Bridges or Barriers? Unpacking the Institutional Drivers of Business Climate Adaptation in the EU

Abstract

This study examines the critical role of institutional quality in driving corporate adaptation to climate change within the EU-27 member states from 2006 to 2023. It aims to investigate how governance factors—control of corruption, government effectiveness, rule of law, and regulatory quality—influence business strategies for environmental resilience and sustainability, focusing on environmental investments and industrial production. Employing fixed and random effects regression models on a balanced panel dataset, we analyze two dependent variables: environmental protection investment corporations (EPIC), measuring investments in pollution prevention and environmental degradation reduction, and industrial production (IP), reflecting output in mining, manufacturing, and utilities. A composite institutional quality index, derived through principal component analysis (PCA) from the four governance indicators, captures their collective impact, reducing multicollinearity and enhancing analytical robustness. Control variables, including final energy consumption, environmental tax revenues, expenditure on environmental protection, and a Paris Agreement dummy, are incorporated to test the institutional quality effect. Results demonstrate that higher institutional quality significantly enhances EPIC, particularly in countries with greater environmental tax revenues, indicating that robust governance and fiscal policies incentivize sustainable corporate investments. Conversely, the effect on IP is less consistent, with higher fossil energy consumption and lower environmental tax revenues driving production, suggesting a reliance on high-polluting industries. The Paris Agreement positively influences IP, reflecting stronger climate-focused industrial strategies post-2015. These findings underscore the pivotal interplay between institutional quality and environmental fiscal policies in fostering corporate adaptation to climate change. Over the long term, strong governance is essential for aligning business practices with sustainability goals, reducing environmental degradation, and mitigating climate risks across the EU. This study highlights the need for cohesive policies to support green investments and transition industries toward renewable energy sources, addressing disparities in environmental performance among EU member states.

1. Introduction

In the context of today’s business environment, climate change generated unprecedented challenges to the businesses worldwide, by threatening operational stability or disrupting supply chains altogether. Evidence indicates that Europe is warming faster than the global average, amplifying its vulnerability [1]. The economic consequences are substantial; between 1980 and 2021, weather- and climate-related extremes resulted in economic losses exceeding EUR 560 billion across the EU-27, with average annual losses reaching EUR 26 billion in the last decade. This reality underscores the urgent need for adaptation measures alongside ongoing mitigation efforts aimed at reducing greenhouse gas emissions and negative impact on the environment [2].

Climate adaptation involves adjustments in natural or human systems in response to actual or expected climatic stimuli or their effects, with the goal of moderating harm or exploiting beneficial opportunities [3]. It is distinct from mitigation, which focuses on reducing greenhouse gas emissions, but is equally critical, as mitigation alone cannot prevent all climate change impacts, even under optimistic scenarios. Recognizing this, the EU has developed a strategic framework for adaptation, launching its first strategy in 2013 and updating it in 2021. These strategies aim to contribute to a climate-resilient Europe by 2050, which is the main goal in the European Climate Law. In this respect, significant financial resources have been allocated, with at least EUR 8 billion budgeted for adaptation in 2014–2020 and EUR 26 billion in 2021–2027. However, the cross-cutting nature of adaptation makes precise funding estimates challenging.

Nonetheless, while policy frameworks provide direction, the effective implementation of adaptation measures relies heavily on actions taken at various levels, including national, regional, local, and, crucially, the business sector. Businesses across numerous sectors, including energy, transport, tourism, and manufacturing, are directly exposed to climate risks, such as operational disruptions, supply chain vulnerabilities, and asset damage [4]. Due to the extreme weather events, shifting market demands, and evolving regulatory landscapes, the corporate sector needs to adopt proactive strategies to mitigate environmental risks and capitalize on emerging opportunities driven by climate change, such as innovation and development of new markets for climate-resilient goods and services. Therefore, corporate strategies, investments, and operational adjustments are central to the EU’s overall adaptation capacity and the transition towards climate resilience.

However, the EU’s adaptation policy framework, while robust, exhibits implementation gaps. Research indicates a disconnect between high-level strategic objectives and the uptake of adaptation measures at the business level, where operationalization is critical. To reiterate, businesses’ capacity to effectively navigate these challenges is not solely determined by their internal resources and capabilities. Still, it is also significantly shaped by the external environment in which they operate [5], namely the quality of institutions, which encompasses the formal and informal rules, norms, and organizations that govern societal interactions. Recent literature critiques the EU’s reliance on market mechanisms and technological innovation, arguing for deeper systemic changes to support adaptation, particularly through strengthened institutional frameworks.

A potential disconnect may exist between high-level strategic objectives and the awareness and uptake of adaptation measures at the local and business levels, where operationalization primarily occurs [1]. The discourse surrounding the EU adaptation policy has also been critiqued for potentially over-relying on market mechanisms and technological innovation without sufficiently addressing the need for more fundamental systemic changes [6]. This highlights a critical need to understand the factors that drive or hinder business adaptation actions in practice. The economic rationale for adaptation, emphasized by the high costs of inaction, may be mediated by other factors, including the broader institutional context within which firms operate.

For this reason, the primary objective of our study is to offer a better understanding of how institutional quality affects business adaptation to the multifaceted challenges posed by climate change within the 27 EU member states from 2006 to 2023. Specifically, the research aims to investigate the individual effects of four dimensions of institutional quality, defined by control of corruption, government effectiveness, rule of law, and regulatory quality, on corporate environmental protection, whilst analyzing the individual effects of the same dimensions on the industrial production index. Furthermore, by constructing a composite indicator using principal component analysis (PCA), we have assessed its combined effects on both environmental protection investment corporations and industrial production from an environmental adaptation standpoint.

This research is necessary to provide a deeper understanding of how specific dimensions of institutional quality—control of corruption, government effectiveness, regulatory quality, and rule of law—shape business adaptation strategies to climate change within the EU. By examining both their individual and combined effects on corporate environmental protection investments and industrial production, while controlling for fiscal policies, energy consumption, and international agreements, the study addresses a significant gap in the literature where these factors have rarely been integrated comprehensively. The results offer crucial insights for policymakers seeking to strengthen institutional frameworks and align governance reforms with environmental policies to enhance business resilience and sustainability.

This research contributes to the existing literature in environmental economics, governance studies, and corporate strategy in several ways. First, it provides specific empirical evidence on how different facets of institutional quality shape distinct types of business responses to climate change pressures—proactive environmental investment versus adjustments in industrial output—within the context of developed EU economies. Furthermore, by comparing the effects of individual institutional quality indicators with a composite measure, the study offers insights into whether specific institutional reforms or broad improvements in overall governance quality are more strongly associated with these business adaptation proxies. In addition, the inclusion of relevant control variables representing energy consumption patterns, environmental fiscal instruments, and a major international policy milestone (the Paris Agreement) allows for a more comprehensive modeling of the drivers of business adaptation.

As strengthening the institutional framework is vital for promoting business adaptation to climate change and sustainable practices across the EU, such an approach can be achieved through enhancing transparency, controlling corruption, improving public administration efficiency, developing clear regulations, ensuring consistent law enforcement, encouraging stakeholder participation, increasing data transparency, and building institutional capacity via training and cooperation. Thus, our findings highlight institutional quality—proxied by governance indicators like control of corruption, government effectiveness, regulatory quality, and rule of law—as a key driver of corporate environmental protection investments (EPIC) and industrial production (IP).

2. Literature Review

2.1. Institutional Quality, Governance, and Environmental Outcomes

The concepts of governance and institutional quality are central to understanding the context within which economic and environmental policies operate. Governance can be broadly understood as the set of traditions and institutions by which authority in a country is exercised. This encompasses the processes by which governments are selected, monitored, and replaced; the capacity of the government to effectively formulate and implement sound policies; and the respect of citizens and the state for the institutions that govern economic and social interactions among them [7]. Institutional quality refers more specifically to the nature and effectiveness of these formal and informal rules, enforcement mechanisms, and organizational structures that shape human interaction [8].

A growing body of theoretical and empirical work highlights the critical importance of institutional quality and good governance for achieving positive environmental outcomes and ensuring the effectiveness of environmental policies. Several key mechanisms link institutional quality to environmental performance. Strong institutions, characterized by high government effectiveness and adherence to the rule of law, are better equipped to design, implement, and monitor environmental regulations consistently and reliably [9]. Effective enforcement mechanisms ensure that environmental laws are not merely symbolic but translate into tangible changes in behavior [10].

As a stable framework for property rights and contract enforcement, the rule of law can promote long-term investment horizons and more sustainable resource management practices. Third, the control of corruption is critical since it allows for the weakening of environmental regulation through the diversion of resources meant to protect the environment and the continuation of polluting activities by underhanded means. Fourth, political stability and democratic accountability enable better environmental outcomes. More stable governments may be able to pursue long-term environmental goals better. In contrast, democratic institutions, especially those ensuring voice and accountability and a free press, lead to greater public awareness and pressure for environmental protection, making governments more responsive to environmental issues. Finally, in the context of eco-innovation, a high regulatory quality encourages the diffusion of eco-innovations by establishing clear rules and standards as well as by providing incentives. These relationships are often tested in empirical studies using world governance indicators or analogous indices. The results of analyses of data in various socio-geographical contexts—Africa, BRICS, G7, EU member states, and global samples [11,12,13,14,15]—generally indicate significant correlations between better governance indicators (rule of law, government effectiveness, regulatory quality, political stability, and less corruption) and better environmental outcomes, whether in terms of lower carbon dioxide emissions, smaller ecological footprints or better scores on environmental performance indices. The beneficial influence of institutional quality on environmental outcomes seems relatively robust, indicating an underlying relationship. However, the specific channels and the magnitude of the effects can vary by context, specific environmental issues and the dimensions of governance considered [16].

2.2. The Nexus Between Institutional Quality and Corporate Environmental Investment

While establishing a broader relationship between institutions and environmental outcomes, a more specific strand of the literature explores the implications of institutional quality for corporate environmental practices, namely environmental investments and expenditures, which are typically proxied by measures similar to environmental protection investment corporations (EPIC) or wider environmental, social, and governance (ESG) performance indicators.

The theoretical expectation is rather that a greater institutional quality should induce firms to contribute more to environmental protection [17]. Multiple premises lead to this hypothesis. Good institutions provide a less risky and more predictable regulatory context for long-term investments, including those in environmental protection [18]. The environmental rule of law—substantial environmental rules and standards—never operate in a vacuum. Bureaucracies that operate efficiently and have a low level of corruption minimize transaction costs in the process of obtaining environmental permits or carrying out environmental projects. In societies characterized by good governance, there may also be heightened public awareness and stakeholder scrutiny (in the form of investors, consumers, and communities) on environmental matters.

Firms invest more in environmental protection to enhance their legitimacy and maintain their social license to operate (i.e., the conditions under which society approves of their practices) and a positive corporate reputation. Finally, sound institutional frameworks, especially those fostering development and transparency in financial markets, could reduce barriers to accessing finance, especially green finance, for environmental investment.

Overall, empirical evidence tends to support the positive relationship between institutional quality and corporate environmental action. Research on European companies has revealed a positive relationship between corporate sustainability performance and institutional quality, especially on dimensions such as the rule of law and control of corruption. This suggests that firms can positively impact their sustainability performance and potentially their financial performance through such efforts. Studies of EU countries have shown that better governance is also related to better performance in certain areas of environmental policy, such as waste recycling [19].

Internationally, better institutional quality is related to higher general environmental performance indices that aggregate different environmental results are likely affected by firm behavior. Some studies further connect institutional quality with a rise in green innovation, which typically requires environmental investments. Similarly, the effectiveness of government environmental expenditures, which may interact with corporate expenditures, has also been shown to be contingent on governance quality [20].

Although institutional quality adds an important context, corporate decision making regarding environmental protection investments in corporations (EPIC) is a complex multi-factorial phenomenon. Regulatory pressure is consistently cited as one of the top drivers. In terms of energy and climate, this also includes national and international environmental policies and standards, permits (which fall under the EU’s Industrial Emissions Directive, the successor of IPPC Directive), emissions trading schemes (including the EU ETS), and environmental taxes, whilst directly creating incentives and requirements to invest in these activities [21].

Furthermore, the linkage to financial performance or profitability is multifaceted: some maintain that profitability allows investment, while others conclude that environmental outlays can have a short-term cost but offer longer-term payback, such as improved reputation or lower costs of finance. The nature of the industry is important. Companies in more pollution-intensive or energy-intensive industries have higher environmental obligations, both in terms of being subject to specific regulations and facing greater scrutiny to invest in environmental projects. Investment can also be spurred by export orientation, as firms competing in international markets may be required to achieve higher environmental standards or satisfy environmentally concerned consumers.

Market and stakeholder pressures are also important. Environmental spending is mainly motivated by pressure from investors, customers, local communities, and NGOs, as well as the desire to build a positive “green” corporate image and enhance legitimacy. Strong ESG performance is emerging as a prominent investment criterion for investors and other stakeholders [22].

Technological and economic factors could be deemed as determinants as well. Environmental investments are frequently concurrent with the implementation of cleaner technologies or the pursuit of green innovation, in line with the Porter hypothesis that requires that well-designed environmental regulations could drive innovation. The resources available and the financing constraints allow or prevent firms from undertaking environmental projects [23].

Fiscal policies strongly interact with corporate decisions through environmental taxes: they can increase the cost of pollution (in relation to EPIC), while public expenditures could complement or substitute for private investment (in some cases, crowding it out). Environmental subsidies can also be a factor in undertaking environmental protection investments.

Lastly, regional factors, including local air quality, local specific regulatory frameworks, or spill-over effects of green investments by neighboring firms, impact a firm’s environmental behavior [24].

2.3. The Role of Environmental Investment in Mitigating Climate Change Risks

Environmental fiscal instruments, namely environmental taxes and public environmental expenditures, represent key policy levers used by governments to influence environmental outcomes and shape the economic context for businesses. This study includes environmental tax revenues and expenditure on environmental protection, both measured as a percentage of GDP, as control variables. The first captures revenues collected from taxes levied on activities with proven negative environmental impacts (e.g., energy use, transport, pollution, resource extraction). The second represents financial resources allocated by the public sector specifically for the prevention, reduction, and elimination of pollution and other environmental degradation [25].

Environmental taxes are market-based instruments designed to internalize environmental externalities by incorporating their costs into market prices, adhering to the “polluter pays” principle. By making environmentally damaging activities more expensive, they aim to incentivize behavioral changes, such as reducing pollution, conserving resources, and improving energy efficiency. Furthermore, environmental taxes can stimulate innovation in cleaner technologies (consistent with the Porter hypothesis) and generate public revenue. The concept of environmental tax reform often involves using these revenues to reduce other, potentially more distortionary taxes, such as those on labor or capital, aiming for a “double dividend” of environmental improvement and economic benefits (e.g., increased employment or growth). Evidence from the EU suggests that well-designed environmental taxes can be effective in achieving environmental objectives, such as reducing CO₂ emissions, although their effectiveness hinges on factors like the tax base, rate structure, exemptions, and overall policy context. Potential regressive impacts on lower-income households are key considerations in tax design and revenue recycling [26,27].

Public expenditures on environmental protection represent a more direct form of government intervention. These expenditures fund activities such as waste and wastewater management, biodiversity protection, environmental R&D, and administration. They can directly contribute to environmental improvements and support the development of green infrastructure and technologies. Studies have linked higher government environmental spending to better national ESG performance and reductions in certain pollutants. However, the effectiveness of expenditures on environmental protection can be influenced by the quality of governance overseeing its allocation and implementation [28,29].

Beyond the direct impact of fiscal instruments, the broader institutional context plays a pivotal role in shaping the effectiveness of environmental investments in addressing climate change risks. The interplay between environmental investments and climate change adaptation is further underscored by the role of institutional frameworks in fostering resilient economic systems. Classic literature, such as North’s (1990) work on institutions and economic performance, emphasizes that robust institutional structures facilitate adaptive capacity by providing stable rules and incentives for long-term planning [30]. In the context of climate change, high-quality institutions enable firms to align their environmental investments with adaptation strategies, such as adopting climate-resilient technologies or diversifying supply chains to mitigate risks from extreme weather events. Empirical studies, drawing on frameworks like those of Acemoglu and Robinson (2012), suggest that inclusive institutions—characterized by transparent governance and stakeholder engagement—enhance firms’ ability to respond to climate risks by fostering collaboration between public and private sectors [31]. This collaboration is critical for scaling up investments in green infrastructure and ensuring that adaptation measures are both economically viable and environmentally sustainable, as highlighted in analyses of EU adaptation policies post-Paris Agreement [32].

Moreover, the effectiveness of environmental investments in mitigating climate risks is contingent on the coherence of policy instruments and their alignment with institutional quality. Drawing on Ostrom’s (1990) insights into collective action and resource governance, well-designed environmental policies—supported by strong regulatory quality and low corruption—can incentivize firms to invest in adaptation measures that address both local and global climate challenges [33]. Recent studies, such as those by Mazzucato (2018), underscore the role of mission-oriented innovation policies in directing corporate environmental investments toward transformative adaptation outcomes, such as flood-resistant urban infrastructure or drought-tolerant agricultural practices [34]. These findings align with empirical evidence from the EU-27, where countries with higher governance scores on world governance indicators exhibit greater corporate engagement in climate adaptation, particularly in sectors like energy and agriculture, which face heightened climate vulnerabilities [35].

The preceding literature review reveals several significant insights that form the foundation and rationale for our research. However, adapting to climate change is a priority challenge for both the European Union as a whole and economic sectors within Member States, which will play a central role in the design and implementation of cross-sectoral adaptation measures. In this respect, the quality of institutions is the core of the governance level, which determines environmental and economic results. It expresses the success of policies and the stability of regulatory frameworks, as well as the wider climate for business. General empirical literature supports a positive link between stronger institutional quality and corporate environmental performance and investment, as well as industrial and economic productivity. Nonetheless, such relationships are complicated and come with trade-offs, particularly around the burden of regulation. Specific environmental regulations, firm-level characteristics, energy consumption and energy costs, environmental tax reforms, environmental expenditure programs, and significant international policy developments like the Paris Agreement all fall under this umbrella.

To address these complexities, this study investigates the following research question: What is the impact of distinct dimensions of institutional quality—namely, control of corruption, government effectiveness, rule of law, and regulatory quality—both individually and as a composite index, on corporate environmental investments and climate change adaptation outcomes across EU-27 member states over the period 2006–2023? Despite this existing knowledge, specific gaps remain that our study aims to address. There is little research that investigates the impact of separate components of institutional quality on various aspects of business adaptation and examines the collective effects of these components via a composite index. Furthermore, such analysis is needed within the specific, relatively high-governance context of the EU-27, covering the recent period (2006–2023) marked by significant environmental policy evolution.

While the individual dimensions of governance—such as control of corruption, government effectiveness, rule of law, and regulatory quality—offer important insights, we place particular emphasis on their combined effect, captured through a principal component analysis (PCA) to construct a composite institutional quality index. This approach helps mitigate multicollinearity and better reflects the overall governance environment. By synthesizing these dimensions, the composite index reflects the synergistic impact of governance quality, aligning with the presumption that institutions shape economic incentives through stable and predictable frameworks. Moreover, this approach allows us to capture the broader institutional context within the EU-27, where high governance standards amplify the effectiveness of environmental policies, as evidenced by post-Paris Agreement advancements. Additionally, testing individual dimensions ensures a comprehensive analysis, revealing whether specific governance aspects (e.g., rule of law) have distinct impacts, thus contributing to a nuanced understanding of institutional influences.

Accordingly, we propose the following research hypotheses:

H1: 

Institutional quality—measured through a principal component aggregating control of corruption, government effectiveness, rule of law, and regulatory quality—has a statistically significant positive effect on environmental protection investment corporations (EPIC) in the EU-27 over the period 2006–2023.

H2: 

Institutional quality—captured by the principal component of the world governance indicators—affects industrial production levels due to burdensome bureaucracy, reflecting business adaptation to climate change, with statistically significant effects across the EU-27 over the period 2006–2023.

3. Materials and Methods

We start by presenting the data collected annually for the 27 EU member states from 2006 until 2023.

Table 1. Description of the variables employed in the analysis.

Variable	Abbreviation	Description	Source
Control of corruption	CC	CC measures the extent to which public power is exercised for private gain (including petty and grand forms of corruption), reflecting their private interests.	World Bank Group—Worldwide Governance Indicators
Government effectiveness	GE	GE captures the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government’s commitment to such policies.
Rule of law	RL	RL captures the extent to which agents have confidence in and abide by society’s rules, the quality of contract enforcement, property rights, the police, and court laws, and the likelihood of crime and violence.
Regulatory quality	RQ	RQ measures the government’s ability to formulate and implement sound policies and regulations that permit and promote private-sector development.
Environmental protection investment corporations—total environmental protection activities (million Euros)	EPIC	Environmental protection expenditures refer to investments, consumption, and other expenses related to preventing, reducing, and eliminating pollution and other degradations of the environment.	Eurostat
Production in industry (annual data 2015 = 100)	IP	The industrial production index (IPI) measures real output and is expressed as a percentage of real output in a base year. IPI covers production output in mining, manufacturing and public utilities (electricity, gas and water), but excludes construction.	Eurostat
Final energy consumption—tons of oil equivalent (TOE) per capita	FEC	“Final energy consumption” covers only the energy consumed by end users, such as industry, transport, households, services, and agriculture; it excludes the energy sector’s energy consumption and losses occurring during energy transformation and distribution.	Eurostat
Environmental tax revenues (% of GDP)	ETR	ETR, measured as a % of GDP, refers to funds collected by governments through taxation on activities that have negative environmental impacts, such as pollution or resource extraction.	Eurostat
Expenditure on environmental protection (% of GDP)	EEP	EEP, measured as a % of GDP, represents financial resources allocated by the public sector towards activities whose primary purpose is the prevention, reduction, and elimination of pollution and any other degradation of the environment.	Eurostat
Paris Agreement dummy	PAD	This variable has a value of 0 before 2015 and 1 starting from 2015; the Paris Agreement was adopted on 12 December 2015, and is considered on a five-year cycle, with increasingly ambitious climate action carried out by countries.	n.a

Source: Authors’ compilation.

presents the indicators considered in our analysis.

The data available for the environmental protection investment corporations were completed to run the regression models on a balanced panel, using the imputation method, based on the average values of the data available for every country reviewed.

Because our study is based on regression analysis, we start by testing the stationarity of every variable and transforming several indicators: we applied the natural logarithm to the environmental protection investment corporations, obtaining an indicator with a level similar to the rest of the variables; we applied the first-order difference to the environmental tax revenues and expenditure on environmental protection.

Our study tries to explain how institutional quality influences business adaptation strategies to climate change through various means, such as energy consumption, environmental taxes, or expenditures for environmental protection. The regression models employed consider two dependent variables, relating these response indicators to business adaptation to climate change: the environmental protection investment corporations and the production in industry. Institutional quality, observed through the quality of governance, focuses on the world governance indicators (WGI) related to public authorities and governance: control of corruption, government effectiveness, rule of law, and regulatory quality. Although we test the individual influence of the governance indicators on the dependent variables, we also consider a principal component to encompass the strength of the four governance indicators. Through linear combinations of the original WGI variables, this component will maximally explain the variance of all the variables, being further considered the proxy of institutional quality. Through principal component analysis (PCA), we also mitigate the collinearity among the world governance indicators, omitting highly correlated variables from the model, ensuring statistical validity of the regression results.

We present the following linear models, which will be tested for fixed effects (FE) and random effects (RE) within panel data, covering the whole EU.

Business Adaptation Proxy_it = α + β₁CC_it + β₂GE_it + β₃RL_it + β₄RQ_it + μ_it + ϵ_it,

(1)

Business Adaptation Proxy_it = α + β₁PCinst.qual._it + μ_it + ϵ_it

(2)

These are the main models considering institutional quality and business adaptation proxies—the environmental protection investment corporations (EPIC) and the industrial production index (PI). We incorporate relevant control variables based on prior research to isolate the impact of institutional quality, ensuring that our findings remain consistent under different model specifications. The potential influence of additional explanatory factors is carefully managed through robustness checks by including fixed and random effects models. The models will be developed with supplementary indicators related to energy consumption (FEC), environmental taxes (ETR), and environmental protection (EEP). These undertake the role of control variables to test any changes in the institutional quality effect on the dependent variables. In addition, a dummy variable (PAD) will be included to test the influence of the adoption of the Paris Agreement within the EU.

Business adaptation Proxy_it = α + β₁PCinst.qual._it + β₂FEC_it + β₃ETR_it + β₄EEP_it + β₄PAD_t + μ_it + ϵ_it

(3)

Endogeneity concerns will be addressed through instrumental variable methods, employed through dynamic analysis, with generalized method of moments (GMM). By leveraging external instruments that are theoretically and empirically justified, we enhance results robustness and develop discussions.

4. Results and Discussion

We start by presenting the results of the principal component analysis, which gathers the influences from governance indicators into a component presenting institutional quality. In

Table 2. Principal component analysis applied to the world governance indicators related to public authorities.

Component	Eigen Value	Cumulative Proportion	Variable	Eigen Vectors/ Scoring Coefficients (Comp1)
Comp1	3.7562	0.9391	CC	0.5037
Comp2	0.1367	0.9732	GE	0.5006
Comp3	0.0606	0.9884	RL	0.5063
Comp4	0.0465	1.0000	RQ	0.4893

Source: Authors’ processing in Stata 17.

, we observe that the four world governance indicators may be reduced to one based on dimensionality reduction and the machine learning method carried out through principal component analysis.

Figure 1 below reflect postestimation indicators from the principal component analysis undertaken. The figure on the left helps identify the first component as the one worth retaining to illustrate institutional quality. The loadings plot presented on the right side clarifies how WGI variables shape the new dimensions. Positive loadings indicate that an increase in the variables pushes the component in a positive direction. From the four WGI, we observe the highest loading from regulatory quality (approximately 0.9), while the other three governance indicators (rule of law, control of corruption, and government effectiveness) have moderate loadings (approximately 0.5).

We expect a positive influence from the governance indicators related to regulations and institutions. This comes from the broad institutional context shaping the effectiveness of environmental investments in addressing climate change risks. As evidenced in the literature review, even from the early 1990s, the recent papers evidenced the effectiveness of environmental investments in mitigating climate risks with a dependence on policy instruments and alignment with institutional quality [30,31,32,33]. Further on, we will overview the individual effects of the world governance indicators, but our focus is to observe their overall effect through an institutional quality proxy obtained through PCA.

In

Table 3. Results of regression models reflecting the influence of institutional quality on environmental protection investment corporations.

	(FE)	(RE)	(FE)	(RE)
Variables	EPIC	EPIC	EPIC	EPIC
CC	0.110	0.150
	(0.162)	(0.160)
GE	−0.00132	0.00531
	(0.163)	(0.162)
RL	0.182	0.188
	(0.208)	(0.207)
RQ	0.121	0.119
	(0.173)	(0.172)
PCinst.qual.			0.120 **	0.137 ***
			(0.0506)	(0.0481)
Constant	4.900 ***	4.851 ***	5.341 ***	5.341 ***
	(0.192)	(0.357)	(0.0198)	(0.298)
Observations	486	486	486	486
Hausman–chi2 (prob.)		2.02 (0.7317)		1.20 (0.2727)
R-squared (within)	0.0132	0.0132	0.0121	0.0121
R-squared (between)	0.1322	0.1345	0.1278	0.1278
R-squared (overall)	0.1225	0.1247	0.1183	0.1183
F statistic/Wald chi2	1.52	8.60 *	5.61 **	8.08 ***
Number of countries (ID)	27	27	27	27

Standard errors in parentheses; *** p < 0.01, ** p < 0.05, * p < 0.1. Source: Authors’ processing in Stata.

, we present the results from the regression model that reflects the influences of institutional quality on environmental protection investment corporations. After initially testing the influence of WGI, we observe that most governance indicators carry a direct influence on EPIC, but they are not statistically significant. However, for the institutional quality proxy, there is a significance at the 1% level, indicating that the quality of public authorities and good governance would induce investments and consumption for preventing, reducing, and eliminating pollution or environmental degradation, being associated with higher levels of environmental protection investment corporations. In both cases, the Hausman test indicated that the random effects model is more appropriate for describing the influence of WGI or principal component on EPIC, considering the EU sample.

We continue by adding supplementary variables in separate stages to assess the impact of energy consumption or specific tax revenues and any changes in the influence of institutional quality on EPIC. Results are presented in

Table 4. Results of regression models reflecting the influence on environmental protection investment corporations.

	(FE)	(RE)	(FE)	(RE)	(FE)	(RE)	(FE)	(RE)	(RE*)
Variables	EPIC	EPIC	EPIC	EPIC	EPIC	EPIC	EPIC	EPIC	EPIC
PCinst.qual.	0.143 ***	0.162 ***	0.125 **	0.143 ***	−0.0216	0.0996	0.152 ***	0.174 ***	0.177 ***
	(0.0511)	(0.0491)	(0.0544)	(0.0514)	(0.114)	(0.0934)	(0.0548)	(0.0525)	(0.0542)
FEC	−0.189 **	−0.175 **					−0.226 ***	−0.207 ***	−0.203 **
	(0.0735)	(0.0712)					(0.0818)	(0.0788)	(0.0807)
ETR			0.140 *	0.140 *	0.360 ***	0.353 ***	0.148 *	0.147 *	0.151 *
			(0.0840)	(0.0839)	(0.132)	(0.133)	(0.0834)	(0.0833)	(0.0847)
EEP					0.215 ***	0.225 ***
					(0.0695)	(0.0697)
PAD									0.0109
									(0.0448)
Constant	5.790 ***	5.756 ***	5.345 ***	5.345 ***	5.294 ***	5.296 ***	5.880 ***	5.835 ***	5.819 ***
	(0.176)	(0.346)	(0.0209)	(0.302)	(0.0318)	(0.309)	(0.194)	(0.359)	(0.365)
Observations	486	486	459	459	271	271	459	459	459
Hausman–chi2 (prob.)		1.96 (0.3751)		1.16 (0.3609)		3.41 (0.3322)		2.07 (0.5582)
R-squared (within)	0.0262	0.0258	0.0183	0.0183	0.0584	0.0542	0.0356	0.0351	0.0350
R-squared (between)	0.0763	0.1018	0.1300	0.1298	0.0588	0.1653	0.0608	0.0924	0.0972
R-squared (overall)	0.0711	0.0940	0.1197	0.1199	0.0036	0.1280	0.0579	0.0860	0.0904
F statistic/Wald chi2	6.15 ***	14.07 ***	4.02 **	10.52 ***	4.99 ***	15.85 ***	5.28 ***	17.49 ***	26.37 ***
No. of ID	27	27	27	27	27	27	27	27	27

Standard errors in parentheses; *** p < 0.01, ** p < 0.05, * p < 0.1. Source: Authors’ processing in Stata.

. Even with the control variables progressively included in the model, the positive influence of institutional quality on EPIC is maintained, carrying a statistical significance for the great majority of the models tested, except for the one including environmental tax revenues and expenditures on environmental protection next to the principal component. Because the latter seems to influence the statistical significance of the other explanatory variables, we omit it from the last models employed, keeping along with institutional quality the final energy consumption, environmental tax revenues, and the dummy variable. The adoption of the Paris Agreement did not prove its influence on EPIC, as its regression coefficient is not statistically significant. The variable FEC represents an important factor of influence on EPIC, proving that higher energy consumption, resulting in more tons of oil equivalent per capita, comes with a decrease in EPIC, limiting investments, consumption, and other expenses related to preventing, reducing, and eliminating pollution and environmental degradation. Based on the results obtained, an increase in the environmental tax revenues and in the expenditure on environmental protection is also expected to support business investment and consumption to reduce pollution and environmental degradation.

The last model employed to describe the variance in EPIC (with results presented in column “RE*”) is a random effects model corrected for heteroscedasticity and autocorrelation. Based on the Hausman test, the random effects were more appropriate for all models, which led us to believe that the specific characteristics of the EU countries would not induce differences across the countries for the influences of independent and control variables on EPIC. Accordingly, we expect a better business adaptation to climate change based on a larger level of environmental protection investment corporations in countries with better governance that register larger environmental tax revenues, spend more on environmental protection, and where businesses and citizens consume less energy coming from fossil sources.

To enhance interpretation, we continue with the coefficient plots for the main regression models, representing the estimated effects of predictors on the dependent variable, EPI as depicted by Figure 2 below. C. By considering 95% confidence intervals, the plots suggest the precision and uncertainty of the estimates of the regression model with random effects, with the institutional quality proxy as the independent variable, and the final model (the random effects model corrected for heteroscedasticity and autocorrelation). The coefficient plot illustrates how independent variables stand out as strong predictors, with narrow confidence intervals suggesting high precision.

Further, we consider the business adaptation strategies reflected through the industrial production index (variable IP), which measures the production output in mining, manufacturing, and public utilities within a country. The first step is to review the influence coming from the world governance indicators. Based on the regression coefficients of the first two models presented in

Table 5. Results of regression models reflecting the influence of institutional quality on the industrial production index.

	(FE)	(RE)	(FE)	(RE)
VARIABLES	IP	IP	IP	IP
CC	21.74 ***	13.06 ***
	(5.363)	(4.009)
GE	−21.34 ***	−13.97 ***
	(5.405)	(4.774)
RL	16.97 **	5.446
	(7.020)	(5.770)
RQ	−5.308	−8.324 *
	(5.739)	(4.838)
PCinst.qual.			3.643 **	0.799
			(1.746)	(0.648)
Constant	93.77 ***	109.9 ***	104.2 ***	104.0 ***
	(6.265)	(3.629)	(0.698)	(1.325)
Observations	468	468	468	468
Hausman–chi2 (prob.)	35.29 (0.0000)		3.08 (0.0794)
R-squared (within)	0.0855	0.0645	0.0098	0.0098
R-squared (between)	0.0014	0.0003	0.0103	0.0103
R-squared (overall)	0.0097	0.0197	0.0035	0.0035
F statistic/Wald chi2	10.23 ***	19.35 ***	4.35 **	1.52
Number of countries (ID)	27	27	27	27

Standard errors in parentheses; *** p < 0.01, ** p < 0.05, * p < 0.1. Source: Authors’ processing in Stata.

, higher corruption and bureaucracy would constrain industrial production. At the same time, government efficiency and confidence in the rules of society and better law enforcement support the increase in industrial production. Overall, institutional quality seems to have a positive influence on the industrial production index. Opposed to the previous analysis of EPIC, the Hausman tests indicate that for the IP variable, the fixed effects model is more appropriate.

We add the supplementary variables (energy consumption, environmental tax revenues, environmental protection, dummy) and observe any changes in the influence of institutional quality on IP. From the comparative results presented in

Table 6. Results of regression models reflecting the influence on industrial production.

	(FE)	(RE)	(FE)	(RE)	(FE)	(RE)	(Corr *)
VARIABLES	IP	IP	IP	IP	IP	IP	IP
PCinst.qual.	2.677	0.323	−5.856 **	−0.913	−0.836	−0.932	−0.266
	(1.752)	(0.820)	(2.390)	(0.607)	(2.057)	(0.791)	(0.294)
FEC	8.290 ***	1.306			12.89 ***	1.218	−0.486
	(2.531)	(1.256)			(3.399)	(1.343)	(0.377)
ETR			−6.953 **	−7.107 ***	−3.908 *	−3.198	−2.821
			(2.724)	(2.693)	(2.307)	(2.323)	(2.155)
EEP			8.027 ***	8.429 ***	7.617 ***	7.169 ***	7.240 ***
			(1.423)	(1.413)	(1.196)	(1.203)	(2.662)
PAD					12.81 ***	13.08 ***	13.23 ***
					(1.378)	(1.365)	(3.453)
Constant	84.47 ***	100.9 ***	105.2 ***	105.8 ***	66.03 ***	92.79 ***	96.678 ***
	(6.058)	(3.304)	(0.713)	(1.208)	(7.876)	(3.484)	(3.432)
Observations	468	468	261	261	261	261	261
Hausman–chi2 (prob.)	12.84 (0.0016)			4.30 (0.2309)	14.03 (0.0154)
R-squared (within)	0.0330	0.0331	0.1919	0.1770	0.4460	0.4176	0.3266
R-squared (between)	0.0036	0.0031	0.0147	0.0254	0.0372	0.0003
R-squared (overall)	0.0030	0.0029	0.0419	0.1406	0.0371	0.3125
F statistic/Wald chi2	7.59 ***	2.62	18.36 ***	50.78 ***	37.04 ***	165.94 ***	36.23 ***
No. of ID	27	27	27	27	27	27	27

Standard errors in parentheses; *** p < 0.01, ** p < 0.05, * p < 0.1. Source: Authors’ processing in Stata.

, we observe some inconsistency in the influence of institutional quality on industrial production because its regression coefficient becomes negative. However, in most models with many explanatory variables, it is not statistically significant. An increase in energy consumption coming from fossil fuels would support the increase in the index of industrial production. Moreover, production is also greater in countries that spend more on environmental protection. Also, the industrial production index is better when environmental tax revenues are lower, in association with the fact that higher industrial production is expected within countries where citizens and businesses are large consumers of fossil energy. In this model, the adoption of the Paris Agreement has a significant positive influence on IP. From all the models regressed, the Hausman test indicated a preference for the model with fixed effects, proving that industrial production and its influential factors could be specific to countries based on their individual features (economies, degrees of development, regimes, etc.). The final model employed corrects for heteroskedasticity and serial correlation, with results presented in the last column of the table. From the indicators overviewed in this study, the strongest influence on industrial production within EU countries comes from the expenditure on environmental protection (EEP) and the dummy variable emphasizing the influence of the Paris Agreement, indicating that businesses do focus their attention and strategies towards mitigating climate change risks and reducing their negative impact on the environment.

We continue with the coefficient plots for the simple regression model and the final one, applied for the dependent variable IP. In this case the final model depicted in Figure 3 below refers to a fixed effects model corrected for heteroskedasticity and serial correlation.

Furthermore, we approach the two-stage least squares (2SLS) model with instrumental variables with the dynamic model through the generalized method of moments (GMM). 2SLS is particularly useful when dealing with endogeneity, referring to a situation where an independent variable is correlated with the error term, potentially biasing ordinary least squares estimates. Because our model cannot capture all the influential factors of dependent variables, omitted variables, measurement errors, or simultaneity between the indicators employed in the analysis may affect the results. 2SLS uses instrumental variables, allowing us to estimate causal effects. By replacing the endogenous variable with its predicted value from the first stage, the model ensures consistency. The Arellano–Bond GMM estimator is introducing additional moment conditions to improve efficiency, and it also considers the dynamics within the dependent variables, overviewing their past values’ influence on the present. We tested the final and corrected models for describing the variance in EPIC and IP, respectively, and for the dynamic models we considered the Sargan test and the Arellano–Bond test for zero autocorrelation to test the validity of the GMM estimators. Results are presented in

Table 7. Results of 2SLS and GMM regression models reflecting the influence on environmental protection investment corporations and on industrial production.

	(2SLS)	(2SLS Robust)	(GMM)	(2SLS)	(2SLS Robust)	(GMM)
VARIABLES	EPIC	EPIC	EPIC	IP	IP	IP
EPIC/PI_L1			0.793 ***			0.591 ***
			(0.016)			(0.057)
EPIC/PI_L2			0.212 ***			0.171 ***
			(0.022)			(0.037)
PCinst.qual.	0.359 ***	0.359 ***	0.099 ***	−0.266	−0.266	−2.029 *
	(0.048)	(0.044)	(0.028)	(0.431)	(0.380)	(1.088)
FEC	−0.147 *	−0.148 **	−0.052	−0.486	−0.486	11.565 ***
	(0.077)	(0.086)	(0.035)	(0.725)	(0.591)	(1.749)
ETR	0.291	0.291	0.227 ***	−2.821	−2.821	−3.187 ***
	(0.2923)	(0.240)	(0.052)	(2.576)	(3.515)	(1.088)
EEP				7.240 ***	7.240 ***	3.064 ***
				(1.373)	(1.183)	(0.48)
PAD	0.073	0.073	0.092 ***	13.23 ***	13.23 ***	4.382 ***
	(0.147)	(0.141)	(0.007)	(1.565)	(1.024)	(0.385)
Constant	5.661 ***	5.661 ***		96.678 ***	96.678 ***
	(0.213)	(0.194)		(2.152)	(1.487)
Observations	468	459	432	261	261	261
R-squared	0.1274	0.1274		0.3266	0.3266
Wald chi2	66.99 ***	106.20 ***	222,487.39 ***	126.59 ***	219.66 ***	5348.17 ***
Sargan test			26.382 (0.9837)			25.544 (1.000)
Arellano–Bond test (ord.1, ord.2)			−2.2407 ** −0.6806			−3.763 *** 1.4054
No. of ID	27	27	27	27	27	27

Standard errors in parentheses; *** p < 0.01, ** p < 0.05, * p < 0.1. Source: Authors’ processing in Stata.

.

After testing the results of the 2SLS models, we received the indication that the models contain no endogenous variables. Results from the dynamic model proved that the lagged values of EPIC and IP (lag 1 and lag 2) also induce a significant positive influence on their present values. Accordingly, the GMM results suggest a significant direct effect from the level of the dependent variables (EPIC and IP, respectively) registered in the previous two years. These findings allow us to confirm that results obtained from the linear models with fixed or random effects suggest the correct relationships towards the dependent variables, environmental protection investment corporations and industrial production.

Based on the results obtained, lower environmental tax revenues, consistent expenditures on environmental protection, and high fossil energy consumption are expected to support industrial production, with an emphasis on the fact that these relationships might differ across regions because they seem influenced by the characteristics of the EU member states. This divergence highlights a tension noted by Taylor et al. (2025), where governance may prioritize environmental outcomes over industrial productivity in high-pollution sectors [35]. The significant role of EEP and PAD suggests that public investment and global climate commitments are critical for aligning industrial strategies with climate goals, a finding consistent with Mazzucato’s (2018) advocacy for mission-oriented policies [34]. However, the negative ETR effect on IP indicates potential economic trade-offs, as higher taxes may deter production in energy-intensive industries, a challenge also identified by OECD [36].

Following the statistically significant results obtained through our linear regression analysis, we realized two diagrams (Figure 4 and Figure 5) to visually represent the connections between institutional quality, energy consumption, environmental taxes, environmental protection, and the Paris Agreement enactment, with the dependent variables reflecting the response indicators to business adaptation to climate change (environmental protection investment corporations and production in industry). Indicators with a negative influence on the dependent variables are evidenced in a red background, while those carrying a direct or positive influence are highlighted in green.

Our findings contribute to the literature by demonstrating that institutional quality’s influence varies by adaptation proxy, with stronger effects on proactive environmental investments (EPIC) than on industrial output (IP), offering nuanced insights for policymakers aiming to balance sustainability and economic growth in the EU.

5. Conclusions

This study explores the moderating role of institutional quality on business adaptation, observing the role of the public sector in stimulating companies to undertake environmental protection investments and supporting industry production. The overview is from a European panel, between 2006 and 2023, reflected through energy consumption, environmental tax revenues, and environmental protection. The results illustrate that better quality of public authorities and good governance would stimulate businesses to realize more investments for preventing, reducing, and eliminating pollution or environmental degradation. These investments are expected to be more prominent in countries with larger environmental tax revenues, and they are also specific to regions where businesses and citizens consume less energy from fossil sources. This is in accordance with previous findings presented in the literature [7,10], confirming the capacity of the government to effectively formulate and implement sound policies, achieving positive environmental outcomes. Thus, the study contributes to the literature by demonstrating how institutional quality, as a component of governance theory, interacts with fiscal tools to drive environmental outcomes at the macroeconomic level.

Government efficiency and confidence in the rules and legislation support the increase in industrial production. Although countries that invest more in environmental protection see higher production levels, an increase in energy consumption from fossil fuels tends to boost the industrial production index as well. But nowadays, as our study proves, industrial production performs better when environmental tax revenues are lower, because higher industrial production is recorded in countries where citizens and businesses heavily consume fossil energy. Therefore, we see an urgent need for businesses to develop and turn to environmental practices, investing in their operations and activities to make them more sustainable. Over the long term, these investments for preventing, reducing, and eliminating pollution and environmental degradation will also help the EU countries align in terms of environmental taxation, regulations, and preference for energy consumption, reducing the disparities within the EU member states from factors such as high greenhouse gas emissions, lagging climate policy, or high fossil fuel use. These findings also offer practical implications for policymakers aiming to balance industrial productivity with environmental targets through improved fiscal and institutional coordination.

Fiscal policies represent the key levers in the relationship between government and businesses’ investments in adaptation to climate change, as our study evidenced the role of environmental tax revenues and expenditures on environmental protection. Lower environmental tax revenues are specific to countries with increased production in high-polluting industries (e.g., mining, manufacturing, and public utilities). But the environmental protection activities from corporations are better represented in countries with higher environmental tax revenues, which have stricter environmental regulations and policies. Here, businesses try to make green investments, seeking cost-effective ways to reduce their tax burden. Additionally, environmental taxation may create financial incentives, which make businesses more willing to adopt sustainable practices. Therefore, environmental taxes may induce sustainable investments and economic development because they generate public revenues while promoting environmentally friendly behavior by taxing activities with negative environmental impacts. This supports a theoretical contribution by integrating environmental economics and institutional governance in explaining the adaptive behavior of firms under varying regulatory regimes.

The expenditure on environmental protection sustains both industrial production and environmental protection investment. Investments in environmental protection may lead to the development of new technologies and processes that improve business efficiency through cleaner production techniques, cost savings, and increased productivity. This sustains the positive influence of the regulatory pressure and the role of government environmental expenditures in corporate decisions in investments evidenced in the literature [20,21]. Financial support coming from governmental subsidies or tax incentives can offset the costs of environmental investments and make it more feasible for companies to adopt sustainable practices. Accordingly, investing in environmental protection can help companies manage risks associated with environmental liabilities and make them comply with the specific environmental regulations. Our overall results indicate that within EU countries, businesses adopt proactive strategies through sustainable investments to mitigate climate change risks. These results provide a framework for designing environmental fiscal policies that align incentives across public and private sectors. Future research may explore response at a firm level or assess the differentiated effects across sectors and regions.

Although the adoption of the Paris Agreement did not indicate a significant influence on the environmental protection investment corporations variable, it proved its influence on the industrial production index. As the Paris Agreement provides a unified global framework for climate action, setting clear goals for reducing greenhouse gas emission levels, it is expected that companies will invest more in sustainable technologies, products, and services. This will improve the economic activities of companies in terms of reducing greenhouse gas emissions and negative environmental impact. These investments also build on the businesses’ reputation and brand image, adding to the potential of increased customer loyalty and attracting environmentally conscious customers and consumers. New financing opportunities may be available as governments committed to the Paris Agreement often provide funding, grants, and incentives for businesses that invest in sustainable practices. Accordingly, sound sustainability policies and practices applied by companies may improve their activities in terms of attracting capital and enhancing their reputation. This highlights the practical need for international climate agreements to be reinforced with strong institutional mechanisms at the national level to enable more effective implementation.

Our findings prove that nowadays, although institutional quality has a rather limited effect on businesses and industry, it has significant potential to influence the development of investments in environmentally friendly practices, mitigating the harmful impact of industrial production and protecting the environment. Public policies could also influence individuals’ and businesses’ preferences for energy consumption, transferring it to renewable sources, through regulations for limitation of greenhouse gas emissions, tax incentives for the installation of renewable energy systems, or funding allocation for research and development in renewable energy technologies. Over the long term, institutional quality plays a crucial role in influencing business adaptation strategies to climate change. Such an approach supports a model in which institutional capacity and regulatory efficiency act as catalysts for long-term climate adaptation. Future studies could build on these findings by incorporating qualitative case studies or cross-sectoral analysis to better understand the pathways through which institutional quality shapes business behavior.