Introduction
Problem statement
Foreign direct investment (FDI) and exports play a crucial role in fostering economic growth, particularly in developing countries, as highlighted by both theoretical and empirical literature New growth theories emphasize the significance of investment and trade openness, leading to strategies that promote FDI and exports, often referred to as 'FDI-led growth' or 'export-led growth.' International free trade is recognized as an "engine of growth," with studies showing that countries engaged in free trade experience higher growth rates compared to those with closed economies The implementation of open economies and free trade results in increased economic growth, higher income levels, and improved living standards Through trade, export sectors can generate more profits, enhance savings, and create foreign exchange earnings and job opportunities Moreover, the competitiveness of export markets encourages export-oriented policies that positively impact economic growth and facilitate integration into the global economy Consequently, the export-led growth hypothesis supports the idea that export expansion is a key driver of economic growth, while productivity improvements and cost reductions also enhance export potential.
Foreign direct investment (FDI) is on the rise, significantly contributing to trade and economic growth It enhances productivity, fosters employment, advances technology, improves social welfare, and alleviates poverty, particularly in developing nations According to Chiara and Sasidharan (2009), FDI is crucial for economic development as it introduces unique technological assets unavailable in the host country Additionally, trade serves as a conduit for FDI, facilitating the flow of capital, technological advancements, and managerial expertise.
Foreign direct investment (FDI) significantly enhances economic growth and plays a crucial role in promoting exports Consequently, the interplay between FDI, exports, and economic growth has become increasingly important to policymakers and researchers alike.
Economists and researchers have long been intrigued by the interplay between Foreign Direct Investment (FDI), exports, and economic growth Numerous empirical studies have employed time series, cross-sectional, and panel data to analyze the effects of FDI and exports on economic growth, particularly focusing on the FDI-led and export-led growth hypotheses Early research utilized simple correlation coefficients and regression equations based on Neoclassical growth theory to assess the relationship between exports and economic growth More recent studies have highlighted the causality among FDI, export growth, and economic growth through cointegration techniques and Granger causality tests applied to time series and panel data Various empirical investigations have explored these causal links in regions such as Asia and Africa, particularly in developing countries, with notable examples including studies by Ekanayake (1999), Ismaid and Harjito (2003), and Bahmani-Oskooee.
Numerous studies, including those by Sinoha-Lopete (2006), Pham (2008), and Awan et al (2012), reveal a complex relationship between Foreign Direct Investment (FDI), exports, and economic growth, which varies by country and region It is crucial for policymakers and researchers to thoroughly analyze these interconnections to formulate effective strategies that enhance economic growth, particularly in developing nations Notably, Malaysia and Thailand exemplify developing countries that have achieved sustained long-term economic growth.
Malaysia and Thailand have successfully boosted their economic growth through increased exports and foreign direct investment (FDI), particularly in the manufacturing sector (Todaro & Smith, 2003) Vietnam shares similar comparative advantages and economic conditions, making the growth-promoting policies of Malaysia and Thailand valuable lessons for other nations This thesis aims to explore the causal relationship between FDI, exports, and economic growth by employing cointegration and causality techniques on time series and panel data from 1989 to 2010, focusing on Malaysia, Thailand, and Vietnam in the developing Southeast Asia region The findings are anticipated to enhance the empirical literature using modern methodologies.
Research objectives
The objectives are as follows:
• To examine the causality relationship between foreign direct investment, exports, and economic growth in these countries
• To suggest appropriate measures for exports expansion and attracting FDI in order to stimulate economic growth in these countries.
Research questions
In order to achieve the research objectives:
• Is there a causal relationship between FDI, exports, and economic growth in Malaysia, Thailand, and Vietnam countries?
• What policy implications could help improve exports and environment for FDI in these countries?
Research methodology
This paper uses annual time series data and panel data of three countries in Southeast Asia region including Malaysia, Thailand, and Vietnam over the period of 1989-2010
This study investigates the relationship between foreign direct investment (FDI), exports, and economic growth using various statistical methods For time series data, the Augmented Dickey-Fuller (ADF) test and Phillips and Perron (PP) test are employed, along with Johansen's cointegration technique and Granger causality test In the case of panel data, the analysis includes the Im, Pesaran, and Shin (IPS) test, the Augmented Dickey-Fuller Fisher (ADF-Fisher) test, Johansen Fisher panel cointegration, Kao tests, and panel Granger causality tests.
Structure of the thesis
This thesis comprises six chapters, starting with Chapter 1, which outlines the problem definition, research objectives, and questions, along with a brief overview of the methodology Chapter 2 offers a comprehensive theoretical framework and literature review Chapter 3 discusses the relationship between foreign direct investment, exports, and economic growth Finally, Chapter 4 details the methodology employed for the research study.
Chapter 5 indicates empirical results corresponding to each estimation technique
The last chapter will give conclusions of empirical results, policy implications, and limitations of the thesis.
Literature Review
Theoretical Literature
2.1.1 Relationship between foreign direct investment and economic growth
Foreign direct investment (FDI) serves as a crucial capital source that enhances domestic private investment, creating new job opportunities and facilitating technology transfer This influx of investment significantly contributes to economic growth in host countries through various mechanisms.
The Neoclassical growth model posits that technological progress and labor force dynamics are exogenous factors, suggesting that foreign direct investment (FDI) boosts investment volume and stimulates economic growth However, FDI's impact on growth is primarily short-term due to diminishing returns on capital In contrast, the new endogenous growth theory emphasizes that long-term growth is driven by technological change; if FDI enhances technology, it can significantly elevate growth rates in host economies through mechanisms like technology transfer and spillover effects Research by Herzer et al (2006) and Makki and Somwaru (2004) highlights that FDI positively influences economic growth in both the short and long term, particularly through the diffusion of technology from developed to developing nations.
Economic growth significantly influences foreign direct investment (FDI) inflows into a host country, as a robust economy tends to attract more investment Higher levels of economic growth can lead to the expansion of domestic markets and businesses, making the country a more appealing destination for FDI (Agiomirgianakis et al., 2006).
Rapid economic growth generates significant aggregate demand, which in turn boosts the need for investments, particularly foreign direct investment (FDI) Moreover, improved economic conditions in host countries enhance FDI attractiveness by offering better infrastructure and increased profit opportunities.
Johnson (2006) state that FDI inflows enhance economic growth of a host country and the growth of economic in tum may attract FDI inflows and the cycle continues
2.1.2 Relationship between exports and economic growth
Exports play a crucial role in driving economic growth, particularly in developing countries, as there is a significant correlation between the two The export-led growth hypothesis is supported by various theoretical arguments that highlight the importance of exports in fostering economic development.
A study by Balassa (1978) indicates that export growth significantly contributes to economic growth, demonstrating a strong correlation between the two Additionally, the research highlights a positive relationship between exports and domestic savings, suggesting that increased exports can attract substantial foreign capital and enhance labor opportunities.
This paper supports export-oriented policies as a catalyst for economic growth Tyler (1981), aligning with Balassa's perspective, analyzed the relationship between growth and export expansion using cross-sectional data from 55 developing countries His findings revealed a significant positive correlation between growth and exports However, mere correlation analysis does not account for the influence of other variables To address this, he developed a model based on the Cobb-Douglas production function, incorporating three key factors.
Where Xi is country i's GNP, A is a technological constant, Ki is country i's capital stock services, Li is a country i' s labor force inputs and Ei is country i' s exports
This regression analysis highlights the significant impact of capital and exports on economic growth, surpassing models that only consider capital and labor force The findings reveal that a 17.5% increase in exports correlates with a 1% growth in the economy Therefore, the results underscore the crucial role of exports in driving economic growth in developing countries.
Export orientation and promotion are advantageous for both developed and developing nations, as they leverage economies of scale and technological advancements to boost productivity and generate employment (Medina-Smith, 2001) Expanding exports alleviates current account pressures for foreign capital goods by enhancing external earnings and attracting foreign investment Additionally, K6nya (2002) highlights that promoting export activities fosters economic growth, as it encourages the production of goods for export, leading to specialization, economies of scale, and the utilization of a nation's comparative advantages.
Export expansion is crucial for economic growth, as it increases foreign demand for domestic products, leading to job creation and higher incomes in the export sector This growth in exports facilitates the efficient reallocation of resources and the realization of economies of scale, resulting in enhanced productivity Additionally, increased exports foster technological advancements, skill development, and improved management practices due to competition in foreign markets This dynamic not only generates foreign exchange for importing capital and intermediate goods but also creates a cycle where output growth stimulates further exports Ultimately, the interplay between exports and output growth leads to greater employment and income, driving productivity and reinforcing the export growth cycle.
Besides, there are also theoretical reasons to support the growth-led export
Neoclassical trade theory posits that economic growth stimulates higher exports through economies of scale, which reduce costs and enhance comparative advantage As economies grow, they also improve skills and technology across various sectors, leading to increased productivity (Krugman, 1984) Similarly, Ram (2003) emphasizes that advancements in skills and technology foster a comparative advantage in producing certain goods, thereby expanding exports Furthermore, Majeed and Ahmad (2006) demonstrate that GDP and GDP growth positively impact exports, particularly in developing countries.
Therefore, it is important to maintain a high and sustainable economic growth which is a vital factor to promote exports because bidirectional causality between exports and output growth can exist
2.1.3 Relationship between FDI and exports
Foreign Direct Investment (FDI) is primarily driven by the potential for high profits in emerging markets It influences a host country's export performance through the activities of foreign affiliates and the enhancement of exports by local firms (Lipsey, 2004) Multinational corporations' affiliates leverage factor endowments, such as abundant resources and lower labor costs, to enhance their competitiveness in global markets, ultimately improving the overall export performance of the host country.
Foreign Direct Investment (FDI) indirectly influences local firms' exports by enhancing their competitiveness through technology transfer, improved management, and skill development, which ultimately boosts production efficiency Njong (2008) highlights that FDI shifts from high labor cost countries to lower labor cost host nations can further increase the export competitiveness of multinational corporations (MNCs) and improve their overall export performance.
Exports significantly influence Foreign Direct Investment (FDI) through various mechanisms Key factors driving FDI inflows include high per capita income, a strong orientation towards international trade, infrastructure development, and attractive rates of return on investment (Akinkugbe, 2003) Additionally, market size, infrastructure quality, economic stability, and the presence of free trade zones are crucial determinants of FDI, with investment decisions also being shaped by fiscal incentives, the overall investment environment, labor costs, and trade openness (Lim, 2004).
Empirical studies
A study by Babalola et al (2012) analyzed the interconnections between exports, foreign direct investment (FDI), and economic growth in Nigeria from 1960 to 2009 The findings revealed six cointegration vectors among FDI, capital formation, openness, imports, and terms of trade, as determined by the Johansen cointegration test These variables demonstrated a long-term relationship and significantly contributed to Nigeria's economic landscape.
Javed et al (2012) investigated the interplay between foreign direct investment (FDI), trade, and economic growth in India, Bangladesh, Sri Lanka, and Pakistan from 1973 to 2010 using the Generalized Method of Moments (GMM) The study found that exports positively influence economic growth in all countries studied, along with FDI, although Sri Lanka showed an exception Additionally, domestic investment and the labor force also contribute positively to economic growth.
Mangir (2012) used cointegration and Granger causality test to analyze the relationship between export and economic growth in Turkey for the period of 2002
A quarterly time series analysis from 2011 to 2020 reveals a long-run cointegration between exports and economic growth in Turkey The Granger causality test indicates a unidirectional causality from exports to economic growth in the short run, while in the long run, a bidirectional causality relationship is observed.
Hossain (2012) analyzed both the short-run and long-run relationship between FDI and economic output in South Asian countries using data from 1972 to
A 2008 study employing three econometric models—ADF test, Engle-Granger test, and VECM—along with Granger causality analysis, examined the impact of Foreign Direct Investment (FDI) on economic output in Bangladesh, India, and Pakistan The findings revealed no cointegration between FDI and GDP in both the short and long run for Bangladesh and India In contrast, Pakistan exhibited cointegration in both time frames Additionally, there was no causal relationship between FDI and GDP in Bangladesh, while a one-way relationship was identified in Pakistan and India, indicating that FDI positively influences economic output in these countries.
A study conducted by Sun (2011) analyzed the relationship between foreign direct investment (FDI) and economic growth in China from 1985 to 2010 using a co-integration approach The findings revealed that FDI and economic growth are cointegrated, indicating a long-term relationship Additionally, the Granger causality test demonstrated that economic growth in China significantly drives the increase in FDI.
Erecakar (2011) examined the interplay between growth, foreign direct investment (FDI), trade, and inflation in Turkey from 1970 to 2008 Utilizing a cointegration test, the study revealed a single long-run relationship among the variables The findings demonstrated that FDI, inflation, and trade surplus positively influence economic growth.
In his 2011 study, Tekin investigates the Granger causality between real GDP, real exports, and inward foreign direct investment (FDI) in Least Developed Countries from 1990 to 2009 Utilizing a novel panel-data approach that incorporates Seemingly Unrelated Regression (SUR) systems and Wald tests, the research identifies significant causal relationships among these variables The findings indicate that export-led growth and FDI-led growth exist, while also revealing an inverse relationship between FDI and exports.
Safdari et al (2011) examined the causal relationship between exports and economic growth in thirteen Asian developing countries from 1988 to 2008 The study utilized panel data, measuring GDP and exports in constant 2000 US dollars, with the GDP deflator applied To analyze the data, the research employed four panel unit root tests developed by Levin et al (LLC, 2002), Im et al (IPS, 2003), and Breitung.
The study employs the Fisher-type test by Maddala and Wu (1999) and Choi (2001) to examine stationarity, while the panel cointegration tests developed by Pedroni (1999, 2004) and Kao (1999) are utilized to assess the cointegration relationship between export and output growth.
A panel-VECM causality analysis using the Wald test reveals the relationship between real exports and real GDP in thirteen selected Asian developing countries The findings indicate that exports do not Granger-cause economic growth; instead, there is a one-way causality from economic growth to exports.
Eusuf and Ahmed (2010) investigated the causal relationship between export and economic growth in South Asian countries using the Engle-Granger error correction model Their study analyzed annual time series data from seven countries, covering varying periods: India, Nepal, Sri Lanka, and Pakistan from 1965 to 2005, and Bangladesh and Maldives from 1980 to 2005.
This study analyzes the relationship between exports and economic growth in South Asian countries, utilizing indices such as the consumer price index, unit value index for exports, and GDP deflator from 1980 to 2005 The ADF and PP tests were employed to assess stationarity, while the Engle-Granger procedure examined the long-run relationship between exports and growth Causality was tested using the F-test and error correction term The findings reveal that real exports and real GDP are cointegrated in Bangladesh, Pakistan, and Nepal Export-led growth was identified in Pakistan, Sri Lanka, and Bhutan, both in the short and long term, whereas growth-led exports were observed in India, Nepal, and the Maldives However, no feedback export-led growth relationship was established for Bangladesh, leading to mixed results that do not conclusively support export-led growth across South Asian nations.
Bahmani-Oskooee and Economidou (2009) conducted a study on export-led growth and growth-led exports using annual data from 1960 to 1999 across 61 least developed countries (LDCs) The analysis employed five key variables: gross domestic product, gross capital formation, exports, imports (in constant 1995 US dollars), and total labor force Utilizing Johansen's cointegration technique, the study found no cointegration vector for 14 countries, while the null hypothesis of no cointegration was rejected for the others, indicating at least one cointegrating vector exists among the variables The relationship between exports and output was categorized into four groups: a feedback relationship in the long run for Algeria, Gambia, Ghana, Malawi, Senegal, Hungary, El Salvador, and Honduras; no long-run relationship for Burkina Faso, Burundi, Gabon, Kenya, Lesotho, Mali, Niger, Nigeria, Togo, India, Korea, Thailand, Egypt, Israel, Argentina, Bolivia, Brazil, Costa Rica, Dominican Republic, Guatemala, Mexico, and Trinidad and Tobago; a long-run stimulation of output by exports in Congo, South Africa, Swaziland, Tunisia, Ecuador, and Nicaragua; and a one-way relationship from output growth to export growth in Benin, Guinea-Bissau, Rwanda, Zambia, Bangladesh, Indonesia, Papua New Guinea, Chile, and Colombia Overall, the findings highlight the country-specific nature of these relationships.
A study by Rudra et al (2009) examined the cointegration and causality relationship between foreign direct investment (FDI) and economic growth in five ASEAN countries—Indonesia, Malaysia, Singapore, the Philippines, and Thailand—over the period from 1970 to 2007 The findings revealed a long-run relationship at the panel level for all five countries, while individual analysis showed significant cointegration only for Singapore and Thailand Additionally, bi-directional causality was identified between FDI and economic growth for all countries except Malaysia, as determined by Granger causality tests.
Miankhel et al (2009) investigated the causal links between foreign direct investment (FDI), exports, and GDP in six emerging economies—India, Pakistan, Malaysia, Thailand, Chile, and Mexico—covering the period from 1970 to 2005, analyzing both short-term and long-term relationships.
Conceptual framework
The conceptual framework, illustrated in Figure 2.1, highlights the interconnections between foreign direct investment, exports, and economic growth It also outlines research methodologies that employ time series or panel data to explore the causal relationships among these variables This framework effectively summarizes the key components of the study.
Fi~un: 2.1: Conceptual fnmu.•nmãk in this stud~
Capital sources Increasing domestic Cost reduction Create employment markets and
Job opportunities businesses Advancement Improving income skills and
Technology transfer Good infrastructure technology Technological progress
• IPS and ADF Fisher tests
• Kao and Panel Johansen cointegration tests
Foreign Direct Investment, exports, and economic growth in Malaysia, Thailand, and Vietnam: Descriptive and Comparative Analysis
Foreign direct investment, exports, and economic growth in Vietnam
The 'Doi Moi' reform, initiated in 1986, marked a pivotal moment in Vietnam's economic and social development, transforming the nation into a prominent example of a successful transitional economy Today, Vietnam boasts one of the fastest-growing economies globally, showcasing the significant impact of these reforms on its economic landscape.
The average growth rate is about 7.4% annually for period 1994 - 2010, nominal GDP of US$ 106,427 million, and GDP per capita ofUS$ 1,224.3 (2010)
Vietnam was significantly impacted by the financial and economic crises of 1997-1998, with GDP growth dropping to 5.8% in 1998, a decline of 3.6% from 1996 In 1999, GDP growth further decreased by about 1% compared to the previous year However, the Vietnamese economy demonstrated a remarkable recovery, achieving a GDP growth rate of 7.1% by 2002.
The main drivers of the economic growth were household consumption, investment and total exports in the period of 1989 - 2010 (Table 3.4 )
Table 3.4: 11te contribution l~{'compouents of' total demand to economic xrowlh iu Vietnam
Notes: C 8 , CP, I, E, M are government consumption, household consumption, investment, exports and imports, respectively
Source: Calculated from World Development Indicators, World Bank (2012)
In 2007, fixed capital formation increased by 24.2%, with the fixed capital investment to GDP ratio reaching 38.3%, maintaining over 30.0% for the previous decade (World Bank, 2012) This investment growth was fueled by rising domestic credit, decreasing inflation, and lower interest rates Notably, consumption expenditure emerged as the largest contributor to GDP growth, with household consumption accounting for approximately 71% of GDP between 1989 and 2010, while exports contributed over 51% during the same period.
THble 3.5: Correlation between the ~:rowth rafei; l~/'the real GDP and its components in Vietnam, 1989-2()1() c Ir E M
Notes: C, lg, lp, Ir, E, M are the growth rates of consumption, government investment, public investment, foreign investment, exports and imports, respectively
Source: Calculated from Government Statistics Office, 20 12
Table 3.5 presents government investment has a correlation closely with economic growth and foreign, private investment have a negative relationship with
GDP growth in 1990-1997, however, for the period of 1998-2010, foreign, private investment and economic growth have a strong positive correlation Inversely, for government investment and GDP growth have a negative correlation in 1998-2010
Exports have also positively relation to economic growth in the period of 1998-
Following the 'Doi Moi' reforms in 2010, government investment initially stimulated economic growth in Vietnam However, in subsequent years, this investment began to negatively impact growth, leading to an economy increasingly reliant on foreign investment and exports Ultimately, during this period, Vietnam's national economy primarily depended on external factors for its growth.
Table 3.6: G'DP growth (g=A}/}), Rate r~f investment (Ill), ;:1}//, /COR in Vietnam
Source: Calculated from Government Statistics Office, 2012
Increased investment drives economic growth by enhancing capital stock and expanding production capacity The impact of investment on economic growth is influenced by both the investment rate (I/GDP) and investment efficiency (I1GDP/I).
Table 3.6 reveals that economic growth is primarily driven by the investment rate rather than investment efficiency, indicating that the quantity of investors plays a more significant role than the quality of their investments With the investment rate surpassing 42%, it is approaching saturation levels Furthermore, the increasing ICOR indicators throughout the study period suggest a significant decline in investment efficiency, indicating a worsening trend.
Figun' 3.8: G~DP, exports and investmellf in Viellutm, 1989-2010 (VND billion)
Figure 3.8 also indicates that, the correlation between real GDP, exports and investment is relative clearly
The Vietnamese economy has undergone a significant transformation from a traditional agricultural base to a focus on industry and services This shift is largely attributed to the decline in agricultural prices and unfavorable agricultural terms of trade in international markets.
Table 3.7: Structural change iu Vietnam /989-21JJ(J (percentage)
Source: Calculated from World Development Indicators, 2012
Moreover, the demand for food rises slowly compared with other goods and services The share of industry in GDP is more and more increasing and attains over
41% in 2010 The contribution of services sector to economic growth is significant and it is concentrated on tourism
Following the 'Doi Moi' reform, Vietnamese exports experienced significant growth, reaching approximately 30% by 1991, with an average annual increase of about 19% from 1990 to 2005 However, in 2006, export growth sharply declined to -10.1%, primarily due to export quotas, trade barriers, and anti-dumping duties affecting seafood and leather products.
Figure 3.9: The J.:rowth t~fexports in Vietnam, 1990-2()/(J (percenlaJ.:I!)
In addition, exports increased slowly by the management of immanent shortcomings of economy
Joining in WTO in 2007 had helped exports back grew and reached to 11.3%
(2007) Nevertheless, Vietnamese exports also have suffered the strongest negative impact and the export of growth is decline from 11.29% in 2007 to 5.05% in 2008 by the global crisis (World Bank, 2012)
Table 3.8: E.\]JOrfs and Imports in Vietnam (perccnlaJ.:e of' GDP)
The decline in export revenues has severely impacted exporting companies, particularly those in the manufacturing sector, such as garments, footwear, furniture, seafood, and agricultural products, putting many at risk of closure.
Since the post-reform period, Vietnam has consistently faced a trade deficit, with exports consistently falling short of imports This negative trade balance can be attributed to several factors: high domestic consumption of imported goods coupled with low added value in exports, the imposition of import barriers by various countries on Vietnamese products, and the overall low competitiveness of Vietnam's goods in both domestic and international markets.
Vietnam's economy remains heavily reliant on agriculture and natural resources, with major exports consisting of agricultural products, raw materials, and low-value-added processed goods due to a workforce primarily composed of unskilled labor Although the export value index experienced slow growth from 1989 to 2001, it has seen a significant increase in recent years.
Table 3.9: Export mlue iudex iu Vietnam, 1989-2010
Year 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 Export 13.5 16.6 14.4 17.9 20.7 28.1 37.7 50.3 63.3 64.8 79.9 Year 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Export 100.0 104.0 115.6 139.5 183.3 224.6 275.7 336.1 433.9 395.2 496.0 Source: World Development Indicators, 2012
Vietnam's export economy has historically relied on imported raw materials and intermediate goods, often at high prices While mineral and food exports dominated in 1997, there has been a notable shift towards manufactured goods in subsequent years By 2009, manufactured exports accounted for over 60% of total exports; however, this sector remains largely in its infancy in Vietnam.
Figunã 3.10: Export struclure in Vietnam
97 2000 2003 2007 manufactures • mineral 11 food agricultural • others
Source: Calculated from World Development Indicators, 2012
Between 1989 and 1992, Vietnam experienced minimal foreign direct investment (FDI) inflows compared to other Southeast Asian countries However, from 2006 to 2010, Vietnam's FDI inflows began to align with those of regional peers like Malaysia and Indonesia, showing a significant increase compared to previous years.
Figure 3.11: FDI inflows in the Southeast countries (SUS million)
Source: Calculated from World Development Indicators, 2012
Registered investment is the amount of investment pledged by foreign investors and their domestic partners Actual investment implementation is usually below commitments
Foreign Direct Investment (FDI) inflows to Vietnam experienced significant growth in the early 1990s, peaking around 1996 for commitments and 1997 for disbursements, alongside an increase in the number of foreign projects However, this growth was followed by a sharp decline due to the Asian economic crisis, which negatively affected Vietnam's investment environment compared to regional competitors By 2002, registered capital hit a low despite a high number of projects Following 2003, both registered and implemented capital began to rise again, culminating in peak investment levels by 2008, marking a significant recovery in FDI commitments and disbursements since 1989.
Figure 3.12: Foreign direct imãe.\ãfment i11 J "ietuam, /989-20 I()
-Registered capital -Implementation capital ,._Number of projects
Source: Calculated from Government Statistic Office, 2012
In general, after Asian financial and monetary crises, most of countries in the region have considerably improved their investment environment to attract FDI
Vietnam has significantly transformed its Foreign Direct Investment (FDI) policies, leading to a substantial increase in FDI inflows from 2003 to 2008 due to an enhanced investment environment However, the global financial crisis of 2008 had a profound impact, resulting in a decline in both investment commitments and disbursements, which posed challenges for multinational corporations (MNCs) and caused a decrease in FDI inflows to Vietnam and other countries.
Especially, registered capital had declined over 65% in 2009 compare to 2008 implying that the disbursements ofFDI has been postponed or even cancelled
Tahl.: 3.10: Foreign direct im•eIJJU'llt in.flows hy Vietnam\ region and province
Northern midlands and mountain areas 160.4 2.3 644.3 3.2
Source: Calculated from Vietnam Government Statistic Office, 2012
Research Methodology
Data sources
This thesis examines the causal relationship between foreign direct investment (FDI), exports, and economic growth in Malaysia, Thailand, and Vietnam from 1989 to 2010, utilizing data from the World Bank's World Development Indicators Due to limited availability of Vietnamese data, the study incorporates both annual time series and panel data for the specified period The analysis focuses on key variables, including real gross domestic product (GDP), real exports of goods and services (EX), and foreign direct investment (FDI).
Variable measured in constant 2000 US dollars.
Model Specification
To analyze the causal relationship between foreign direct investment (FDI), exports, and economic growth, a Vector Autoregression (VAR) model was employed, incorporating GDP, exports, and FDI as key variables The real values of exports, FDI, and GDP were transformed into logarithmic form, represented as lnFDI, lnEX, and lnGDP, prior to analysis This model estimates the long-term relationships among these three variables across three countries in the Southeast Asia region.
The model is expressed in linear form as in the following equation: lnGDPit =Po+ P1i lnFDiit + P2i lnEXit + Eit where: i is i th country and t is the time period for each country;
GDP is gross domestic product;
EX is total export values of goods and services;
FDI is foreign direct investment inflows;
P 1 and P 2 represents the long run elasticity of economic growth with respect to foreign direct investment and exports respectively; and
Po is the constant term and Et is the random error term
4.3 Estimation techniques 4.3.1 Individual economy's Granger causality test
This paper aims to investigate the causal relationship between foreign direct investment (FDI), exports, and economic growth in Southeast Asia To determine the direction of causality among these variables, Granger causality tests are employed Before conducting these tests, the study first assesses the stationarity of each time series using the Augmented Dickey-Fuller (ADF) and Phillips and Perron (PP) tests.
The Johansen cointegration test is employed to analyze the cointegration relationship among the variables By assessing the time series characteristics of each country, a Vector Autoregression (VAR) or Vector Error Correction Model (VECM) is estimated for the Granger causality test Detailed explanations of each test are provided below.
4.3.1.1 Unit root tests for stationary time series
Preliminary analysis of the data using the Augmented Dickey-Fuller (ADF) (Dickey and Fuller, 1981) and the Phillips and Perron (PP) (Phillips and Perron,
Unit root tests are essential for determining the stationary properties of time series data, specifically assessing whether the series is stationary at its level, first difference, or second difference Non-stationary time series data can undermine forecasting accuracy and lead to spurious regression results, as highlighted by Gujarati (2011) Thus, conducting unit root tests is crucial to avoid misleading conclusions in regression analysis Generally, a variable is considered stationary after differencing d times, denoted as integrated of order d, or I(d), with most economic variables typically being integrated of order one (Asteriou and Hall, 2007).
Augmented Dickey Fuller test bases on rejecting a null hypothesis (H 0 : 8=0) of unit root (the series are non-stationary) in favor of the alternative hypothesis (Ha:
To assess the stationarity of the time series Y1, which can represent lnGDP, lnEX, or lnFDI, we conduct a unit root test The optimal lag length is identified using either the Akaike Information Criterion (AIC) or the Schwarz Information Criterion (SIC) A rejection of the null hypothesis of a unit root occurs when the absolute value of the ADF statistic exceeds the critical value, indicating that the series is stationary The tests account for random walks with or without drift and include a time trend for each series The three configurations of the ADF test are outlined in specific equations.
~Yt = 8Yt-I + 'Lf=1 /3i~Yt-i + et pure random walk (4.3)
~Yt =a+ 8Yt-I + 'Lf= 1 /3i~Yt-i + e 1 random walk with intercept (4.4)
~Yt =a+ yT + 8Yt-I +'Lf= 1 /3i~Yt-i + e 1 random walk with intercept and time trend (4.5) where:
~ is the first difference operator; a is a constant;
T is a linear time trend; and e is the random error term
The Phillip-Perron (PP) test, introduced in 1988, enhances and generalizes the Augmented Dickey-Fuller (ADF) test by addressing the limitations of the ADF's assumptions regarding error terms Unlike the ADF test, which assumes uncorrelated error terms with constant variance, the PP test accounts for serial correlation in the error process by adjusting the t statistic of the AR(1) regression coefficient This modification allows for a more flexible approach to testing for unit roots in time series data.
Similarly, the null hypothesis of PP test is rejected as well as ADF test With bandwidth are selected by Newey-West Bartlett kernel
Most economic time series exhibit non-stationarity, necessitating tests to determine if all variables are integrated of the same order before proceeding with cointegration analysis This thesis employs the Johansen approach, as established by Johansen (1988) and Johansen and Juselius (1990), to investigate the cointegration relationship among exports, foreign direct investment inflows, and economic growth within a trivariate model for three Southeast Asian countries The variables lnGDPt, lnEXt, and lnFDit are considered endogenous, forming the vector Zt = [lnGDPt, lnEXt, lnFDit], which is integrated of order one, I(1) The analysis focuses on a model with two variables (n=2), representing the simplest scenario for the Johansen cointegration test; however, with more than two variables, there can be n-1 cointegrating vectors.
This study determines the optimal lag length by minimizing the Akaike Information Criterion (AIC) and Schwarz's Bayesian Criterion (SBC) The common approach involves estimating a Vector Autoregression (VAR) model for all variables, initially using a large number of lags and then gradually reducing them by reestimating the model until reaching zero lags Consequently, a VAR model is utilized to investigate the cointegration relationship, with the model for Zt expressed accordingly.
Zt = AIZt-1 + A2Zt-2+ + AkZt-k + Et
It can be reformulated in a Vector Error Correction Model (VECM) as:
L1Zt = riLlZt-1 + r 2LlZt-2 + + r k-ILlZt-(k-1) + nzt-1 + Et where:
(4.8) ri=(I-AI-A2-ããã -Ak)(i= 1,2, ,k-l)andTI=-(I-AI-A2-ããã -Ak)
~ is the first difference operator;
Zt is the set of variables discussed above;
Et ~ niid (O,L), J.l is a drift parameter;
TI is a (r x r) matrix with rank r (r :S 3), r determine the number of cointegrating vector; and n = aw where a will be the speed of adjustment to equilibrium coefficients while
W will be the long run matrix of coefficients
Johansen (1988) and Johansen and Jeselius (1990) identified two statistical tests for determining the number of cointegration vectors The first test, known as the trace statistic (Atrace), utilizes a likelihood ratio test focused on the trace of the matrix The second test, referred to as the maximal eigenvalue statistic (Amax), is based on the maximum eigenvalue.
Atrace(r) =- T If=r+lln(l - Ar+l) Amax(r, r + 1) =- T ln (1-Ar+l) where:
X is the estimated eigenvalue; and
T is the number of observations
If the test statistic is larger the critical value indicating the hypothesis of full rank or the null hypothesis of no co integration is rejected
Cointegration among variables I(1) indicates a causal relationship, though it does not specify the direction of causality As noted by Mehrara (2007), when variables are cointegrated, the Vector Error Correction Model (VECM) is the most effective method for testing Granger causality The VECM effectively addresses the limitations of VAR-based models by distinguishing between long-run and short-run relationships among variables Therefore, the VECM is utilized to examine the causal relationships between lnEXt, lnFDit, and lnGDPt, based on the following VAR model formulation.
L1lnEXt = ~o + L~=l ~1il'1lnEXt-i + L~=l ~2il'1lnGDPt-i + L~=l ~3iL1lnFDit-i + A-2ECT2,t-I + E2t (4.12) L1lnFDit =Yo+ L~=l y 1 il'1lnFDit-i + L~=l y 2 il1lnEXt-i + L~=l y 3 iL1lnGDPt-i + A3ECT3,t-I + E3t (4.13) where:
~ is the first difference operator;
The residual Eit is assumed to be normally distributed and white noise;
ECTt-I is the one period lagged error correction term derives from the long run cointegration equation (this term will be excluded if the variables are not cointegrated); and
/ represent the deviation of the dependent variables from the long run equilibrium
If cointegration exists between two variables, error correction models will be utilized to test Granger causality as outlined in equations (4.11), (4.12), and (4.13) Conversely, if the series are not cointegrated, the standard Granger causality test will be conducted using vector autoregression (VAR) in first differences, excluding the error correction terms from the aforementioned equations.
The coefficients AJ, A2, and A3 in the error correction terms indicate the speed of adjustments for ~lnGDPt, ~lnEXt, and ~lnFDit in long-run equilibrium, while the lagged terms ~lnGDPt-i, ~lnEXt-i, and ~lnFDit-i capture the short-run dynamics among these variables The Vector Error Correction Model (VECM) investigates the Granger causality relationship between exports and economic growth in both the short and long run In the short run, weak Granger causality is assessed using the F Wald test, while long-run causality is evaluated through the error correction term coefficients based on t statistics Strong Granger causality reflects the coordination between short-run and long-run causal relationships in the model, necessitating the testing of specific null hypotheses.
Short run Granger causality (F statistic) (a) H0 : L~=l a2 i = 0 or exports do not cause economic growth (b) Ho: L~=l ~zi = 0 or economic growth does not cause exports Long run Granger causality (t statistic)
(c) H0: A 1 = 0 or Granger non causality in the long run (d) H 0 : A 2 = 0 or Granger non causality in the long run Strong Granger causality
(e) H 0 : A 1 = L~=l a 2 i = 0 or exports do not strongly cause economic growth (f) H 0 : A 2 = L~=l ~zi = 0 or economic growth does not strongly cause exports
4.3.2 Panel data Granger causality test
This research employs panel data analysis to mitigate distortions in size that may arise from time series analysis due to limited observations The advantages of using panel data include a larger number of observations, increased degrees of freedom, reduced collinearity among variables, and enhanced efficiency (Baltagi, 2001; Erdil and Yetkiner, 2006) The study investigates the causal relationship between Foreign Direct Investment (FDI), exports, and economic growth using modern econometric techniques, which involve three key steps First, a panel unit root test is conducted to determine the order of integration for each variable If a unit root is present, the second step employs a panel cointegration test to identify any long-term relationships among the variables If such a relationship exists, the final step involves estimating a Vector Error Correction Model (VECM) to analyze the Granger causal relationship between economic growth and exports, while a Vector Autoregression (VAR) model is utilized to explore the causal links among these panel variables.
It is important to know the stationary properties of the panel variables
Testing for stationarity in panel data differs from unit root tests in time series, as panel unit root tests exhibit greater power than individual time series tests Various methods have been proposed for detecting unit roots in panel data This paper specifically employs two types of panel unit root tests to assess the order of integration of the panel variables, including the Im, Pesaran, and Shin (IPS, 2003) test, as well as Fisher-type tests utilizing the Augmented Dickey-Fuller (ADF) approach developed by Maddala and Wu.
1999) IPS and Fisher-ADF assume cross-sectional independence
Im, Pesaran and Shin (2003) proposed the test statistic using the following model:
.1yi,t = Uj + YiYi,t-1 + L j~l Pã Lhi.1Yi,t-j + Ci,t (4.17) where:
Yi,t (i = 1, 2, , n; t = 1, 2, , T) is the series for country i over period; and
In the ADF regression, Pi represents the number of lags, while the errors si,t are assumed to be independent, normally distributed random variables with a mean of zero and finite heterogeneous variance Additionally, both Yi and Pi in equation (4.17) can vary across different countries.
Empirical Results
Unit root tests
The most commonly tests of the unit root in time series are the ADF test and
This study employs the PP test and ADF unit root test to determine the presence of a unit root in time series data for various countries, utilizing a sample size of 22 observations per country The analysis relies on MacKinnon's p-values and critical values, as established in 1996, which were derived from a dataset of 20 annual observations and are accessible through econometric software packages.
Tahlc 5.1: ADF ami PP unit root tests on level series for the indilãidua/s
Country Dependent ADF test PP test variables t -statistic Prob t -statistic Prob
Thailand In EX -2.1900 0.4704 -2.0086 0.5634 lnFDI -2.2683 0.4341 -2.2683 0.4341 lnGDP -2.7059 0.2444 -2.4766 0.3346
Vietnam In EX -0.6121 0.9671 -0.4419 0.9782 lnFDI -2.1496 0.4847 -7.0799 0.0001 lnGDP -3.8944** 0.0322 -1.8909 0.6234
The test equations include constant and trend terms Null hypothesis: series has a unit root
The lag length is selected by the minimum AIC or SIC for ADF test and by Newey- West Bandwidth for PP test
The critical values are calculated based on McKinnon ( 1996)
***, **,*denote rejection of null hypothesis at the 1%, 5%, I 0% level of significance, respectively
Macroeconomic variables often display trends over time, making it essential to use a regression equation that incorporates both constant and trend at the level form This study includes constant and trend terms in the regression equation for unit root tests of time series and panel data Additionally, since first differencing may eliminate any deterministic trends in the variables, the regression should include only the constant term.
The results of the ADF and PP tests for both individual and panel series are detailed in Tables 5.1, 5.2, and 5.3 In Table 5.1, it is noted that Malaysia's FDI is stationary at both constant and trend terms, while Vietnam's GDP exhibits mixed results, being stationary in the ADF test but not in the PP test The remaining variables are identified as non-stationary at their level forms, indicating the presence of a unit root This conclusion is supported by comparing the absolute values of the ADF and PP test statistics with the critical values at the 1%, 5%, and 10% significance levels.
Table 5.2: ADF aud PP uni; root tests on t!Jefirst d~fference ,\erie.\'for the indhãiduals
Country Dependent ADF test PP test variables t-statistic Prob, t-statistic Prob
The test equations include constant terms Null hypothesis: series has a unit root
The lag length is selected by the minimum AIC or SIC for ADF test and by Newey-West Bandwidth for PP test
The critical values are calculated based on McKinnon (1996)
***, **, * denote rejection of null hypothesis at the 1%, 5%, 10% level of significance, respectively
Table 5.2 displays the results of the ADF and PP tests for the first difference series, indicating that all variables are stationary, with consistent findings across both tests, except for Vietnam's GDP, which is not stationary according to the PP test The null hypothesis of non-stationarity is rejected at the first difference for each variable at both the 1% and 5% significance levels, with the exception noted.
Thailand's GDP is stationary at the 10% level of significance) for all variables of each country Thus, the variables for each country are integrated of order one, I (1)
This paper examines various panel data unit root tests, highlighting the potential for differing results Specifically, the IPS test and ADF-Fisher test are employed to conduct the panel data unit root analysis.
Tahlc 5.3: Panel unit root te\t\
Panel root Level First difference tests In EX lnFDI lnGDP ~lnEX ~lnFDI ~lnGDP
The numbers in parenthesis are p-value
***, **, * denote rejection of null hypothesis: panel series has a unit root, at the I%, 5%, I 0% level of significance, respectively
Table 5.3 displays the test results for both variables in levels and first differences, revealing that the IPS and ADF-Fisher tests indicate non-stationarity in the three level series Conversely, the panel unit root tests confirm that all panel series are stationary in their first differenced forms This implies that the three panel variables—FDI, exports, and economic growth—are integrated of order one, denoted as I(1).
Cointegration analysis
The unit root test results indicate that both time series and panel data variables are integrated of order one, I(1) Consequently, a co-integration analysis is performed to investigate the long-run relationships among the variables, utilizing the Johansen cointegration test for time series and the Kao test along with the Johansen Fisher panel cointegration test for panel data.
The empirical findings of the cointegration relationship are detailed in tables 5.4 and 5.5, focusing on time series and panel data The individual cointegration test results in table 5.4 reveal that all variables are cointegrated for Thailand and Vietnam, while Malaysia does not exhibit this relationship In Thailand, two cointegrating vectors were identified: one at a 5% significance level and another at a 10% significance level.
Tahll' 5.-t: Result\ of.lohan-.eu cuime;.:rmhm /estfiu iudhãiduol coull!fJ'
No ofCE Trace test Pro b Max-eigen test Prob
The test equations include: Intercept (no trend) in CE- no intercept in V AR
***, **, * denote rejection of null hypothesis at the 1%, 5%, I 0% level, respectively
In Vietnam, a significant cointegration vector is identified at the 5% level, indicating a long-term equilibrium relationship among exports, foreign direct investment, and economic growth in both Thailand and Vietnam.
As seen from table 5.5, both Johansen fisher test and Kao test suggest rejection of the null of no cointegration for groups of Southeast Asia countries
Therefore, the existence of cointergation relationship implying that there is a long run association between the panel variables
Johansen ftsher panel cointegration test
No of CE Trace test Pro b
In Johansen fisher test, the test equation include: Intercept (no trend) in CE - no intercept in V AR In Kao test, the test equation only individuals intercept
***,**,*denote rejection of null hypothesis at the 1%, 5%, 10% level, respectively
The long-run cointegration relationship signifies a causal link between variables, but it does not specify the direction of this causality To identify the causal relationship, the Engle and Granger test is commonly employed However, applying the Granger causality test to first-differenced variables through a VAR model can yield misleading results in the presence of cointegration Therefore, it is essential to implement a long-run panel causality test and a time series causal test for individual countries, such as Thailand and Vietnam, utilizing the Granger causality test based on the Vector Error Correction Model (VECM).
The findings in Table 5.6 indicate that Thailand's economy exhibits a bidirectional causality relationship between economic growth and exports, while there is a unidirectional causality from foreign direct investment to exports.
In Thailand, there is no evidence of a short-run causal relationship among the three variables studied However, in Vietnam, the null hypothesis that economic growth and exports do not Granger cause Foreign Direct Investment (FDI) is rejected at the 1% significance level, indicating a strong long-run and short-run Granger causality between these factors Additionally, a long-run causal relationship is identified from FDI and exports to economic growth at a 10% significance level.
Table 5.6: Granger ctw.mlily te.~t based on VECJVI j(nã 11wilmul ami Vietnam
Country Dependent Short run causality (F-test) Long run variable causality (t-test)
The p-values are in the parentheses
***, **, * indicate the statistical significance at the 1%, 5%, 10% levels, respectively
The findings indicate a reciprocal relationship between foreign direct investment (FDI) and GDP, with a long-term causality flowing from exports to economic growth in Vietnam Conversely, in the short term, economic growth is shown to drive exports.
Tahk 5.7: Granger cãtm.mli~\' test based on VAR mode/for lHalt~v\iu
Country Dependent Short run causality (F-test) variable LllnEX LllnFDI LllnGDP
The p-values are in the parentheses
***, **, * indicate the statistical significance at the 1%, 5%, 10% levels, respectively
Table 5.7 presents the results of Granger causality test based on the estimation of V AR model using the first difference series for Malaysia
Surprisingly, no causality relation has been found for FDI, exports, and economic growth variables
Table 5.8 reveals three significant long-run bidirectional causal relationships: between exports and foreign direct investment (FDI), exports and economic growth, and FDI and economic growth, all at the 1% significance level Conversely, in the short run, there is a unidirectional causality from exports to FDI at the same level of significance for the group of countries studied.
(0.0029) 0.0059 (0.8140) The p-values are in the parentheses
***, **, * indicate the statistical significance at the 1%, 5%, I 0% levels, respectively
The results do not provide evidence for short run Granger causality between FDI and economic growth, exports and economic growth
Table 5.9 presents a summary of the findings for Malaysia, Thailand, Vietnam, and the combined panel of these three countries Variations in study outcomes can be attributed to several factors, such as differing time periods, sample intervals, methodologies, and other influencing elements.
Table 5.t): The £'tlu.mli(r relations iuthis paper
Direction of causality Short run Long run Short run Long run Short run Long run Short run Long run
FDI-> GOP GOP-> FDI FDI +->GOP FDI 0 GOP EX-> GOP GOP-> EX
EX +->GOP EXOGDP FDI-> EX EX-> FDI FDI +->EX FDI 0 EX Notes: -+ : one-way impacts
Major Findings and Policy Implications
Major findings
This study investigates the causal relationship between economic growth, exports, and foreign direct investment in three countries over the period from 1989 to 2010 Utilizing both time series and panel data, the research employs advanced econometric techniques The analysis begins with unit root tests, including the ADF and PP tests for individual countries, as well as the Im, Pesaran, and Shin (IPS) and Maddala and Wu (ADF-Fisher) tests for the panel Subsequently, cointegration techniques are applied, featuring individual Johansen tests and Kao and Johansen Fisher panel cointegration tests Finally, the study conducts Granger causality tests at both individual and panel levels to assess the relationships among the variables.
V AR model or VECM are used to find the causal relations between the variables
The major findings of the thesis are summarized as follows:
Descriptive statistics indicate a strong relationship between foreign direct investment (FDI), exports, and economic growth in Malaysia, Thailand, and Vietnam In these countries, the industrial and services sectors contribute a larger share to GDP compared to the agricultural sector Additionally, the manufacturing industry plays a crucial role in both export activities and the inflow of foreign direct investment.
The unit root test results indicate that most variables are integrated of order one, with the exception of Vietnam's economic growth in the PP test Additionally, two distinct panel unit root tests confirm that the variables for the three-country panel are stationary at their first difference.
The individual Johansen cointegration tests reveal a cointegration relationship for both Thailand and Vietnam, while Malaysia shows no such relationship Additionally, the results from the panel cointegration tests indicate that all panel variables are cointegrated.
The Granger test results indicate a unidirectional long-run causality from foreign direct investment (FDI) to economic growth and exports in Thailand, while Vietnam shows a long-run causal link from exports and economic growth to FDI, as well as a feedback relationship between FDI and economic growth In Vietnam, a short-run causality exists from economic growth to exports, but no causal relationship is found in Malaysia among economic growth, exports, and FDI The differing results between Malaysia and Thailand, despite their similarities, are noteworthy and align with Miankhel's (2009) findings on the interplay of these variables Additionally, the panel Granger test results reveal a bidirectional long-run causal relationship among the variables, with a short-run unidirectional causality from exports to FDI across the three countries.
This study demonstrates that foreign direct investment (FDI) and exports drive economic growth, while also influencing each other Additionally, a significant interaction between FDI and exports is observed across the panel of three countries analyzed.
This study supports the hypotheses that FDI-led growth, export-led growth, and FDI-led exports are significant for Malaysia, Thailand, and Vietnam The findings indicate that foreign direct investment inflows and exports play a crucial role in boosting economic growth in these Southeast Asian countries.
Policy implications
Foreign Direct Investment (FDI) and exports play a crucial role in fostering and maintaining economic growth in various countries However, the effects of FDI and exports vary significantly across nations due to distinct economic, political, social, cultural, and other influencing factors.
Malaysia and Thailand share similar characteristics, with both governments focusing on manufacturing exports, which play a crucial role in their economies The manufacturing sector significantly contributes to the export landscape of both countries, emphasizing their export-oriented nature To further boost exports and stimulate economic growth, the Thai government should implement policies aimed at attracting foreign direct investment (FDI).
To boost economic growth, the Vietnamese government should prioritize expanding exports and attracting foreign direct investment (FDI), drawing lessons from Malaysia and Thailand The manufacturing sector, which has accounted for over 81% of FDI and a significant share of exports in the past five years, should be the focal point of this strategy Additionally, implementing policies to effectively reallocate the labor force in response to structural changes is crucial for bridging gaps between sectors Enhancing education and training to support the adoption of foreign technologies is also vital for attracting FDI Therefore, improving the investment environment and developing solutions to expand exports and attract foreign investment is essential for Vietnam's economic progress.
Research limitations
The thesis investigates the causal relationship between foreign direct investment (FDI), exports, and economic growth in Malaysia, Thailand, and Vietnam, but is limited by a small dataset of only 22 observations from 1989 to 2010, leading to no conclusive findings It does not determine the effects of FDI or exports on economic growth, highlighting the need for further research to explore both the short-run and long-run impacts of these factors on economic growth.
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Appendix 3.1: File \intilar c!Jaracleti\tics bct~