.1

186)

(12.

0646

)(1

4.34

33)

(6.3

453)

DA

F–1

.740

6–1

.334

13.

5674

4.44

352.

4202

(2.0

697)

(1.7

652)

(3.0

751)

(2.7

773)

(1.4

989)

DLA

C2.

4895

6.04

45∗∗

6.93

17∗

8.91

12∗∗

4.90

44∗∗∗

(3.6

087)

(2.9

845)

(4.1

568)

(4.2

832)

(1.7

935)

DW

A–7

.693

9–4

.844

1–8

.125

6–9

.484

6–4

.829

1(8

.190

4)(5

.943

9)(7

.213

8)(7

.866

3)(3

.750

5)D

SESE

A2.

3754

–1.5

907

–2.4

927

–1.8

861

2.45

62∗∗

(4.0

978)

(2.2

349)

(2.9

636)

(2.6

160)

(1.1

882)

Tim

e du

mm

y Ye

sYe

sYe

sYe

sYe

sN

um

ber

of o

bser

vati

ons

730

709

472

325

173

Nu

mbe

r of

cou

ntr

ies

5655

4747

24R

2 ove

rall

0.20

170.

3461

0.36

050.

3871

0.64

99F

40.7

9∗∗∗

51.0

1∗∗∗

50.0

9∗∗∗

61.2

8∗∗∗

101.

56∗∗∗

LM te

st

1309

.80∗∗∗

881.

36∗∗∗

359.

18∗∗∗

259.

09∗∗∗

1.01

Hau

sman

test

0.

051.

59

4.60

5.22

2.37

Sou

rce:

Au

thor

’s c

alcu

lati

ons.

Not

es: F

igu

res

in p

aren

thes

is r

epre

sen

t ro

bust

sta

nda

rd e

rror

s; ∗

p<0.

10, ∗∗p

<0.

05, ∗∗∗

p<0.

01.





risk and technological efforts are important determinants of such outward FDI from developing countries. However, the negative sign of political risk on outward FDI highlights the need for improving political governance to prevent investment outflows arising out of higher domestic political risk. At the same time, developing countries must also work towards enhancing their technological capacity through research and development.

Given the higher growth and structural transformation of many developing countries, we can expect further expansion of outward FDI as these countries aspire to become significant regional or global players. The findings of this analysis emphasise the factors that developing countries need to focus on, in order to keep increasing the share of outward FDI in their portfolio of investments. Thus, this analysis has pertinent policy implications as well. In particular, developing countries need to ensure that outward FDI is not at the expense of domestic investment. This can be achieved through suitable governance and policy changes in specific fields.

The results of the estimation should be treated with caution as it is based on aggregate FDI outflows and not on bilateral outward FDI flows (since suitable data on bilateral FDI outflows is available only for a few developing countries and years). Further research could be devoted to examining the relevance of these factors at the bilateral and firm levels (that extends beyond the case of an individual country) and also examine the role played by various domestic regulatory and institutional bottlenecks that might drive outward FDI from developing countries.

appendIx

List of Developing Economies in the Sample

Africa: Algeria, Botswana, Egypt, Mauritius, Morocco, Seychelles, South Africa, Tunisia;

Latin America and Caribbean: Argentina, Bolivia, Brazil, Chile, Colombia, Costa Rica, El Salvador, Guatemala, Jamaica, Mexico, Nicaragua, Panama, Paraguay, Peru, Trinidad and Tobago, Uruguay;

West Asia: Jordan, Kuwait, Saudi Arabia, Turkey;

South, East and South-east Asia: Brunei, China, Hong Kong, India, Indonesia, Korea, Macao, Malaysia, Mongolia, Pakistan, Philippines, Singapore, Sri Lanka, Thailand;

South-east Europe and CIS: Armenia, Azerbaijan, Belarus, Bosnia and Herzegovina, Croatia, Georgia, Kazakhstan, Kyrgyzstan, Montenegro, Moldova, Russian Federation, Serbia, TFYR Macedonia, Ukraine.

These economies are considered to be the developing (or transition) economies in the UNCTAD classification. The sample contains economies for which data were available during 1996–2010 but not necessarily for all the years.



Tabl

e A

1 C

ross

-Bor

der

M&

A D

eals

(by

Dev

elop

ing

Cou

ntr

ies)

Wor

th O

ver

US$

1 b

illi

on C

omp

lete

d in

201

0

Ult

imat

e H

ome

Eco

nom

yIn

dust

ry o

f the

Ult

imat

e A

cqui

ring

C

ompa

nyU

ltim

ate

Hos

t E

cono

my

Indu

stry

of t

he U

ltim

ate

Acq

uire

d C

ompa

nySh

ares

A

cqui

red

Val

ue

($ b

illio

n)R

ank

Indi

aTe

leph

one

com

mu

nic

atio

ns,

ex

cept

rad

iote

leph

one

Kuw

ait

Rad

iote

leph

one

com

mu

nic

atio

ns

100

10.7

2

Hon

g K

ong,

Ch

ina

Inve

stor

s, n

ecFr

ance

Ele

ctri

c se

rvic

es 10

09.

1 4

Ch

ina

Cru

de p

etro

leu

m a

nd

nat

ura

l gas

Spai

nPe

trol

eum

refi

nin

g 40

7.1

10R

uss

ian

Fe

dera

tion

Rad

iote

leph

one

com

mu

nic

atio

ns

Nor

way

Rad

iote

leph

one

com

mu

nic

atio

ns

100

5.5

13

Indi

aIn

vest

ors,

nec

Ven

ezu

ela

Cru

de p

etro

leu

m a

nd

nat

ura

l gas

40

4.8

16C

hin

aM

otor

veh

icle

s an

d pa

ssen

ger

car

bodi

esH

ong

Kon

g,

Ch

ina

Mot

or v

ehic

le p

arts

an

d ac

cess

orie

s 62

4.1

21

Bra

zil

Iron

ore

sU

nit

ed S

tate

sSo

ybea

n o

il m

ills

100

3.8

25C

hin

aC

rude

pet

role

um

an

d n

atu

ral g

asA

rgen

tin

aO

ffice

s of

hol

din

g co

mpa

nie

s, n

ec 5

03.

140

Indi

aB

usi

nes

s se

rvic

es, n

ecA

ust

ralia

Coa

l min

ing

serv

ices

100

2.7

45K

orea

, Rep

ubl

ic o

fN

atio

nal

gov

ern

men

tU

nit

ed

Kin

gdom

Cru

de p

etro

leu

m a

nd

nat

ura

l gas

100

2.6

46

Bra

zil

Iron

ore

sSw

itze

rlan

dO

ffice

s of

hol

din

g co

mpa

nie

s, n

ec 5

12.

549

Mal

aysi

aN

atio

nal

gov

ern

men

tSi

nga

pore

Gen

eral

med

ical

an

d su

rgic

al h

ospi

tals

70

2.4

53K

orea

, Rep

ubl

ic o

fSh

ip b

uild

ing

and

repa

irin

gU

nit

ed A

rab

Em

irat

esN

atio

nal

gov

ern

men

t 7

02.

258

Qat

arN

atio

nal

gov

ern

men

tU

nit

ed

Kin

gdom

Men

’s an

d bo

ys’ c

loth

ing

and

acce

ssor

y st

ores

100

2.2

59

Sin

gapo

reLa

nd

subd

ivid

ers

and

deve

lop

ers,

ex

cept

cem

eter

ies

Hon

g K

ong,

C

hin

aTr

uck

ing,

exc

ept

loca

l 10

02.

261

Col

ombi

aIn

vest

ors,

nec

Can

ada

Cru

de p

etro

leu

m a

nd

nat

ura

l gas

66

2.2

62C

olom

bia

Ban

ksU

nit

ed S

tate

sPo

wer

, dis

trib

uti

on a

nd

spec

ialt

y tr

ansf

orm

ers

100

1.9

70



Sin

gapo

reO

ffice

s of

hol

din

g co

mpa

nie

s,

nec

Au

stra

liaC

oncr

ete

prod

uct

s, e

xcep

t bl

ock

and

bric

k

100

1.8

75

Ch

ina

Cru

de p

etro

leu

m a

nd

nat

ura

l gas

Can

ada

Cru

de p

etro

leu

m a

nd

nat

ura

l gas

601.

7 7

9In

dia

Rad

iote

leph

one

com

mu

nic

atio

ns

Mal

aysi

aIn

vest

ors,

nec

100

1.7

82

Ch

ina

Ele

ctri

c se

rvic

esB

razi

lPo

wer

, dis

trib

uti

on a

nd

spec

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y tr

ansf

orm

ers

75

1.7

83

Th

aila

nd

Bit

um

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s co

al a

nd

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ite

surf

ace

min

ing

Au

stra

liaB

itu

min

ous

coal

an

d lig

nit

e su

rfac

e m

inin

g 8

01.

6 8

7

Bra

zil

Stee

l wor

ks, b

last

furn

aces

an

d ro

llin

g m

ills

Bra

zil

Stee

l wor

ks, b

last

furn

aces

an

d ro

llin

g m

ills

34

1.6

88

Ch

ina

Nat

ion

al g

over

nm

ent

Un

ited

Sta

tes

Ele

ctri

c se

rvic

es 1

61.

6 9

1

Ch

ina

Mot

or v

ehic

les

and

pass

enge

r ca

r bo

dies

Swed

enM

otor

veh

icle

s an

d pa

ssen

ger

car

bodi

es 10

01.

5 9

9

Ch

ina

Cit

y ag

ency

Ch

ina

Mar

ine

carg

o h

and

ling

57

1.5

102

Sin

gap

ore

Ban

ksN

eth

erla

nds

Life

insu

ran

ce 10

01.

510

4B

razi

lO

ffice

s of

hol

din

g co

mpa

nie

s,

nec

Port

uga

lC

emen

t, hy

drau

lic 2

21.

311

1

Bra

zil

Sau

sage

s an

d ot

her

pre

pare

d m

eat

prod

uct

sU

nit

ed S

tate

sIn

vest

ors,

nec

100

1.3

125

Mex

ico

Tele

visi

on b

road

cast

ing

stat

ion

sU

nit

ed S

tate

sIn

vest

ors,

nec

35

1.2

129

Indi

aC

rude

pet

role

um

an

d n

atu

ral g

asU

nit

ed S

tate

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rude

pet

role

um

an

d n

atu

ral g

as 3

81.

113

4C

hin

aC

rude

pet

role

um

an

d n

atu

ral g

asU

nit

ed S

tate

sC

rude

pet

role

um

an

d n

atu

ral g

as 3

31.

114

0R

uss

ian

Fe

dera

tion

Com

mer

cial

phy

sica

l an

d bi

olog

ical

res

earc

hC

anad

aU

ran

ium

-rad

ium

-van

adiu

m o

res

37

1.1

144

Bra

zil

Iron

ore

sU

nit

ed S

tate

sSo

ybea

n o

il m

ills

20

1.0

146

Sou

rce:

Au

thor

’s c

ompi

lati

on fr

om U

NC

TAD

, Wor

ld I

nves

tmen

t Rep

ort,

2011

.



Tabl

e A

2 D

escr

ipti

ve S

tati

stic

s of

the

Var

iabl

es

OFD

IGD

PO

FDIG

FCF

GD

PP

CT

OP

EN

PO

LRIS

KR

DG

DP

RE

ER

1996

Mea

n1.

205.

6743

59.7

979

.97

67.0

80.

5411

4.70

SD(3

.56)

(16.

52)

(587

5.80

)(5

2.73

)(7

.93)

(0.5

0)(1

6.81

)19

97M

ean

1.01

4.12

4448

.30

82.0

569

.05

0.50

117.

65SD

(3.3

7)(1

5.17

)(6

032.

88)

(49.

61)

(8.2

5)(0

.47)

(16.

21)

1998

Mea

n0.

713.

0440

87.1

885

.61

67.6

70.

4811

4.59

SD(2

.96)

(13.

54)

(531

2.57

)(5

2.52

)(9

.71)

(0.4

7)(1

5.49

)19

99M

ean

0.82

3.73

4049

.83

85.8

165

.06

0.51

106.

10SD

(2.1

4)(8

.49)

(519

1.48

)(5

7.20

)(1

0.31

)(0

.48)

(16.

50)

2000

Mea

n0.

873.

7342

80.5

591

.51

64.5

70.

5110

6.00

SD(4

.94)

(20.

24)

(570

2.92

)(6

1.44

)(1

0.24

)(0

.48)

(13.

82)

2001

Mea

n0.

934.

1941

45.3

189

.63

67.0

30.

5110

5.48

SD(3

.29)

(13.

94)

(537

1.14

)(5

8.77

)(9

.82)

(0.5

1)(1

3.38

)20

02M

ean

0.92

5.35

4163

.67

91.9

465

.94

0.50

102.

40SD

(2.7

1)(1

8.41

)(5

415.

03)

(59.

89)

(8.9

6)(0

.50)

(12.

47)

2003

Mea

n0.

944.

2446

17.7

095

.21

66.4

10.

5296

.99

SD(4

.05)

(22.

71)

(580

1.88

)(6

5.68

)(8

.39)

(0.5

2)(9

.41)

2004

Mea

n1.

507.

4353

36.2

310

1.14

67.7

70.

5397

.63

SD(4

.54)

(21.

54)

(667

4.49

)(7

0.77

)(7

.74)

(0.5

4)(6

.16)

2005

Mea

n1.

316.

3861

82.1

210

2.37

67.9

90.

5310

0.00

SD(2

.94)

(14.

65)

(783

9.70

)(7

1.52

)(8

.21)

(0.5

7)(0

.00)

2006

Mea

n1.

698.

3870

75.7

210

4.24

67.9

20.

5910

3.16

SD(4

.05)

(20.

05)

(902

7.49

)(7

4.54

)(7

.99)

(0.6

2)(4

.52)



Tabl

e A

3 C

orre

lati

on M

atri

x of

the

Var

iabl

es

OFD

IGD

PO

FDIG

FCF

GD

PP

CT

OP

EN

PO

LRIS

KR

DG

DP

RE

ER

OFD

IGD

P1

OFD

IGFC

F0.

973

1G

DP

PC

0.43

50.

413

1T

OP

EN

0.59

20.

551

0.52

61

PO

LRIS

K0.

259

0.24

90.

547

0.45

11

RD

GD

P0.

157

0.12

20.

330

0.28

90.

318

1R

EE

R–0

.034

–0.0

610.

019

–0.0

230.

060

–0.1

011

Sou

rce:

Au

thor

’s c

alcu

lati

ons.

2007

Mea

n2.

059.

0281

14.2

010

4.60

.0.

6310

5.96

SD(5

.01)

(24.

08)

(996

6.05

)(7

2.11

).

(0.7

0)(9

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Home Country Determinants of Outward FDI from Developing Countries

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