Analysis of the Factors Affecting Environmental Pollution for Sustainable Development in the Future—The Case of Vietnam

Abstract

In many studies in Vietnam, the scientists only focus on economic growth and attracting foreign direct investment. Environmental pollution has not been paid much attention in Vietnam. Therefore, this paper aims to identify the factors affecting environmental pollution in Vietnam. The author gathered the annual information based on World Bank data from 2000 to 2022. Data were processed via STATA 16.0; linear regression was used in this research. The results show that renewable consumption, economic growth and foreign direct investment inflow positively affect environmental pollution in Vietnam. Renewable consumption, foreign direct investment and economic growth have a strong effect on Vietnam’s environmental pollution. The empirical results show that if renewable consumption increases 1% then CO₂ emission will increase 1.19%; if FDI inflows increase 1% then CO₂ emission will increase 1.39%; and if GDP increase 1% then CO₂ emission increase 1.26%. This research also gives some solutions with which Vietnam could develop a green and sustainable economy in the future.

1. Introduction

Foreign direct investment (FDI) plays important roles in economic growth in developing countries [1]. Developing countries need to attract foreign direct investment (FDI) in order to develop the economy. International and multinational groups prefer to invest in developing countries such as Vietnam due to the young population and low labor costs. Their investments in Vietnam also create more CO₂ emissions; therefore, the air is affected by environmental pollution [2]. In recent years, the Vietnamese government has focused on economic growth and protecting the environment. For example, farmers are encouraged to use more organic fertilizers to reduce greenhouse gas emissions [3]. The Vietnamese government has a policy to attract FDI to build a waste factory for sustainable solid waste management [4].

Banerjee, K. et al. studied the FDI inflows in ASEAN+4 and BCIM, BIMSTEC+1 countries [5]. Bassey Enya, N. et al. focus on the corruption and economic growth in Nigeria. They use the Autoregressive Distributed Lag Approach (ARDL) [6]. Khan, H. et al. discuss the relationship between innovations, energy consumption and carbon dioxide emissions in the global world countries [7]. Raihan, A. et al. explain the nexus between energy use, industrialization, forest area and carbon dioxide emissions with new insights from Russia [8].

Xuan et al. (2020) researched the factors affecting foreign direct investment (FDI) in Vietnam [9,10,11,12]. FDI funds play important roles in the country’s economic development. However, environmental pollution problems are also of concern within the Vietnamese government. Vietnam’s policies focus on economic growth, and on attracting FDI but decreasing CO₂ emissions in order to achieve sustainable development in the future. Therefore, financial development and renewable consumption are important factors in Vietnam [13].

In this paper, the author refers to the determinants affecting the CO₂ emissions for the period of 2000–2022. The results given in this paper are of importance for the Vietnamese government in their efforts to develop the economy and protect the environment in the future.

The study consists of 5 sections. Following Section 1, introduction to the topic, Section 2 presents literature review. Section 3 contains the data and methodology. Section 4 presents the study conducts data description and regression analysis, the results of the research. Section 5 provides conclusions and suggests policies based on the results.

2. Literature Review

The relationship between economic growth and FDI and environmental pollution is discussed in many papers. Le, T.T.H. et al. (2022) showed that environmental pollution and FDI positively affected the GDP in Vietnam [1]. Joo et al. (2022) also showed a positive relationship between FDI and economic growth [14]. In addition, they found that variance in host country characteristics also affected economic growth.

Chen, N. et al. referred the sustainable development of economy. They said that the development of night-time economy in South Korea help reduction in CO₂ emission [15].

Fadly, D. focused the environmental management standard in Vietnam. He discussed the sustainability efficiency of Vietnamese firms that care about green industry, which means the necessity to reduce CO₂ emission [16].

Nguyen (2016) also showed that regional characteristics affected the ability to attract FDI in Vietnam [17].

Fiori, A. referred to a model to develop sustainability in the hospitality FDI of small and medium enterprises [18]. Flammini, A. et al. suggested a product involving activated carbon in coffee shops in Vietnam. They also addressed the circular economy within the green product market [2]. Khan, H. also showed a relationship between the innovations and global energy consumption on CO₂ emission. This research is quite new and has attracted the attention of many researchers all over the world [7].

Le, T.T.H. et al. focus on the impacts of environmental pollution and foreign direct investment on economic growth in Vietnam with a Non-Linear ARDL Co-Integration Approach. This method is quite new and helps to explain the economic growth in Vietnam in recent years [1].

Li, M. et al. show the rise of the integrations of regions in China. They noted that the sustainability development of the economy needed the integrations, green economy and reduction in carbon dioxide emission [19].

Liem, L.T.T. et al. show that using organic fertilizer in a province in Vietnam Mekong Delta region helped the reduction in environmental pollution. They suggested the Vietnam government should promote the policies using the organic fertilizer [3]. Nguyen, T.T. et al. referred to the role of organic waste material in Southeast Asian Countries. The policy marker needs the financial sponsor to green waste material [13].

Phan, T.H. noted the relationship between working conditions, export decisions and firm constraints to sustainability development of Vietnam small and medium enterprises [20]. Phan, T.H. et al. also referred to export decisions and credit constraints to sustainability development of Vietnam firm in recent year [21].

Raihan, A. et al. studied the impacts of industrialization, energy consumption and forest area on CO₂ emission at Russia [8]. They discuss that carbon dioxide (CO₂) emissions, contribute significantly to global climate change, which, in turn, threatens the environment, development and sustainability.

3. Data and Methodology

3.1. Data

The author collected data based on the World Bank indicator from 2000 to 2022, including the following.

CO₂ emissions (million ton per year) measure the environmental pollution in Vietnam; renewable consumption (TWh) refers to the amount of green electricity generated per year, such as wind, water and solar electricity. FDI inflows in Vietnam are measured in USD, and GDP denotes economic growth, measured in USD.

3.2. Methodology

The following research diagram, shown in Figure 1, was used in this study.

The research model is as follows.

We have the functions Y = F(X1, X2, X3…), in which the variances are

• Y: CO₂ emissions, which measures environmental pollution;
• X1: renewable consumption;
• X2: FDI inflows;
• X3: Gross domestic product (GDP).

The author uses linear regression analysis, as shown in Equation (1), such as

Y = Bo + B1X1 + B2X2 + B3X3 + ε

(1)

The authors assume that the functions between the dependence variable (Y) and the independence X1, X2, X3 are linear line curve to simple analysis, in which we can see the variances as follows:

Y: dependence variable is CO₂ emissions; the unit is million tons. This measures environmental pollution at the particular time.

Bo: A constant is the CO₂ emissions when X1 = 0; X2 = 0; X3 = 0. It means the CO₂ emissions are measured in millions of tons, assuming the renewable consumption equals zero, FDI inflows equal zero and Gross domestic product equal zero.

X1: independence renewable consumption measured by green energy from solar, wind and water electricity; the unit is TWh.

X2: independence variable FDI inflows measured by foreign direct investment inflows to Vietnam; the unit is billions of USD.

X3: independence variable GDP- gross domestic product, the unit is billions of USD.

Specifically, the following hypotheses are tested:

Hypothesis 1 (H1)

: Renewable consumption affects CO₂ emissions.

Hypothesis 2 (H2)

: FDI inflows affect CO₂ emissions.

Hypothesis 3 (H3)

: GDP affects CO₂ emissions.

The independent variables considered in the linear regression model are described in

Table 1. Interpretation of the independent variables in the linear regression model.

Variable	Explanation	Expected
X1	Renewable consumption, such as water, solar or wind electricity consumption.	−/+
X2	Foreign direct investment (FDI) inflows in Vietnam.	−/+
X3	Gross domestic product (GDP)	+

(Sources: complied by author).

.

4. Results

The link between FDI inflows, environmental pollution and economic performance has been widely discussed in recent years. However, there is a shortage of research on the impacts of FDI, renewable consumption and economic growth on CO₂ emission in Vietnam. Empirical studies have shown that CO₂ emission can foster firm growth as well as the economy in general. Therefore, the authors study the impacts of renewable consumption, FDI inflows and economics growth on environmental pollution. This research helps the policy maker pay attention to the protect environment for sustainability development in Vietnam. The description analysis is presented in

Table 2. Description analysis of the variables.

Variable	Obs	Mean	Std. Dev.	Min	Max
Country	Vietnam
Code	VNM
Year	23	2011	6.78233	2000	2022
CO2 Million ton	23	151.1594	69.23378	52.601	269.7901
Renewable	23	124.723	77.68318	40.419	288.9172
FDIUS	23	9.39 × 109	7.34 × 109	1.30 × 109	2.80 × 1010
GDPUS	23	1.52 × 1011	1.05 × 1011	3.12 × 1010	3.88 × 1011

(Sources: compiled by author).

.

The data collected in Vietnam from 2000 to 2022 provided 23 observations. Dependence Y is CO₂ emissions, with a mean of 151.16 million tons per year, a minimum value in 2000 of 52.6 million tons and a maximum value in 2022 of 269.79 million tons.

Independence X1 is renewable consumption, with a mean of 124.723 TWh, a minimum value in 2000 of 40.419 TWh and a maximum value in 2022 of 288.9172 TWh.

Independence X2 is FDI inflows, with a mean of USD9.39 billion, a minimum value in 2000 of 1.3 billion USD and a maximum value in 2022 of USD 28 billion.

Independence X3 is GDP, with a mean of USD152 billion, a minimum value in 2000 of USD105 billion and a maximum value in 2022 of USD388 billion.

A graph of Y, X1, X2, X3 from 2000 to 2022 is shown in Figure 2 in which the vertical axes are as follows:

CO₂ emissions (Y) from 2000 to 2022, the unit is million tons.

Renewable consumption (X1) from 2000 to 2022: green electricity from solar, wind and water, the unit is TWh.

FDI inflows (X2) from 2000 to 2022: the foreign direct investment inflows to Vietnam; the unit is billion USD.

GDP (X3): gross domestic product from 2000 to 2022; the unit is billion USD.

The horizontal axes from the year 2000 to 2022.

The results of linear regression analysis between GDP (X3) and CO₂ emissions (Y) are shown in

Table 3. The linear regression between the GDP (X3) and CO₂ emissions (Y) from 2000 to 2022.

Source	SS		df	MS	No. of Observations = 23
					F(1,22) = 514.85
Model	605,125.877		1	605,125.877	Prob > F= 0.0000
Residual	25,857.5518		22	1175.34327	R-squared = 0.9590
			23	27,434.0621	Adj R-squared = 0.9572
Total	630,983.428				Root MSE = 34.283
CO2 Million ton	Coef.	Std. Err.	t	P > |t|	[95% Conf. Interval]
GDP Current USD	8.83 × 10−10 ***	3.89 × 10−11	22.69	0.000	8.03 × 10−10	9.64 × 10−10

(Sources: compiled by author). Note: *** p < 0.001.

. The p-value = 0.000 shows the correlation between the GDP and CO₂ emissions. The adj R-squared = 0.9572 indicates that 95.72% the GDP fluctuation can explain the CO₂ emissions.

The results of linear regression analysis show us the function between Y (CO₂ emissions) and X3 (GDP) in Equation (2), as follows:

Y = 25857.5518 + 8.83 × 10⁻¹⁰ X3

(2)

We can calculate the elasticity in 2022 of Y to X3 as EX3 = 8.83 × 10⁻¹⁰ × 388 × 10⁹/269.79 = 1.26.

These results indicate that if the Vietnamese GDP increases by 1%, then the CO₂ emissions will increase by 1.26%. These values show that economic growth has significantly affected environment pollution in Vietnam for a long time. The results indicate that the problem needs to be reconsidered. Vietnam focused on economic growth for more than two decades, without considering the environment. The country maintained a high economic growth rate for 40 years, and the environment became polluted. Nowadays, Vietnam requires both economic growth and a clean environment in order to achieve sustainable development.

The results of linear regression analysis between renewable consumption (X1) and CO₂ emissions (Y) are shown in

Table 4. The linear regression between the renewable consumption (X1) and CO₂ emissions (Y) from 2000 to 2022.

Source	SS		df	MS	No. of Observations = 23
					F(1, 22) = 525.28
Model	605,618.783		1	605,618.783	Prob > F = 0.0000
Residual	25,364.6457		22	1152.93844	R-squared = 0.9598
			23	27,434.0621	Adj R-squared = 0.9580
Total	630,983.428				Root MSE = 33.955
CO2 Million ton	Coef.	Std. Err.	t	P > |t|	[95% Conf. Interval]
Renewable Consumptions	1.111116 ***	0.04848	22.92	0.000	1.010575	1.211658

(Sources: compiled by author). Note: *** p < 0.001.

. The p-value = 0.000 shows the correlation between the renewable consumption and CO₂ emissions. The adj R-squared = 0.9580 indicates that 95.80% of the change in renewable consumption can explain the CO₂ emissions. The results of linear regression analysis show us the function between Y (CO₂ emissions) and X1 (renewable consumption) in Equation (3), as follows:

Y = 25,364.6457 + 1.111116X1

(3)

We can calculate the elasticity in 2022 of Y to X1 as EX1 = 1.11 × 288.91/269.79 = 1.19

These results show that if renewable consumption increases by 1%, then CO₂ emissions will increase by 1.19%. The author suggests that the Vietnamese government should place a greater emphasis on renewable consumption in the future. In the long term, the more renewable electricity that is consumed, the lower the CO₂ emissions will be and the relationship between CO₂ emissions and renewable consumption will become negative.

The results of linear regression analysis between FDI (X2) and CO₂ emissions (Y) are shown in

Table 5. The linear regression between the FDI (X2) and CO₂ emission (Y) from 2000 to 2022.

Source	SS		df	MS	No. of Observations = 23
					F(1, 22) = 242.26
Model	578,454.171		1	578,454.171	Prob > F = 0.0000
Residual	52,529.2575		22	2387.69352	R-squared = 0.9168
			23	27,434.0621	Adj R-squared = 0.9130
Total	630,983.428				Root MSE = 48.864
CO2 Million ton	Coef.	Std. Err.	t	P>|t|	[95% Conf. Interval]
FDI US	1.34 × 10−8 ***	8.62 × 10−10	15.56	0.000	1.16 × 10−8	1.52 × 10−8

(Sources: compiled by author). Note: *** p < 0.001.

. The p-value = 0.000 shows the correlation between the FDI and CO₂ emissions. The adj R-squared = 0.9130 indicates that 91.30% of the change in FDI can explain the CO₂ emissions.

The results of linear regression analysis show us the function between Y (CO₂ emissions) and X2 (FDI inflows) in Equation (4), as follows:

Y = 52529.2575 + 1.34 × 10⁻⁸ X2

(4)

We can calculate the elasticity in 2022 of Y to X2 as EX2 = 1.34 × 10⁻⁸ × 28 × 10⁹/269.79 = 1.39.

These results show that if FDI inflows increase by 1%, then CO₂ emissions will increase by 1.39%. The author suggests that the Vietnamese government should place a greater emphasis on green FDI in the future. If this is implemented over the long term, the more FDI inflows received, the lower the CO₂ emissions will be, and the relationship between CO₂ emissions and FDI inflows will become negative.

5. Conclusions and Recommendations

The statistical results of the CO₂ emissions data show that several countries have achieved stable levels of CO₂ emissions; however, in Vietnam, levels of CO₂ showed an increasing trend from 2020 to 2022. This demonstrates that other countries are focused on and succeed in developing a green economy, while Vietnam has not yet successfully implemented policies towards a green economy, as it is a low-carbon-developed economy. We have developed the economy by attracting polluted FDI and focusing only on increasing the GDP without protecting the environment.

For Vietnam, with the levels of CO₂ continuously increasing in recent years, it is observed that Vietnam tends to import in industries that use a large amount of fossil energy (thermal power, etc.), with the technology used being obsolete. At the same time, this also indicates that the use of clean energy in Vietnam is not as effective as in other countries in the region. Given the advantages of exploiting the abundant fossil fuel resources, it is easy to fully utilize these resources. The promotion of clean energy development is, therefore, not considered urgent.

This paper shows that CO₂ emissions have a positive impact on the economic growth rate. This result contrasts those obtained in the studies of Omri et al. (2015) and Tang et al. (2015) [12,13]. However, these results are similar to those obtained in the study of Le et al. [1]. The results suggest that green growth will have a long-term impact on the economic growth of the country. At the same time, the study also confirms that using a large amount of fossil energy (coal, gas) or heavy industry will cause the economy to decline in the future. At the same time, CO₂ emissions also have an impact after 1 year; in other words, after CO₂ is released into the environment, it will only affect the economy after 1 year, and there is no immediate impact (the economy has not shown any signs of impact) of CO₂ emissions.

Furthermore, research results show that FDI has an impact on economic growth immediately and after 1 year; it can be observed that FDI investment is deployed rapidly in the host country. The rapid implementation within one year will lead to items related to construction materials and equipment for project construction being promoted more strongly. This study also has very clear implications for economic growth, which cannot exclude FDI. However, the issue of how to choose an investment partner, and the development of policies and solutions to enhance the attraction and efficiency of FDI, such as continuing to improve the legal framework of investment and amending investment incentive policies in the most favorable direction, are crucial. These efforts should be consistent, public and transparent. It is also necessary to adjust and supplement mechanisms and policies to encourage domestic and foreign private investors to invest in the field of infrastructure, and to perfect these mechanisms and policies so as to encourage the interest of appropriate and high-tech projects in other countries (especially developing countries such as Vietnam).

Vietnam should implement policies to attract FDI to stimulate domestic growth, because this capital source not only has a positive impact on economic development in the same fiscal year, but also has the ability to stimulate growth for at least one year thereafter. In addition, to boost GDP growth in the future, governments should also reconsider the use of fossil fuels, with the aim of promoting economic production activities at all costs. Thus, investing in energy-intensive industries is also not a wise choice for sustainable economic development.

This paper has some limitations, such as the authors do not refer to the impacts of innovations and forest area in Vietnam on environmental pollution, similar to the papers of Raihan, A. et al. and Khan, H. et al. [7,8]. The authors hope that we can study these issues in Vietnam in the future.