Factors of Environmental Degradation and Economic Growth in Vietnam: The Role of Innovation

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Introduction Recently, the effects of economic activities on carbon emissions have aroused growing concern. This concern manifested itself worldwide through the organization of environmental conferences in Stockholm (1979), Rio de Janeiro (1992), Johannesburg (2002), Copenhagen (2009) and Durban (December 2011). Many countries including Vietnam are facing a major challenge, namely, the multi-directional links between economic, social and environmental aspects of development. Vietnam jointly with world organizations, such as the United Nations or the World Economic Forum, have made some attempts to reduce the adverse impacts of global warming and climate change on the economy. As an effort to mitigate greenhouse gas emissions, the Kyoto protocol to the United Nations Framework Convention on Climate Change was introduced. The objective of the 1997 Kyoto protocol was to reduce greenhouse gases by 5.2% compared to the level in 1990 (for the period from 2008 to 2012). Though Vietnam signed the Kyoto protocol to curb emission levels, there still exist environmental concerns due to the country’s recent economic growth. Over the past two decades, Vietnam has emerged as the fastest-growing greenhouse gas emitter (per capita) in the world - with an increase of about 5% annually [World Bank 2021]. Among important driving forces of economic growth, the energy sector dominates as a greenhouse gas emitter both in Vietnam and in the world. According to the World Resources Institute (2020), energy consumption is by far the biggest source of human-caused greenhouse gas emissions, responsible for a whopping 73% worldwide. On the other hand, in the process of socio-economic development of Vietnam over the last few decades, energy has played an important role not only as fuel for economic growth, but also as a principal contributor to the country’s export earnings, GDP and government revenues in Vietnam. Despite a significant contribution to Vietnam’s economy, energy with its accelerated exploitation of natural resources is posing serious risks to preservation and sustainable development of natural resources and is somewhat discouraging innovation and investment to build up new capacities instead of relying on natural endowments. Besides energy consumption, carbon emissions are also generated by other driving forces of economic growth, namely, urbanization, trade openness and innovation. In terms of urbanization, Vietnam is undergoing one of the fastest urban transitions in the world. The rapid urban expansion has seriously affected the environment quality and created harm to public health. With regard to the trade openness, trade liberalization has led to a higher level of investment; however, foreign investment mostly concentrates in pollution-intensive activities, so far. The digital era, with its technological innovation triggers energy efficiency and productivity, requires the response to the environmental challenge [Balsalobre et al. 2018; Samargandi 2017]. Hence, technological innovation plays an undoubtedly important role in mitigating carbon emission. However, the empirical nexus between innovation and CO2 emissions is not monotonic. This effect can differ across countries and regions, due to the regional properties, policies, infrastructures and nature of innovation itself. Therefore, the purpose of the study is to empirically examine the interaction between innovation, energy consumption, trade openness, urbanization, economic growth and the emission of carbon dioxide in Vietnam in 1986-2020, and to withdraw policy implications on Vietnam’s way towards green development. This article is organized as follows: Section 2 reviews the literature; Section 3 presents the research methods; Section 4 provides findings and discussions; Section 5 is the conclusion. Literature review and research statement The linkages between energy consumption, innovation, economic growth and carbon emissions have been examined in economic literature [Ali et al. 2017, 2018], Kumar and Managi [2009], Helpman [1998] and Shabax et al. [2012], Ozturk and Alumami [2011]. For each of the determinants, some empirical results have been found in the literature: Shabaz et al. [2013] and Ali et al. [2018] showed that the impacts of energy consumption on carbon emission are positive since high-temperature treatment in the production process resulting from energy consumption causes the emission of large amounts of carbon dioxide. As far as the impacts of innovation are concerned, the results are rather mixed. Fan et al. (2006) have indicated that technological innovation and CO2 are interconnected but they are different across the countries. Kumar and Managi [2009] showed that technological innovation mitigates carbon emission in developed countries, but it increases CO2 emission in developing economies. Meanwhile, regarding the pollution haven hypothesis, the expected impacts of trade openness on CO2 emission is found mixed in economic literature. While Nasir and Rehman [2001] and Haliciouglu [2009] support the pollution haven hypothesis i.e., a positive relationship between trade openness and carbon emissions, Helpman [1998] and Shabaz et al. [2012]suggest the opposite. Also, the impact of urbanization on CO2 emission was found ambiguous in the past research. While Wang et al. [2016], Dugan and Turkekul [2016] suggested a positive impact, York et al. [2003], Xu and Zhang [2016] and Ali et al. [2017] supported the negative one. Furthermore, the impact of economic growth on CO2 emission provides evidence regarding the environmental Kuznets curve. The carbon emissions increase as the economy grows at the early period of development of a country due to the extensive industrial-heavy production. However, as the national income becomes higher, the industrial-heavy production is phased out in favor of a technological advances and service-centralized production leading to a negative relationship between growth and environmental quality. This effect is therefore expected to be negative in the long-term according to Halicioglu [2009], Pao and Tsai [2011] as well as Ozturk and Alumami [2011]. As for the studies on Vietnam, Tang et al. (2016) and Nguyen and Le [2018] investigated relationships between economic growth and carbon emissions while Linh and Lin [2014] examined the linkages between energy consumption, economic growth and foreign direct investment. Tu [2021] has added another dimension by indicating that corporate environmental responsibility differs across company types (e.g., FDI, state or nonstate) while Cao [2017] showed an ambiguous impact of openness on environment. Le [2021] has investigated carbon emissions in the field of land use, land use change, and forestry in Vietnam mainland. Avitabile [2016] analyzed carbon emissions from land cover change in Central Vietnam. Despite the voluminous previous research that has explored the determinants of CO2 emission with practical implications, further research from various aspects especially on Vietnam is of great need due to many reasons. Firstly, a research examining impacts of innovation on carbon emission in Vietnam is missing, so far. Secondly, empirical investigations have shown mixed results that hamper policy making process; hence, a comprehensive research of factors affecting carbon emission in Vietnam including technological innovation is important. This article fills in this gap. Therefore, the present study contributes to the literature in several ways. Firstly, this study examines the effect of factors affecting CO2 emission by exploring the role of technological innovation, which recently has attracted little attention. Secondly, with the existence of innovation, this research investigates the pollution haven hypothesis in Vietnam by estimating impacts of trade openness. Thirdly, this study revisits the environmental Kuznets curve hypothesis with the existence of innovation in Vietnam: whether Vietnam is still on the “bad” side of the curve or the country starts to move to its “good” side. Fourthly, this research examines impacts of energy consumption and urbanization on carbon emission in the existence of innovation in Vietnam. Methodology Model and data This paper adopts the STIRPAT model to examine determinants of environmental deterioration as follows: ln⁡〖〖CO〗_2t 〗=α_1+α_2 ln⁡〖〖ENC〗_t 〗+α_3 ln⁡〖〖INNOV〗_t 〗+α_4 ln⁡〖〖TRO〗_t 〗+α_5 ln⁡〖〖UBN〗_t 〗+α_6 ln⁡〖〖GDP〗_t 〗+e_t, where CO2 denotes the carbon dioxide emissions measured in metrics tons per capita; ENC indicates the energy consumption per capita measured in kilograms of oil equivalent per capita; INNOV represents the innovation proxied by the R&D spending as percentage of GDP; TRO represents the trade openness - the sum of exports and imports of goods and services measured as a share of GDP; UBN (unsatisfied basic needs) means the annual urban population growth, a proxy for urbanization referring to people living in urban areas measured in percentage; GDP is the real GDP per capita (constant 2010 US dollars). The study employs annual time-series data covering the period between 1986 and 2020. The data for GDP per capita, CO2 emissions, energy consumption, innovation and urbanization have been received from the World Development Indicators of the World Bank (data.worldbank.org), while the source for trade openness data was the United Nations Conference on Trade and Development (unctadstat.unctad.org). All the variables have been transformed into their natural logarithms to run the model. In order to estimate the long-run and short-run effects of technological innovation, economic growth, urban population growth, energy consumption and trade openness on carbon emissions, this research uses the autoregressive distributed lag model (ARDL). The ARDL method has many advantages over the other co-integration methods. Firstly, its main advantage over traditional co-integration techniques is that ARDL is appropriate even when the order of integration of the variables is a mix of I(0) and I(1). Secondly, in a case of small sample size, ARDL approach is statistically more significant to test co-integration than the Johansen’s co-integration technique that requires large sample size to achieve reliability. Thirdly, in contrast to conventional methods for finding long-run relationships, the ARDL method does not estimate a system of equations. Instead, it only estimates a single equation. Fourthly, it can effectively correct the endogenous problem of explanatory variables. Last, it has the ability to estimate the short-term dynamic and long-term co-integration relationship between variables simultaneously. Empirical results Unit Root Test The application of ARDL model does not require all the variables to be single ordered stationary, however it must be confirmed that none of the variable is a second order stationary before applying ARDL bound testing approach. Therefore, the Augmented Dickey-Fuller (ADF) is used with results in Table 1. The test result confirms that LnCO2, LnENC, LnINNOV, LnTRO, LnGDP are stationary I(1) and LnURN is stationary at I(0) and I(1). According to Pesaran and Shin (2001, variables are not at the same level of association I(1) or I(0), then applying ARDL is the most relevant procedure. Table 1. Summary of Unit Root Testing Variables Augmented Dickey-Fuller I(0) I(1) LnCO2 0.161 -3.797 LnENC -0.062 -5.147 LnINNOV -2.57 -8.208 LnTRO -2.15 -5.517 LnURN -3.56 -3.96 LnGDP -0.704 -4.319 Test critical values 1% level -3.65 5% level -2.957 10% level -2.617 Source: Authors’ calculations The Bound Test As the number of observations in this research is small, it uses the AIC lag selection criteria. The optimum lag lengths of the variables CO2 emissions, energy consumption, innovation, trade openness, urbanization and economic growth are found (1,0,1,0,0,1). Therefore, the selected model is ARDL (1,0,1,0,0,1). After having selected the relevant lag, the results from the Bound test are shown in Table 2. Since the Bond F test is significant at 1%, the null-hypothesis of no-co-integration is rejected indicating that there is a long-run co-integration between CO2 emissions, energy consumption, innovation, trade openness, urbanization and economic growth. Table 2. Results of ARDL Bounding Test Model: LnCo2 = f(LnECN, LnINNOV, LnTRO, LnURN, LnGDP) Bond test F-statistic 4.245* Significance 1% Lower I(0) Bound 2.26 Upper I(1) Bound 3.35 Note: * indicate the significance level at 1%. Source: Authors’ calculations ARDL estimation results The result of the long and short run equilibrium relationship between the variables applying the ARDL (1,0,1,0,0,1) is summarized in Table 3. Table 3. Long and short run estimations Long run (Panel A) Short run (Panel B) Dependent variable: LnCO2 LnECN 1.058*** (0.135) ∆lnENC 1.0896*** (0.027) LnINNOV -0.211** (0.102) ∆lnINNOV -0.0157** (0.007) LnTRO 0.431** (0.204) ∆lnTRO -0.0635** (0.026) LnURN -0.053** (0.022) ∆lnURN 0.031 (0.151) LnGDP -0.673*** (0.141) ∆lnGDP 0.0517 (0.823) C -6.112*** (1.901) ECT(-1) -0.701*** (0.131) Diagnostic test F-statistic p-value RESET test 0.629 0.428 Breusch-Godfrey Serial Correlation LM test 0.862 0.353 Breusch -Pagan -Godfrey heterokedasticity test 0.016 0.899 Note: *** and ** denotes significant at 1% and 5% significance level, respectively. The standard errors in parentheses. ECT is error correction term. Source: Authors’ calculations It is noteworthy that coefficient of error correction term (ECT) is negative and significant at 1% level. A negative coefficient of error correction term (ECT) indicates the viability to achieve long-term equilibrium. The coefficient of ECT shows the rate of adjustment back to long-run equilibrium path. The estimations allow to conclude that when economy fluctuates from its equilibrium path, CO2 emissions can return to a long-run equilibrium. The ECT coefficient 0.701 shows that 70.1% adjustments occur during a year. Besides, to check the overall fitting of the model we use RESET test, LM test and Breusch-Pagan-Godfrey. The insignificant results of RESET test indicate that the overall fitting of the model is relevant. To determine the serial correlation in the estimated model, we employ Breusch-Godfrey LM test. The insignificant results of Breusch-Godfrey LM test have confirmed that there is no serial correlation. Finally, Breusch-Pagan-Godfrey heteroscedasticity null is no heteroscedasticity. Overall, it can be stated that model is appropriately specified and the results can be used for policy formulation. Findings and discussion Results of the long run estimation (Table 3-Panel A) shed lights on various aspects. It is seen that the relationship between innovation and CO2 emission is significant at 5% level. The negative coefficient indicates that the higher the rate of innovation the lower CO2 emissions are. This finding is encouraging since in Vietnam innovation is a new and important driving force of economic development, and the attention to and investment in innovation and technology have been rapidly increasing in current Vietnam. The Government has even set “Solidarity, discipline, innovation, inspiration for development” as the motto for 2021. The Ministry of Planning and Investment has actively developed and implemented the program to support digital transformation in 2021-2025. The goal suggests that by 2025, 100% of businesses should have their awareness of digital transformation increased and at least 100,000 businesses should receive technical support for digital transformation. This article provides evidence to expect the environment upgrading in Vietnam will result in a more developed innovation ecosystem. Our result is supported by the endogenous growth theory indicating that technological progress improves the capability of a nation to replace the polluting resources with other environmentally friendly resources. Our results are in line with the studies of Fernández et al. [2018]. Furthermore, the effect of trade openness on CO2 emissions is found positive and significant at 5% level that confirms the existence of “pollution haven hypothesis” in Vietnam. Along with the process of opening up, Vietnam has been under a lot of pressure on environmental deterioration, and has put much effort on reducing this negative effect of openness. Virtually, the ongoing draft Law on Environmental Protection (amended) is expected to prevent and screen projects with outdated technology for foreign investment in Vietnam, and creates a favorable legal environment for Vietnam to join new- Free Trade Agreements (FTAs) generation that requires very strict environmental commitments such as the Vietnam-EU FTA (EVFTA). Our finding reaffirms that openness increases the environmental deterioration in Vietnam, suggests that the government should take more drastic action on this issue. The result also shows that the relationship between energy consumption and CO2 emission is positive and significant at 1% level that indicates that the higher the energy consumption the higher the CO2 emissions result is. Virtually, total electricity consumption in Vietnam has tripled in the past ten years, faster than electricity production. With an increasing reliance on fossil fuels, the energy sector in Vietnam currently emits nearly two-thirds of the country's total greenhouse gas emissions [World Bank, 2021]. It can be stated that the main culprit behind increasing CO2 emissions in Vietnam is energy consumption. Our finding really sets an urgent need to accelerate the transition to clean energy in Vietnam. Turning to urbanization, the finding reveals a negative and significant impact of urbanization on carbon emissions in Vietnam, which means that urban development is not an obstacle to the improvement of environmental quality. The impact of urbanization on the environment is not monotonic, but very complex via many different, sometimes contradictory, channels. The likely reason is that the positive effect of urbanization that push the polluting industries away from the city, setting up the commercial and service sectors instead may dominate all the negative effects. Our finding shows the initial effectiveness of urbanization policy in Vietnam. Vietnam moves in the right direction; the urbanization policy should be forced towards green cities to take advantage of this positive effect. Hence, urbanization should not be considered an obstacle when initiating policies that will be used to reduce environmental deterioration in Vietnam. The relationship between economic growth and CO2 emissions is negative and significant at 1%. It shows that Vietnam has reached the environmental Kuznets curve turning point of income level. Virtually, Vietnam approved the National Green Growth Strategy (VGGS) for the period 2011-2020 with a vision to 2050 with a focus on low-emission development, reduced GHG emission, green production, green lifestyle and sustainable consumption. After almost ten years of implementation, it helped raise public awareness about the significance of green growth. Measures to cut greenhouse gas emissions were carried out widely, resulting in such emissions falling 12.9 per cent compared to the normal development scenario. In particular, outstanding loans funding green growth stood at nearly VND238 trillion (USD10.36 billion) by 2018, or 235 per cent higher than in 2015 [New Green Growth Strategy: 18.05.2021]. This article shows evidence that Vietnam’s growth reduces the environmental deterioration which can prove the success of the current VGGS. The finding also supports a new national strategy on green growth for 2021-30 being drafted by the MPI with a stronger commitment to make Vietnam a carbon-neutral economy as soon as possible [MPI 2021]. The error correction model employing ARDL approach to measure the short-run dynamic relationship between CO2 emissions, energy consumption, innovation, trade openness, urbanization and economic growth. The results are shown in Table 3-Panel B. With regards to innovation and energy consumption, the impacts in short run and long run reveal to be like. Turning to the effects of urbanization and economic growth on CO2 emissions in the short-run, the model suggests no statistical evidence for this interaction. The only attention is paid on the impact of trade openness. Trade openness has negative impact on CO2 emissions, and it is significant at 5% level in the short run, while it is positive and significant in the long run. This result shows that Vietnam puts efforts to reduce the impact of trade openness on CO2 emissions in the short-run; however, the policy formulation and implementation is not good enough for that effect to persist in the long run. This result insists that policy makers should amend the Law on Environmental Protection, as far as better management of international integration activities related to environmental protection is concerned.

About the authors

Thi Mai Phuong Chu

Foreign Trade University

Email: maiphuongchu@ftu.edu.vn
Ph.D. (Economics), Lecturer, Faculty of International Economics, Foreign Trade University, Hanoi Hanoi

Thuy Anh Tu

Foreign Trade University

Email: thuyanh.tu@ftu.edu.vn
Ph.D. (Economics), Assoc. Prof., Editor-in-Chief of Journal of International Economics and Management, Head of Department of Applied Economics, Faculty of International Economics, Foreign Trade University, Hanoi Hanoi

Thi Thanh Binh Dinh

Foreign Trade University

Email: binhdtt@ftu.edu.vn
Ph.D. (Economics), Head of Department of Econometrics, Faculty of International Economics, Foreign Trade University, Hanoi Hanoi

References

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