Are Merchandise Exports and FDI Inflows an Engine of Growth for ASEAN-10 Countries? New Evidence Using the Pooled Mean Group Estimation Method

Abstract

The Association of Southeast Asian Nations (ASEAN) has made remarkable economic progress in terms of rapid economic growth and expanding export trade and foreign direct investment (FDI). Theoretically speaking, both merchandise exports and FDI can be regarded as the key driving forces behind the ‘economic miracle’ of the regional economy. The major contribution of this study is that it is the first effort to empirically analyse the short-run and long-run growth effects of merchandise exports and FDI on the ASEAN-10 countries using time-series panel data. In this regard, this study aims to ascertain whether the spectacular regional growth is export- and FDI-driven, based on the ASEAN-10 panel data spanning from 1970 to 2016 using the pooled mean group (PMG) method. The findings show that merchandise exports are a key source of growth for the regional economy, attributable to the joint liberalisation efforts of the member states to expand trade and FDI. The study does not find evidence of FDI-led growth because the bulk of the FDI was invested in only a few ASEAN countries, and the minor FDI-recipient countries are at an early stage to benefit from the growth impacts of FDI, owing to lower absorptive capacity.

JEL Classification: C51, F21, F23, O19

Keywords

Economic growth Merchandise export FDI inflows ASEAN-10 Heterogeneous region Pooled mean group

1. Introduction

The Association of Southeast Asian Nations (ASEAN)¹ is a heterogeneous regional economy² which has grown rapidly recently. Currently, it consists of ten countries, namely, Brunei Darussalam, Cambodia, Indonesia, Laos, Malaysia, Myanmar, the Philippines, Singapore, Thailand and Vietnam. This economic grouping is denoted as ASEAN-10 and is one of the fastest-growing economic regions in the world. According to the ASEAN Secretariat (2015, pp. 1–2), during 2007–2014, ‘ASEAN gross domestic product (GDP) almost doubled to over US$2.57 trillion with total trade increased by nearly US$1 trillion, and has become one of the world’s fastest growing investment destinations, accounting for 11% of total global foreign direct investment (FDI) inflows’. Moreover, as reported by the Asian Development Bank Institute, the regional member states aim to triple their average real per capita GDP to US$10,000 by 2030.

The region’s rapid economic growth could be attributed to the adoption of outward-oriented policies such as the continued falling barriers to trade and the opening-up of the regional market to FDI. Two important observations follow from this outward orientation. The first pertains to the export-led growth hypothesis (ELGH), which is in line with the argument that export trade can be an ‘engine of growth’ for ASEAN. Although the export growth is externally driven, there are supply factors within the regional economy that can increase productivity and competitiveness. For instance, exporting countries tend to have higher productivity because of specialisation of production, economies of scale and the ‘learning-by-exporting effect’ (Asafu-Adjaye & Chakraborty, 1999; Chen & Tang, 1990; Wagner, 2007). Moreover, the neoclassical economists strongly believe that the exposure of export trade does have a positive influence on higher growth in GDP and income per capita (The World Bank, 1987). There is considerable empirical evidence advocating the ELGH. Both cross-section and time-series studies had shown a significant correlation between the growth of exports and the growth of national income (Balassa, 1971; Emery, 1967; Kravis, 1970; Westphal, 1978). The second observation is in connection with the FDI-led growth hypothesis (FLGH), suggesting that FDI inflows should result in an increase in productivity and competitiveness of ASEAN domestic industries through the transfer of technology and knowledge,³ which in turn promotes economic growth. Therefore, FDI inflows could be an important growth impetus, beyond exports, to explain the strong economic growth of ASEAN member states. As described by Blomstrӧm and Kokko (1998), FDI inflows could contribute to economic growth through the following spillover channels. First, foreign multinationals could lead to spillovers through labour mobility, that is, when a worker joins a local firm from a multinational firm and brings better management skills and technical knowledge. Second, it occurs through the demonstration effect, that is, when local firms adopt the technology and/or better business practices of foreign multinationals, thereby increasing the productivity of local suppliers. Third, through the competition effect, that is, as local firms are forced to use their current resources more efficiently and look for more advanced technologies in order to enhance their competitiveness and resilience as a result of the entry or presence of foreign multinationals, with positive impacts on their productivity.

Empirical studies on whether exports and FDI inflows are an engine of growth for ASEAN countries using time-series panel data are limited. Some studies have examined individual ASEAN countries (Adil, Shandre, & Kaliappa, 2009; Hsiao & Hsiao, 2006; Nguyen, 2011). From our intensive literature search, Fauzi and Nooraini (2012) is the only study which examined the relationship between FDI inflows, exports and growth in four ASEAN countries, namely, Malaysia, Thailand, Indonesia and the Philippines. However, their study used a static panel data approach, assuming that the slope coefficients and error variances are identical. Given that the ASEAN is a heterogeneous region, an empirical study using the static panel data approach appears to be inappropriate. The present study could extend the existing literature by examining the relationship between FDI inflows, exports and GDP growth among all ASEAN countries using the pooled mean group (PMG) estimation method. As highlighted by Pesaran, Yongcheol and Ron (1999), the PMG method could take care of the heterogeneity problem by allowing both the short-run coefficients and error variance to vary across countries while imposing equality of coefficients across countries in the long run. To our knowledge, this methodology has not been applied to examine the said economic relationship, which attempts to explain whether exports and FDI inflows are twin engines of growth for ASEAN in the long run.

The structure of this article is as follows. The second section discusses the main theoretical approaches to modelling the economic relationship between FDI inflows, exports and economic growth as well as the empirical findings. The third section presents the models, methodology, the estimated techniques, data description and data sources used in this study. The fourth section reports the findings based on the methodology outlined in the third section, and the fifth section provides the conclusions and policy implications.

2. Literature Review

2.1 Export-led Growth Hypothesis (ELGH)

The ELGH argues that a country that pursues an export-oriented strategy tends to promote higher growth than a country that undertakes import substitution. The former is outward looking, which involves liberalisation of trade so that exports are encouraged based on specialisation or comparative advantage, and importing goods, which are relatively costlier to produce domestically. On the other hand, the latter is inward looking, which involves the imposition of tariff and non-tariff barriers to protect domestic industries until they become efficient enough to compete internationally. Krueger’s (1984) study strongly supports export-oriented policies as a strategy of economic development. The World Bank also reports a similar trend, namely, ‘countries which adopted outward-oriented policies not only experienced higher growth in GDP and income per capita but also had higher rapid growth in manufactured exports’ (The World Bank, 1987, p. 84). Therefore, it can be postulated that growth could be achieved by export promotion strategy. However, it is plausible to have reverse causality running from economic growth to exports, which is known as the ‘growth-led export’ hypothesis (GLEH). As argued by Bahmani-Oskooee and Economidou (2009), over time, economic growth is instrumental in increasing economies of scale and reducing cost, and thereby encouraging exports.

2.2 FDI-led Growth Hypothesis (FLGH)

The FDI has played a pivotal role in the Asian economies in terms of maintaining cost competitiveness and sustaining economic growth (Islam & Chowdhury, 1998). In early neoclassical growth models, economic growth could be encouraged by FDI through capital formation. In these models, the impact of FDI inflows on economic growth is exactly the same as the increase in domestic capital investment, which is to raise labour productivity and hence, growth (Solow, 1956). Besides, FDI could enhance the factors of production via various channels of transmission and raise long-run growth through its positive influence on technology owing to foreign multinationals’ industrial expertise and know-how. Ali (1994) pointed out that technology transfer is usually ‘packaged’ with foreign expertise and capital equipment bundled together, that is, it is associated with the increasing quality of inputs such as capital and labour overtime. Apart from the employment of foreign personnel and the import of capital goods, foreign multinationals could also increase growth through knowledge transfer in relation to better management and organisational skills and superior business practices (Dunning, 1992). It is also argued that the entry of foreign multinationals could result in productivity spillovers to domestic firms attributable to greater competition (e.g., the presence of foreign multinationals propels domestic firms to be more efficient and to adopt newer technologies), skills transfer (e.g., the movement of workers from foreign multinationals to domestic firms), imitation (e.g., imitating foreign multinationals’ high-end production processes and professional know-how by domestic firms) and access to new markets (e.g., MNCs’ established international distribution network opening up export opportunities to competent local firms) (see Aitken & Harrison, 1999; Aitken, Gordon, & Harrison, 1994; Blomström & Kokko, 1998; Haskel, Pereira, & Slaughter, 2002).

However, the strength of this transfer channel depends on the absorptive capacity of local firms. Blomström and Kokko (1997) argued that such spillover effects have a higher tendency to occur in developed countries where local firms have stronger absorptive capacities. Nevertheless, foreign multinationals can prevent local firms from accessing their technology by protecting their intellectual property and trade secrets or locating in industries where local firms have limited imitation capacities (Javorcik, 2004). In fact, the presence of more efficient foreign multinationals can also result in market-stealing effects, for example, less efficient local firms losing market share or being driven out of the industry as a result of fierce competition (Aitken & Harrison, 1999). Hence, the benefits from positive spillovers may be offset by negative spillovers.

2.3 Recent Empirical Literature

Empirical studies testing the ELGH and FLGH hypotheses are primarily based on country-level data and panel data analyses. For instance, Cuadros, Orts and Alguacil (2004), who used a trivariate vector autoregressive regression (VAR) model, found evidence of the FLGH in Mexico and Argentina but not in Brazil. Other findings that corroborate the FLGH can be found in Basu, Chakraborty and Reagle (2003), Hermes and Lensink (2003), Makki and Somwaru (2004), Li and Liu (2005), Lensink and Morrissey (2006), Ghatak and Halicioglu (2007), Batten and Vo (2009), and Alfaro, Areendam, Sebnem and Selin (2010). The cross-sectional study by Makki and Somwaru (2004), who used the three stage least squares (TSLS) estimation method, found a strong, positive interaction between FDI and trade, which in turn encouraged economic growth. They pointed out that the ingredients for FDI-driven growth to occur were sound macroeconomic policies and institutional stability. On the other hand, Sahoo and Mathiyazhagan (2003) found that growth in the Indian economy was largely driven by exports rather than FDI. Thus, they proposed liberalising export-oriented sectors in the economy to achieve higher economic growth for India. Subsequently, Kishor (2012) confirmed that ELGH prevailed only in the post-liberalisation period in India. Comparable evidence can be found in Nguyen (2011), who studied the impact of trade liberalisation on economic growth for Malaysia and South Korea, in that exports were long-run sources of their economic growth. Whereas Ana, Vicente and Maite (2006) contended that the importance of openness involved more than just liberalisation of trade against the backdrop of an unprecedented increase in global FDI flows. Their findings indicated that both exports and FDI should be adopted by Mexico, Brazil and Argentina in their outward-oriented strategies. By the same token, using time-series and panel data from 1986 to 2004, Hsiao and Hsiao (2006) found that the economic growth of eight Asian economies, namely, China, Korea, Taiwan, Hong Kong, Singapore, Malaysia, the Philippines and Thailand, as a group was jointly driven by exports and FDI inflows, supporting ELGH and FLGH. In addition, they suggested that FDI could also promote economic growth through the setting up of export-oriented processing zones for FDI.

The only empirical study that uses panel data of ASEAN-4⁴ to examine the relationship between FDI, export and growth is Fauzi and Nooraini (2012). They studied the impact of FDI, openness and gross fixed capital formation on economic growth from 1981 to 2008. Using panel estimation methods (such as the pooled, fixed effects [FE] and random effects [RE] models), they found that FDI was instrumental in promoting economic growth of the ASEAN-4. However, panel estimation methods have some limitations. For instance, the homogeneity assumption is imposed on all the cross-section regressions, while the intercept heterogeneity is only permitted by the FE estimators. In a dynamic model, although the parameter estimates based on the former are consistent, in the case of coefficient heterogeneity, the pooled estimators are not consistent (Pesaran et al., 1999, pp. 624–625). As a result, this could lead to serious bias. The present study aims to overcome this bias by adopting a dynamic panel data approach using the PMG method, which allows for a greater degree of parameter heterogeneity by imposing a common long-run relationship across countries while allowing for heterogeneity in the short-run responses and intercepts. This is a less restrictive specification than standard ordinary least squares (OLS) and FE estimations.

3. Analytical Framework, Data and Methodology

This study ascertains the possible effects of merchandise exports and FDI inflows on economic growth in the ASEAN-10 countries using panel data based on the theoretical frameworks developed by Hsiao and Hsiao (2006) and Sahoo and Mathiyazhagan (2003). The former used the national income model to examine the causal relations of these three variables, while the latter applied the production function developed by Barro and Sala-i-Martin (1995) to show that FDI, as well as exports, mattered in the economic growth process. The analytical model for this empirical study can be written as:

l r G D P_{i, t} = β_{0} + β_{1} l r E X P_{i, t} + β_{2} l r F D I_{i, t} + ε_{i, t}

(1)

where Equation (1) is expressed in real terms and in log-linear form as denoted by lr, β₀ is the intercept and ε_i,t is an error term that has well-defined probabilistic properties. By estimating Equation (1), we can make a comparison between the magnitude and sign of the β coefficients. According to the ELGH, export growth (hereafter, EXP_i,t) could cause economic growth (hereafter, GDP_i,t) because of specialisation and higher productivity (as a result of free trade) and economies of scale (attributable to large foreign market size). In this regard, we expect the estimated β₁ to have a positive sign. However, the magnitude of the estimated β₁ may differ across the ASEAN-10 countries due to varying degrees of trade openness. It is postulated that GDP_i,t is a positive function of FDI_i,t provided that the channels of transmission (such as the absorptive capacity and availability of human capital of the host country) are strong (see Borensztein, De Gregorio, & Lee, 1998).

3.1 Data and Methodology

The estimation period for the current study spans 47 years from 1970 to 2016 for 10 ASEAN countries, namely, Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, the Philippines, Singapore, Thailand and Vietnam. Both GDP and FDI data are gathered from the United Nations Conference on Trade and Development (UNCTAD) database, while the data on merchandise exports are obtained from the World Development Indicator database. The raw data are denominated in US$ and expressed in real terms using the GDP deflator before they are transformed into logarithmic terms for the estimation regression.

Panel Unit Root Tests

Basically, in the literature of panel series there are two strands of panel unit root tests which are the individual and common panel unit root tests. The IPS (Im–Pesaran–Shin), Fisher ADF and Fisher PP tests are in the class of individual panel unit (IPS) root tests, whereas the Breitung, Hadri, Levin-Li-Chu tests are the common panel unit root tests. Intuitively, the IPS root tests are less restrictive than the common panel unit root (Im, Pesaran, & Shin, 2003). However, in the literature it is noted that none of the panel unit root tests have exact superiority over another (Verbeek, 2008, pp. 392–393). In another perspective, there is no accepted way to select the type of panel unit root test to decide whether there is a panel unit root. In this study, we choose to conduct the IPS and common unit root tests (Breitung) to eliminate the shortcomings of both types of tests.

Pooled Mean Group Test

After testing for a panel unit root, we proceed with the model specification using the recently developed dynamic panel data methodology. Pesaran et al. (1999) suggested two different estimators, specifically, mean group (MG) and PMG estimators, which are particularly appropriate for analysing panels with large time- and cross-section dimensions. The former estimates N separate regressions and calculates the average of the coefficient from the separate regression for each group in the panel. This estimator provides consistent estimates of the parameters’ averages (Pesaran & Smith, 1995). Pirotte (1999) also shows that in a large sample size, the MG estimator provides efficient long-run estimators. Under the MG assumption, both the slope and intercepts are allowed to vary across countries. The latter is an intermediate estimator that constrains the long-run coefficient to be identical, but allows the short-run coefficient to differ across groups. With regard to the PMG estimator, the error terms are well behaved so that the explanatory variables are exogenous. The model assumes that there exists a long-run relationship between the dependent variable and its determinants, with equality of coefficients in the long run.⁵ Therefore, the long-run relationships between FDI, exports and economic growth are expected to be identical from country to country, whereas the short-run coefficients are expected to be country-specific. The null hypothesis of homogeneity in the long-run coefficients can be confirmed with the Hausman test.

When FDI, exports and economic growth are I(1) and cointegrated, ε_it is supposed to be I(0) for all i and is independently distributed across t. The choice of the lag length of the relationship between FDI, exports and economic growth can be selected by the Akaike Information Criterion (AIC). The autoregressive distributed lag (ARDL) (1, 1, 1) model is expressed as follows:

\begin{matrix} l r G D P_{i, t} = α_{1 i} + α_{2 i} t + λ_{i} l r G D P_{i, t - 1} + β_{i 1} l r F D I_{i, t} + β_{i 2} l r E X P_{i, t} + \\ δ_{i 1} l r F D I_{i, t - 1} + δ_{i 2} l r E X P_{i, t - 1} + ε_{i, t} \end{matrix}

(2)

and the equilibrium error correction representation of the error correction equation is as follows:

\begin{matrix} Δ l r G D P_{i, t} = δ_{i 1} Δ l r F D I_{i, t} + δ_{i 2} Δ l r E X P_{i, t} + φ_{i} (l r G D P_{i, t - 1} - {\hat{θ}}_{i 0} \\ - {\hat{θ}}_{i 1} l r F D I_{i, t - 1} - {\hat{θ}}_{i 2} l r E X P_{i, t - 1}) + ε_{i, t} \end{matrix}

(3)

where ${\hat{θ}}_{i 0} = \frac{α_{i}}{1 - λ_{i},} {\hat{θ}}_{i 1} = \frac{δ_{i 1} + β_{i 1}}{1 - λ_{i}}, {\hat{θ}}_{i 2} = \frac{δ_{i 2} + β_{i 2}}{1 - λ_{i}} a n d φ_{1} = - (1 - λ_{i})$

4. Empirical Results

Prior to estimating the PMG model, it is essential to confirm the order of integration for FDI, merchandise exports and economic growth variables, that is, lrFDI, lrEXP and lrGDP, respectively. Both the IPS and Breitung panel unit root tests are used to determine whether each series in level and first difference contains a unit root. Table 1 reports the results of the panel unit root tests for each variable. Both tests could not reject the null hypothesis of a panel unit root at the 1 per cent significance level for lrEXP and lrGDP in levels. However, if these two variables are written in first difference, both tests clearly suggest the rejection of the null hypothesis at the 1 per cent significance level, concluding that they are integrated of order one, I(1).

Table 1
IPS and Breitung Common Panel Unit Root Tests

Variables IPS Panel Unit Root Test
Breitung Common Panel Unit Root Test

Level First Difference Level First Difference

lrGDP 3.906 −9.931* 3.197 −5.789*

lrFDI −3.547* −11.761* 0.380 −6.523***

lrEXP −1.271 −14.973* 0.885 −7.300*

Variables	IPS Panel Unit Root Test	Breitung Common Panel Unit Root Test
lrGDP	3.906	−9.931***	3.197	−5.789***
lrFDI	−3.547***	−11.761***	0.380	−6.523***
lrEXP	−1.271	−14.973***	0.885	−7.300***

Source: The raw data on GDP and FDI are retrieved from the UNCTAD database, while the raw data on merchandise exports are obtained from the World Development Indicator database.

Notes: All variables are in natural log form; ***, ** and * indicate significance at the 1%, 5% and 10% levels, respectively.

Concerning the panel unit root tests for lrFDI, the results of the test statistics are inconclusive. Based on the IPS panel unit root test statistic, it is I(0), stationary in level, while the Breitung’s test statistic suggests in favour of I(1) in level. When lrFDI is expressed in first difference, both test statistics confirm it is I(1). Despite the mixed panel unit root test results for lrFDI, as highlighted by Kim, Lin and Suen (2010) and Iwata, Okada and Samreth (2011), the PMG estimation could provide consistent estimators regardless of whether the variables are I(0) or I(1), as long as there exists a unique long-run relationship among the variables. The next step is to determine the order of lag length for the PMG model. Given the limited sample size, a maximum lag length of three is imposed on the model. The most adequate model chosen based on AIC is ARDL (2, 3, 3).

Table 2 presents the estimated models with PMG and MG using the Hausman test to examine whether the null hypothesis of long-run homogeneity (i.e., there is equality of coefficients across countries in the long run) is accepted or rejected. According to the Hausman test statistic, the null hypothesis of homogeneous long-run coefficients cannot be rejected at the 5 per cent significance level, suggesting that PMG is a preferred estimator to MG. The Jarque–Bera test statistic does not reject the null hypothesis of normality, indicating that the normality conditions in this model are satisfied. The estimated error correction term for the PMG model is significant at the 1 per cent level with a negative sign, which implies the existence of a long-run relationship between lrGDP and its determinants, lrFDI and lrEXP. The magnitude of the estimated error-correction term is 0.075, implying that the average speed of adjustment of lrGDP for the ten ASEAN countries to restore long-run equilibrium is slow. One plausible explanation for the slow average speed of adjustment is the inherent ASEAN diversity and the varying degree of trade openness among the ten ASEAN member states.

Table 2

Results of the MG and PMG Estimations: Dependant Variable—lrGDP (10 Countries, 1970–2016)

	Pooled Mean Group (PMG)	Mean Group (MG)	Hausman Test Long-run Homogeneity
Long-run coefficients			Chi-square
lrFDI	0.049 (0.086)	−0.716 (0.599)	3.19 (0.2031) PMG more efficient
lrEXP	0.785*** (0.043)	0.527*** (0.119)	3.19 (0.2031) PMG more efficient
Short-run coefficients
ΔlrFDI	0.032 (0.034)	−0.001 (0.012)
ΔlrEXP	−0.012 (0.017)	0.032 (0.021)
Error-correction term	−0.029*** (0.009)	−0.060** (0.024)

Source: The raw data on GDP and FDI are retrieved from the UNCTAD database, while the raw data on merchandise exports are obtained from the World Development Indicator database.

Notes: ***, ** and * denote significance at the 1%, 5% and 10% levels, respectively; figures in parentheses are standard errors except in the Hausman test, where they represent the p-value; Δ represents the first difference operator

The findings⁶ show that the long-run coefficient of lrEXP⁷ is significant at the 1 per cent level, but it is inelastic (as it has an estimated value of 0.78), indicating an increase in lrEXP would lead to a less than proportionate increase in lrGDP. This evidence supports the ELGH, which states that merchandise exports are an important source of growth for the ASEAN economy. On the other hand, the PMG estimation results do not advocate the FLGH (as the long-run coefficient of lrFDI is insignificant), conforming to the comparative study undertaken by Iamsiraroj and Ulubaşoğlu (2015) where 40 per cent of empirical studies of the effect of FDI on growth was found to be statistically insignificant, notwithstanding the fact that FDI inflows could be growth-enhancing in the host economy through the transfer of technology and knowledge. One plausible explanation for this is that the major share of FDI in ASEAN is highly concentrated in only a few member states, namely, Singapore, Indonesia, Thailand and Malaysia,⁸ whereas other minor FDI-recipient countries may not be able to benefit from the growth effect of FDI owing to their lower absorptive capacity due to a lower level of human capital.

5. Conclusions

Despite a slow start since its inception in 1967, ASEAN-10 has made remarkable economic progress in terms of rapid economic growth and expanding trade and FDI. Theoretically speaking, both exports and FDI can be regarded as the key driving forces behind the ‘economic miracle’ of the regional economy. In this regard, this study aims to ascertain whether the regional spectacular growth is export- and FDI-driven, based on the ASEAN-10 panel data spanning from 1970 to 2016 using the PMG method. The findings suggest that both merchandise exports and FDI were less likely to have short-run effects on growth for the ASEAN-10 countries. However, the long-run empirical results imply that merchandise exports are a key source of growth for the regional economy, attributable to the joint liberalisation efforts implemented by the member states to expand trade and investment.

Conversely, the findings do not reveal a positive effect of FDI on economic growth, implying local firms may lack absorptive capacity to benefit from positive FDI spillover effects, if any. Currently, the ASEAN region is facing a shortage of human capital,⁹ which is an important determinant of spillover benefits in the presence of foreign multinationals. Moreover, the Economist Corporate Network (2013) reported that some markets in ASEAN countries remain protected and are susceptible to economic uncertainty, which possibly may hinder the positive effect of FDI on economic growth.

In order to achieve sustainable economic growth in the era of globalisation, the ASEAN-10 countries should take advantage of its economic diversity by further liberalising trade and investment regionally and internationally. All the ASEAN countries should continue pursuing export-oriented foreign investment strategies in order to create regional value chains to expand export trade and FDI. Since the absorptive capacity of local firms is an important determinant of FDI spillover effects, there is a need to reinforce their absorptive capacity through improving organisational management skills, enhancing the skills of the workforce through investing in education and training programmes and upgrading and benchmarking against best international practices. These efforts are vital for reaping the benefits from positive FDI spillovers and learning by exporting.

The findings from this study could offer lessons to other regional groupings of developing countries like the South Asian Association for Regional Cooperation (SAARC), which shares similar characteristics with ASEAN-10 such as scale (in terms of market size by population) and economic diversity (in terms of per capita income and trade openness) (see Table A1 in Appendix). The presence of heterogeneous market size and economic diversity among member countries in SAARC could create opportunities for production fragmentation by multinationals (see Plummer, 2009) if both trade and investment barriers in the region were to be reduced. In this regard, foreign and South Asian multinationals that find it is more expensive producing in one of the member countries could shift their production platforms to another member country, which is relatively more cost-effective and/or has a bigger market size. Hence, the liberalisation of regional trade and investment in SAARC could encourage multinationals to reorganise their production and distribution activities by relocating their plants and affiliates across the region according to the members’ countries’ comparative cost and locational advantages in the face of the various operational and legal challenges in the host countries.

Last but not the least, intra-ASEAN trade is one of the key drivers of regional economic integration for ASEAN. The top four countries in terms of intra-ASEAN trade in 2016 were Singapore, Malaysia, Thailand and Indonesia, while countries like Brunei, Cambodia, Laos, Myanmar, the Philippines and Vietnam still need time to catch up with the top four on intra-ASEAN trade though ASEAN is a regional entity (see Table A1 in Appendix). The ASEAN economic integration is still evolving with major challenges, such as sustaining growth in individual country members, reducing the cost of doing business in the region, and emerging economic competitors like China and India. Future research, that ascertains the intra- and extra-ASEAN trade linkages through regional production networks, could shed light on further deepening ASEAN economic integration.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship and/or publication of this article: This work was supported by a RUI research grant, 1001/CDASAR/816277 from Universiti Sains Malaysia.

Footnotes

Appendix

Table A1

ASEAN Economic Indicators, 2016

Countries	GDP (US$ million)^a	GDP per capita^a	Population (thousand)	Merchandise Trade (US$ million)^b	Intra-trade (US$ million)^b	FDI Inflows (US$ million)^b
Brunei	13,301.37	31,430.74	423.20	4,912.55	1,216.70	5,739
Cambodia	16,998.19	1,078.40	15,762.37	10,099.01	867.60	16,656
Indonesia	1,037,688.09	3,974.06	261,115.46	136,845.63	28,355.41	234,961
Laos	11,378.06	1,683.55	6,758.35	4,167.84	2,151.41	5,639
Malaysia	344,045.40	11,031.60	31,187.27	188,709.96	55,655.28	121,621
Myanmar	621,81.59	1,175.78	52,885.22	11,725.10	3,511.37	22,666
Philippines	284,476.90	2,753.35	103,320.22	56,126.06	7,674.10	64,249
Singapore	294,944.90	52,458.38	5,607.28	330,684.28	95,220.63	1,096,320
Thailand	410,601.50	5,962.54	68,863.51	213,761.91	54,415.96	188,651
Vietnam	164,104.86	1,735.29	92,701.10	175,637.62	17,449.17	102,791
ASEAN	2,577,539.27	113,283.69	638,623.98	1,132,669.96	266,517.63	1,859,293

Source: UNCTAD, Direction of Trade, IFS, IMF.

Notes: a. Constant 2010 US$.

b. As of 2016.

Notes

References

Adil

K. M.

Shandre

M. T.

& Kaliappa

(2009). Foreign direct investment, exports, economic growth in selected emerging countries: Multivariate VAR analysis (Working Paper No. 23). Tokyo: Center for Contemporary Asian Studies, Doshisha University.

Aitken

B. J.

Gordon

H. H.

& Harrison

A. E.

(1994). Spillovers, foreign investment, and export, behavior (NBER Working Paper No. 4967). Cambridge, MA: National Bureau of Economic Research.

Aitken

B. J.

& Harrison

A. E.

(1999). Do domestic firms benefit from direct foreign investment? Evidence from Venezuela. American Economic Review, 89(3), 605–618. doi: 10.1257/aer.89.3.605

Alfaro

Areendam

Sebnem

K.-O.

& Selin

(2010). Does foreign direct investment promote economic growth? Exploring the role of financial markets on linkages. Journal of Development Economics, 91(2), 242–256. Retrieved from https://doi.org/10.1016/j.jdeveco.2009.09.004

Ali

(1994). Technology transfer. In Jomo

K. S.

(Ed.), Malaysia’s economy in the Nineties (pp. 171–194). Selangor: Pelanduk Publications.

Ana

Vicente

& Maite

(2006). Openness and growth: Reexamining foreign direct investment, trade and output linkages in Latin America. The Journal of Development Studies, 40(4), 167–192. Retrieved from https://doi.org/10.1080/00220380410001673238

Asafu-Adjaye

& Chakraborty

(1999). Export-led growth and import compression: Further time series evidence from LDCs. Australia Economics Papers, 38(2), 164–175. Retrieved from https://doi.org/10.1111/1467-8454.00049

ASEAN Secretariat (2015). ASEAN investment report 2015: Infrastructure, investment and connectivity. Jakarta: ASEAN Secretariat.

Bahmani-Oskooee

& Economidou

(2009). Export-led growth vs. growth-led exports: LDCs’ experience. Journal of Developing Areas, 42, 121–179. doi: 10.1353/jda.0.0030

10.

Balassa

(1971). Trade policies in developing countries. American Economic Review, 61(2), 178–187.

11.

Barro

& Sala- i-Martin

(1995). Capital mobility in neo-classical models of growth. American Economic Review, 85(1), 103–115. doi: 10.3386/w4206

12.

Basu

Chakraborty

& Reagle

(2003). Liberalization, FDI, and growth in developing countries: A panel cointegration approach. Economic Inquiry, 4, 510–516. Retrieved from https://dx-doi-org.web.bisu.edu.cn/10.1093/ei/cbg024

13.

Batten

J. A.

& Vo

X. V.

(2009). An analysis of the relationship between foreign direct investment and economic growth. Applied Economics, 41(13), 1621–1641. Retrieved from https://doi.org/10.1080/00036840701493758

14.

Blomström

& Kokko

(1997). The impact of foreign direct investment on host countries: A review of the empirical evidence (Policy Research Working Paper No. 1745). Washington, DC: The World Bank.

15.

Blomström

& Kokko

(1998). Multinational corporations and spill-overs. Journal of Economic Surveys, 12(3), 247–277. doi: 10.1111/1467-6419.00056

16.

Borensztein

De Gregorio

& Lee

J. W.

(1998). How does foreign direct investment affect economic growth? Journal of International Economics, 45(1), 115–135. Retrieved from https://doi.org/10.1016/S0022-1996(97)00033-0

17.

Chen

T. J.

& Tang

D. P.

(1990). Export performance and productivity growth: The case of Taiwan. Economic Development and Cultural Change, 38(3), 577–585.

18.

Cuadros

Orts

& Alguacil

(2004). Openness and growth: Re-examining foreign direct investment, trade and output linkages in Latin America. International Economic Journal, 40(4), 167–192. Retrieved from https://doi.org/10.1080/00220380410001673238

19.

Dunning

J. H.

(1992). Multinational enterprises and the global economy. London: Addison-Wesley.

20.

Economist Corporate Network (2013). Rising the ASEAN elephant: How business is responding to an unusual animal. Retrieved from http://www.bakermckenzie.com/files/Uploads/Documents/Publications/bk_ap_ridinasean_2013.pdf

21.

Emery

R. F.

(1967). The relation of exports to economic growth. Kyklos, 20(2), 470–496. doi: 10.1111/j.1467-6435.1967.tb00859.x

22.

Fauzi

& Nooraini

(2012). Economic growth in ASEAN-4 countries: A panel data analysis. International Journal of Economics and Finance, 4, 119–129. Retrieved from https://dx-doi-org.web.bisu.edu.cn/10.5539/ijef.v4n9p119

23.

Ghatak

& Halicioglu

(2007). Foreign direct investment and economic growth: Some evidence from across the world. Global Business and Economic Review, 9(4), 381–394. Retrieved from https://doi.org/10.1504/GBER.2007.015101

24.

Haskel

J. E.

Pereira

S. C.

& Slaughter

M. J.

(2002). Does inward foreign direct investment boost the productivity of domestic firms? (NBER Working Paper No. 8724). Cambridge, MA: National Bureau of Economic Research. doi: 10.3386/w8724

25.

Hermes

& Lensink

(2003). Foreign direct investment, financial development and economic growth. The Journal of Development Studies, 40, 142–163. Retrieved from https://doi.org/10.1080/00220380412331293707

26.

Hsiao

F. S. T.

& Hsiao

M. C. W.

(2006). FDI, exports, and growth in East and Southeast Asia: Evidence from time-series and panel data causality analyses. Journal of Asian Economics, 17(6), 1082–1106. Retrieved from https://doi.org/10.1016/j.asieco.2006.09.011

27.

Iamsiraroj

& Ulubaşoğlu

M. A.

(2015). Foreign direct investment and economic growth: A real relationship or wishful thinking? Economic Modelling, 51, 200–213. doi: 10.1016/j.econmod.2015.08.009

28.

K. S.

Pesaran

M. H.

& Shin

(2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics, 115(1), 53–74. doi: 10.1016/S0304-4076(03)00092-7

29.

Islam

& Chowdhury

(1998). Asia-Pacific economies: A survey. London: Routledge.

30.

Iwata

Okada

& Samreth

(2011). A note on the environmental Kuznets curve or CO₂: A pooled mean group approach. Applied Energy, 88(5), 1986–1996. Retrieved from https://dx-doi-org.web.bisu.edu.cn/10.1016/j.apenergy.2010.11.005

31.

Javorcik

B. S.

(2004). Does foreign direct investment increase the productivity of domestic firms? In search of spill-overs through backward linkages. American Economic Review, 94(3), 605–627. doi: 10.1257/0002828041464605

32.

Kim

D. Y.

Lin

S. C.

& Suen

Y. B.

(2010). Dynamic effects of trade openness on financial development. Economic Modelling, 27, 254–261. doi: 10.1016/j.econmod.2009.09.005

33.

Kishor

K. G.

(2012). Relationships among export, FDI and growth in India: An application of the auto regressive distributed lag (ARDL) bounds testing approach. Journal of International Business Research, 11, 1–18.

34.

Kravis

I. B.

(1970). Trade as a handmaiden of growth. Economic Journal, 80, 850–872. Retrieved from https://dx-doi-org.web.bisu.edu.cn/10.2307/2229902

35.

Krueger

A. O.

(1984). Trade policy in developing countries. In Jones

& Kenen

P. B.

(Eds), Handbook of international economics (pp. 107–123). Amsterdam: North Holland.

36.

Lensink

& Morrissey

(2006). Foreign direct investment: Flows, volatility, and the impact on growth. Review of International Economics, 14(3), 478–493. doi: 10.1111/j.1467-9396.2006.00632.x

37.

& Liu

(2005). Foreign direct investment and economic growth: An increasingly endogenous relationship. World Development, 33, 393–407. Retrieved from https://doi.org/10.1016/j.worlddev.2004.11.001

38.

Makki

& Somwaru

(2004). Impact of foreign direct investment and trade on economic growth: Evidence from developing countries. American Journal of Agricultural Economics, 86(3), 795–801. Retrieved from http://hdl.handle.net/10.1111/j.0002-9092.2004.00627.x

39.

Nguyen

H. T.

(2011). Exports, imports, FDI and economic, growth (Working Paper No. 11–03). Boulder, CO: Department of Economics, University of Colorado.

40.

Pesaran

M. H.

& Smith

R. P.

(1995). Estimation of long-run relationships from dynamic heterogeneous panels. Journal of Econometrics, 68, 79–113. Retrieved from https://doi.org/10.1016/0304-4076(94)01644-F

41.

Pesaran

M. H.

Yongcheol

& Ron

P. S.

(1999). Pooled mean group estimation and dynamic heterogeneous panels. Journal of the American Statistical Association, 94(446), 621–634.

42.

Pirotte

(1999). Convergence of the static estimation toward the long-run effects of dynamic panel data models. Economics Letters, 63, 151–158. Retrieved from https://doi.org/10.1080/1350485032000137486

43.

Plummer

M. G.

(2009). ASEAN economic integration: Trade, foreign direct investment, and finance. Singapore: World Scientific Publishing.

44.

Sahoo

& Mathiyazhagan

M. K.

(2003). Economic growth in India: Does foreign direct investment inflow matter? The Singapore Economic Review, 48(2), 151–171. Retrieved from https://doi.org/10.1142/S0217590803000748

45.

Solow

R. M.

(1956). A contribution to the theory of economic growth. Quarterly Journal of Economics, 70(1), 65–94. Retrieved from https://doi.org/10.2307/1884513

46.

The World Bank (1987). World development report 1987. Oxford: Oxford University Press.

47.

Verbeek

(2008). A guide to modern econometrics (3rd ed.). West Sussex: John Wiley & Sons Ltd.

48.

Wagner

(2007). Exports and productivity: A survey of the evidence from firm-level data. The World Economy, 30(1), 60–82. doi: 10.1111/j.1467-9701.2007.00872.x

49.

Westphal

L. E.

(1978). The Republic of Korea’s experience with export-led industrial development. World Development, 6(3), 347–382.