ABSTRACT This research study investigate and assess the green innovation in ASEAN. The object is to estimate the change in green innovation in 10 ASEAN countries from 2009 to 2019 through the relationship between green innovation with other factors such as twoway foreign direct investment (FDI) and environmental regulation. Data from reputable sources, such as the World Bank, Statista and Our World in Data, were collected and analyzed using econometric methods, including ordinary least square regression analysis. The findings of the study indicate that inward FDI (IFDI) has a positive impact on green innovation (GI), suggesting that higher levels of FDI contribute to the development and implementation of environmentally friendly technologies and practices. Environmental regulation (ER) is found to have a negative impact on GI, indicating that stricter regulations can hinder green innovation. Additionally, government support (GS) is positively associated with GI, highlighting the importance of creating an enabling environment for sustainable businesses and technologies. The paper recommends streamlining bureaucratic processes associated with environmental regulations while maintaining their effectiveness. Investing in green infrastructure and promoting sustainable practices can further foster green innovation.
FOREIGN TRADE UNIVERSITY FACULTY OF INTERNATIONAL ECONOMICS *** MIDTERM ASSIGNMENT THE IMPACT OF TWO-WAY FDI AND ENVIRONMENTAL REGULATION ON GREEN INNOVATION IN 10 ASEAN COUNTRIES FROM 2009 TO 2019 Group: Group Class: ESP231 Instructor: Ms Phan Kim Thoa Ha Noi, May 2023 ABSTRACT This research study investigate and assess the green innovation in ASEAN The object is to estimate the change in green innovation in 10 ASEAN countries from 2009 to 2019 through the relationship between green innovation with other factors such as two-way foreign direct investment (FDI) and environmental regulation Data from reputable sources, such as the World Bank, Statista and Our World in Data, were collected and analyzed using econometric methods, including ordinary least square regression analysis The findings of the study indicate that inward FDI (IFDI) has a positive impact on green innovation (GI), suggesting that higher levels of FDI contribute to the development and implementation of environmentally friendly technologies and practices Environmental regulation (ER) is found to have a negative impact on GI, indicating that stricter regulations can hinder green innovation Additionally, government support (GS) is positively associated with GI, highlighting the importance of creating an enabling environment for sustainable businesses and technologies The paper recommends streamlining bureaucratic processes associated with environmental regulations while maintaining their effectiveness Investing in green infrastructure and promoting sustainable practices can further foster green innovation CONTENTS INTRODUCTION SECTION 1.1 LITERATURE REVIEW .4 Review of previous studies 1.1.1 Two-way FDI 1.1.2 Green Innovation 1.1.3 Two-way FDI and Green Innovation 1.1.4 Environmental Regulation and Green Innovation 1.2 Research gap SECTION METHODOLOGY AND DATA 10 2.1 Methodology 10 2.2 Empirical Model 10 2.2.1 Model specification .10 2.2.2 Variables definition 11 2.3 Data 13 2.3.1 Data source 13 2.3.2 Descriptive statistics and variables interpretation .15 2.3.3 Correlation matrix between variables 16 SECTION MODEL ESTIMATION AND STATISTICAL INFERENCES .17 CONCLUSION AND RECOMMENDATION 21 REFERENCES 23 INTRODUCTION Context The word “green'' has never been as omnipresent as it is nowadays After the detrimental effect of the Covid-19 pandemic on the environment, many governments as well as citizens have acknowledged the importance of nature protection It is common that the term appears in the latest articles as “green growth”, “green product”, “green economy”, and “green technology”, and became one of the most popular phrases after the epidemic It also projects a new trend in the macroeconomic outlook in the near future In today's world, many nations have progressively shifted to a green economy - an economy that cares about happiness, social justice, and the environment in addition to economic benefits, in response to the negative social and environmental effects of establishing the brown economy This pattern is not exclusive to ASEAN countries Recently, a series of strategies and policies across sectors and fields have also been updated, revised, and promulgated In order to achieve green economic objectives, green innovation (GI) is of significance as it provides a number of benefits to the countries Xu L et al (2021) noted that in the host economies, green innovation may reduce CO2 emissions and create a clean environment According to Yin et al (2018), green innovation appears to have a major influence on creating a society that is resource- and environmentally friendly for sustainable development From another perspective, green innovation has a "double externality", which benefits businesses financially as well as in terms of the environment and society (Grekova et al., 2013; Feng & Chen, 2018; Rennings, 2000) Green innovation is a practical way for businesses to comply with environmental laws, absorb and lower environmental management costs, and capitalize on new development opportunities (Hamamoto, 2006) In other words, developing nations should look for green innovation and environmentally friendly industrial methods because of how effectively green innovation can address environmental concerns This paper will study the factors affecting green innovation in 10 ASEAN countries (except for Timor-Leste since this country was only officially accepted to join ASEAN in 2022), namely inward and outward FDI and environmental regulation Significance a Theoretical significance This paper contributes newly to the discussion by examining the effect of both inward and outward FDI, and environmental regulation on green innovation in 10 ASEAN countries (Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, Philippines, Singapore, Thailand, and Vietnam), through the model in Figure 1, using the hypothesis-driven approach b Practical significance The biggest expectation of developing countries in attracting foreign investment is to target economic growth for two main reasons First, foreign investment is considered an important source of capital to supplement Second, foreign investment creates opportunities for poor countries to access more advanced technology, facilitate technology transfer, promote the dissemination of knowledge, and improve skills This effect is considered as a spillover effect of foreign investment, contributing to increasing domestic enterprises' productivity and ultimately to economic growth in general So the spillover effect is an indirect effect that occurs when the presence of FDI enterprises causes domestic enterprises to change their behavior such as changing technology, changing production, and business strategies… Research questions, aim, and objectives The aim of this research is to investigate and assess the effects of two-way FDI and Environmental regulation on green innovation in ASEAN In order to achieve the research aim, the objectives of this study are to (1) investigate and analyze the relationship between twoway FDI and environmental regulation on green innovation in ASEAN and (2) propose possible solutions and policies for the government Therefore, the following research questions were formulated to support the paper’s objectives: Do inward FDI and outward FDI encourage the improvement of green innovation in ASEAN? What is the impact mechanism of environmental regulation on green innovation in ASEAN? What part does environmental regulation play in the two-way FDI process affecting green innovation in ASEAN? The effective answers to the above questions will be discussed in this paper Scope The scope of this study is limited to the following industries in 10 ASEAN countries: Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, the Philippines, Singapore, Thailand, and Vietnam Furthermore, in order to collect enough observations to generalize the sample and propose the most reliable result, this research will be studied in the time span of 11 years, from 2009 to 2019, before the outbreak of the Covid-19 pandemic SECTION LITERATURE REVIEW 1.1 Review of previous studies 1.1.1 Two-way FDI According to UNCTAD (2017), Foreign Direct Investment (FDI) is defined as an investment involving a long-term relationship and reflecting a lasting interest and control by a foreign direct investor or parent enterprise in one economy but not the economy of the foreign investors OECD Benchmark Definition of FDI (2008) recommended that FDI data can be presented under the directional principle to reflect the direction of influence underlying the direct investment Directionally, FDI is divided into inward foreign direct investment (IFDI) and outward foreign direct investment (OFDI) 1.1.1.1 Inward FDI When FDI flows inward, it means that its influence originates abroad and results in the establishment of a direct investment company in the host country (OECD, 2008) Therefore, inward FDI can be defined as the direct investment made by non-resident investors in the reporting economy Inward FDI includes all liabilities and assets transferred between resident enterprises and their direct investors It also covers transfers of assets and liabilities between resident and non-resident fellow enterprises, if the ultimate controlling parent is not a resident of the compiling economy (The World Bank) 1.1.1.2 Outward FDI In contrast to inward FDI, when FDI flows outward, it indicates that the influence giving rise to it originated within the compiling economy, and that it resulted in the establishment by a resident direct investor of a direct investment enterprise abroad (OECD, 2008) Thus, outward FDI can be defined as direct investment made by residents of the reporting economy to external economies, including assets and liabilities transferred between resident direct investors and their direct investment enterprises Moreover, OFDI also covers transfers of assets and liabilities between resident and non-resident fellow enterprises, if the ultimate controlling parent is resident (The World Bank) 1.1.2 Green Innovation Despite its positive influence on economic growth, FDI is concerned to have a potential negative environmental impact due to increased CO2 emissions In such a context, business innovation must be accompanied by sustainable development goals (Chang, 2011; Huang & Li, 2015) For this reason, Chen et al (2006) proposed the term "green innovation", which refers to designing green products or services that use natural resources to decrease environmental damage, save energy, prevent pollution, or enable waste recycling Green innovation can also be defined as a process that contributes to the creation of new products and technologies in order to minimize environmental risks such as pollution or resource exploitation (Castellacci and Lie, 2017) It ensures that natural resources are used in the most effective way possible Therefore, green innovation appeared to be a key impact factor in maintaining environmental management (Aguilera-Caracuel and Ortiz-de-Mandojana, 2013) as well as augmenting resource efficiency and creating an environmentally friendly society for sustainable development (Yin et al., 2018) Besides, green innovation can help achieve competitive advantages (Zimmerling et al., 2017), support strategic goals (Yang et al., 2016), and enhance positive performance in an organization (Roy and Khastagir, 2016) Undoubtedly, developing green innovation is vitally important for firms, especially in recent years ASEAN’s economy and enterprises are also accelerating towards green production for sustainable development For instance, in Vietnam, CIO (2018) reported that Vietnam’s investment in green technology has significantly improved the air quality 1.1.3 Two-way FDI and Green Innovation 1.1.3.1 Inward FDI and Green Innovation The relationship between FDI and green innovation has been paid attention to not only by environmental scientists but also by economic researchers; however, there is no consistent result The Pollution Halo Hypothesis claims that IFDI can improve the green innovation efficiency of a host country through green technology spillovers as the resident enterprises can improve their technological levels and therefore enhance their green innovation ability (Zarsky, 1999) Several empirical studies show that the greater the IFDI, the higher the technical and knowledge base of domestic firms, contributing to the development of green innovation In studying the influence of FDI on China‘s green innovation in manufacturing system (Bi et al., 2013), it is concluded that FDI inflows have a beneficial impact on green innovation competence, but have a negative impact on manufacturing green innovation people resources Moreover, Song et al (2015) found that not only has IFDI contributed to the rapid growth of China‘s economy, but also promoted the green innovation capability of Chinese enterprises through technology spillovers On the other hand, the huge inflow of foreign capital accompanied by environmental pollution and resource depletion seriously restricts the green development of the local economy (Singhania and Saini, 2021; Zhang and Zhou, 2016) The Pollution Haven Hypothesis (Walter and Ugelow, 1979) indicated that developed countries implement stricter environmental regulations than developing countries, resulting in the transfer of polluting industries among them That would further exacerbate the environmental pollution in developing countries (Güvercin, Handbook of Research on Economic and political implications of Green Trading and energy use 2020) Lifeng Chen, Fuxuan Guo, & Lingyan Huang (2023) investigate the impact of foreign direct investment (FDI) on green innovation in 31 provinces in China from 2003 to 2020 Results show that FDI has a positive and dynamic evolution feature, increases green innovation in eastern and western regions, and can positively moderate the impact of FDI on green innovation Based on the above literature, we propose the first hypothesis as follows: (H1) IFDI has a positive impact on green innovation 1.1.3.2 Outward FDI and Green Innovation In the analysis of green technology innovation, Jia et al (2014) found that China’s OFDI has promoted the knowledge and development of green technology in the home country Similarly, Gong et al (2017) found that OFDI might increase the efficiency of green industrial innovation through three mechanisms: agglomeration scale economic impact, agglomeration structure lightening effect, and agglomeration resource allocation effect In the same year, Cheng and Yang also arrived at the conclusion that OFDI has contributed to technological improvement in China During the process of investing in developed and developing countries, Chinese enterprises can bring certain green innovation resources to the home country through purchases, mergers and acquisitions and thus, enhance the capability of green innovation in China As Borensztein et al (1998) and Görg and Greenaway (2004) found that OFDI can promote technological development in the home country, they also claimed that there is a threshold effect related to the absorption capacity in the home country, specifically, human capital In addition, in their research on outward FDI and domestic innovation performance using data from China, Strange & Ning (2016) stated that in order for OFDI to generate technology spillovers to utilize new knowledge and turn it into usable one for application, human capital of the host country is required to reach a certain threshold Based on the above literature, we propose the second hypothesis as follows: (H2) OFDI has a positive impact on green innovation Degree of economic OPEN openness Total import and export % volume divided by GDP World Bank 2.3.2 Descriptive statistics and variables interpretation We use the “sum” command to determine descriptive statistics, number of Observations, Mean value, Standard Deviation, Min and Max of the variables The below table is a conclusion for the descriptive statistics of our sample data: Table 2: Descriptive statistics Variable Obs Mean Std Dev Min Max logGI 81 2.22699 9818595 -.6931472 4.256888 OFDI 94 8.64e+09 1.40e+10 -1.16e+10 6.61e+10 IFDI 110 1.26e+10 2.06e+10 -1.51e+10 1.05e+10 ER 36 3.236111 4998015 2.5 CI 110 31.16791 19.90151 3.21 90.43 GS 66 4797.683 2965.635 652.8694 9900.892 OPEN 110 39.29709 14.90176 12.32 65.32 The data of 10 ASEAN countries are from 2009 to 2019 with 110 observations ● logGI ranges from -.69% to 4.26% with mean value of 2.23% ● OFDI ranges from -1.16e+10 to 6.61e+10 with mean value at 8.64e+09 ● IFDI ranges from -1.51e+10 to 1.05e+10 with mean value at 1.26e+10 ● ER ranges from 2.5 to with mean value at 3.24 ● CI ranges from 3.21 to 90.43 with mean value at 31.17 ● GS ranges from 652.87 to 9900.89 with mean value at 4797.68 15 ● OPEN ranges from 12.32 to 65.32 with mean value at 39.3 2.3.3 Correlation matrix between variables The research group calculates correlation coefficients among variables by using the “corr" command The table as following is the correlation matrix between the variables that we use in the model: Table 3: Correlation matrix between variables logGI OFDI IFDI ER CI GS logGI 1.0000 OFDI 0.1662 1.0000 IFDI 0.1362 -0.0128 ER -0.4023* 0.0226 0.1162 1.0000 CI 0.1649 -0.0158 0.0769 -.02685* 1.0000 GS 0.4659* 0.2788* -0.0346 -0.3040* 0.1088 1.0000 OPEN 0.4529* 0.2760* 0.0161 -0.3214* 0.0171 0.5851* OPEN 1.0000 *p