Outward Foreign Direct Investment and Corporate Environmental Investment: Competition or Cooperation?

Abstract

China is currently in a crucial phase of establishing a new domestic and international “dual circulation”, and a new model of sustainable development. OFDI and environmental investment play significant roles in both external and internal economic cycles. In this study, we constructed a multi-period difference-in-differences (DID) model, using data from listed companies in China from 2008 to 2022, to analyze how OFDI impacts domestic environmental investment and its underlying mechanism. The findings demonstrated that OFDI can significantly reduce the environmental investment made by domestic enterprises. There exists a capital competition relationship between these two activities due to financing constraints, although OFDI can mitigate environmental issues by reducing pollution emissions and promoting industrial structure upgrading within the home country, resulting in savings on environmental investments. Heterogeneity analysis revealed that the negative impact of OFDI on environmental investment is primarily observed in non-state-owned enterprises, firms investing in developed countries, and those subject to strict environmental requirements imposed by host governments. This study explains the internal logic of China’s environmental investment reduction from the perspective of OFDI, deepens the study of the environmental consequences of OFDI, broadens the applicable boundaries of the theory of OFDI’s impact on environmental investment, and provides insights for the government to establish a high-level opening-up pattern and address the dilemma of environmental governance.

1. Introduction

For many years, China’s high-pollution, high-energy-consumption, crude development model has put economic development and ecological civilization construction in an overlapping forward- and load-bearing state. Environmental investment is an important aspect of easing structural pressures on ecological and environmental protection and provides an important guarantee of sustainable economic development. The January 2024 State Council’s Guidelines for Enhancing the Development of Beautiful China emphasizes fostering high-standard ecological conditions to bolster quality growth. It urges expediting the establishment of a novel paradigm for Beautiful China, emphasizing the harmonious union between humanity and nature, and calling for anchoring the goal of the construction of a beautiful China, adhering to precise pollution treatment, scientific pollution treatment, and lawful pollution treatment, and increasing efforts towards solving ecological and environmental problems. This policy emphasizes the important role of environmental investment in improving the quality of the ecological environment and achieving sustainable economic development. However, according to the Ministry of Ecology and Environment (MEE), China’s total investment in environmental pollution control has been declining year by year as a share of GDP since 2010, with China’s total investment in environmental pollution control amounting to CNY 665.42 billion, or 1.86% of GDP, in 2010, and dropping to 0.7% of GDP by 2022. Meanwhile, China’s environmental governance has been effective, with the latest data from the Pollutant Information Disclosure Index (PITI), developed by the Institute of Public and Environmental Affairs (IPE), showing that China’s concentration of the key atmospheric pollutant PM2.5 has declined by about 50% from 2006 to 2023, and the proportion of surface water with poor water quality has fallen from 28% in 2006 to 0.7% in 2023. How can China ensure that environmental investment is lowered without lowering environmental quality? An in-depth analysis of this issue will be important for China and other emerging countries to further improve their environmental governance systems and enhance their sustainable economic development. This research attempted to analyze this issue from the perspective of outward foreign direct investment (OFDI).

The existing literature has focused mostly on the environmental impacts of OFDI on host countries. The “pollution paradise” group, represented by Copeland and Taylor (1994), He (2006), and Levinson and Taylor (2008) et al., believe that OFDI is an important factor in exacerbating the pollution problem in host countries [1,2,3]. The “pollution halo” faction, represented by Kirkpatrick C et al. (2005), Zhang and Zhou (2016), and Shao et al. (2021), believe that OFDI has the potential to drive advancements in corporate green technology and enhance corporate management efficiency in the host country [4,5,6]. Some researchers have also focused on the environmental effect of OFDI on home countries, but no consensus has yet been reached. Some researchers have argued that OFDI helps to improve enterprises’ environmental investment (Wang et al. 2022) [7], increasing the innovation of green technology (Zhang et al., 2023; Chaudhry, 2021; Ji and Mou, 2023) [8,9,10], promoting domestic green total factor productivity (GTFP) (Song et al., 2021) [11], optimizing the industrial structure and green technology development transformation, and reducing resource consumption and environmental pollution in domestic enterprises (Nie and Qi, 2019; Hao et al., 2020) [12,13]. There is also a view that OFDI can worsen the domestic environment, suggesting that OFDI by firms from countries with low economic development and a high share of manufacturing increases environmental pollution in home countries (Yu, 2017) [14]. OFDI has been reported to contribute to an increase in CO₂ emissions in the home country (Cheng and Huan, 2022; Yang et al., 2021; Tan et al., 2021) [15,16,17]. Shen Chen et al. (2022) reported that OFDI exhibits a U-shaped relationship with domestic GTFP. In the short term, OFDI is constrained by the scale effect and negatively impacts the pollution control efficiency and domestic GTFP [18]. Although there has been a useful exploration of OFDI and environmental issues in the literature, there are still deficiencies: In terms of research content, the literature focusing on OFDI and environmental issues concentrates on the consequences of environmental pollution and the effects on technological innovation of OFDI, pays little attention to the impact of OFDI on the governance process of environmental investment, and fails to explain the deeper reasons for the decreasing environmental investment in China in recent years from the perspective of the internationalization of enterprises. In terms of research mechanisms, the existing literature fails to study the internal logic of OFDI’s impact on environmental investment from the dual perspective of the competition effect and cooperation effect. This research was based on addressing the above issues.

Corporations constitute the primary contributor to environmental pollution, yet they also hold the pivotal role in environmental stewardship and funding. Thus, they stand as the cornerstone for driving sustainable development forward. Enterprise-based environmental investment for the implementation of environmental engineering projects and pollution management to provide financial security are important aspects of solving ecological and environmental problems. However, environmental investments involve substantial funding, significant unpredictability, lengthy payback periods, and personal expenses surpassing private gains. Moreover, they divert resources from production costs, misaligning with corporate objectives of maximizing profits. Consequently, enterprises often demonstrate limited eagerness to preserve the environment (Christainsen et al., 1980; Kachelmeier et al., 2008; Cao and Han, 2015) [19,20,21]. Only when enterprises are faced with life-and-death competitive pressures or strong profit drivers will they be motivated to participate in environmental governance and green production transformation, and OFDI provides such an opportunity for two reasons. OFDI and environmental investment both rely on a large amount of capital, and there is a capital-competitive relationship between them. In recent years, the Chinese government has been expanding the degree of openness, especially since the start of the “Belt and Road” initiative, and has introduced a series of incentives to encourage enterprises to actively participate in the international market. The degree of facilitation of outward foreign direct investment has been continuously improved, and as a result enterprises are increasingly active in implementing internationalization and participating in OFDI. Further, multinational enterprises have a natural advantage in learning and applying advanced environmental protection technologies in the host country, which helps domestic enterprises to transition to a sustainable development model and reduces their environmental governance costs. Especially after the official implementation of the new Environmental Protection Law in 2015, China has taken more stringent administrative regulatory measures and increased environmental penalties, which, coupled with the downward pressure on China’s economy in recent years, has resulted in a stronger demand from enterprises to reduce costs. The reverse spillover effect of OFDI is conducive to innovation among enterprises in clean production and pollution control technology, and the effect of industrial structure upgrading is conducive to the acceleration of green transformation and a reduction in pollution control costs in enterprises, thus forming a cooperative effect with environmental investment.

Seeking a broad international market with a comparative advantage in technology resources to carry out outward foreign direct investment is the rational decision of enterprises in pursuit of profit maximization. Utilizing OFDI to implement environmental governance from the source to the end, accelerate the green sustainable changes to enterprise production technology to reduce pollution emissions, and optimize the industrial structure to improve the efficiency of pollution treatment is the inevitable choice for enterprises to achieve long-term sustainable development. How does OFDI by enterprises affect domestic environmental investment? What are the underlying mechanisms? These were the main questions to be answered in this paper. The empirical results showed that enterprise OFDI reduces environmental investment in the home country. OFDI and environmental investment have both financial competition effects under financing constraints and cooperation effects, which together promote industrial structure upgrading and pollution emission reduction. The potential contributions of this study include using the characteristics of OFDI and environmental investment to reveal the reasons for China’s declining environmental investment while ensuring environmental quality and providing a reference for the sustainable development of emerging economies. Second, we explained the competition and cooperation mechanism of OFDI’s impact on environmental investment in terms of financing constraints and OFDI’s emission reduction effect and industrial structure upgrading effect, deepening the understanding of the environmental consequences of OFDI and providing ideas for the Chinese government to further build a high-level opening-up pattern and address the dilemmas of environmental governance. Thirdly, the heterogeneity of home countries, host countries, and OFDI enterprises broadens the application of the theory of the negative impact of OFDI on environmental investment, which provides a basis for multinational enterprises to optimize their OFDI decisions and realize green and sustainable development.

2. Theoretical Analysis and Research Hypothesis

2.1. OFDI and Environmental Investment

OFDI and environmental investment both rely on significant resources. An enterprise’s environmental investment in the home country will inevitably cause competition for resources with OFDI. Compared with OFDI, environmental investment is a passive investment. Environmental investment includes externalities and public goods, and the benefits generated are not only limited to the investors themselves, but also have a positive external impact on the whole of society, meaning individuals or enterprises will typically not carry out environmental governance (Clarkson et al., 2004; Orsato, 2006) [22,23]. As institutional theory suggests, government regulation is the primary driver of corporate environmental governance behavior (Berrone et al., 2013; Kang and He, 2018) [24,25]. Second, demand rigidity is insufficient. Although Porter’s hypothesis suggests that well-designed environmental regulations can drive firms to make environmental investments, improve production technology and product design to reduce compliance costs, and generate an “innovation compensation” effect [26], according to the factor endowment hypothesis, firms’ environmental investments are rational choices that weigh the costs of investment against the benefits of compliance [27]. Businesses frequently contemplate shifting operations to jurisdictions with relaxed environmental standards. This move not only allows them to bypass their home country’s environmental restrictions, thereby lessening domestic environmental investment expenses, but also presents opportunities to tap into the resources and markets of the host nation, ultimately seeking additional compensatory benefits. For this reason, OFDI can substitute for environmental investment. Additionally, environmental investment is not interest-driven. Enhancing and modernizing environmental management equipment and technology require research and development, testing, adjustment, and the consumption of enterprise resources, with high investment costs, a long payback time, and poor realizability [28]. It is difficult for the enterprise to obtain direct economic benefits [23,29]. Moreover, OFDI crowds out normal productive investment, which is the main source of corporate profits and cash flow. Despite the fact that environmental investments yield economic and societal dividends over the long haul, their short-term impact is challenged by the inherent externalities, making it challenging to immediately secure a direct influx of economic benefits, resulting in a potential imbalance between the cost of corporate pollution and the benefits of governance [30,31]. As a result, there is insufficient incentive for companies to make environmental investments. In contrast, OFDI is attractive in terms of addressing home country environmental issues and enterprise interests. First, reverse-gradient investment can promote the transfer of advanced technology from abroad to home country enterprises, which not only creates good external conditions for promoting the development of green and clean production by enterprises, but also facilitates the transformation and upgrading of other technologies. Secondly, down-gradient OFDI can place domestic industries at a comparative disadvantage, especially low-end manufacturing industries, which not only reduces domestic energy consumption and pollution, but also makes full use of inexpensive foreign factors and optimizes the layout of the industrial structure. Thirdly, horizontal OFDI can open the international market and reduce the environmental investment per unit of product through the scale effect. In summary, in developing countries with a relative shortage of capital, compared with environmental investment, OFDI is more attractive. Based on this, we put forward the following:

H1: 

OFDI will reduce the environmental investment of home country enterprises.

2.2. The Effect of Competition for Capital Due to Financing Constraints

Developing countries have the problem of capital scarcity, so overseas investment often raises concerns about economic activity in the home country, and it may reduce domestic economic activity [32]. In markets that are not fully efficient, the disparity in information and the expenses associated with transactions often lead to a higher cost of procuring external funding compared to utilizing internal sources of capital, and a company’s external financing activities are constrained to some extent [33]. In terms of capital demand, OFDI enterprises need to pay higher fixed costs and production variable costs when entering a new market [34], requiring a large amount of capital with higher risk and return uncertainty. These unfavorable investment characteristics increase the external financing cost and difficulty of OFDI, and imperfect financial markets and biased financing patterns in emerging markets will further exacerbate the capital constraints on OFDI firms [35]. From the angle of capital provision, the capital of Chinese OFDI enterprises mainly comes from their own funds and financial institutions in their home countries. According to the statistics of the CCPIT Research Institute, 70% of Chinese enterprises mainly rely on their own funds to make direct investments, and only 16% receive support from financial institutions for outward investment [36], so the utilization of foreign funds is very limited.

Both OFDI and environmental investment are characterized by long payback periods and uncertain returns, and financial institutions are not highly motivated to provide financial support. In addition, China’s domestic financial market is imperfect, financial inhibition exists, financial resources are relatively limited, and enterprise financing constraints are a reality. In the short term, the capital stock available for investment by enterprises in the home country is established, and there is significant capital competition between OFDI and environmental investment. OFDI is more attractive under the conditions of capital competition due to the reverse technology spillover effect, industry transfer effect, and scale effect compared with environmental investment, which is characterized by passive demand, insufficient rigidity, and lower returns. Superimposed on the high demand for funds for OFDI and the limited supply of funds in China’s financial market, OFDI squeezes the share of funds for domestic environmental investment. The more severe the financing constraints, the more environmental investment is vulnerable to the negative impact of OFDI in the competition for funds.

Accordingly, we hypothesized the following:

H2: 

The negative impact of OFDI on domestic environmental investment is mainly due to financing constraints.

2.3. Emission Reduction Effect of OFDI

The concept of sustainability and green production methods of multinational investment enterprises operating abroad have important spillover effects on the production methods and pollution control of domestic enterprises. Host country environmental regulations become external constraints for energy saving, emission reduction, and the green management of overseas subsidiaries. As the concept of sustainable development takes root in people’s minds, host countries are paying more attention to environmental protection issues, and environmental regulations and green requirements for foreign investment are becoming increasingly stringent. Since 2012, the international investment treaties of more than 150 countries have included a sustainable development orientation, explicitly requiring that investment liberalization should not be at the expense of health and environmental protection, such as the China–EU Comprehensive Investment Agreement, which binds both investing parties to carry out value-based investments based on the principle of sustainable development and puts forward clear requirements for the environment, climate, and so on. The implementation of green production and the reduction in pollution emissions by multinational enterprises is a necessary part of achieving legitimacy in the host country. Moreover, foreign subsidiaries have a natural advantage in learning and acquiring advanced pollution control models, environmental management concepts, and clean technologies from abroad. And all of this advanced knowledge overflows to the home country through the exchange and feedback mechanisms within the group, thus affecting the overall pollution emissions and governance methods of the enterprise. On the other hand, the reverse spillover effect of green technology from OFDI has become an endogenous impetus to promote energy conservation and emission reduction by enterprises in home countries. According to the Ministry of Commerce, the proportion of China’s manufacturing OFDI has been rising, from 4.22% in 2008 to 16.6% in 2022, making it a major industry for Chinese enterprises to “go global”. Manufacturing OFDI provides innovative convenience and competitive power for China to embed itself in high-tech industrial clusters in developed countries and understand green and clean production technology. Firstly, by using cross-border mergers and acquisitions (M&A) or cooperating in setting up factories, overseas subsidiaries are able to learn and apply green production technology and pollution control technology via production cooperation and technological exchanges with enterprises of developed countries, and diffuse them to the parent company through the group’s internal feedback mechanism, thus promoting the green transformation of production technology of the enterprises of the home country and reducing pollution emissions and the required pollution control investment. Secondly, overseas subsidiaries can further update and optimize the clean production and pollution control technologies of developed countries in overseas production and research and development, thus achieving the advantages of green technology, reduced pollution control costs, and social responsibility soft power. Finally, foreign subsidiaries can utilize green production technology to reduce pollution treatment costs, establish a highly socially responsible corporate image, and compete with similar domestic enterprises, and this green competitive advantage pushes domestic enterprises to enhance their own clean production capacity and reduce pollution emissions. Therefore, Wu put forward the following hypothesis:

H3: 

OFDI can lead to decreased environmental investments by diminishing domestic pollution levels.

2.4. Industrial Structure Upgrading Effect of OFDI

China’s economic development is constrained by the domestic resources and environment, and there are structural problems of duplicated construction and overcapacity in some industries. Enterprises “going out” with domestically disadvantaged industries address resource constraints and spur industrial upgrading. First, by relocating excess capacity, they facilitate green transformation and environmental sustainability. According to the theory of marginal industrial expansion, enterprises can obtain cheaper production factor resources in host countries than in their home countries, enjoy favorable investment policies, etc., and reverse domestic inferior production capacity into the host country’s comparatively advantageous assets [37]. This can not only promote the vitality of domestic traditional industries, expand the international market share, and optimize China’s industrial layout, but also promote China to remove industries that lose their comparative advantage. The released factor resources can then be transferred to the green industries of the home country, shrinking high-pollution, high-energy sectors in the economy, addressing the “low lock” dilemma, fostering tech-intensive, eco-friendly transformations from resource- and labor-intensive industries, and increasing the contribution of high value-added and cleaner industries to the economy, thereby reducing the need for investment in the treatment of environmental pollution at the source. Secondly, OFDI accelerates the technological upgrading of the pollution control industry and improves the efficiency of environmental end-of-pipe treatments. Enterprises engaged in OFDI, through technical cooperation and personnel exchanges, have direct contact with the host country’s pollution management technology, accelerating the development of the home country’s overall pollution control industry’s technology, upgrading of equipment, and organization and management, thereby improving the efficiency of industry pollution management and reducing the need for environmental investment. Based on the preceding analysis, we formulate the following hypothesis:

H4: 

OFDI reduces enterprises’ environmental governance investment through upgrading the industrial structure.

3. Research Design

3.1. Data Sources and Sample Selection

Focusing on the influence of OFDI on domestic enterprises’ environmental investments, this research analyzed a selected sample of listed Chinese companies from Shanghai and Shenzhen, spanning 2008–2022, due to data constraints. In order to ensure the reasonableness of the research, the relevant financial data were based on consolidated financial statements. The sample data were filtered as follows: (1) Excluded financial and insurance listed companies. (2) ST and ST* listed companies were excluded. (3) Excluded listed companies that only invest in “tax havens”, such as the Cayman Islands, British Virgin Islands, and Bermuda. (4) Listed companies with missing or incomplete data were excluded. According to the above conditions, the unbalanced panel data of 2594 observations of listed companies were screened out. To eliminate the influence of outliers and extreme values in the sample on the empirical results, the main continuous variables in the sample were subjected to 1% winsorize shrinkage treatment.

The main data were from the CSMAR database. The data on corporate environmental investment were from the environmental investment sub-database, which has provided data related to environmental investment of some listed companies in China since 2008. The OFDI data were from the overseas affiliates sub-database, which has provided data on overseas affiliates of Chinese listed companies since 1999, such as subsidiaries, joint ventures, and affiliates. Industrial structure data were from the official website of the National Bureau of Statistics of China. Carbon emissions data were from the China Carbon Accounting Databases (CEADs). Financing constraints and other control variables were taken from firm characteristics data from the CSMAR database of the Corporate Research Series sub-database.

3.2. Model Construction

This research constructed a DID model to investigate the influence of OFDI on the environmental investment of domestic enterprises, largely alleviating the selective bias and endogeneity problems that may be caused by non-random variables other than policy variables through differentiation [38]. The sample enterprises were categorized into experimental (engaged in OFDI) and control (non-OFDI) groups, distinguished by a dummy variable ‘treat’ (1 for experimental, 0 for control). Furthermore, a time dummy variable ‘post’ indicated whether the enterprise had made its first OFDI (1 post-investment, 0 pre-investment). As the timing of OFDI varied among enterprises, the following multi-period DID model was established:

Environmental investment_i,t = α₀ + α₁ treat_i × post_i,t + α₂ control + industry + year + ε_i,t

(1)

This study emphasizes the estimated coefficient α₁, reflecting the net impact of OFDI on corporate environmental investment. A negative α₁ signifies a significant reduction in environmental investment among experimental group enterprises post-OFDI, compared to controls, indicating OFDI’s adverse effect on environmental investments. The model includes control variables, industry and year fixed effects, with i, t, and ε representing enterprise, time, and random error, respectively.

3.3. Variable Selection and Definition

3.3.1. Explained Variables

Environmental investment: Refers to the investment in environmental protection, such as environmental pollution treatment, prevention and control, and environmental protection equipment maintenance, made by enterprises in the home country. We measured environmental investment as a percentage of total assets at period-end, and employed the proportion of environmental investment in owner equity for robustness checks.

3.3.2. Explaining Variables

Treatment effect: The cross-multiplier of the time dummy variable and the group dummy variable. treat was the firm dummy variable, 1 if the OFDI group, 0 otherwise, and post was the time dummy variable, 1 if after OFDI, 0 otherwise.

3.3.3. Mechanism Variables

Financing constraints: This research measured firms’ financing constraints by drawing on Hadlock and Pierce (2010) [39]. Calculation of the financing constraint index was carried out using model (2). A larger index value indicated more severe financing constraints for the firm.

Financing constraints = −0.737 × size + 0.043 × size²−0.040 × age

(2)

Carbon emissions: Carbon emissions per unit of GDP of the region where the enterprise was located were used as its proxy variable.

Industrial structure: Drawing on the method of Sun et al. (2022) [40], the added value of the primary, secondary, and tertiary industries were assigned weights 1, 2, and 3 as measures of the industrial structure. The calculations are shown in model (3) below:

$$Industrialstructure={\sum }_{j=1}^{3}j\times p_j$$

(3)

where p_j denotes the share of the added value of the jth industry in the total output value.

3.3.4. Control Variables

We controlled for company micro-characteristics such as asset size, financial leverage, profitability, free cash flow, capital intensity, growth, and property rights. In order to eliminate the impact of agency problems caused by internal governance on environmental investment, we also controlled for agency costs, corporate governance characteristics such as ownership concentration, the proportion of independent directors, and other indicators. In addition to the above indicators, we also controlled for year and industry fixed effects.

Table 1. Variable definitions and measures.

Variable	Calculation Method
environmental investment	(Total environmental investment ×100)/total assets
post	Time dummy variable, 1 if after OFDI, 0 otherwise
treat	Firm dummy variable, 1 if OFDI group, 0 otherwise
export	Export volume/GDP
trade	Import and export volume/GDP
ofdiflow	Outward foreign direct investment flow/GDP
financing constraints	SA = −0.737 × size + 0.043 × size2 − 0.040 × age
carbon emissions	Carbon emissions per unit of GDP
industrial structure	$\sum _{\mathrm{j}=1}^3\mathrm{j}\times {\mathrm{p}}_{\mathrm{j}}$, pj is the proportion of the added value of the j industry to GDP
soe	1 if state-owned enterprise, 0 otherwise
size	The natural log of total assets
roe	Net profit/average net asset
top1	The shareholding ratio of the controlling shareholder is determined. If not disclosed, the shareholding ratio of the largest shareholder will be considered
boardscale	The natural logarithm of the total number of directors
ratio of independent directors	Independent directors No./total directors No.
lev	Total liabilities/total assets
grow	Growth rate of business revenue
free cash flow	Net cash flow from operating/total assets
agent cost	Administrative expenses/revenue
capital-intensity	Fixed assets, intangible assets, and other long-term assets/total assets

presents the definitions and measurement of variables.

3.4. Descriptive Statistics

Table 2. Descriptive statistics.

	Full Sample					OFDI	Non-OFDI
Variable	Observation	Mean	SD	Min	Max	Mean	Mean
environmental investment	2571	0.670	1.561	0.001	11.96	0.822	0.564
treat × post	2594	0.586	0.493	0	1	0	1
grow	2571	0.188	0.324	−0.199	1.939	0.230	0.159
lev	2571	0.438	0.197	0.0630	0.888	0.401	0.463
free cash flow	2571	0.06	0.068	−0.137	0.259	0.0550	0.0630
size	2571	22.9	1.494	20.33	27.35	22.36	23.27
soe	2593	0.422	0.494	0	1	0.472	0.386
top1	2593	37.42	16.71	0	91.74	38.68	36.54
ratio of independent directors	2593	37.63	5.670	33.33	60	37.28	37.87
roe	2594	0.0800	0.146	−2.141	1.332	0.0710	0.0870
agent cost	2553	0.0670	0.047	0.007	0.270	0.073	0.063
capital-intensity	2571	0.251	0.16	0.006	0.687	0.266	0.241

reports the descriptive statistical results of the main variables of the full sample, OFDI enterprise sample, and non-OFDI enterprise sample. The mean value of the environmental investment variable of OFDI enterprises was 0.564, which was smaller than that of non-OFDI enterprises (0.822). Preliminarily, this showed that OFDI enterprises exhibited lower levels of environmental investment compared to non-OFDI enterprises, but the specific relationship needs to be further tested. The standard deviation of the environmental investment was above 1, indicating large sample differences.

4. Empirical Analysis

4.1. Benchmark Regression

Table 3. The impact of OFDI on environmental investment.

Variables	(1)	(2)	(3)	(4)
	Environmental Investment
treat × post	−0.282 ***	−0.257 ***	−0.172 **	−0.163 **
	(−3.314)	(−3.007)	(−2.355)	(−2.259)
grow			0.081	0.090
			(0.960)	(1.070)
lev			0.211	0.077
			(1.010)	(0.367)
free cash flow			0.850	0.906 *
			(1.553)	(1.646)
size			−0.096 **	−0.080 **
			(−2.510)	(−1.985)
soe			−0.004	0.025
			(−0.047)	(0.277)
top1			−0.000	−0.000
			(−0.228)	(−0.117)
ratio of independent directors			−0.001	−0.002
			(−0.231)	(−0.359)
roe			0.615 **	0.524 **
			(2.449)	(2.135)
agent cost			0.101	−0.190
			(0.092)	(−0.158)
capital-intensity			1.682 ***	1.788 ***
			(5.289)	(4.781)
year	yes	yes	yes	yes
industry	no	yes	no	yes
Observations	2574	2574	2556	2556
R2	0.041	0.073	0.076	0.104

Note: ***, **, and * are significant at the 1%, 5%, and 10% levels, respectively. The t value is in parentheses, and the estimated results are clustered to the enterprise level for standard errors.

presents the results of the multi-period DID benchmark regression, with columns (1)–(4) progressively controlling for year and industry fixed effects, as well as control variables; the gradual increase in the R² value indicated the increasing effectiveness of the model fit. The empirical results showed that the coefficient of the interaction term treat × post was always significantly negative regardless of the inclusion of control variables, and passed the statistical test at the 5% significance level, suggesting that OFDI is not only an important aspect of international circularity, but also has the capacity to influence the economic “inner circle” through linkages between foreign subsidiaries and domestic parent firms, reducing the level of environmental investment by home country firms, and affirming hypothesis H1.

The validity of model (1)’s DID estimation hinges on the parallel trend assumption, requiring pre-shock parallel trends between the experimental and control groups; a parallel trend test was imperative. Additionally, it also can test the time lag effect for the impact of OFDI on corporate environmental investment. Given the long span of the sample period, we retained the first three periods before OFDI and the four periods after OFDI, and winsorized the remaining data. To avoid multicollinearity problems, the data from the current period of OFDI were eliminated, and model (4) examines both the parallel trend hypothesis and the persistence of OFDI’s influence on environmental investment.

$$\begin{array}{c}{environmentalinvestment}_{i,t}\\ \hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em} ={\beta }_0+{\beta }_1{treat}_i\times {post}_{i,t}^{-3}+{\beta }_2{treat}_i\times {post}_{i,t}^{-2}\\ \hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em} +{\beta }_3{treat}_i\times {post}_{i,t}^{-1}+{\beta }_4{treat}_i\times {post}_{i,t}^1\\ \hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em} +{\beta }_5{treat}_i\times {post}_{i,t}^2\\ \hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em} +{\beta }_6{treat}_i\times {post}_{i,t}^3{+\beta }_7{treat}_i\times {post}_{i,t}^4+\lambda {control}_{i,t}\\ \hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em} +\mathrm{i}ndustry+year+{\epsilon }_{i,t}\end{array}$$

(4)

where post⁻ⁿ_i,t is a dummy variable that is 1 when the time is in the n period before OFDI and 0 otherwise; similarly, postⁿ_i,t is 1 when it is in the n period after OFDI and 0 otherwise.

Table 4. Parallel trend test.

	(1)	(2)	(3)	(4)
Variables	Environmental Investment
treat × post−1	0.547	0.485	0.576	0.524
	(1.332)	(1.188)	(1.420)	(1.293)
treat × post−2	0.581	0.428	0.579	0.451
	(1.424)	(1.056)	(1.444)	(1.134)
treat × post−3	0.157	0.106	0.213	0.172
	(0.547)	(0.380)	(0.795)	(0.663)
treat × post1	−0.371 ***	−0.366 ***	−0.291 ***	−0.276 ***
	(−3.123)	(−3.103)	(−2.690)	(−2.607)
treat × post2	−0.148	−0.159	−0.104	−0.108
	(−0.985)	(−1.098)	(−0.715)	(−0.775)
treat × post3	−0.089	−0.134	0.013	−0.044
	(−0.546)	(−0.841)	(0.080)	(−0.274)
treat × post4	−0.280 ***	−0.241 ***	−0.158 **	−0.137 *
	(−3.240)	(−2.772)	(−2.076)	(−1.813)
grow			0.067	0.077
			(0.785)	(0.902)
lev			0.243	0.106
			(1.154)	(0.502)
free cash flow			0.812	0.870
			(1.496)	(1.589)
size			−0.094 **	−0.080 *
			(−2.394)	(−1.909)
soe			0.012	0.038
			(0.138)	(0.415)
top1			−0.001	−0.000
			(−0.266)	(−0.122)
ratio of independent directors			−0.001	−0.002
			(−0.200)	(−0.334)
roe			0.603 **	0.516 **
			(2.394)	(2.096)
agent cost			0.077	−0.215
			(0.071)	(−0.181)
capital-intensity			1.694 ***	1.798 ***
			(5.282)	(4.769)
year	yes	yes	yes	yes
industry	no	yes	no	yes
Observations	2574	2574	2556	2556
R2	0.047	0.077	0.081	0.107

Note: ***, **, and * are significant at the 1%, 5%, and 10% levels, respectively. The t value is in parentheses, and the estimated results are clustered to the enterprise level for standard errors.

presents model (4)’s test results, with the indistinctive coefficient of treat × post⁻¹, treat × post⁻², and treat × post⁻³ indicating no significant pre-OFDI trend differences in environmental investment, supporting the parallel trend hypothesis. Notably, treat × post¹ and treat × post⁴ exhibit significant negative effects on environmental investment, with treat × post¹ being more pronounced. These findings suggest a lagged, diminishing impact of OFDI on environmental investment over time.

To minimize the influence of omitted variables on the estimation results, this study included a placebo test. The cross-term was randomly sampled 1000 times, and the random sampling results were regressed to generate the kernel density distribution plot of the estimated coefficients (Figure 1). The majority of estimated coefficients from the random sampling regression were centered around 0, which significantly deviated from the actual estimated coefficients of model (1) depicted by the dotted line. This indicated that the negative effect of OFDI on environmental investment remains unaffected by random disturbances, thereby addressing the endogenous problem in the causal identification of model (1) to a certain extent.

4.2. Endogeneity Test

Enterprises have the option to relocate industries overseas depending on their level of investment in environmental protection. The relationship between OFDI and environmental investment poses a bidirectional causality issue. To address the problem of endogeneity caused by reverse causal spillover and omitted variables, and obtain consistent estimates, we attempted to construct three sets of instrumental variables for further analysis.

According to the eclectic paradigm, enterprises must possess ownership advantages, locational advantages, and internalization advantages to engage in cross-border investment. Otherwise, they can engage in direct foreign trade or licensed trade. This suggests that OFDI is a gradual substitute for international trade. In addition, the Uppsala model proposes that the process of internationalization for enterprises consists of four stages: the expected export stage, indirect export stage, direct export stage, and international investment stage. OFDI is driven by the acquisition of knowledge and experience through engaging in international trade. The relationship between export trade and OFDI is closely intertwined, so we employed the province’s export dependence and trade dependence degree, where the home country enterprise resides, as the instrumental variable treat × post. Additionally, the ratio of outward foreign direct investment flow to GDP in the province was also chosen as an instrumental variable. These three provincial variables fulfilled the requirement of being correlated with OFDI, and as higher-level foreign economic cooperation indicators, did not directly impact the domestic environmental investment of micro-enterprises, meeting the exogenous requirements.

Table 5. Endogeneity test.

	First Stage			Second Stage
Variables	IV = Export	IV = Trade	IV = Ofdiflow	IV = Export	IV = Trade	IV = Ofdiflow
export	0.516 ***
	(8.718)
trade		0.240 ***
		(7.816)
ofdiflow			4.265 ***
			(4.504)
treat × post				−1.654 ***	−1.795 ***	−2.209 ***
				(−3.930)	(−4.146)	(−2.864)
grow	−0.226 ***	−0.230 ***	−0.232 ***	−0.256 **	−0.289 **	−0.385 **
	(−8.889)	(−9.005)	(−9.095)	(−2.022)	(−2.254)	(−1.992)
lev	0.173 ***	0.187 ***	0.170 ***	0.324	0.340	0.417
	(2.866)	(3.058)	(2.779)	(1.395)	(1.467)	(1.614)
free cash flow	0.352 **	0.364 **	0.396 ***	1.485 **	1.529 **	1.696 **
	(2.317)	(2.387)	(2.613)	(2.315)	(2.335)	(2.320)
size	0.152 ***	0.145 ***	0.149 ***	0.145 **	0.167 **	0.229 *
	(21.016)	(19.500)	(20.154)	(2.332)	(2.426)	(1.911)
soe	−0.192 ***	−0.214 ***	−0.228 ***	−0.322 ***	−0.354 ***	−0.451 **
	(−9.538)	(−10.804)	(−11.442)	(−2.623)	(−2.917)	(−2.298)
top1	−0.002 ***	−0.002 ***	−0.002 ***	−0.003	−0.003	−0.004
	(−3.695)	(−4.130)	(−3.716)	(−1.470)	(−1.583)	(−1.598)
ratio of independent directors	−0.001	−0.001	−0.001	−0.003	−0.003	−0.003
	(−0.455)	(−0.550)	(−0.330)	(−0.507)	(−0.496)	(−0.511)
roe	0.064	0.082	0.078	0.645 **	0.632 **	0.690 **
	(0.936)	(1.181)	(1.124)	(2.431)	(2.339)	(2.413)
agent cost	0.596 ***	0.490 **	0.520 **	0.575	0.624	0.869
	(2.666)	(2.144)	(2.285)	(0.558)	(0.593)	(0.762)
capital-intensity	−0.349 ***	−0.325 ***	−0.385 ***	1.174 ***	1.116 ***	0.946 **
	(−5.440)	(−5.022)	(−5.947)	(3.636)	(3.351)	(2.207)
Constant	−3.338 ***	−3.152 ***	−3.096 ***	−3.264 **	−3.662 **	−5.022 *
	(−16.788)	(−14.183)	(−15.188)	(−2.310)	(−2.303)	(−1.948)
industry	yes	yes	yes	yes	yes	yes
year	yes	yes	yes	yes	yes	yes
Observations	2553	2544	2553	2553	2544	2553
R2				−0.064	−0.097	−0.212
F test	76.00 ***	61.09 ***	20.29 ***	5.664 ***	5.620 ***	4.724 ***
Kleibergen-Paap rk LM				71.434 ***	59.470 ***	18.022 ***
Kleibergen-Paap rk Wald F				76.003 ***	61.089 ***	20.287 ***

Note: ***, **, and * are significant at the 1%, 5%, and 10% levels, respectively. The t value is in parentheses, and the estimated results are clustered to the enterprise level for standard errors.

displays the test results. The first-stage regression shows a strong positive correlation (p < 0.01) between all three instrumental variables and the endogenous variables, indicating a good fit with OFDI. In the second-stage, treat × post coefficients are significantly negative (p < 0.01), exceeding the statistical significance of the benchmark regression, reinforcing the negative impact of OFDI on domestic enterprises’ environmental investment.

4.3. Robustness Test

To mitigate estimation bias from variable measurement, we standardized environmental investment by owner equity for robustness checks, confirming negative treat × post coefficients (p < 0.01) in

Table 6. Robustness test.

	(1)	(2)	(3)	(4)	(5)	(6)
Variables	Replace the Explained Variable		Explanatory Variables One Period Lagged		Changing Sample Period
treat × post	−0.564 ***	−0.516 ***	−0.631 ***	−0.342 *	−0.446 ***	−0.224 *
	(−2.745)	(−2.677)	(−2.916)	(−1.824)	(−2.902)	(−1.778)
grow		0.122		0.015		0.173
		(0.436)		(0.079)		(1.153)
lev		3.683***		−0.377		−0.223
		(4.005)		(−0.769)		(−0.674)
free cash flow		1.773		−1.328		1.485
		(1.060)		(−0.971)		(1.434)
size		−0.268 **		−0.125		−0.134 *
		(−2.549)		(−1.294)		(−1.862)
soe		0.077		0.245		0.128
		(0.329)		(1.040)		(0.813)
top1		−0.001		−0.002		−0.002
		(−0.091)		(−0.321)		(−0.460)
ratio of independent directors		−0.001		−0.010		−0.004
		(−0.040)		(−0.872)		(−0.489)
roe		2.022		1.612 **		0.580
		(1.553)		(2.427)		(1.500)
agent cost		0.918		−0.155		−0.441
		(0.318)		(−0.044)		(−0.242)
capital-intensity		4.034 ***		3.209 ***		2.223 ***
		(4.752)		(3.934)		(3.788)
industry	yes	yes	yes	yes	yes	yes
year	yes	yes	yes	yes	yes	yes
Observations	2571	2553	659	650	1127	1125
R2	0.051	0.086	0.098	0.160	0.101	0.147

Note: ***, **, and * are significant at the 1%, 5%, and 10% levels, respectively. The t value is in parentheses, and the estimated results are clustered to the enterprise level for standard errors.

(Cols. 1–2), consistent with benchmarks. To address endogeneity from bidirectional causality, we lagged all model (1) explanatory variables by one period. Results in Table 6 (Cols. 3–4) reveal significantly negative treat × post coefficients. To further isolate the effects of exogenous shocks, observations from 2008 to 2009 (2008 global financial crisis) and 2020–2022 (2020 COVID−19 outbreak) were excluded from the analysis. The regression coefficient remained significantly negative, thereby reaffirming the conclusion of hypothesis H1.

4.4. Mechanism Testing

Benchmark regressions showed that OFDI reduces the environmental investment of home country firms. Is this reduction simply due to the crowding-out effect arising from competition for capital, or is it an environmental cost-saving effect resulting from OFDI’s improved efficiency in environmental protection and pollution control? It is important to clarify the potential causes for China and other emerging countries to support them to further develop a sustainable economic model. We examined the competition for capital due to financing constraints and the cooperation effect represented by emission reductions and industrial structure upgrading, respectively.

4.4.1. Financing Constraint Effect

OFDI is a channel for the international allocation of resources and an important capital investment activity of enterprises, and the capital demand is large. When there are financing constraints in enterprises, OFDI will form a capital competition effect on other investment activities, including environmental investment, and therefore squeezes domestic environmental investment. If the hypothesis is valid, the negative effect of OFDI on environmental investment should be more significant in enterprises with more serious financing constraints. To test the mechanism, the sample was categorized into high and low financing constraint groups based on Hadlock and Pierce (2010)’s SA index, and

Table 7. Mechanism examination.

	(1)	(2)	(3)	(4)
	High Financing Constraint	Low Financing Constraint	Emission Reduction Effect	Industrial Structure Upgrading Effect
Variables	Environmental Investment	Environmental Investment	Carbon Emission	Industrial Structure
treat × post	−0.336 ***	−0.029	−3.80 ***	0.04 ***
	(−2.805)	(−0.318)	(−2.74)	(3.86)
grow	0.017	0.147	−0.92	0.01
	(0.154)	(1.084)	(−0.67)	(0.58)
lev	−0.092	0.128	−0.16	−0.07 ***
	(−0.245)	(0.482)	(−0.03)	(−2.72)
free cash flow	0.211	1.595 *	−4.53	−0.00
	(0.256)	(1.957)	(−0.54)	(−0.07)
size	−0.093	−0.063	1.83 ***	0.01 ***
	(−1.315)	(−1.556)	(2.61)	(3.11)
soe	0.162	0.014	4.24 **	0.01
	(0.808)	(0.153)	(2.30)	(0.64)
top1	−0.003	0.002	−0.14 **	0.00 ***
	(−0.877)	(0.749)	(−2.57)	(3.66)
ratio of independent directors	−0.001	−0.003	−0.12	0.00
	(−0.111)	(−0.441)	(−1.14)	(0.66)
roe	0.358	0.676 **	0.49	−0.05 *
	(0.980)	(2.183)	(0.16)	(−1.86)
agent cost	−0.351	0.088	13.99	0.16 *
	(−0.169)	(0.076)	(0.93)	(1.65)
capital-intensity	2.377 ***	1.313 ***	3.26	−0.13 ***
	(3.656)	(3.902)	(0.51)	(−4.86)
year	yes	yes	yes	yes
industry	yes	yes	yes	yes
Observations	1228	1243	1458	2553
R2	0.144	0.081	0.13	0.17

Note: ***, **, and * are significant at the 1%, 5%, and 10% levels, respectively. The t value is in parentheses, and the estimated results are clustered to the enterprise level for standard errors.

(Cols. 1–2) displays contrasting results: The high financing constraint group shows a significantly negative cross-multiplier term coefficient (p < 0.01), whereas the low financing constraint group’s coefficient is not significant. It indicates that the environmental investment of enterprises with more serious external financing constraints is more prominently affected by the negative impact of OFDI, which affirms the role of financing constraints in the negative impact of OFDI on the home country’s environmental investment, and is consistent with hypothesis 2.

4.4.2. Emission Reduction Effect of OFDI

Environmental governance encompasses source and end-of-pipe approaches, and the purification and treatment of pollutants generated in production to reduce environmental hazards is an important element of environmental investment. If OFDI can help reduce industrial pollutant emissions, it will inevitably reduce the need for investment in end-of-pipe treatments. In order to test hypothesis 3, we drew on the recommendations of Jiang (2022) [41], and constructed the following model (5):

$${carbon emission}_{i,t}={\gamma }_0+{\gamma }_1{{treat}_i\times post}_{i,t}+\lambda {control}_{i,t}+industry+year+{\epsilon }_{i,t}$$

(5)

Due to the wide range of categories of pollutant emissions at the enterprise level, the units were not uniform, and for the sake of empirical tractability, we utilized the ratio of carbon emissions to GDP of each enterprise’s province, as disclosed by the China Carbon Accounting Databases (CEADs), as a proxy for pollution emissions. Column (3) of Table 7 reveals a significantly negative treat × post coefficient (p < 0.01), suggesting that OFDI substantially decreases pollution emissions in the host region; the positive role of OFDI in energy conservation and emission reduction is verified.

4.4.3. Industrial Structure Upgrading Effect of OFDI

OFDI fosters green and efficient industrial governance in the home country, promoting structural upgrades, mitigating pollution at the source, and curbing environmental investment costs. To test hypothesis 4, the following model (6) was constructed:

$${industrialstructure}_{i,t}={\gamma }_0+{\gamma }_1{{treat}_i\times post}_{i,t}+\lambda {control}_{i,t}+industry+year+{\epsilon }_{i,t}$$

(6)

Column (4) of Table 7 validates hypothesis 4, showing a significantly positive treat × post coefficient (p < 0.01), suggesting OFDI spurs industrial upgrading, thereby decreasing source pollution and enterprise environmental investment costs, OFDI’s crucial role in addressing environmental issues at the source is confirmed.

4.5. Heterogeneity Test

4.5.1. Differences in the Development Level of Host Countries

According to the definition of Makino et al. (2002) [42] of OFDI, the down-gradient investment of multinational enterprises to countries with a lower institutional governance level is often carried out to access the mature technology already in the home country for an ownership advantage, and to transfer it to less technologically advanced countries to obtain high returns in the short term. This is a form of exploitative outward investment. The reverse gradient investment to countries with a higher level of institutional governance can transfer advanced technology, knowledge, and other strategic resources from developed countries, and is a form of exploratory investment. Exploitative investment does not support productivity improvements for enterprises due to the overall low level of technology in the host country (Wang et al., 2019) [43]. Exploratory outward investment to countries with higher levels of development leads to benefits from the host country’s higher level of technology, governance, and environmental requirements. The production technology and environmental management technology are clearer and more advanced, the enterprise’s motivation to seek green advanced technology is stronger, and it can stimulate the exploratory learning and technological innovation of OFDI enterprises, which is conducive to the realization of the reverse green technology spillover effect on the home country and to reducing the need for investment in environmental pollution and management. Therefore, enterprises investing in developed countries have more significant environmental investment savings effects on their home countries. Using the UNDP’s high HDI country list, we categorized host nations as developing or developed, regressing them separately. Results are presented in

Table 8. Heterogeneity test.

	(1)	(2)	(3)	(4)	(5)	(6)
Variables	Developing Country	Developed Country	Strict Environmental Regulation	Relaxed Environmental Regulation	Soes	Non-Soe
treat × post	−0.137 *	−0.194 ***	0.021	−0.178 **	−0.168	−0.177 *
	(−1.935)	(−2.774)	(0.121)	(−2.261)	(−1.489)	(−1.726)
grow	0.092	0.059	0.441	0.004	−0.066	0.171 *
	(1.053)	(0.726)	(1.603)	(0.049)	(−0.445)	(1.693)
lev	0.118	0.053	0.015	0.042	−0.135	0.188
	(0.529)	(0.244)	(0.027)	(0.203)	(−0.366)	(0.764)
free cash flow	0.934	0.809	1.478	0.875 **	0.276	1.204 *
	(1.596)	(1.515)	(0.850)	(2.118)	(0.287)	(1.870)
size	−0.093 **	−0.068	−0.301 **	−0.006	−0.127 **	−0.034
	(−2.026)	(−1.598)	(−2.490)	(−0.218)	(−2.298)	(−0.785)
top1	0.018	0.002	0.001	0.001	−0.001	0.001
	(0.192)	(0.018)	(0.231)	(0.365)	(−0.197)	(0.578)
ratio of independent directors	−0.000	−0.001	0.009	−0.003	0.003	−0.005
	(−0.042)	(−0.432)	(0.635)	(−0.520)	(0.383)	(−0.677)
roe	−0.002	−0.000	0.554	0.353 *	0.330	0.835 **
	(−0.333)	(−0.048)	(1.029)	(1.799)	(1.098)	(2.057)
agent cost	0.553 **	0.480 **	−2.710	0.611	−1.679	1.131
	(2.043)	(1.964)	(−0.766)	(0.653)	(−0.783)	(0.941)
capital-intensity	−0.118	−0.408	2.621 ***	1.420 ***	1.702 ***	1.956 ***
	(−0.091)	(−0.327)	(3.084)	(4.685)	(3.717)	(4.277)
soe	1.801 ***	1.726 ***	0.133	−0.082
	(4.357)	(4.479)	(0.606)	(−1.007)
industry	yes	yes	yes	yes	yes	yes
year	yes	yes	yes	yes	yes	yes
Observations	2276	2457	675	1876	1084	1466
R2	0.102	0.103	0.151	0.091	0.115	0.114

Note: ***, **, and * are significant at the 1%, 5%, and 10% levels, respectively. The t value is in parentheses, and the estimated results are clustered to the enterprise level for standard errors.

(Cols. 1–2). Compared with developing countries, the absolute value of the treat × post coefficients of developed countries was larger, and the level of significance was also higher, which further verified the environmental investment saving effect of the green technology spillover of OFDI.

4.5.2. Government Regulation Differences in Home Countries

As mentioned above, enterprises lack initiative in eco-investments, relying heavily on government regulation. Looser home country environmental policies grant greater autonomy in investment decisions, amplifying OFDI’s negative impact on eco-investments. Conversely, stricter policies increase the ‘rigidity’ of eco-investments, and the space impacted by OFDI is very limited, so the inhibitory effect is weaker. The sample in this study was divided into two groups based on the ratio of total environmental governance investment to GDP of the province where the parent company was located. The group with a higher ratio, exceeding the median environmental governance investment/GDP, was referred to as the strict environmental regulation group. Conversely, the group with a lower ratio, below the median, was referred to as the relaxed environmental regulation group. As shown in Table 8 (Cols. 3–4), the regression coefficient of treat × post in the relaxed environmental regulation group was significantly negative, while there was no significant impact observed within the strict environmental regulation group, thus confirming our conclusions.

4.5.3. Property Rights Difference

Environmental investment entails significant capital consumption and is characterized by externalities, with a social significance that surpasses its economic benefits. Conversely, the economic gains derived from OFDI, such as market expansion, resource acquisition, and efficiency enhancement, are solely enjoyed by the enterprises themselves. Consequently, rational managers driven by profit maximization exhibit less enthusiasm for environmental investment and display a greater inclination towards OFDI. Given their close association with the government, state-owned enterprises (SOEs) do not adhere to the rational decision-making principle of maximizing benefits. Unlike non-state-owned enterprises, whose operations primarily revolve around profit maximization objectives, state-owned enterprises bear numerous social responsibilities and political tasks. Environmental protection and pollution control represent quintessential external economic activities that constitute vital aspects of fulfilling these social responsibilities for state-owned enterprises, while also serving as key business objectives. Environmental investment undertaken by SOEs is more inflexible compared to their non-state-owned counterparts. The adverse impact of OFDI on environmental investment is relatively weaker in this regard. On the other hand, relative to non-state-owned entities, SOEs face fewer constraints pertaining to external financing due to assuming greater political burdens, which consequently give rise to “soft budget constraints”. Through credit rationing mechanisms, along with credit subsidies and financial support provided by the government at a lower cost [44], state-owned enterprises possess more abundant funds, thereby resulting in a weaker negative influence of OFDI on environmental investment than non-state-owned firms. As shown in Table 8 (Cols. 5–6), the regression coefficient of treat × post of the non-state-owned enterprises group was significantly negative, while that of state-owned enterprises was negative but not significantly, indicating that outbound investment of non-state-owned enterprises has a significant negative impact on environmental investment. However, state-owned enterprises are not bothered by this problem.

5. Conclusions and Suggestions

As the concept of sustainable development has gained global consensus, environmental protection and investment have garnered widespread attention. However, China’s environmental investment has been declining in recent years, and there are few reasonable explanations for this in the existing literature. In this paper, we explained this phenomenon from the perspective of OFDI. This study showed that OFDI reduces the level of environmental investment in the home country. Mechanism analysis found that there is a competition effect between OFDI and home country environmental investment when there are financing constraints, and environmental investment is squeezed out by OFDI due to its associated externalities. A cooperative effect is also observed between these two types of investments: OFDI can not only reduce the home country’s energy consumption and pollution emissions, but can also promote the upgrading of China’s industrial structure, to achieve industry greening and efficient governance, to reduce environmental problems at the source, and to reduce the cost of environmental investment. Heterogeneity analysis revealed that the negative impact of OFDI on environmental investment is mainly found in firms investing in developed countries, firms with relatively lax home government environmental regulations, and non-state-owned firms.

This paper makes several contributions to the literature. Firstly, we used the characteristics of environmental investment, such as passive investment, rigidity insufficiency, and low return, and the characteristics of OFDI, such as the reverse technology spillover effect and industrial structure upgrading effect, to reveal the reasons for China’s declining environmental investment, with the premise of guaranteeing environmental quality and providing a reference for the sustainable development of emerging economies. Secondly, we explained the competition and cooperation mechanism between OFDI and environmental investment considering three aspects: financing constraints, the emission reduction effect of OFDI, and the industrial structure upgrading effect, adding to the research on the environmental governance effect of OFDI and providing ideas for the Chinese government to address the environmental governance dilemma and improve the level of international recycling. Thirdly, the heterogeneity analysis of home countries, host countries, and OFDI enterprises broadened the scope of application of the theory that OFDI negatively affects environmental investment, which provides a basis for multinational enterprises to optimize their OFDI decisions and achieve green and sustainable development.

As China is now in a critical period of building a new domestic and international “double-cycle” pattern of economic development and a new model of sustainable development, this paper provides important insights into the need for China and the emerging economies of the world to improve the international economic cycle and enhance the capacity for green and sustainable development. The government should encourage enterprises to overcome the international embargo and participate in global industrial value chains, and should also guide them to enhance their green and sustainable competitiveness. First, at the institutional level, it should promote capital market reform, improve the financing environment, alleviate the financing constraints of enterprises, establish a green and sustainable investment system at home and abroad, balance the financial needs of international development and sustainable development, and reduce the environmental sacrifices caused by competition for capital. Second, it should strengthen the construction of OFDI public service systems to promote the cooperative effect of OFDI and environmental protection, enhance the efficiency of the cross-border flow of resource factors, and facilitate the reverse transfer of green technology from abroad and promote the green upgrading of the domestic industrial structure. Third, it should optimize the environmental governance system, reduce the moral risks caused by lax environmental regulations in home countries, and unify the individual interests of cross-border investment with the public interests of environmental protection for joint promotion.