The Role of Economic and Public Finance Tools in Achieving Energy Transition in Europe

Abstract

Europe’s decarbonization calls for an increase in the resources used to ensure a fairer transition. The objective of this study is to evaluate the role of public finance in the decarbonization process, considering the context of various uncertainties. Data from 1995 to 2023 for selected European countries were analyzed in this sense. We used the cross-sectional dependence–consistent Driscoll–Kraay estimator as the main econometric approach and Feasible Generalized Least Squares (FGLS) as a robustness test. The results revealed a positive impact of public debt, world uncertainty, and gross domestic product on renewable energy usage in European countries. Additionally, general fiscal pressure is shown to have a negative impact on the renewable energy used during the analyzed period. The results showcase the importance of public finance tools adjustments in supporting the race to zero breakthroughs and dawdling climate change. Several policy recommendations were made in this regard.

1. Introduction

While decarbonizing Europe is a top-priority target of the decision makers, the sustainability of public finance is also a primary focus objective at the European level. Short- and long-term fiscal risks are driven by the transition, and decision makers must consider these risks, evaluate their impact, and direct actions on a sustainable path. Under these circumstances, sustainable finance is a critical topic addressed by a significant number of scholars (Bala et al., 2025).

At the European level, several mechanisms and strategies were developed to help European Union (EU) countries tap their renewable energy potential. In this sense, the EU renewable energy financing mechanism, the European Green Deal, the EU Emissions Trading System, the Carbon Border Adjustment Mechanism, and the REPowerEU plan. Moreover, the transition should be just and fair (European Council, 2024). If we add uncertainty to the equation, the outcomes could reshape the original strategic agenda.

These uncertainties had a blended impact on renewable energy generation and consumption. If one considers the COVID-19 pandemic, one should also observe the mixed impact: at first, due to lockdown measures, a period of stalling and slowdowns in both renewable energy generation and the consumption process was registered, after which a recovery period was installed. If one refers to the Russian invasion of Ukraine, and its impact on renewable energy, one should also note the mixed impact interpreted as a collapse followed by an enhancement of this specific element and the proliferation of a new energy paradigm, based on the decreasing importance of fossil fuels in the energy mix. In this sense, the renewable energy transition was significantly pushed by the search for an autonomous energy source at the European Union level, enhancing resilience and aligning short-term objectives with long-term goals in a sustainable approach. Rapid expansion of renewable energy capacity in 2024 (especially from solar, by 21% in 2024) is a relevant proof of the EU undertaking to clean energy (ACER, 2025). As a counterpart, coal power plants are being expected to offset the developments by decreasing their importance.

This process was and still is not an easy one to acquire. It involves shifting resource flows, structural changes, increasing direct and indirect costs, and additional transformations, sometimes unforeseen and unknown ones. At the European Union level, there is a need for an additional EUR 584 billion in energy infrastructure by 2030 (European Commission, 2024) while in 2025, investments in clean energy are expected to reach USD 390 billion. However, the need for a more integrated energy system and investments in storage and grid infrastructure is key for a just transition. Additionally, annual investments during 2025–2050 are expected to surpass EUR 900 billion, according to (IRENA, 2025).

These efforts drove improved outcomes in the European energy mix, with renewable energy generating 50% of electricity according to (IEA, 2025b) while fossil fuels accounted for around 25%.

At the European level, public funding is crucial for supporting renewable energy development and the energy efficiency objective, materializing the 2021–2027 framework (EC, 2025) with 184 billion EUR from the Recovery and Resilience Facility, 373 billion EUR from cohesion policy funds, and another 14 billion EUR from the Modernization Fund. However, private-sector investments must become the key to financing the green transition, given public finance constraints. In this sense, public policies can help direct these structural dynamics by easing private capital flows to foster the green transition in a context of fragmented markets and the complexity of the decision-making process (Cao et al., 2024; Hua & Tong, 2026).

Regarding the total public energy RD&D budgets per the analyzed countries, according to the International Energy Agency (IEA, 2025a), the top investors, including fossil and renewable energy sources, are France, Spain, and Belgium, with 3071.5 million EUR in 2023, 1992.05 million EUR, and 487.9 million EUR, respectively. By contrast, Czechia spent only 90.7 million EUR in 2023. Private sector investments in renewable energy are estimated to account for more than 60% in emerging markets and developing economies to accelerate their energy transition, according to the IEA, and Europe has committed to attracting and mobilizing investments in clean energy projects to support the process. Additionally, according to the Corporate Finance Institute (CFI), global private equity and venture capital investments in renewable energy expanded significantly, driven by their positive characteristics, such as stable returns and long-term growth potential.

Thus, increasing renewable energy consumption in light of the energy transition requires additional funds, both public and private, given fiscal constraints and the goal of maintaining fiscal sustainability. While the impact of debt and other fiscal and budgetary instruments has been studied in the literature in relation to the decarbonization process (proxied by carbon emissions as a percentage) and environmental quality, the influence of public budgetary tools on renewable energy has received less attention. Therefore, considering this research gap, this study sheds light on the mechanisms affecting renewable energy in Europe from a public finance perspective. Additionally, choosing European countries for this study is relevant given their public finance stance and efforts to accelerate the share of renewable energy.

The study’s structure continues with a literature review, followed by the methodology, results, and discussion sections. Finally, the conclusions present relevant elements and the study’s limitations.

2. Literature Review

The clean energy transition, as one of the primary goals of nations, is often based on a variety of instruments, some public, some private, and most of the time mixed. Different theoretical and empirical approaches have highlighted the efficiency of these tools, or the lack thereof. Nevertheless, maximizing the positive effect on environmental stability should be balanced with a country’s economic growth. Several authors (Golosov et al., 2014; Sinclair, 1994; Vardar, 2024) have evaluated the optimal taxation in correlation with the growth rate and renewable or non-renewable resources through different theoretical approaches such as general equilibrium, Ramsey growth model with households, final-good producing firms, and firms that provide energy resources, concluding on the optimality of reducing non-renewable energy resources.

As a response to the climate change stringency, more green fiscal instruments were developed over time to embed sustainability in public finance-related decisions. Their effectiveness varies across countries and socio-economic contexts (Alshaib et al., 2023). Nevertheless, they remain a significant policy option in mitigating climate change effects or pushing the transition towards an environmentally neutral economy.

For instance, Weng et al. (2025) insist that green fiscal instruments significantly improved renewable energy consumption in China between 2005 and 2021, suggesting that coordinated policies increase the effectiveness of fiscal instruments in expanding renewable energy. The coordination in setting adequate fiscal policies is highly significant, taking into account that regions are at different stages of economic development. Furthermore, fiscal decentralization tends to impede renewable energy expansion, as demonstrated by (Wang & Ma, 2024). Based on development asymmetries, national or regional governments may use fiscal instruments to encourage economic activities and lower environmental standards in the process. However, previous research documented that environmental taxation may promote green production, hence mitigating carbon emissions (Sun et al., 2025). At the same time, other studies showcased contradictory findings, indicating positive effects of the environmental taxes on renewable energy consumption for some countries, while for others, inhibiting effects (Degirmenci & Yavuz, 2024). Moreover, Soufiene et al. (2025) considered that environmental taxes are a relevant instrument in mitigating environmental externalities without affecting the nation’s economic development opportunities.

While environmental taxation, which aims to internalize environmental negative externalities using taxes as a tool, has a direct connection with environmental goals, including renewable energy generation or consumption, general taxation or fiscal pressure, which permits the state to accumulate public revenues by taxing different kinds of incomes or activities, has the potential of impeding both investments and consumption, including the ones related to the energy transition and renewable energy (Tao et al., 2025), especially when the tax rate becomes a burden and affects economic decision-making.

Further,

Table 1. Summary of the literature on the impact of fiscal instruments on the energy transition and decarbonization.

Literature	Variables	Econometric Approach	Country/Region and Period	Findings
(Weng et al., 2025)	renewable energy consumption, green fiscal policy, human capital, foreign investment, economic development	multi-period difference-in-differences (DiD)	284 Chinese cities, from 2005 to 2021	green fiscal policy positively influences renewable energy consumption
(Samour et al., 2022)	economic growth, taxation, banking development, renewable energy	Autoregressive Distributed Lag (ARDL)	UAE, from 1988 to 2018	an indirect relationship between taxation and renewable energy consumption on long and short-term
(Van Der Ploeg, 2023)	carbon pricing, fiscal cost, green spending	Dynamic General Equilibrium macroeconomic model	global	recycling carbon tax revenue benefits from considering the income on the whole distribution of households
(Gajdzik et al., 2025)	investment expenditure, deployed renewable capacity, innovation expenditure, renewable electricity production	longitudinal regression analysis and cluster-based segmentation	Poland, from 2010 to 2023	innovation expenditure has a large marginal effect on renewable energy output
(Vardar, 2024)	non-renewable and renewable energy resources, pollution externalities, taxation	modified version of the Ramsey growth model	theoretical approach	different channels influence the path of optimal taxation, depending on the cost of renewable energy and the degree of substitution between renewable and non-renewable resources
(Soufiene et al., 2025)	environmental taxes, renewable energy, economic growth, green innovation and financial development, environmental sustainability	Method of Moments Quantile Regression (MMQR)	G-20 countries from 1990 to 2022	a negative relationship between environmental taxes and sustainability
(F. M. Nuta, 2025)	greenhouse gas, climate actions and policies, environmental protection spending, public debt, environmental tax, gross domestic product	fully modified and dynamic Ordinary Least Squares OLS (FMOLS and DOLS)	selected OECD countries, from 1995 to 2023	environmental taxation improves environmental performance
(Ebaidalla, 2024)	investment in renewable energy, tax revenues, trade, GDP per capita	cross-section ARDL(CS-ARDL) and pooled mean group ARDL (PMG-ARDL)	37 renewable energy-producing countries, from 1996 to 2021	taxation has a negative influence on renewable energy investment; GDP has a positive impact

highlights the results of the previous literature examining the role of fiscal tools in supporting decarbonization.

According to previous findings, specific green fiscal policies positively influence environmental-related actions, even though these studies are not always linked to renewable energy consumption. On the other hand, general fiscal pressure affects investment and consumption decisions, potentially creating trade-offs and generating heterogeneous effects depending on the overall economic state.

Considering the above findings, this study will test the following hypothesis:

H1. 

Fiscal pressure negatively affects the energy transition process.

Furthermore, in turbulent times when public debt and economic struggles hamper climate actions, environmental taxation is a critical instrument meant to penalize emitters and curb environmental degradation (F. M. Nuta, 2025). These results are also confirmed for developing countries, where at first, public debt can compensate the lack of resources and have beneficial effects for the economic growth and energy diversification, claiming an increased fiscal discipline and maximization of the initial benefits of the public debt for ensuring energy transition and environmental regeneration (Hashemizadeh et al., 2021; Kushawaha & Jain, 2025). At the same time, other scholars recognize the role of public debt in reducing energy poverty, but argue that certain contexts, such as institutional prowess and reduced income inequality, enhance these benefits (Benayed et al., 2025). In this regard, the literature review is summarized in

Table 2. Summary of the literature on debt impact in decarbonization.

Literature	Variables	Econometric Approach	Country/Region and Period	Findings
(Kushawaha & Jain, 2024)	debt financing on renewable energy, financial market development, trade openness, GDP per capita, population size, political stability	Driscoll–Kraay approach	12 developing countries, from 2000 to 2020	a U-shaped relationship between debt financing and renewable energy
(Kushawaha, 2025)	public debt, GDP per capita, population, renewable energy consumption, financial development, World Governance Indicators	fixed effects and dynamic system GMM methods	34 countries, from 2000 to 2020	higher public debt reduces donor support for renewable energy
(Getachew et al., 2024)	renewable energy consumption, GDP, financial assistance for renewable energy investment	Autoregressive distributed lag (ARDL) model	Ethiopia, from 2000 to 2022	the use of renewable energy increase based on sustainable finance
(Liu & Shi, 2025)	environmental regulations, debt-to-asset ratios, GDP, inflation, loan interest rate, carbon price, firm debt	dynamic stochastic general equilibrium (EE-DSGE) model	China, from 2008 to 2017	climate policies raise asset values of renewable energy firms
(Onuoha et al., 2023)	public debt, renewable energy consumption, financial development, Gross Domestic Product Per Capita, urbanization, Institutional quality	Feasible Generalized Least Squares (FGLS)	Sub-Saharan Africa, from 1996 to 2020	public debt positively impacts renewable energy consumption
(Biswal et al., 2025)	environmental debt, public debt, GDP per capita, renewable energy, environmental tax	ARDL model	Top ten highly indebted countries, from 1996 to 2022	the initial level of public debt negatively impacts the environmental debt
(Benayed et al., 2025)	energy poverty, public debt, income inequality, economic development, institutional quality	dynamic panel threshold model	27 Sub-Saharan African countries, from 2010 to 2021	public debt can help reduce energy poverty, but only after a certain level of economic development
(F. M. Nuta, 2025)	greenhouse gas, climate actions and policies, environmental protection spending, public debt, environmental tax, GDP	fully modified and dynamic OLS models	selected OECD countries from 1995 to 2023	public debt has environmentally harmful effects
(Auteri et al., 2024)	renewable energy consumption, GDP, general government debt, unemployment rate, trade openness, urban population	FMOLS, DOLS and Quantile Regressions (QR)	G7 countries, from 1990 to 2021	bidirectional causality between government debt and renewable energy consumption
(Kushawaha & Jain, 2025)	public debt, renewable energy, population growth, financial market index	Driscoll–Kraay standard errors, IV-GMM, and Quantile Regression	71 developing countries, from 2000 to 2020	inverse U-shaped relationship between public debt and public investment in renewable energy
(Hashemizadeh et al., 2021)	renewable energy consumption, public debt, GDP, urbanization	Regression with Driscoll–Kraay standard errors	20 emerging countries, from 1990 to 2016	public debt decreases the renewable energy consumption

.

The literature on the direct effects of public debt on renewable energy remains inconclusive. According to the findings highlighted in the table above, even if public debt can negatively affect economic growth when public debt-to-GDP ratios are dramatically increasing, some other studies (Ciaffi et al., 2024) suggest that public investments work as a stimulus for short-term output, private investments, as, for example, the Horizon Europe strategic plan. In this sense, a positive relationship between public debt and renewable energy is expected.

Considering the above results, this study will verify the following hypothesis:

H2. 

Public debt has a positive impact on renewable energy use.

Regarding the effect of uncertainty on renewable energy, the literature is quite diverse (Z. Z. Li et al., 2023), and the results are inconclusive (positive or negative sign), as shown in

Table 3. Summary of the literature on the impact of uncertainty on renewable energy.

Literature	Variables	Econometric Approach	Country/Region and Period	Findings
(Fu et al., 2024)	natural gas price, geothermal energy and biofuels consumption, climate policy uncertainty, consumer confidence index	non-linear autoregressive distributed lag (NARDL)	global, from January 2000 to December 2021	an asymmetric link between variables
(Borozan, 2022)	renewable energy consumption, real GDP per capita, world uncertainty index, economic freedom index, renewable energy, public RD&D budget	non-linear autoregressive distributed lag model (NARDL)	G7 countries, from 1997 to 2019.	a shock in lagged uncertainty reduce renewable energy consumption
(Boulanouar et al., 2025)	energy prices, economic growth, renewable energy consumption,	panel smooth transition regression (PSTR) model	17 MENA countries, from 1995 to 2016	energy prices fluctuations influence renewable energy development
(Petrović and Ostojić, 2025)	world uncertainty index, geopolitical risk index, renewable energy production, GDP, urbanization, renewable energy consumption, FDI, crude oil price, financial development index, total GHGs emissions, gross fixed capital formation	Common Correlated effects Mean Group Generalized Method of Moments (CCEMG-GMM)	42 countries, from 1990 to 2020	policy induced uncertainties do not have any long-term impact on renewable energy
(Xi et al., 2023)	climate policy uncertainty, consumption of five renewable energy sources and total	VAR model	global, January 2000 to November 2021	climate policy uncertainty affects energy consumption on average

. While Bettarelli et al. (2024) concluded that economic and political uncertainty decreases green innovation, measured by green energy patents, due to high financial stress during the recession period, Feng and Zheng (2022) found an increase in renewable energy innovation under the impact of economic policy uncertainty. These contradictory results prompt further investigation into the nexus between uncertainty and renewable energy. Additionally, whilst (Bettarelli et al., 2024) used a panel of 81 advanced and emerging market economies during the period 1976–2020, (Feng & Zheng, 2022) research was based on a panel of 22 countries during the period 1985–2019, both of them are not considering the Russian invasion on Ukraine, and the significant impact this event had on the energy transition and energy independence at the European level, as highlighted by the REPowerEU Plan, forcing the energy diversification and the advancement of energy transition. Thus, our research includes a broader range of uncertainty, expanding the results and highlighting the potential implications of such events.

According to the above findings, the study will evaluate the following hypothesis:

H3. 

Uncertainty effect on renewable energy is ambiguous (positive or negative sign).

As a control variable, we have used economic growth, which is one of the most relevant factors when evaluating the role of economic development and economic status on decarbonization. Moreover, it is well known that when growth is based on industrialization, the increased demand for energy may not be directed toward renewable energy but toward fossil fuels (Assi et al., 2021). Additionally, distinctions between developed and developing nations in supporting and accelerating the energy transition must be considered, in light of a country’s capacity and capability to efficiently direct funds to clean energy, given its economic power, infrastructure, technological, and institutional capabilities (Pereira et al., 2025). Both theoretical and empirical approaches consider economic growth as a pivotal element in supporting or inhibiting decarbonization (as seen in

Table 4. Summary of the economic development on environmentally friendly development.

Literature	Variables	Econometric Approach	Country/Region and Period	Findings
(Çınaroğlu et al., 2026)	innovation, GDP, renewable energy consumption	Panel ARDL/PMG and Panel Granger Causality (VECM)	G20 countries, from 2001 to 2019	a negative relationship between GDP and renewable energy consumption
(R. Li & Lee, 2022)	GDP, renewable energy capacity	PMG	OECD countries in Europe, from 1993 to 2018	a positive relationship between GDP and renewable energy capacity
(García-Riazuelo et al., 2025)	wind energy, photovoltaic energy, GDP per capita, population density	SAR, SAR dynamic and SEM models	European Union, from 2000 to 2018	socio-economic factors are key for renewable energy
(Haar, 2020)	renewable energy, electricity pricing, household income	Qualitative approach	European Union countries from 2007 to 2017	the pricing structure of retail electricity is regressive and correlated to reliance upon renewable energy
(Boulanouar et al., 2025)	energy prices, economic growth, renewable energy consumption	panel smooth transition regression (PSTR) model	17 MENA countries, from 1995 to 2016	energy prices fluctuations influence renewable energy
(A. C. Nuta, 2024)	renewable energy consumption, urbanization, economic growth economic complexity index	cointegration regression (CCR), fully modified OLS, and dynamic OLS (FMOLS–DOLS) approaches	emerging European countries, from 1995 to 2021	economic growth has a positive effect on renewable energy consumption
(Rajkumar & Nagarajan, 2025)	economic growth CO2 emissions, solar, wind, and hydro energy, green technological innovation, foreign direct investment	Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Quantile Regression	10 leading renewable energy-producing countries, from 2007 to 2020	green technological innovation, in conjunction with renewable energy, stimulates economic growth
(Gava et al., 2025)	energy efficiency, energy consumption, and economic growth, non-renewable energy consumption, renewable energy consumption, and energy security	VAR model	South Africa, from 1985 to 2021	a long-run relationship between economic growth, energy efficiency, renewable energy consumption
(Vardar, 2024)	non-renewable and renewable energy resources, pollution externalities, taxation	a modified version of the Ramsey growth model	theoretical approach	different channels influence the path of optimal taxation, depending of the cost of renewable energy and the degree of substitution between renewable and non-renewable resources

). In this sense, using FMOLD and DOLS techniques, Sadorsky (2009) found a positive long-term relationship between economic growth and renewable energy consumption in emerging countries, controlling for per capita values, highlighting the growth–energy nexus. The same direct relationship has been observed in Brazil’s case by (Pao & Fu, 2013) and in ASEAN countries by (Assi et al., 2021). Contrariwise, (Cadoret & Padovano, 2016) found a negative link between GDP growth and renewable energy consumption in European countries, such that, in the short-term, the greater energy demand driven by economic growth is met by fossil fuel sources. Distinguishing between wind and photovoltaic energy (García-Riazuelo et al., 2025) found a positive relationship between GDP per capita, as a measure of regional wealth, and these two types of renewable energy, in the presence of specific spillovers.

As can be observed, the divergences generated by the above studies require additional analysis and interpretation. Beyond the methodological approaches used, relying mainly on ARDL models, other instruments and perspectives are missing.

3. Methodology

3.1. Data

The dataset used in this study to analyze the impact of the independent variables (public debt, fiscal pressure, world uncertainty) and the control variable (economic growth) on the dependent variable (renewable energy consumption) covers several European countries and considers the period from 1995 to 2023 (

Table 5. Variables’ presentation.

Variables	Abbrs.	Def.	Sources
Renewable energy	REN	Renewable energy consumption (% of total final energy consumption)	Our World in Data, Energy Institute and Statistical Review of World Energy (2024)
Public debt	DEBT	Government debt (consolidated) (as % of GDP)	European Central Bank, 2025
Economic growth	GDP	GDP per capita (constant 2015 US$)	Eurostat, 2025
Tax burden	TAX	Tax revenue (% of GDP)	Eurostat, 2025
World Uncertainty Index	WUI	Annual uncertainty index	NBER (Ahir et al., 2022)

).

The proxy used for highlighting the level of decarbonization is the percent of renewable energy consumption in the total final energy consumption. This study reckons this variable as relevant due to a permanent appreciation of renewable energy as a primary factor of the transition to a cleaner economy. The data were collected from Our World in Data and the Energy Institute, in collaboration with the Statistical Review of World Energy.

This study considered public debt and fiscal pressure, measured as a percentage of gross domestic product, as primary instruments of public finance. In this sense, the model can evaluate and demonstrate their role in influencing renewable energy usage. Public debt could represent a source of financing for decarbonization in European countries. All the increased investments necessary to enlarge the potential of producing green energy and expanding energy storage solutions to address spikes and manage waste are being supported by government interventions at national and local levels, beyond the contribution of private or international investments. Instead of using environmental taxation, which is directly linked with environmental objectives, such as reducing carbon emissions, this study uses general taxation or general fiscal burden, which is more likely to influence the decision-making process of households and firms in using different sources of renewable energy, by directly affecting their disposable income, knowing that renewable energy is still based on expensive technologies.

Furthermore, uncertainties must also be rated as essential, keeping in view that uncertain events are influencing regular economic conditions, creating volatility, and shifting the decision-making process. The world uncertainty index considers not only the economic uncertainty shocks like US recession, financial credit crunch, sovereign debt crisis, but also the occurrence of the Coronavirus, war in Ukraine, Brexit, etc., quantifying the overall sentiment. The index has been calculated for every country based on the frequency of the world’s uncertainty in countries’ reports and normalized.

As a control variable, we considered economic growth as having the potential to expand the renewable energy consumption in the analyzed countries.

Figure 1 presents the evolution of the variables considered in the model.

Figure 2, Figure 3, Figure 4 and Figure 5 present all the hexagon plots, highlighting the variables’ interaction.

3.2. Econometric Estimation Techniques

This study relies on a nonparametric covariance matrix estimator, which will generate heteroskedasticity- and autocorrelation-consistent standard errors that are robust, working for both balanced and unbalanced panels, and, considering its small-sample properties, it is a viable option for our case, consisting of small cross-sections and a larger time (Driscoll & Kraay, 1998; Hoechle, 2007). To test the hypothesis of this study, we considered the form of a linear regression model (Equations (1)–(6)) (Hoechle, 2007),

$$y_{it}=x_{it}^{\mathrm{\prime }}\theta +{\epsilon }_{it}$$

(1)

where i = 1, …, N and t = 1, …, T, x_it = a (K + 1) × 1 vector of independent variables, and θ is a (K + 1) × 1 vector of unknown coefficients.

$$\widehat{\theta }={{(X}^{\mathrm{\prime }}X)}^{-1}{X}^{\mathrm{\prime }}y$$

(2)

Then, Driscoll and Kraay’s standard errors will take the following form:

$$V\left(\widehat{\theta }\right)={\left(X^{\mathrm{\prime }}X\right)}^{-1}{\widehat{S}}_T{\left(X^{\mathrm{\prime }}X\right)}^{-1}$$

(3)

where

$${\widehat{S}}_T={\widehat{\mathsf{\Omega }}}_0+{\sum }_{j=1}^{m\left(T\right)}w\left(j,m\right)[{\widehat{\mathsf{\Omega }}}_j+{\widehat{\mathsf{\Omega }}}_j^{\mathrm{\prime }}]$$

(4)

with m(T) being the lag length up to which the residuals may be autocorrelated and

$${\widehat{\Omega }}_j={\sum }_{t=j+1}^T{h}_t\left(\widehat{\theta }\right)h_{t-j}{\left(\widehat{\theta }\right)}^{\mathrm{\prime }}$$

(5)

with

$$h_t\left(\widehat{\theta }\right)={\sum }_{i=1}^{N\left(t\right)}{h}_{it}\left(\widehat{\theta }\right)$$

(6)

The general model applied to our study will take the form from Equation (7), to identify the impact of public debt, fiscal pressure, world uncertainty, and economic growth on renewable energy usage:

$${\mathrm{R}\mathrm{E}\mathrm{N}}_{\mathrm{i}\mathrm{t}}={\mathsf{\beta }}_0+{\mathsf{\beta }}_1{\mathrm{D}\mathrm{E}\mathrm{B}\mathrm{T}}_{\mathrm{i}\mathrm{t}}+{\mathsf{\beta }}_2{\mathrm{G}\mathrm{D}\mathrm{P}}_{\mathrm{i}\mathrm{t}}+{{\mathsf{\beta }}_3{\mathrm{T}\mathrm{A}\mathrm{X}}_{\mathrm{i}\mathrm{t}}+\mathsf{\beta }}_4{\mathrm{W}\mathrm{U}\mathrm{I}}_{\mathrm{i}\mathrm{t}}+{\mathsf{\epsilon }}_{\mathrm{i}\mathrm{t}}$$

(7)

where i = 1, …, N represents the cross-sections and t = 1, …, T are the years included in the analysis.

Furthermore, cross-sectional time-series FGLS regression, with heteroskedastic and cross-sectional correlation, was employed as a robustness test.

Considering the literature findings and the hypothesis set by this study, the expected signs of Equation (7) will be the following:

-

a positive sign for public debt, corresponding to the beneficial influence of public spending, especially for investments in renewable energy development and consumption;

-

a negative expected sign for fiscal pressure, indicating the general effect of a heavy tax system on economic decisions; and

-

a positive or a negative sign of the uncertainty on renewable energy consumption.

4. Results and Discussion

4.1. Initial Tests

Descriptive statistics are presented in

Table 6. Descriptive statistics.

	REN	DEBT	GDP	TAX	WUI
Mean	7.936	71.509	19,711.610	36.419	0.182
Maximum	24.918	244.502	44,731.040	48.500	0.619
Minimum	0.224	6.600	3540.556	20.300	0.001
Std. Dev.	5.546	42.511	11,293.050	6.177	0.116
Observations	319	319	319	319	319

Note: REN = Renewable energy use; DEBT = Public debt; GDP = Gross domestic product; TAX = Fiscal pressure; and WUI = World uncertainty.

. We can observe important variations between the analyzed variables in their minimum and maximum values. Descriptive statistics refers to non-logarithmic values of dependent and independent variables. Standard deviations are smaller than the mean, meaning that the mean of the data reflects the actual dataset characteristics.

The correlation between variables is shown in Figure 6. Generally, there is an average correlation between economic growth and fiscal variables, besides a modest correlation for the other variables. Additionally, apart from fiscal pressure (indirectly associated with the economic growth), all the variables present a direct association.

Because the presence of multicollinearity could distort the significance of the estimations and the levels of standard errors, we checked the multicollinearity concern, and

Table 7. Variance Inflation Factors (VIFs).

	VIF	1/VIF
DEBT	1.90	0.525642
GDP	2.60	0.384597
TAX	2.63	0.379996
WUI	1.01	0.987272
Mean VFI	2.04	-

confirms the absence of this issue for the independent variables included in the model. Thus, all values are below the standard level (Hair et al., 2014), indicating the absence of multicollinearity.

The results of the stationarity test are pointed out in

Table 8. Panel Unit Root using Levin, Lin and Chu test.

	At Level		At First-Difference
	Statistic	Prob.	Statistic	Prob.
REN	−0.177	0.429	−8.495 ***	0.000
DEBT	−2.995 ***	0.001	−4.058 ***	0.000
GDP	−1.792 **	0.036	−6.652 ***	0.000
TAX	−2.495 ***	0.006	−6.982 ***	0.000
WUI	−2.513	0.006	−6.090 ***	0.000

Note: REN = Renewable energy use; DEBT = Public debt; GDP = Gross domestic product; TAX = Fiscal pressure; and WUI = World uncertainty, *** p < 0.01, ** p < 0.05.

. After employing the Levin, Lin and Chu test, we noticed that some of the variables were not stationary at the level. Nevertheless, they become stationary at the first difference.

Table 9. Cross-sectional dependency.

Test Type	Value	Prob.
Friedman	7.628	0.000
Pesaran	76.918	0.000

highlights the cross-section dependence test results, revealing the presence of cross-sectional dependency in the panel.

4.2. Regression Results and Robustness

Regression with Driscoll–Kraay standard errors output is presented in

Table 10. Estimations results.

Variable	Driscoll–Kraay
DEBT	0.195 (0.208)
GDP	1.013 *** (0.086)
TAX	−4.405 *** (0.468)
WUI	0.321 *** (0.068)
Constant	7.746 *** (1.548)
R2	0.306

Note: DEBT = Public debt; GDP = Gross domestic product; TAX = Fiscal pressure; WUI = World uncertainty. Standard errors in parentheses *** p < 0.01.

. The main result is that for selected European countries, public debt enhanced the renewable energy consumption. The coefficient is positive; however, it is not statistically significant. This could be explained by the presence of high levels of public debt, which are being controlled and coordinated by each member state’s medium-term fiscal-structural plans framework. Thus, while financing the transition with public funds would bring a positive impact, the sensitive threshold of public debt levels could not fully realize the potential of these newfound resources, as they create distortions and destabilize the public finance stance. In this sense, to strengthen fiscal sustainability and ensure economic growth, as well as implement all necessary structural reforms in the medium term, public debt should follow a downward trend. Meanwhile, investments should not be neglected to ensure the common priorities of the European Union. The finding is different from (Kushawaha and Jain, 2024), who reported a U-shaped interconnection between debt and renewable energy, (Biswal et al., 2025) and (F. M. Nuta, 2025), referring to the negative effect of public debt on the environment and also findings from (Hashemizadeh et al., 2021), which reported that public debt decreased renewable energy consumption, nevertheless is in line with findings from (Onuoha et al., 2023), which highlighted a positive impact of public debt on renewable energy.

A second important result of the estimations is the impact of the tax burden on the energy transition. In this case, the sign is negative and statistically significant, indicating the detrimental effect of fiscal pressure on renewable energy. As fiscal pressure increases and reduces disposable income, both for investors and consumers, the capacity to implement such renewable-energy-generation and self-consumption projects decreases. The findings are in line with those of (Ebaidalla, 2024) in a study regarding 37 renewable energy-producing countries and those of (Soufiene et al., 2025) in an analysis on G-20 countries during the 1990–2022 period. Therefore, even if such investments are recovered in the short-term, fiscal pressure discourages these initiatives, and this aspect should be taken into account by policymakers when configuring strategies for achieving the green transition. Our approach accounted for the general fiscal pressure and the well-known fact that some fiscal measures affect prices, and, continuing, the level of renewable energy consumed by households and firms, in the light of investment disincentives (https://doi.org/10.1007/s12053-024-10275-0; accessed on 15 October 2025). However, when the model includes only environmental taxation, the effect is completely different, with green fiscal policy increasing renewable energy consumption, as reported by (Weng et al., 2025). Thus, when taxation targets only fossil fuel-based sources, the rollout of renewable energy will be stimulated. In this sense, greener fiscal policies will safeguard the energy transition and ensure the achievement of sustainability goals, aligning decarbonization with fiscal sustainability.

World uncertainty looks like it has a reduced, positive, and statistically significant impact on renewable energy. While uncertainties are increasing the pressure on both private and public budgets and negatively affecting them, the latest important uncertain events that have happened (the COVID-19 pandemic and the war in Ukraine) have increased the effort of European nations to switch from fossil fuels to renewable energy sources, ensuring the sustainability of the energy system. In this sense, COVID-19 reduced energy use for a while. Additionally, the war in Ukraine sped up the pace of the clean energy transition in the European Union, with an increase in renewable energy (mainly based on solar and wind) from 34% in 2019 to 47% in 2024 and a decrease in fossil share form 39% to 29% in the same period (Rosslowe & Petrovich, 2025), reducing its reliance on imported dirty sources. However, periods of high inflation could also temper the pace and alter the gains in this process, and mixed results could also be mentioned. In this respect, the study results are different from (Borozan, 2022), who detected an indirect connection between uncertainty and renewable energy consumption in G7 countries during 1997–2019 period or (Petrović and Ostojić, 2025), who stated that there is no long-term impact of uncertainties on renewable energy, but confirm the results of (Xi et al., 2023). This unexpected event, referring to the Russian invasion in Ukraine, while negatively affecting energy prices, inflation, and economic growth not only in Ukraine, but also in Europe, accelerated the phase-down of fossil fuels in Europe and intensified the usage of renewable energy, ensuring also the efforts for energy security and autonomy in Europe.

The model included economic growth as a control variable. One should observe the positive effect of the level of development of a country on its renewable energy potential. These results are in line with A. C. Nuta’s (2024) findings, which highlight a positive effect of economic growth in emerging European countries during the 1995–2021 period, and with (Gava et al., 2025).

To increase the relevance of our results, we used cross-sectional time-series FGLS regression, with heteroskedastic and cross-sectional correlation functionalities (

Table 11. Robustness test.

Variable	FGLS
DEBT	0.149 *** (0.034)
GDP	1.006 *** (0.003)
TAX	−4.087 *** (0.132)
WUI	0.203 *** (0.018)
Constant	6.407 *** (0.279)

Note: DEBT = Public debt; GDP = Gross domestic product; TAX = Fiscal pressure; WUI = World uncertainty. Standard errors in parentheses *** p < 0.01.

). In this sense, the estimations of the FGLS model confirm the sign and significance of the main model results. Only fiscal pressure negatively influenced renewable energy consumption, while a positive effect of public debt, economic growth, and world uncertainty on renewable energy consumption was highlighted. These findings are increasing the reliability of the Driscoll–Kraay standard errors model.

Additionally, Figure 7 plots the study’s results, emphasizing the role of public finance tools and economic variables in renewable energy consumption.

5. Conclusions

Decarbonization is a vital challenge in mitigating climate change. Decision makers worldwide design various policy instruments and adapt economic and social systems to the struggle of achieving carbon neutrality. European countries are a sustainability spearhead, engaging in ambitious climate actions and initiatives. However, the transition supposes significant efforts and certain social categories, even entire regions, are more susceptible to suffering the costs. That is the reason for ensuring a fair and just transition. Under these circumstances, a rigorous allocation of financial resources is much needed. In this context, this research aims to explore the role of public finance in the process of decoupling economic and social life from carbon, taking into account the uncertain events that can occur in the meantime and hinder these efforts. Data from a selection of European countries between 1995 and 2023 were used for the empirical analysis. The methodological apparatus consisted of the Driscoll–Kraay estimator as the main instrument. Furthermore, the FGLS was used to test the results’ robustness.

The main findings showcase the importance of public finance tools in supporting the zero-carbon targets in Europe and dawdling climate change. The results contribute to a better understanding of several key public finance features, such as public debt and fiscal measures. For instance, it is revealed that public debt has a positive impact on renewable energy usage. The meaning of this can be related to the fact that a significant part of the financial resources that add to the public debt are directed towards investments for expanding renewable energy production capacities and other environmental regeneration initiatives. In this sense, decision makers should consider the approach and support public investments in renewable energy and transition energy consumption from fossil fuel sources to cleaner ones. Additionally, the results posit that world uncertainty and gross domestic product also positively impact renewable energy usage in Europe. Thus, expanding economic growth in European countries will help steer capital flows toward the energy transition, improving energy efficiency, expanding renewable energy generation and grid infrastructure, and advancing energy technologies and distribution networks. Moreover, supporting households’ adoption of renewable energy and their transition to clean energy fuels is a key element of the transition, in line with sustainable development goals such as affordable and clean energy and decent work and economic growth.

In addition, our robust results show a negative effect of the general fiscal pressure on renewable energy use. On the one hand, the reason can be that there is still a growth potential for renewable energy, provided that companies are allowed to invest more in such objectives from a fiscal perspective. On the other hand, this proves that fiscal measures are reliable instruments that can moderate and incentivize the willingness to adopt an increased share of renewable energy.

Based on these findings, several policy recommendations can be substantiated. First, it is critical that an eventual public debt expansion be used for environmentally friendly purposes and energy capacities that ensure the further move towards carbon neutrality. Green public finance instruments play an essential role in this approach.

The study’s limitations relate to several aspects. In this sense, including in the model the institutional and technological variables, as well as the roles of private investment and research and development in renewable energy. Furthermore, applying different econometric approaches, such as dynamic panel data, will improve the results by considering several adjustment mechanisms and uncovering dynamic patterns, resulting in a more accurate representation of these relationships.