Linking among economic growth, technology innovation, carbon dioxide emissions in Vietnam: evidence from three stage least squares models

Thi, Duyen My Thi; Hong, Hue Trinh Hoang; Tran, Tinh Do Phu Article Linking among economic growth, technology innovation, carbon dioxide emissions in Vietnam: evidence from three stage least squares models Cogent Economics & Finance Provided in Cooperation with: Taylor & Francis Group Suggested Citation: Thi, Duyen My Thi; Hong, Hue Trinh Hoang; Tran, Tinh Do Phu (2024) : Linking among economic growth, technology innovation, carbon dioxide emissions in Vietnam: evidence from three stage least squares models, Cogent Economics & Finance, ISSN 2332-2039, Taylor & Francis, Abingdon, Vol. 12, Iss. 1, pp. 1-14, https://doi.org/10.1080/23322039.2024.2407237 This Version is available at: https://hdl.handle.net/10419/321610 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Cogent Economics & Finance ISSN: 2332-2039 (Online) Journal homepage: www.tandfonline.com/journals/oaef20 Linking among economic growth, technology innovation, carbon dioxide emissions in Vietnam: evidence from three stage least squares models Duyen My Thi Thi, Hue Trinh Hoang Hong & Tinh Do Phu Tran To cite this article: Duyen My Thi Thi, Hue Trinh Hoang Hong & Tinh Do Phu Tran (2024) Linking among economic growth, technology innovation, carbon dioxide emissions in Vietnam: evidence from three stage least squares models, Cogent Economics & Finance, 12:1, 2407237, DOI: 10.1080/23322039.2024.2407237 To link to this article: https://doi.org/10.1080/23322039.2024.2407237 © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group Published online: 25 Sep 2024. Submit your article to this journal Article views: 979 View related articles View Crossmark data Citing articles: 1 View citing articles Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=oaef20 DEVELOPMENT ECONOMICS | RESEARCH ARTICLE Linking among economic growth, technology innovation, carbon dioxide emissions in Vietnam: evidence from three stage least squares models Duyen My Thi Thi a,b , Hue Trinh Hoang Hong a,b and Tinh Do Phu Tran a,b a University of Economics and Law, Ho Chi Minh City, Vietnam; b Vietnam National University, Ho Chi Minh City, Vietnam ABSTRACT To accomplish the goal of net emissions to ‘zero’by 2050 while maintaining growth in Vietnam, interrelationship among technological innovation (TI), growth and emissions need to be considered. The goal of this research is to evaluate the bidirectional causality linkages among TI, growth and CO 2 emissions (CO 2 E) in Vietnam over the period of 1990–2021 by using the simultaneous equation model with the three-stage least squares models. Empirical results show the existence of bidirectional causality among growth, CO 2 emissions and TI. Specifically, growth positively influence on carbon emissions, and CO 2 emissions affect on growth positively. Furthermore, innovation positively influences on growth, while growth positively impact on innovation. There is a negative link among innovation and carbon emissions. Implying that innovation negatively effect on CO 2 emissions and carbon emissions has a negative influence on innovation. Findings indicate that growth contributes to environmental pollution in Vietnam, and technology innovation is an important factor for promoting economic growth and protecting the environment. Therefore, policymakers should encourage technology innovation for the advancement of clean energy, and apply advanced techniques in production to save fuel, contribute to protect the environment by reducing emissions. IMPACT STATEMENT The results of this research have considerable policy implications for Vietnam with respect to innovations, growth, and environmental quality. ARTICLE HISTORY Received 13 June 2023 Revised 17 September 2024 Accepted 17 September 2024 KEYWORDS Economic growth; technology innovation; CO 2 emissions; SEM; 3SLS; Vietnam SUBJECTS Sustainable Development; Environmental Economics; Economics 1. Introduction Global economies, including Vietnam, are aiming for sustainable development, reducing emissions by half by 2030 and achieving zero emissions by 2050, while ensuring growth. This can be done through applying technological innovation (TI) in production, and enhancing the use of clean technology. According to Stocker et al. (2013), carbon emissions is the main cause of greenhouse gas emissions globally. The research also found that 76.7% of greenhouse gas emissions caused by carbon emissions are mainly from developing nations in the world. Hope (2006) argues that although the change of climate may initially have some positive effects on many developed countries, in the long run, it will harm the environment. According to Grossman and Krueger (1995), growth pollutes the environment in the early stages, then improves as the nations reaches a certain level of income, as the adoption of better technology can reduce environmental degradation. It is necessary to encourage technology innovation to ensure energy efficiency and environmental sustainability while maintaining growth. Many studies indicated that higher growth through industrial activities lead to environmental pollution (X. Chen et al., 2023; Jiang & Liu, 2023; Raihan, 2023). However, others show the opposite outcomes (Mughal et al., 2022; Zhang, 2021). A lot of research showed that CO 2 emissions (CO 2 E) stimulate economic CONTACT Duyen My Thi Thi [email protected]; Hue Trinh Hoang Hong [email protected]; Tinh Do Phu Tran [email protected] University of Economics and Law, Ho Chi Minh City, Vietnam ß2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. COGENT ECONOMICS & FINANCE 2024, VOL. 12, NO. 1, 2407237 https://doi.org/10.1080/23322039.2024.2407237 growth (Iqbal et al., 2023; Olubusoye & Musa, 2020). On the other hand, some researches have explored that carbon emissions has a negative impact on economic expansion (Abdouli & Hammami, 2020; Abdouli & Omri, 2021; F. Sharif & Tauqir, 2021). Also, some works suggested that TI is an vital driver for economic development (Fan & Hossain, 2018; Manigandan et al., 2023). Meanwhile, others showed the opposite (Ayvaz & € Over, 2023; Mtar & Belazreg, 2023). Many studies explored that technology innovation may increase environmental quality by lessening emissions (Rafique et al., 2020; Saliba et al., 2022; Shahbaz et al., 2020). On the contrary, Demircan C¸akar et al. (2021) argued that innovation effect on CO 2 emissions positively. Several studies found the bidirectional relation among growth, innovation and CO 2 emission (Khan et al., 2023); and a bidirectional relation among growth and innovation (Mtar & Belazreg, 2023); bidirectional relation among growth and carbon emissions (Chang et al., 2023). Previous studies show that the interrelationship between innovation, growth and emissions is likely to exist. There have been no empirical studies investigating this relationship in Vietnam, and that is the gap for this study. After doi moi, Vietnam’s economic growth has changed significantly, namely the value of GDP per capita increased from 96.719 US $ in 1990 to 3756.489 US $ in 2021 (World Development Indicators [WDI], 2023), along with an increase in CO 2 emissions from 0.318 tons per capita in 1990 to 3.344 tons per capita in 2021. According to Raihan (2023) the consumption of energy and economic growth are responsible for emissions in Vietnam, the study suggest adoption of clean technology is necessary to lessen emissions, while ensuring growth. How to lessen emissions while maintaining economic growth is a challenge for policymakers in Vietnam. As suggested by Ren et al. (2021) and Khan et al. (2023) use a simultaneous equation model (SEM), namely applying three-stage least squares equation models (3SLS) to consider the interrelationship among growth, innovation and emissions because this method is considered more effective than other approach. Findings indicate that there exists a two-way relationship among growth, innovation and CO 2 emissions in Vietnam. Specifically, economic growth positively affects on CO 2 emission, and carbon emissions impact on growth positively. Furthermore, technology innovation has a positive influence on growth, and economic expansion positively influence on innovation. Moreover, there is a negative link among innovation and emissions. Empirical results support the view that innovation is an important factor in promoting growth and lessening CO 2 E. This research supplies to existing literature in some ways. Most of previous works assessed the one-way effect among variables. For instance, many studies have examined either the influence of innovation on CO 2 E or the influence of CO 2 emissions on innovation. Some researches have investigated either the effect of technology innovation on growth or the influence of growth on technology innovation. Likewise, most studies examined either the effect of growth on emissions or the effect of CO 2 emissions on growth. As suggested by Khan et al. (2023) showed that an interrelationship exists between innovation, growth and CO 2 emissions. Our research will accrete more proofs to the literature in Vietnam, by considering this interrelationship in Vietnam. From the results, some suggestions will be given to policy makers. The rest of the research follows the following structure: the literature review will be shown in Section 2, the methodology and data description will be shown in Section 3,Section 4 is about empirical outcomes and discussions, Section 5 represents conclusion. 2. Literature review 2.1. Studies on the linking among innovation and emissions Many researches have been conducted investigating the linkages between innovation and environmental pollution. Some studies have found that innovation slows down environmental degradation (Ahmed et al., 2022; Amin et al., 2023; X. Chen et al., 2023; Jena et al., 2022; Jin et al., 2022; Thi & Do, 2024; Razzaq et al., 2021), while others show the opposite outcomes (Demircan C¸akar et al., 2021; Khan et al., 2022; Raghutla & Chittedi, 2023). Additionally, some studies suggest that renewable energy (RE) and foreign direct investment (FDI) inflows help improve environment quality (Karaaslan & C¸amkaya, 2022; Samour et al., 2022), while growth and global tourism stimulate environmental degradation (Kumail et al., 2020; Nawaz et al., 2020; Raihan, 2023; Raihan et al., 2022). Furthermore, some articles investigated the response of innovation implementation in the context of increasing the change of climate. For the case of 70 countries, Su and Moaniba (2017) have investigated 2 D. MY THI THI ET AL. the response of innovation to climate change, they show that rising of emissions from gas and liquid fuels allow increase innovations, while increases in emissions from the use of solid fuel and other greenhouse gas emissions make reduce innovations. Besides, Khan et al. (2022) indicated that CO 2 emissions and the growth stimulate innovations while FDI lessen innovations. In contrast, Song et al. (2023) show that air pollution impedes urban innovation. Studies demonstrate the existence of a two-way causal relation among innovation and environmental pollution (Mensah et al., 2019). In general, many studies have examined either the influence of innovation on CO 2 E or the influence of CO 2 emissions on innovation. Our research will supplement to the existing literature on the link among innovation and CO 2 emissions by examining their interrelationship in the case of Vietnam. Thereby, the following hypothesis is formed: H 1 : There exists a two-way nexus among carbon emissions and innovation. 2.2. Studies on the nexus among innovation and economic development Many studies investigated the relation among technology innovation and growth, some studies have suggested that TI is a vital driver for economic development (Acheampong et al., 2022; Ahmad et al., 2023; Fan & Hossain, 2018; Thi & Do, 2024). However, some studies argued that TI has not yet promoted economic growth (Mtar & Belazreg, 2023). Moreover, some research found that growth pressure reduce innovation (Shen et al., 2021; Yu et al., 2023). For examples, Mtar and Belazreg (2023) investigate linkages among innovation, trade, financial development (FD) and growth applying a panel-a vector autoregression (VAR) approach and found that a negative relation among innovation and growth. Yu et al. (2023) indicate that growth pressure negatively affects green technology innovation, using data from 285 cities in China from 2006 to 2018. Shen et al. (2021) found that growth targets negatively influence on innovation in 244 cities of China from 2004 to 2016. Meanwhile, Khan et al. (2023) showed that economic growth increase innovation. Other research showed the interrelationships among innovation and growth (Akinwale, 2022). Khan et al. (2023) indicated a bidirectional causality among innovation and growth. Akinwale (2022) showed a bidirectional among innovation and growth for 1985–2015 period in South Africa. Maradana et al. (2019) showed a nexus among innovation and growth for 19 European nations from 1989 to 2014. Pradhan et al. (2018) indicated a bidirectional among innovation and growth in 49 European nations from 1961 to 2014. In general, most studies have investigated either the effect of technology innovation on growth or the influence of economic growth on technology innovation. There exists a two-way nexus among innovation and growth (Khan et al., 2023). Our research will supplement to the existing literature on the nexus among innovation and growth by examining their interrelationship in the case of Vietnam. In general, the following hypothesis is formulated: H 2 : There is a bidirectional relation among technology innovation and economic growth. 2.3. Studies on the link among economic development and CO 2 emissions Many works have analyzed the link among economic development and environmental pollution. Some studies show that CO 2 emissions promote the economic growth (Iqbal et al., 2023; _ Inal et al., 2022; Olubusoye & Musa, 2020). On the other hand, some researches have found that CO 2 emissions has a negative influence on economic expansion (Abdouli & Hammami, 2020; Abdouli & Omri, 2021; F. Sharif & Tauqir, 2021). Besides, others explored that economic growth harms the environment by increasing CO 2 E (Bhuiyan et al., 2023; Mamkhezri & Khezri, 2023; Raghutla & Chittedi, 2023; Raghutla & Kolati, 2023; Raihan & Tuspekova, 2023). Meanwhile, some studies show that GDP growth curbs emissions (Mughal et al., 2022; Zhang, 2021). Some studies show a two-way causal relationship among economic growth and CO 2 emissions (Naseem et al., 2023; You et al., 2022). COGENT ECONOMICS & FINANCE 3 In general, many studies examined either the effect of growth on emissions or the effect of CO 2 emissions on growth. Therefore, we will put on more proofs to existing literature on interrelationship among emissions and growth in the case of Vietnam. Thereby, the following hypothesis is formed: H 3 : There is a bidirectional relation among carbon emission and growth. 3. Methodology 3.1. Data and variables This article analyzes the linkages among TI, economic growth and CO 2 emissions in Vietnam from 1990 to 2021. The data of all variables have collected from Our World in Data, International Monetary Fund and World Bank by using the 3SLS. Table 1 presents details of variables 3.2. Theoretical framework and methodology Ehrlich and Holdren (1971) first proposed the IPAT (Impact by Population, Affluence, and Technology) model to measure the effect of economic growth on the environment degradation. Dietz and Rosa (1994) reconstructed the IPAT model in a stochastic form called the STIRPAT model to test the hypotheses more rigorously. The general STIRPAT model is represented as follows: It¼aPb tAc tTd tet, (1) where I,P,Aand Trepresent environmental degradation, the size of population, national influence and the progress of technology, respectively. ais the intercept term, b,cand dshow elasticities of the environmental influence on P,Aand T, respectively. e t is a random error term, and subscript tindicate the time dimension of model. To evaluate the link among innovation, growth and CO 2 emissions in Vietnam, authors extend the STIRPAT model according to the STIRPAT theoretical framework. More specifically, based on the original model, labor force, the capital stock, FDI inflows, RE consumption, tourism, corruption and FD are included in the new expansion models. 3.2.1. Economic growth model Achieving the goal of sustainable, zero-emissions development by 2050 requires that investment factors for economic development such as capital, labor force and energy be combined and used in an ecofriendly manner environment. Economic expansion requires higher energy consumption, which has a negative impact on the environment, TI can help promote growth, minimizing harmful influence on the environment. Based on STIRPAT model and inheritance from previous studies (Abdouli & Omri, 2021; Table 1. Details of variables. Variables Symbol Variables measurement Data source Carbon dioxide emissions CO 2 Annual CO₂emissions (tons per capita) (Our World in Data-OWID, 2023) Gross domestic product GDP GDP per capita (current US$) (WDI, 2023) Technology innovation TI Patent applications, residents (WDI, 2023) Renewable energy RE Renewables (% equivalent primary energy) (Our World in Data-OWID, 2023) FDI inflows FDI FDI, net inflows (% of GDP) (WDI, 2023) Tourism Tourism International tourism, number of arrivals (WDI, 2023) The capital stock K Gross fixed capital formation (constant 2015 US$) (WDI, 2023) Labor force L Labor force participation rate, total (% of total population ages 15–64) (WDI, 2023) Control of corruption CC Control of Corruption captures perceptions of the extent to which public power is exercised for private gain, including both petty and grand forms of corruption (WDI, 2023) Financial development FD Financial development index (International Monetary Fund, 2023) WDI, World Development Indicators. 4 D. MY THI THI ET AL. _ Inal et al., 2022; Khan et al., 2023; Meirun et al., 2021; Mtar & Belazreg, 2023; X. Wang et al., 2023)to fully understand the influence of CO 2 E(I), TI (T), labor (P) and other factors (U) on the growth (GDP) is built as follows: GDPt¼a1Ib1 tTc1 tPd1 tUe1 te1t, (2) where a 1 is the intercept term, b 1 ,c 1 ,d 1 and e 1 show elasticities of the growth influence on I,T,Pand U, respectively. e 1t0 is a random error term, and subscript tindicate the time dimension of model. 3.2.2. Environmental pollution model According to Raihan and Tuspekova (2023); Raihan and Voumik (2022); Ren et al. (2021) and W.-Z. Wang et al. (2021) economic expansion and international tourism causes harmful effects on the environment while TI, REC, FDI inflows allows to reduce environmental degradation, based STIRPAT model and the inheritance from previous studies, to fully understand the influence of economic growth (A), technology innovation (T), labor (P) and other factors (X) on carbon emissions (I) is developed as follows: It¼a2Ab2 tTc2 tPd2 tXe2 te2t, (3) where a 2 is the intercept term, b 2 ,c 2 ,d 2 and e 2 show elasticities of the environmental influence on A,T, Pand X, respectively. e 2t0 is a random error term, and subscript tindicate the time dimension of model. 3.2.3. Technology innovation model Ahmad et al. (2023) show that innovation play a vital role for sustainable development, helping economic expansion without harmful effects on the environment. Furthermore, there are many studies investigating the response of innovation to increasing the change of climate and economic growth (Khan et al., 2022; Su & Moaniba, 2017). Based on the inheritance of previous studies (Akinwale, 2022; Dauda et al., 2019; Naseem et al., 2023; A. Sharif et al., 2023), to more fully understand the influence of economic expansion (A), CO 2 E(I) and other factors (Y) on innovation (T) is built as follows: Tt¼a3Ab3 tIc3 tYd3 te3t, (4) where a 3 is the intercept term, b 3 ,c 3 and d 3 show elasticities of the TI influence on A,Iand Y, respectively. e 3t0 is a random error term, and subscript tindicate the time dimension of model. According to the above analytical framework, to comprehensively study the linking among the growth, innovation and CO 2 E in Vietnam, based on the STIRPAT model, and the inheritance from previous studies, this study utilizes, labor force, the capital stocks, FDI inflows, the use of RE, tourism, corruption and FD as control variables. TI, growth, and CO 2 emissions represent three endogenous variables in this paper. To solve concurrency among innovation, growth and emissions (cause of endogeneity), the SEM combined with threestage least squares is applied. Because this method is considered more effective than two-stage least squares method (3SLS) (Belsley, 1988; Intriligator, 1978). As suggested by Malik (2021) and Gani (2021), a SEM combined with 3SLS, will be used in our study. The econometric model is presented as follows: GDPt¼a0þa1CO2tþa2TItþa3FDItþa4Ktþa5Ltþe1t, (5) CO2t¼b0þb1GDPtþb2TItþb3FDItþb4REtþb5TOURISMtþe2t, (6) TIt¼l0þl1CO2tþl2GDPtþl3FDItþl4CCtþl5FDtþe3t, (7) where CO 2 emission is measured by annual carbon dioxide emissions (tons per capita); GDP is measured by gross domestic product per capita (current US$); TI proxy by the number of patent applications, residents; FDI is measured by foreign direct investment, net inflows (% of GDP); The capital stocks (K) proxy by gross fixed capital formation (constant 2015 US$); Labor force is measured by the rate of labor force participation, total (% of total population ages 15–64); RE is measured by renewables (% equivalent primary energy); Tourism is measured by international tourism (number of arrivals); Control of corruption (CC) is measured by the extent to which public power is exercised for private gain, including both petty and grand forms of corruption; FD is measured by FD index; a 0 ,b 0 and m 0 are intercept, a 1, a 2, a 3, a 4, a 5, COGENT ECONOMICS & FINANCE 5 b 1, b 2, b 3, b 4, b 5 , and m 1, m 2, m 3, m 4, m 5 indicate the coefficients, ¾ 1t0 ,¾ 2t0 and ¾ 3t0 are errors term, tindicates the time dimension. 4. Results and discussions In this work, we present the outcome of the link among innovation, economic growth and emissions. Variables descriptive statistics outcomes are shown in Table 2, describing characteristics of the variables used in the three-stage least squares equation model (3SLS). There is a difference among the average values of the variables. The variables maximum values such as GDP per capita and the capital (K) are higher than the values of other variables. We check the data with serial correlation test, Table 3 indicates that no high connection between independent variables utilized in Equations (1)–(3). The correlation coefficient among independent variables is less than 0.5, so the data is reliable and suitable for regression analysis. Before analyzing time series data, it is necessary to check the (non) stationarity of the data set. if authors apply a nonstationary series for regression, it will lead to the occurrence of pseudo-regression. Therefore, before performing regression analysis, authors need to check the robustness of economic variables. This article use augmented Dickey Fuller test to check the stationarity of data. Table 4 show all variables are stationary at first difference, therefore, it is appropriate to use them for further statistical analysis. Table 2. Statistical value of variables. Variables Mean Minimum Maximum Standard deviation GDP 1335.378 96.7193 3756.489 1221.11 CO 2 1.370059 0.307592 3.560416 0.9809968 TI 250.4839 22 1021 262.2487 RE 20.28217 12.84675 24.9727 3.399654 FDI 5.485844 2.781323 11.93948 2.219416 Tourism 5434000 1351000 18009000 4421609 K 49538849734 11110952440 110459947208.857 30887499453 L 79.84812 75.863 82.476 1.957135 CC −0.54632 −0.75666 −0.28578 0.12137 FD 0.322215 0 0.454462 0.101632 Data source: World Bank and International Monetary Fund. Table 4. Test unit root for each variable. Variables Level First difference GDP 3.538 (1.0000) −2.960 (0.0388) CO 2 1.340 (0.9968) −4.272 (0.0005) TI −2.676 (0.0782)−5.665 (0.0000) RE −2.464 (0.1245) −5.361 (0.0000) FDI −2.442 (0.1303) −4.835 (0.0000) Tourism −2.080 (0.2528) −5.364 (0.0000) K−1.737 (0.4122) −5.511 (0.0000) L−1.296 (0.6311) −3.077 (0.0283) CC −2.914 (0.0438) −11.453 (0.0000) FD −2.918 (0.0433) −6.198 (0.0000) p<0.01, p<0.05, p<0.1. Source: Author’s own compilation from data processing using Stata. Table 3. Correlations between variables. GDP CO 2 TI RE FDI Tourism K L CC FD GDP 1 CO 2 0.9761 1 TI 0.1341 0.0905 1 RE −0.0782 −0.229 0.2604 1 FDI −0.2479 −0.2685 −0.3013 0.1981 1 Tourism 0.2761 0.2675 −0.0658 −0.4344 −0.1689 1 K 0.4357 0.3751 0.2351 −0.2514 −0.1467 0.578 1 L 0.2623 0.1284 0.3249 0.4619 0.2084 −0.1338 0.0456 1 CC −0.7496 −0.7228 −0.2194 0.0061 0.1976 −0.3016 −0.3689 −0.084 1 FD 0.2818 0.2888 0.1769 −0.4019 −0.1981 0.3778 0.4292 0.3035 −0.1649 1 Source: Author’s own compilation from data processing using Stata. 6 D. MY THI THI ET AL. Next, authors proceed the 3SLS approach to consider interrelationships among growth, carbon emissions, and technology innovation. The three corresponding equations (Equations 1–3) are estimated simultaneously. 4.1. Our baseline results from 3SLS estimates Table 5 indicates the evidence of bidirectional causality among growth and CO 2 emissions, growth and technology innovation, CO 2 emissions and technology innovation. Therefore, H 1 ,H 2 ,H 3 hypothesis are accepted. Specifically, Table 5 reports that CO 2 emissions positively effect on growth at 1% significant level, showing that a 1% rise of emissions allow GDP per capital increase by 1175.065%. This results is the same with the finding of Ren et al. (2021) for China. They explored that CO2 emissions in the steel industry of China influence on growth positively. Similarly, Raihan (2024) have investigated the impact of FDI and CO 2 emissions on economic growth in Vietnam for 1990–2021 period. They found that CO 2 E has a positive influence on the growth in Vietnam. This is explained because during this period Vietnam’s economy witnessed rapid growth, GDP per capita increased from 96 US dollars in 1990 to 3756 US dollars in 2021. Also, during this period, Vietnam witnessed an increase in CO 2 emissions per capita from about 0.318 tons in 1990 to 3,345 tons in 2021. However, to achieve the goal of sustainable development, Vietnam’s emissions must halve by 2030 and reach zero by 2050. To achieve this goal, it requires policies for green growth to be implemented by all levels of government. Moreover, a positive and significant influence of innovation on growth is found at 1% level. The coefficient of innovation variable is 42.519, indicating that GDP per capital increase by 42.519 percent when there is a 1% rise in innovation. This outcome is consistent with empirical study of Meirun et al. (2021) for Singapore. This mean that the number of patent applications help promote growth. Similarly, research result by Thi and Do (2024) also show that innovation is an important factor promoting the economy of countries. This is also understandable because innovation allows the optimization of national resources with a reasonable and modern economic structure, in order to achieve high economic growth rates toward sustainable development. In Vietnam, during this period, innovation activities also increase significantly, which allowed to promote economic growth. Therefore, the Vietnamese government needs to have appropriate policies to promote sustainable growth in the coming time. Furthermore, FDI inflows are found to be a positive and significant correlation with GDP per capita with a coefficient of 51.835. Implying that 1% increase in FDI inflows will increase economic growth by 51.835%. This finding is similar with outcome of Khan et al. (2023) for 35 Belt and Road nations. Besides, Raihan (2024) show that FDI has a positive influence on the growth in Vietnam. During this period, Vietnam also relied on foreign direct investment to promote economic growth, accompanied by an increase in CO 2 emissions. Therefore, in the coming time, Vietnam’s economic growth based on scientific and TI is necessary because it allows reduce emissions and toward the goal of sustainable development. Besides, the capital and labour force positively impact on growth but not statistically significant. The empirical outcomes about Equation (2) illustrate that growth positively influence on CO 2 emissions. These outcomes are consistent with Thi et al. (2023) for 53 countries, Raihan (2023) for Vietnam, Karaaslan and C¸amkaya (2022) for Turkey. The findings show the growth reduce environmental quality by upsurging Table 5. Our baseline results from 3SLS estimates. Variables Equation 1: GDP Equation 2:CO 2 Equation 3:TI GDP 0.001 (0.00005) 0.022 (0.004) CO 2 1175.063 (83.818) −26.457 (5.270) TI 42.519 (8.815) −0.039 (0.012) RE −0.002 (0.008) FDI 51.835 (30.871) −0.048(0.026) −1.264(0.709) Tourism −0.002 (0.003) K 1.355 (3.712) L 6.903 (22.131) CC −0.019 (0.176) FD −0.022 (0.063) Constant −1791.688 (1685.547) 1.181 (0.240) 29.708 (7.589) p<0.01, p<0.05, p<0.1. Source: Author’s own compilation from data processing using Stata. COGENT ECONOMICS & FINANCE 7 Saliba, C. B., Hassanein, F. R., Athari, S. A., D€ ord€ unc€ u, H., Agyekum, E. B., & Adadi, P. 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