# Fiscal Rules and Environmental Spending: Navigating the Trade-off between Discipline and Green Priorities

Ablam Estel Apeti, Bao We Wal Bambe, Jean-Louis Combes, Pascale Combes Motel, Rayangnewendé Frans Sawadogo

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# Fiscal Rules and Environmental Spending: Navigating the Trade-off between Discipline and Green Priorities

Ablam Estel Apeti, Bao We Wal Bambe, Jean-Louis Combes, Pascale Combes Motel et Rayangnewendé Frans Sawadogo

MISE EN LIGNE / ONLINE | 11/02/2026

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# Fiscal Rules and Environmental Spending: Navigating the Trade-off between Discipline and Green Priorities*

Ablam Estel Apeti¹ • Bao We Wal Bambe²,³ • Jean-Louis Combes³ • Pascale Combes Motel³ • Rayangnewendé Frans Sawadogo³

¹ECONOMIX-CNRS, UNIVERSITY OF PARIS NANTERRE, PARIS, FRANCE

²GERMAN INSTITUTE OF DEVELOPMENT AND SUSTAINABILITY (IDOS), BONN, GERMANY

³UNIVERSITÉ CLERMONT AUVERGNE, UNIVERSITÉ D'ORLÉANS, LEO, 45067, ORLÉANS, FRANCE

## Abstract

Environmental concerns are becoming more pressing as the climate emergency intensifies, posing a major challenge for many governments: increasing green investments to promote better adaptation and resilience to climate events, while maintaining fiscal discipline. This raises the question of whether governments that operate under fiscal rules tend to safeguard environmental spending in light of the climate emergency, or whether they are more inclined to scale it back to meet their fiscal targets, given that such investments require substantial public funding. Using data covering 31 advanced economies between 1995 and 2021, we find robust evidence that the strengthening of fiscal rules significantly reduces environmental spending, in particular debt rules and expenditure rules. Moreover, the adverse impact of fiscal rules on environmental expenditures is amplified during election periods, whereas it is mitigated in the presence of sound past fiscal conditions, the Kyoto Protocol, and stringent environmental policies. Further analysis reveals that although fiscal rules tend to reduce environmental spending, they are associated with greater efficiency in such spending.

**Keywords:** Fiscal Rules • Environmental Spending • Fiscal Sustainability

**JEL Codes:** E6 • Q58 • E62 • H6

<footnote>*Corresponding author: Ablam Estel Apeti. aapeti@parisnanterre.fr. We thank Daniel Mirza, Chahir Zaki, and Sonia Schwartz for their valuable comments and discussions. We also appreciate the insightful feedback from participants at the Laboratory of Economics of Orléans (LEO) seminar. All findings, interpretations, and conclusions expressed in this paper are our own. The usual disclaimers apply. Data Availability: Data are available upon request. The authors declare no conflict of interest.</footnote>
> "Governments in advanced economies face two major challenges. The first is the need to fight global warming. The second is to keep public debt under control. The tension between the two is obvious and, indeed, at the center of disagreements about new EU fiscal rules being discussed in Brussels right now. How to best reconcile the two?" — Olivier Blanchard, Peterson Institute For International Economics, December 19, 2023.

# 1 Introduction

The urgency of climate action has never been more apparent, and combating climate change requires substantial environmental investments to accelerate the ecological transition and foster a sustainable, low-carbon future. Yet, the fiscal space to finance it has never been more constrained. Advanced economies, already burdened with historically high public debt, face a difficult trade-off: how to finance the transition to a sustainable future while ensuring fiscal discipline. This dilemma has become particularly acute following a series of global crises that have substantially widened fiscal deficits, most prominently the COVID-19 pandemic and recent geopolitical tensions, which have driven a sharp increase in military spending. These shocks have had significant repercussions for borrowing costs and have amplified uncertainty in financial markets.

In pursuing fiscal consolidation, governments may be compelled to scale back certain public investments, such as environmental spending, which often entail substantial financial commitments. This dilemma is central to current debates involving scholars and policymakers. Critics argue that higher environmental expenditure could undermine fiscal discipline by requiring additional borrowing and raising debt sustainability risks (Pekanov et al., 2020). On the other hand, given the potentially severe long-term economic costs of inaction, some advocate for a “green golden rule” exempting environmental expenditures from fiscal constraints,<fnref n="1" /> thereby allowing governments to finance green initiatives without breaching deficit or debt limits (Darvas and Wolff, 2022). The required investments are particularly substantial given the rising costs associated with climate change. For example, the Draghi report estimates that the European Union would need an additional €750–800 billion annually to restore productivity and meet its environmental objectives, including industrial decarbonization (European Commission, 2024). Similarly, the IMF notes that G20 countries will require cumulative public investments equal to 0.5–4.5 percent of GDP over the next decade, primarily targeting renewable energy, electricity

<footnote n="1">¹This could be justified, in principle, by two different arguments: (i) « that the costs associated with higher deficits and debt are less relevant when the deficits and debt arise from green spending » or (ii) « that the advantages arising from green spending are such that they justify accepting higher costs (at least in terms of risks) that may potentially arise from higher deficits and debt » (Cottarelli, 2020).</footnote>
networks, and energy efficiency (International Monetary Fund, 2021). This tension between
upholding fiscal discipline and sustaining environmental investment becomes even more pro-
nounced as the costs of climate change escalate, and is not merely theoretical: some examples
suggest that governments may hinder rather than protect environmental expenditures. For in-
stance, in early 2024, the French government announced a €10 billion cut in state spending to
meet deficit reduction targets, including more than €2 billion in ecological budget reductions.<fnref n="2" />
Similarly, in December 2023, the German government announced a €45 billion reduction by
2027 in its Climate and Transformation Fund, following a constitutional court ruling.<fnref n="3" /> Beyond
budgetary costs, a further challenge arises from public opinion: while citizens are aware of cli-
mate change, resistance to carbon pricing often limits support for climate policies (Fairbrother,
2022; Kantorowicz et al., 2024).

The trade-off between fiscal discipline and environmental expenditures may be particu-
larly challenging in countries with fiscal rules designed to restrain policymaking behaviors that
may lead to excessive deficits and ensure public finance sustainability. Governments pursuing
fiscal consolidation within rules-based fiscal frameworks may be particularly inclined to reduce
environmental expenditures for several reasons. Maintaining fiscal discipline in such frame-
works is critical, as significant deviations from the intended targets can erode policy credibility
and sharply increase borrowing costs (Kalan et al., 2018; Apeti et al., 2025). Further, such in-
vestments are sometimes perceived as less immediately profitable than other expenditures, such
as social programs or pensions. Similarly, measures to finance green expenditures can include
credit-market instruments, such as green bonds and debt-for-climate swaps (Kantorowicz et al.,
2024), as well as other financing tools, including carbon taxes or emissions trading schemes,
which may be politically and socially challenging to implement (Maestre-Andrés et al., 2019).
While this debate is both compelling and policy-relevant, whether fiscal rules impact environ-
mental spending remains largely unexplored. This paper, therefore, seeks to fill this gap. We
argue that fiscal rules may influence environmental expenditure through two channels. First, by
constraining the overall volume of public spending, fiscal rules can directly reduce resources
available for environmental policies. Second, fiscal rules may alter the composition of pub-
lic spending, with ambiguous consequences for environmental outlays. The effects may also
vary over time: in the short term, fiscal rules limit governments’ flexibility, potentially reduc-
ing funds for climate initiatives. In the long term, by lowering debt burdens and thus interest
payments, which crowd out productive spending, fiscal rules may indirectly free resources for
environmental investment (Boly et al., 2022b).

<footnote n="2">²Source: BFM Business.</footnote>

<footnote n="3">³Source: The Clean Energy Wire.</footnote>
Using data for 31 advanced countries with well-documented environmental expenditure over the 1995-2021 period, we examine whether fiscal rules tend to exert downward pressure on environmental spending.<fnref n="4" /> Our key findings show that stricter fiscal rules lead to a reduction in environmental spending, with impacts that are both statistically and economically significant. Our findings are robust to extensive checks, including additional controls, tests for sample dependence, and alternative measurement choices. Endogeneity concerns related to fiscal rules must be seriously addressed to avoid estimation biases (Heinemann et al., 2018). Hence, beyond the baseline Ordinary Least Squares (OLS) specification, we further address endogeneity concerns by implementing an instrumental variables (IV) approach that exploits regional variation in the strength of fiscal rules as an exogenous source of identification, and by estimating a dynamic specification with a system GMM estimator. We also identify several sources of heterogeneity. The decline in environmental spending induced by stronger fiscal rules is more pronounced when spending levels are moderate or high, and only expenditure rules and debt rules significantly decrease environmental spending. Moreover, factors such as elections amplify the negative effects of fiscal rules. In contrast, sound fiscal preconditions, the Kyoto Protocol, and stringent environmental policies mitigate these adverse effects. Extending the analysis, we examine whether the reduction in environmental spending is associated with a deterioration in its efficiency. Our results indicate that, although stricter fiscal rules reduce overall environmental spending, they simultaneously enhance its efficiency, suggesting a more optimal allocation of environmental resources despite the decline in their levels.

This paper contributes to the literature in (at least) two distinct ways. First, our analysis advances the ongoing debate on green fiscal rules by providing systematic evidence on the tension between fiscal policy sustainability and environmental objectives, highlighted in the recent literature (Cottarelli, 2020; Pekanov et al., 2020; Darvas and Wolff, 2022; Blanchard, 2023; Caselli et al., 2024; Medas et al., 2025). Indeed, while unlikely to persist in the long term, this trade-off is highly plausible in the short term (Boly et al., 2022b). The literature has mostly focused on the normative case for exempting green investment from fiscal constraints (the so-called “green golden rule”),<fnref n="5" /> while empirical evidence on how existing fiscal rules shape environmental goals has been missing so far. We address this gap by providing empirical evidence that fiscal rules in advanced economies can constrain environmental spending, supporting the risks anticipated in the theoretical arguments of Cottarelli (2020) and Caselli et al. (2024). At the same time, we show that fiscal rules does not necessarily lead to suboptimal use of environmental resources.

<footnote n="4">⁴Our analysis excludes developing countries due to limited environmental spending data for these nations, with most observations only beginning in 2018.</footnote>

<footnote n="5">⁵These recent works focus more on simulations, propositions, or theoretical discussions of the trade-off between fiscal discipline and the importance of environmental spending in the context of fiscal rules.</footnote>
On the contrary, it tends to enhance spending efficiency by promoting better allocation and likely reducing fiscal waste, that is, massive public expenditures that yield only modest benefits, or practices that undermine their effective use, including corruption in public procurement and insufficient transparency (Bandiera et al., 2009). By linking the objective of fiscal discipline with its potentially constraining effects on green expenditures, our paper complements existing normative proposals by providing empirical evidence while highlighting the positive efficiency effects of fiscal rules despite spending reductions. This offers a more nuanced perspective on the interaction between binding fiscal governance frameworks and the green transition.

Second, this paper contributes to the literature on the determinants of environmental expenditures, a field that remains surprisingly limited. To the best of our knowledge, only one previous study has explored these determinants, focusing on strategic and spatial interactions across countries. Using a panel of 28 OECD countries from 1995 to 2017, Le Gallo and Ndiaye (2021) document positive spatial dependence in environmental spending, suggesting that governments respond to their neighbors’ policies through imitation or yardstick competition. Le Gallo and Ndiaye (2021) also identify other factors such as population size, unemployment, and urbanization that influence environmental expenditures. Our study complements this literature by focusing on a factor that has received relatively little attention so far, namely: fiscal rules.

The remainder of the paper is organized as follows. Section 3 discusses the importance of environmental spending and how governments may operate within the framework of fiscal rules. Section 3 presents the data and highlights key stylized facts. Section 4 outlines the empirical methodology and reports the main findings. Section 5 conducts a series of robustness checks to assess the reliability of the results. Section 6 examines heterogeneous effects across initial spending levels, types of fiscal rules, and several economic and political conditions. Section 7 examines whether the decline in environmental spending results in higher efficiency in the environmental sector. Finally, Section 8 concludes and discusses policy implications.

# 2 Background

## 2.1 The case for increasing environmental spending

Beyond their contribution to mitigation objectives, environmental investments also yield substantial domestic economic benefits. Such spending can stimulate economic growth by promoting green job creation and fostering innovation. Investments in green projects, such as renewable energy, green infrastructure, sustainable agriculture, conservation, and reforestation,
create jobs across multiple sectors, including construction, engineering, energy efficiency, waste management, and research and development (R&D). For instance, the European Environment Agency (EEA) reports that the growth in green jobs between 2010 and 2020 in the EU was mainly driven by an increase of 503,000 full-time equivalent (FTE) positions related to energy resource management,<fnref n="6" /> while waste management jobs increased by 238,000 FTEs.<fnref n="7" /> Furthermore, environmental spending can encourage investment in green technologies, fostering the development of new industries and markets, and thereby enhancing a country's competitiveness on the global stage. The positive effects of green spending on economic performance are supported by Afonso et al. (2025), who show that, in EU countries, although the GDP multiplier of such expenditures is moderate, they effectively stimulate private investment and are perceived by markets as more sustainable. This spending appears to bolster economic agents' confidence, notably through its role in driving the energy transition, reducing long-term energy costs, and enhancing political credibility over the long term. On the welfare side, investments in clean air and water, pollution control, and climate resilience improve public health, protect populations from environmental shocks, and reduce future adaptation and damage costs, thereby enhancing societal stability and well-being. Finally, while environmental investments can yield substantial socio-economic co-benefits, it is equally important to recognize that the costs of inaction may be severe, underscoring the urgent need to significantly scale up environmental investments, a substantial share of which should be borne by public resources (International Monetary Fund, 2021; European Commission, 2024; Sweatman et al., 2024).

## 2.2 How could governments behave within the fiscal rules framework?

While environmental spending supports ecological goals and boosts the domestic economy, it often requires additional financing that can be politically and socially costly, for example, through carbon taxes (Maestre-Andrés et al., 2019). Governments prioritizing fiscal discipline may thus restrain or reduce such spending, particularly in countries with fiscal rules where maintaining fiscal discipline is a key priority. Fiscal rules are permanent constraints on fiscal policy, which may be numerical or procedural, and may relate to debt, deficits, expenditure, or revenues. They are designed to “tie governments’ hands” to ensure fiscal sustainability, by tackling three main issues in public finance management: the common pool problem, the agency problem, and dynamic incoherence. An extensive body of literature on fiscal rules provides robust evidence of their favorable effects on fiscal discipline (see, among others, Alesina et al.,

<footnote n="6">⁶This includes jobs linked to renewable energy production, manufacturing of renewable energy equipment like wind turbines and photovoltaic cells, energy-efficient equipment manufacturing, R&D, installation, consultancy, and management services.</footnote>

<footnote n="7">⁷See the European Environment Agency's statistics.</footnote>
1999; Primo, 2006; Debrun et al., 2008; Debrun and Kumar, 2009; Tapsoba, 2012; Badinger and Reuter, 2017; Combes et al., 2018; Caselli and Reynaud, 2020; Apeti et al., 2025). Capitalizing on this, our reading is that the fiscal constraints imposed by fiscal rules can shape environmental spending through at least two channels.

First, the discipline imposed by fiscal rules entails adjusting tax revenues and public ex-
penditures according to the level of debt, to reduce deficits or improve the budget balance, in line
with Bohn (2008). The scope for increasing taxes, however, is very limited, as most advanced
economies appear to have reached the Laffer threshold. Even if this were not the case, taxation
cannot be raised indefinitely due to economic distortions (see, among others, Koester and Kor-
mendi, 1989; Barro, 1990; Ihori, 2001; Romer and Romer, 2010). This argument is supported
by Asatryan et al. (2018), who show that fiscal rules are unlikely to trigger significant increases
in taxation. Consequently, expenditure cuts emerge as the most viable option for debt reduction,
as emphasized in the fiscal consolidation literature. Nevertheless, adjustments through spending
have important composition effects. Current expenditures, including employee compensation,
subsidies, and social benefits, are relatively difficult to reduce due to their high political costs,
linked to electoral considerations. In contrast, investment or capital expenditures are easier to
adjust, as their effects materialize in the long term (Blanchard and Giavazzi, 2004). However, a
fiscal consolidation predominantly achieved through cuts in public investment is likely to induce
a larger economic contraction than one relying primarily on reductions in current expenditures
(Ardanaz et al., 2024). In this context, empirical evidence suggests that fiscal rules tend to
protect productive or other growth-enhancing public investments (Ardanaz et al., 2021). Envi-
ronmental expenditures, which typically have lower multipliers than other types of investment
(Afonso et al., 2025), may be particularly vulnerable to cuts as governments strive to meet their
fiscal targets.

Second, the reduction of public expenditures may entail political costs, such as a loss of
popularity, strong political opposition, and, in some cases, governmental instability. However,
national elections over the past two decades suggest that environmental concerns have not been
a central priority for many voters, with green parties rarely securing a majority of votes, par-
ticularly in Europe (Gourley and Khamis, 2023).<fnref n="8" /> Moreover, while environmental issues are
undeniably important, they do not rank among the top three priorities for aging populations.<fnref n="9" />
Darvas and Wolff (2022) also note that in aging societies, typically advanced economies, the
interests of future generations, such as environmental protection and climate change mitigation,

<footnote n="8">⁸For a review of the literature devoted to the interactions between citizens’ environmental concerns and the electoral cycle, see Boly et al. (2022a).</footnote>

<footnote n="9">⁹See The World Economic Forum.</footnote>
receive comparatively less electoral support.<fnref n="10" /> Politicians seeking to maximize votes are therefore more likely to make decisions that work against long-term interests. Consequently, within a fiscal rules framework, this shift in electoral priorities may create political space for governments to reduce environmental expenditures, which attract comparatively less attention from their electorate. Fiscal rules can also incentivize governments to reduce fossil fuel subsidies. However, policymakers appear reluctant to cut subsidies that favor carbon-intensive activities, such as transportation, which still account for a substantial share of global GDP, over 5 percent. Major emitters, including the EU, the USA, and China, remain the largest subsidy providers worldwide (Coady et al., 2019), with a 2023 estimate placing global fossil fuel subsidies at 7.1 percent of world GDP black2023imf. A recent World Bank study highlights limited public support for subsidy reform, a situation exacerbated by low awareness of energy subsidies within countries (Hoy et al., 2023). The IMF emphasizes the need for targeted fiscal adjustments, particularly regarding energy subsidies and pension systems (International Monetary Fund, 2025).

Finally, another factor that may explain the relationship between fiscal rules and environmental spending lies in the risks associated with financing such expenditures through public debt. In addition to directly worsening budget deficits, debt-financed environmental spending may also prove detrimental to environmental performance, at least in the long run. While it is well established that high debt levels reduce governments' ability to pursue expansionary fiscal policies for environmental goals (Clootens, 2017), recent studies suggest that public debt and environmental debt act as substitutes in the short run but become complements in the long run (Boly et al., 2022b; Baret and Menuet, 2024). The intuition is that although debt accumulation initially provides resources to support environmental objectives, particularly when the initial debt level is low, over time the rising burden of debt servicing crowds out public investment, especially in environmental projects. This is all the more relevant since environmental spending typically yields limited revenues and rarely generates sufficient returns to cover debt obligations (Minea and Villieu, 2012; Blanchard, 2023). Consequently, these analyses suggest that fiscal rules may significantly constrain the use of public debt as a financing instrument for environmental expenditures.

<footnote n="10">¹⁰However, severe environmental degradation can harm population health, particularly among the elderly, potentially increasing support for pro-environmental measures. Yet, econometric evidence suggests that this effect is generally limited and not the dominant driver of environmental policy support (see, for instance Wu and Cutter, 2011).</footnote>
# 3 Data and stylized facts

## 3.1 Data

Our paper aims to investigate the effect of fiscal rules on environmental spending. We use annual panel data covering 31 advanced countries from 1995 to 2021. The choice of our sample and the time coverage was conditioned by the availability of data on environmental spending. Likewise, our paper focuses on advanced countries, as our environmental spending data is only available for these countries. The outcome variable captures government spending on environmental protection, expressed as a percentage of GDP. It includes expenditures on a defined set of activities according to the Classification of Functions of Government (COFOG) framework, namely: pollution abatement, biodiversity conservation, waste management, and related initiatives. The variable is from the IMF's Climate Change Indicators.

Our variable of interest, fiscal rules, is drawn from the IMF's Fiscal Rules Dataset, which provides information on national and supranational fiscal rules across four categories: balanced budget rules (BBR), debt rules (DR), expenditure rules (ER), and revenue rules (RR). The dataset further captures five key features of fiscal rules: legal basis, coverage, enforcement, flexibility, and supporting procedures. The 'legal basis' feature reflects the statutory strength of the rule, ranging from political commitments (lowest) to constitutional provisions (highest). The 'coverage' feature indicates the scope of the rule, from the central government to the general or wider public sector. The 'enforcement' feature combines the presence of formal correction mechanisms and external monitoring. The 'flexibility' feature considers escape clauses, cyclical adjustments, and exclusions of public investment from spending targets to accommodate economic shocks. The 'supporting procedures' encompass multi-year spending ceilings and an independent fiscal body that sets budgetary assumptions and monitors their implementation.<fnref n="11" /> Following previous studies (e.g., see Schaechter et al., 2012; Gootjes et al., 2021; Gootjes and De Haan, 2022), we construct a fiscal rules index, which aggregates five broad features described above: legal basis, coverage, enforcement mechanisms, supporting procedures, and flexibility measures.<fnref n="12" /> We further follow Schaechter et al. (2012) and give equal weight to each feature. Finally, the index is normalized to unity, so that higher values indicate more

$$FRI = \text{Legal basis} + \text{Coverage} + \text{Enforcement} + \text{Flexibility} + \text{Supporting} \quad (1)$$

<footnote n="11">¹¹All specific features in the IMF dataset are coded as 0–1 dummies, except for ‘coverage’ and ‘legal basis’. Coverage is coded as no coverage=0, central government=1, general government/wider public sector=2, with potential upward adjustments of 0.5 for partial applicability. Legal basis is codified on five different values: political commitment=1, coalition agreement=2, statutory basis=3, international treaty=4, constitutional=5.</footnote>

<footnote n="12">¹²The specification of the equation is as follows:</footnote>
stringent fiscal rules.

Next, we include a set of macroeconomic and institutional control variables, namely the output gap, debt-to-GDP ratio, trade openness, age dependency ratio, unemployment rate, and democracy. The output gap may have a twofold effect. From a Keynesian perspective, and under a counter-cyclical fiscal policy, upturn (downturn) phases of the economic cycle are expected to be associated with lower (higher) environmental spending, particularly when such expenditures have significant multiplier effects. Conversely, if environmental spending has limited multiplier effects, which the literature finds inconclusive (see Afonso et al., 2025 and Shah and Wu, 2025), it may increase even during economic expansions, financed by higher tax revenues through automatic stabilizers. Examining the cyclicality of government environmental protection spending in OECD countries, Abbott and Jones (2023) show that these fluctuations are largely driven by political pressures and governments' responsiveness to changes in voters' perceptions of the economic cycle. An increase in public debt can provide financing for environmental investments, such as low-carbon technologies, clean energy projects, or R&D activities that primarily benefit future generations (Bénassy-Quéré et al., 2010). On the other hand, under significant budgetary constraints, the government may be reluctant to finance environmental expenditures through additional debt, particularly since these expenditures do not yield immediate returns, or may even reduce such spending in favor of other investments deemed more profitable (Fodha and Seegmuller, 2014; Boly et al., 2022b). Trade openness may stimulate environmental spending through a scale effect: as increased trade can raise CO2 emissions by expanding production and energy consumption (Antweiler et al., 2001; Farhani et al., 2014), governments may be prompted to increase environmental expenditures. An alternative argument emphasizes the technique effect, whereby trade fosters the diffusion of cleaner production technologies. In this case, trade can either complement environmental spending by supporting additional initiatives or reduce it by lowering pollution intensity per unit of output (Antweiler et al., 2001; Dauda et al., 2021). Regarding the dependency ratio, since countries with higher dependency face increased demand for social spending (e.g., programs for childcare, education, pensions, and healthcare), this is likely to reduce allocations to environmental expenditures (Tang et al., 2017; Le Gallo and Ndiaye, 2021). Similarly, the unemployment rate can reflect competing expenditure priorities that may negatively influence environmental spending. Higher unemployment rates often shift fiscal resources toward welfare programs rather than environmental initiatives (Le Gallo and Ndiaye, 2021). Finally, democracy can play a crucial role in shaping environmental preferences, with theoretically ambiguous effects. By ensuring media freedom and access to information, democracies make environmental issues more salient to the public, thereby generating political pressure on governments to improve environmental quality (Payne,
1995; Li and Reuveny, 2006). Conversely, free and independent media within a democratic
framework can favor polarizing opinions and amplify the visibility of extreme positions, typ-
ically those of climate skeptics, which may reduce political pressure on environmental issues.
Table A.7 in the Appendix describes our variables and their data sources.

**3.2 Stylized facts**

Panel A of Figure 1 depicts the average environmental spending (as a percentage of GDP) across countries in our sample over the study period. The figure highlights a general upward trend, reflecting the increasing climate-related concerns in advanced economies, while also showing notable fluctuations in these expenditures. First, a marked decline is observed until 2000, largely driven by countries such as Australia, Austria, Cyprus, Finland, Germany, Greece, Ireland, Iceland, Italy, Lithuania, Latvia, Sweden, and Singapore, which allocated significantly fewer resources to environmental priorities during this period, likely reflecting competing demands in other sectors such as health and social protection spending (OECD, 2007). Environmental spending then rose steadily until 2009 before declining again until 2011, a pattern plausibly explained by the fiscal pressures of the 2008–2009 Global Financial Crisis, when many countries faced deficits and macroeconomic imbalances. Third, environmental spending shows a renewed increase from 2011, peaking in 2012, before stabilizing thereafter with relatively modest fluctuations. This notable rise coincides with the first commitment period (2008–2012) of the Kyoto Protocol, which spurred substantial investments to achieve the target of reducing emissions by 5 percent relative to 1990 levels.<fnref n="13" /> Panel B (Figure 1) reveals substantial cross-country variation in environmental spending within our sample. Over our study period, on average, countries such as the Netherlands, Malta, Japan, Belgium, and Slovakia report the highest average levels of environmental spending, fluctuating around 1 percent of GDP, whereas Singapore, Cyprus, Finland, Sweden, and Latvia exhibit the lowest levels, ranging from 0.15 to 0.49 percent of GDP.<fnref n="14" />

Figure 2 shows the average evolution of the aggregate fiscal rules index across our sample over the study period. The index averaged 0.48, exhibiting a marked upward trend with a first peak in 2005, a period of stabilization thereafter, and a renewed surge following the Global Financial Crisis in 2011, before stabilizing around 2016. Across categories, balanced budget rules are the most prominent, with an average value of 0.44, followed by debt rules (0.34).

<footnote n="13">¹³To ensure that our results are not driven by these episodes of sharp fluctuations in environmental spending, we conduct robustness checks excluding, respectively, the 2008–2009 Global Financial Crisis period and the Kyoto Protocol first commitment period (2008–2012). The results, reported in Subsection 5.2, confirm the robustness of our main findings.</footnote>

<footnote n="14">¹⁴To ensure that our results are not driven by these high- or low-spending countries, we perform a sensitivity analysis excluding them from our full sample.</footnote>
<figure><img src="image_5.png" /><figcaption>Figure 1: Average trends in environmental spending.</figcaption></figure>

Source:

Authors' from the IMF Climate Change Indicators.

and expenditure rules (0.24). Expenditure rules gained prominence primarily in the post-crisis
years, whereas balanced budget and debt rules were already firmly established by the mid-
1990s. Revenue rules remain the least developed, but display a steady upward trajectory, with
an average value of 0.17 over the period. France, Sweden, Switzerland, Norway, Australia, and
China (Hong Kong SAR) report an average fiscal rules index above the sample mean, ranging
from 0.6 to 0.9. By contrast, Iceland, Canada, Singapore, Portugal, the Netherlands, Greece,
Italy, and the Czech Republic exhibit below-average levels, with values between 0.2 and 0.4.

<figure><img src="image_6.png" /><figcaption>Figure 2: Average trends in the fiscal rules index from 1995 to 2021.</figcaption></figure>

Source: Authors, from the IMF Fiscal Rules Dataset.

4 Methodology and core findings

This paper investigates the effects of fiscal rules on environmental spending. To do so, we exploit annual panel data, including both country fixed effects to account for country-specific, time-invariant unobserved heterogeneities; and year fixed effects to capture time-varying common shocks in the sample, which may be correlated with fiscal rules and environmental spend-
ing. Drawing on the OLS estimator, we estimate the following equation:

$$Y_{i,t} = \alpha + \beta_1 Fiscal Rules_{i,t} + \beta_2 X_{i,t} + \mu_i + \tau_t + \varepsilon_{i,t} \quad (2)$$

where $Y_{i,t}$ measures the government's environmental spending (as a share of GDP) in country $i$ at time $t$. $Fiscal Rules_{i,t}$ captures the strength of fiscal rules and can range from 0 to 1. $X_{i,t}$ is the set of controls previously described: output gap, debt-to-GDP ratio, trade openness, age dependency ratio, unemployment rate, and democracy. $\mu_i$ controls for time-invariant country-specific characteristics, while $\tau_t$ controls for time-varying common shocks in the sample. $\varepsilon_{i,t}$ represents the idiosyncratic error term.<fnref n="15" />

Our main results are reported in Table 1. Column [1] presents a naive regression, i.e., the single response of environmental spending following tighter fiscal rules, using a univariate regression and controlling for country and time fixed effects. Columns [2] to [6], then progressively add our main control variables. Column [7] reports our benchmark specification, which includes the full set of controls as well as country and time fixed effects. The results indicate a significant negative effect of fiscal rules on environmental spending, at the 1 percent threshold. By multiplying the estimated coefficient by the standard deviation of environmental spending (0.34, see Table A.2), we find that a one standard deviation increase in the fiscal rules reduce environmental spending by about 0.04 percentage points of GDP, or nearly 6 percent of the average environmental spending, suggesting an economically significant effect of fiscal rules. Regarding the baseline model's control variables, we observe that the debt-to-GDP ratio is positively associated with environmental spending, while the age dependency ratio and the unemployment rate have a negative effect.

# 5 Robustness checks

Our main estimates provide evidence that fiscal rules contribute to a reduction in environmental spending in advanced economies. In this section, we further extend these findings and assess their robustness using a comprehensive set of economic and econometric tests.

<footnote n="15">¹⁵Before proceeding to our econometric analysis, we conduct unit root tests to assess the stationarity of the baseline model's variables, thereby mitigating potential concerns of spurious regression. The results of the Augmented Dickey-Fuller (ADF) and Im-Pesaran-Shin (IPS) tests, reported in Table A.3, indicate that all baseline variables are stationary in levels, denoted I(0), while trade openness is non-stationary in levels but stationary in first differences, denoted I(1).</footnote>
<table><caption>Table 1: Fiscal Rules and Environmental Spending</caption><thead><tr><th>Environmental Spending (% of GDP)</th><th>[1]</th><th>[2]</th><th>[3]</th><th>[4]</th><th>[5]</th><th>[6]</th><th>[7]</th></tr></thead><tbody><tr><td>Fiscal Rules</td><td>-0.102***<br>(0.035)</td><td>-0.100***<br>(0.035)</td><td>-0.114***<br>(0.036)</td><td>-0.117***<br>(0.036)</td><td>-0.120***<br>(0.036)</td><td>-0.129***<br>(0.037)</td><td>-0.130***<br>(0.037)</td></tr><tr><td>Output gap</td><td></td><td>0.023<br>(0.018)</td><td>0.036**<br>(0.018)</td><td>0.039**<br>(0.019)</td><td>0.039**<br>(0.019)</td><td>0.025<br>(0.020)</td><td>0.024<br>(0.019)</td></tr><tr><td>Debt-to-GDP</td><td></td><td></td><td>0.002***<br>(0.001)</td><td>0.002***<br>(0.001)</td><td>0.002***<br>(0.001)</td><td>0.003***<br>(0.001)</td><td>0.003***<br>(0.001)</td></tr><tr><td>Trade Openness</td><td></td><td></td><td></td><td>0.001<br>(0.001)</td><td>0.001<br>(0.001)</td><td>0.001<br>(0.001)</td><td>0.001<br>(0.001)</td></tr><tr><td>Age Dependency ratio</td><td></td><td></td><td></td><td></td><td>-0.007**<br>(0.003)</td><td>-0.010***<br>(0.004)</td><td>-0.010***<br>(0.004)</td></tr><tr><td>Unemployment Rate</td><td></td><td></td><td></td><td></td><td></td><td>-0.016***<br>(0.005)</td><td>-0.016***<br>(0.005)</td></tr><tr><td>Democracy</td><td></td><td></td><td></td><td></td><td></td><td></td><td>-0.014<br>(0.035)</td></tr><tr><td>Country FE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Time FE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Observations</td><td>724</td><td>724</td><td>724</td><td>724</td><td>724</td><td>724</td><td>724</td></tr><tr><td>R<sup>2</sup></td><td>0.7462</td><td>0.7468</td><td>0.7549</td><td>0.7555</td><td>0.7572</td><td>0.7612</td><td>0.7613</td></tr></tbody></table>

Notes: This table reports OLS estimates of the impact of fiscal rules on environmental spending. The fiscal rules index ranges from 0 to 1, and the dependent variable is environmental spending, measured as a share of GDP. Column [7] presents our baseline result. All regressions include a constant (not reported). Robust standard errors are in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1.

## 5.1 Omitted factors

To mitigate potential multicollinearity, our baseline model uses a limited set of controls. However, to address possible omitted variable bias, we extend the specification by adding three additional groups of control variables.<fnref n="16" /> Before turning to the extended specification, we check that our baseline results are not driven by overlapping cyclical indicators. Since the unemployment rate can be correlated with the output gap, we re-estimate the model without the unemployment rate, ensuring that cyclical conditions are captured consistently and without redundancy across controls. We then expand our analysis by incorporating political factors, namely government ideology (left- or right-wing), the degree of government fragmentation, and media freedom. Although policymaking lies with the government, it is strongly shaped by the ruling party’s ideology. The political economy literature underscores that government ideology matters for environmental outcomes. Several studies show, for instance, that left-wing governments tend to devote more attention to environmental issues than their right-wing counterparts, as they place greater emphasis on public welfare (Neumayer, 2003, 2004; Chang and Berdiev, 2011; Wen et al., 2016). Government fragmentation can influence environmental spending through two opposing mechanisms. According to the “common pool” theory, partisan politics tends to increase public spending, potentially financed by debt, to satisfy the demands of multiple coalition

<footnote n="16">¹⁶Detailed definitions of the variables are provided in Table A.8 in the Appendix.</footnote>
members (Weingast et al., 1981; Kontopoulos and Perotti, 1999). From this perspective, greater fragmentation could raise environmental spending, provided that environmental protection is a priority for some coalition members. By contrast, the “veto player” perspective suggests that fragmentation constrains spending initiatives, since coalition members can exercise veto power over policy proposals (Blais et al., 2010). In this case, environmental spending is likely to fall, particularly when influential parties prioritize economic, industrial, or social objectives over environmental protection. Finally, a free and transparent media environment facilitates the wide dissemination of information on environmental issues, including both the benefits of protection and the costs of neglect. By reducing the information gap between governments and citizens, media freedom raises public awareness and, in turn, places pressure on policymakers to prioritize environmental concerns and allocate resources accordingly (Riti et al., 2021; Boly et al., 2023). Yet, this dynamic may also be ambivalent: as discussed previously, by amplifying polarizing voices, media freedom can increase the visibility of extreme positions, most notably those of climate skeptics, thereby reducing political pressure to advance environmental protection.

Next, we incorporate additional economic and environmental factors, namely, financial development and environmental tax revenues. Financial development can play a pivotal role in shaping environmental quality, as a well-developed financial sector can help provide more financing at lower costs, particularly for investments in environmentally oriented projects (Tamazian et al., 2009). However, greater financial development can also boost economic activity and thus lead to more environmental damage. Environmental public spending may need to increase to mitigate these negative effects. The impact of financial development is therefore ambiguous (Ganda, 2019). Environmental taxation can expand the financial resources available to governments, thus contributing to financing environmental initiatives. This aligns with the notion that higher environmental taxes signal a strengthening of environmental policy. Such tightening generally goes hand in hand with increased environmental expenditures, as governments need to support regulation with complementary investments and mitigation measures.

Lastly, following Le Gallo and Ndiaye (2021), we incorporate demographic controls, including urbanization and population size. Greater urbanization and larger populations are often associated with intensified environmental degradation, thereby increasing the demand for environmental expenditures. At the same time, larger populations may generate economies of scale by spreading fixed costs of environmental protection across a wider base, which lowers the relative per capita burden of such expenditures.

The results reported in the second column, which exclude the unemployment rate from the baseline controls to mitigate potential multicollinearity with the output gap, remain stable. Columns [3] to [10] of Table 2 sequentially introduce each of these additional controls, while the
last column includes all new controls in the same regression. Our baseline results remain stable, confirming the robustness of our findings. Regarding the new controls, the results indicate that a shift in government political ideology from left to right is associated with a decrease in environmental expenditures, while government fragmentation, financial development, and urbanization have a positive effect.

<table><caption>Table 2: Robustness check: Omitted factors</caption><thead><tr><th rowspan="2">Environmental Spending (% of GDP)</th><th colspan="10">Baseline</th></tr><tr><th>[1]</th><th>[2]</th><th>[3]</th><th>[4]</th><th>[5]</th><th>[6]</th><th>[7]</th><th>[8]</th><th>[9]</th><th>[10]</th></tr></thead><tbody><tr><td>Fiscal Rules</td><td>-0.130***<br>(0.037)</td><td>-0.120***<br>(0.036)</td><td>-0.122***<br>(0.045)</td><td>-0.124***<br>(0.040)</td><td>-0.143***<br>(0.039)</td><td>-0.118***<br>(0.038)</td><td>-0.158***<br>(0.042)</td><td>-0.129***<br>(0.037)</td><td>-0.163***<br>(0.036)</td><td>-0.193***<br>(0.053)</td></tr><tr><td>Output gap</td><td>0.024<br>(0.019)</td><td>0.039**<br>(0.018)</td><td>0.025<br>(0.021)</td><td>0.026<br>(0.021)</td><td>0.015<br>(0.019)</td><td>0.017<br>(0.020)</td><td>0.027<br>(0.021)</td><td>0.024<br>(0.019)</td><td>0.026<br>(0.020)</td><td>0.019<br>(0.021)</td></tr><tr><td>Debt-to-GDP</td><td>0.003***<br>(0.001)</td><td>0.002***<br>(0.001)</td><td>0.003***<br>(0.001)</td><td>0.003***<br>(0.001)</td><td>0.003***<br>(0.001)</td><td>0.003***<br>(0.001)</td><td>0.002***<br>(0.001)</td><td>0.003***<br>(0.001)</td><td>0.003***<br>(0.001)</td><td>0.002***<br>(0.001)</td></tr><tr><td>Trade Openness</td><td>0.001<br>(0.001)</td><td>0.001<br>(0.001)</td><td>0.002<br>(0.001)</td><td>0.002<br>(0.001)</td><td>0.001<br>(0.001)</td><td>0.001<br>(0.001)</td><td>0.001<br>(0.001)</td><td>0.001<br>(0.001)</td><td>0.001<br>(0.001)</td><td>0.002<br>(0.002)</td></tr><tr><td>Age Dependency ratio</td><td>-0.010***<br>(0.004)</td><td>-0.007**<br>(0.003)</td><td>-0.009**<br>(0.004)</td><td>-0.011***<br>(0.004)</td><td>-0.004<br>(0.004)</td><td>-0.012***<br>(0.004)</td><td>-0.010***<br>(0.004)</td><td>-0.011***<br>(0.003)</td><td>-0.011**<br>(0.005)</td><td>-0.014**<br>(0.005)</td></tr><tr><td>Unemployment Rate</td><td>-0.016***<br>(0.005)</td><td></td><td>-0.017***<br>(0.005)</td><td>-0.020***<br>(0.005)</td><td>-0.028***<br>(0.005)</td><td>-0.013**<br>(0.005)</td><td>-0.015***<br>(0.005)</td><td>-0.017***<br>(0.005)</td><td>-0.015***<br>(0.005)</td><td>-0.024***<br>(0.007)</td></tr><tr><td>Democracy</td><td>-0.014<br>(0.035)</td><td>0.001<br>(0.034)</td><td>-0.030<br>(0.035)</td><td>-0.026<br>(0.035)</td><td>-0.033<br>(0.033)</td><td>-0.019<br>(0.034)</td><td>-0.028<br>(0.036)</td><td>-0.009<br>(0.034)</td><td>-0.021<br>(0.036)</td><td>-0.018<br>(0.035)</td></tr><tr><td>Government Ideology</td><td></td><td></td><td></td><td>-0.028***<br>(0.009)</td><td></td><td></td><td></td><td></td><td></td><td>-0.035***<br>(0.013)</td></tr><tr><td>Government Fragmentation</td><td></td><td></td><td></td><td></td><td>0.064<br>(0.045)</td><td></td><td></td><td></td><td></td><td>0.104*<br>(0.062)</td></tr><tr><td>Freedom of Media</td><td></td><td></td><td></td><td></td><td></td><td>-0.003<br>(0.004)</td><td></td><td></td><td></td><td>-0.006<br>(0.004)</td></tr><tr><td>Financial Development</td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.737***<br>(0.158)</td><td></td><td></td><td>0.690***<br>(0.227)</td></tr><tr><td>Environmental Tax</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.063**<br>(0.026)</td><td></td><td>0.033<br>(0.036)</td></tr><tr><td>Urban Population</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>0.005<br>(0.004)</td><td>0.025***<br>(0.008)</td></tr><tr><td>Population (Log)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>-0.380*<br>(0.198)</td></tr><tr><td>Country FE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Time FE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Observations</td><td>724</td><td>724</td><td>645</td><td>675</td><td>563</td><td>694</td><td>649</td><td>724</td><td>663</td><td>489</td></tr><tr><td>R<sup>2</sup></td><td>0.7613</td><td>0.7572</td><td>0.7651</td><td>0.7616</td><td>0.7877</td><td>0.7648</td><td>0.7626</td><td>0.7617</td><td>0.7749</td><td>0.7820</td></tr></tbody></table>

**Notes:** This table reports robustness checks of our baseline estimates using alternative specifications to address potential omitted variable bias. We sequentially re-estimate the benchmark model by adding additional control variables drawn from the literature. The variable of interest is the fiscal rules index (ranging from 0 to 1), and the dependent variable is environmental spending, measured as a share of GDP. Column [1] reports the baseline estimates for comparison. Column [2] excludes the unemployment rate from the baseline controls to mitigate potential multicollinearity with the output gap. Columns [3] to [10] extend the benchmark specification by sequentially introducing additional control variables, including political ideology, government fragmentation, freedom of media, financial development, the environmental tax-to-GDP ratio, urban population, and population size (in log). Column [10] includes all additional controls simultaneously. Political ideology is coded as -1 for left, 0 for centrist, and 1 for right. All regressions include the constant (not reported). The reduction in the number of observations across specifications reflects differences in data availability for the additional variables. Robust standard errors are in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1.
## 5.2 Sample dependence

Sample dependence is a particularly important concern in our analysis, given that the study period encompasses major events that could influence the results. To address this issue, this section examines whether our main findings are robust to the systematic exclusion of specific country subgroups, key macroeconomic events, or participation in certain programs and agreements from the full sample. A potential concern is that EU countries experienced numerous institutional and policy changes over the study period, while simultaneously strengthening their fiscal rules framework, developments that could have influenced our core estimates. To ensure that our results are not driven by these countries, we exclude EU member states in Column [2] of Table 3 (see Gootjes et al., 2021 for a similar approach). Another potential concern is that major global shocks, such as the 2007–2008 Global Financial Crisis or episodes of debt crises, undoubtedly affected fiscal deficits and, indirectly, environmental spending, independently of fiscal rules. To mitigate this risk, we sequentially exclude these periods in Columns [3] and [4] (Table 3), thereby minimizing potential confounding effects. As noted in subsection 3, the Kyoto Agreement likely prompted countries to increase environmental spending substantially to meet its targets, namely an average 5 percent reduction in emissions relative to 1990 levels during the first commitment period from 2008 to 2012, which resulted in a peak in environmental expenditure in 2012. To account for potential bias, Column [5] excludes this first Kyoto commitment period. Similarly, we exclude the post-Paris Agreement period from 2016 to 2021 in Column [7], as the agreement obliges governments to combat climate change by limiting global temperature increases by 2100, which may have redirected budgetary priorities toward environmental spending. We also exclude the post-COVID-19 period from 2020 to 2021 in Column [9], during which most countries temporarily suspended fiscal rules and prioritized economic recovery over environmental concerns. Finally, two countries in our sample, Canada and Iceland, adopted and subsequently abandoned fiscal rules. It is plausible that these deviations were driven by non-fiscal factors or implementation challenges, leaving these countries unconstrained by the initially imposed fiscal targets and potentially allowing them to increase environmental spending. To mitigate this potential bias, we exclude these countries in Column [9]. The results reported in Columns [2] to [9] of Table 3 confirm that our main findings remain robust across all these sample restrictions.

As a final check for sample dependence, we perform a leave-one-out analysis to assess the robustness of our results to potential outliers. Specifically, we re-estimate our benchmark model by sequentially excluding each country at a time. The results, presented in Figure A.2 in the Appendix, show that the coefficient of fiscal rules remains negative and statistically significant throughout, with confidence intervals consistently excluding zero. This confirms that our core
<table><caption>Table 3: Robustness check: Sample dependence</caption><thead><tr><th></th><th>Baseline</th><th>EU countries</th><th>GFC (2008-2009)</th><th>Global Crises</th><th>Kyoto Objectives</th></tr><tr><th>Excluding</th><th>[1]</th><th>[2]</th><th>[3]</th><th>[4]</th><th>[5]</th></tr></thead><tbody><tr><td>Fiscal Rules</td><td>-0.130***<br>(0.037)</td><td>-0.085*<br>(0.045)</td><td>-0.136***<br>(0.041)</td><td>-0.154***<br>(0.038)</td><td>-0.170***<br>(0.047)</td></tr><tr><td>Output gap</td><td>0.024<br>(0.019)</td><td>-0.018<br>(0.031)</td><td>0.022<br>(0.020)</td><td>0.028<br>(0.022)</td><td>0.031<br>(0.022)</td></tr><tr><td>Debt-to-GDP</td><td>0.003***<br>(0.001)</td><td>0.003*<br>(0.001)</td><td>0.003***<br>(0.001)</td><td>0.003***<br>(0.001)</td><td>0.004***<br>(0.001)</td></tr><tr><td>Trade Openness</td><td>0.001<br>(0.001)</td><td>0.002<br>(0.001)</td><td>0.001<br>(0.001)</td><td>0.001<br>(0.001)</td><td>0.001<br>(0.001)</td></tr><tr><td>Age Dependency ratio</td><td>-0.010***<br>(0.004)</td><td>-0.025***<br>(0.008)</td><td>-0.010***<br>(0.004)</td><td>-0.010**<br>(0.004)</td><td>-0.011***<br>(0.004)</td></tr><tr><td>Unemployment Rate</td><td>-0.016***<br>(0.005)</td><td>-0.046**<br>(0.021)</td><td>-0.018***<br>(0.005)</td><td>-0.021***<br>(0.005)</td><td>-0.022***<br>(0.005)</td></tr><tr><td>Democracy</td><td>-0.014<br>(0.035)</td><td>0.087<br>(0.267)</td><td>-0.013<br>(0.035)</td><td>-0.037<br>(0.037)</td><td>-0.019<br>(0.034)</td></tr><tr><td>Country FE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Time FE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Observations</td><td>724</td><td>169</td><td>662</td><td>587</td><td>602</td></tr><tr><td>R<sup>2</sup></td><td>0.7613</td><td>0.8549</td><td>0.7615</td><td>0.7868</td><td>0.7667</td></tr></tbody></table><table><thead><tr><th></th><th>Baseline</th><th>Paris Agreement</th><th>Post Covid-19</th><th>Breaking Rules</th></tr><tr><th>Excluding</th><th>[6]</th><th>[7]</th><th>[8]</th><th>[9]</th></tr></thead><tbody><tr><td>Fiscal Rules</td><td>-0.130***<br>(0.037)</td><td>-0.156***<br>(0.039)</td><td>-0.151***<br>(0.036)</td><td>-0.192***<br>(0.040)</td></tr><tr><td>Output gap</td><td>0.024<br>(0.019)</td><td>0.010<br>(0.019)</td><td>0.021<br>(0.020)</td><td>0.026<br>(0.020)</td></tr><tr><td>Debt-to-GDP</td><td>0.003***<br>(0.001)</td><td>0.003**<br>(0.001)</td><td>0.003***<br>(0.001)</td><td>0.004***<br>(0.001)</td></tr><tr><td>Trade Openness</td><td>0.001<br>(0.001)</td><td>0.001<br>(0.001)</td><td>0.001<br>(0.001)</td><td>0.001<br>(0.001)</td></tr><tr><td>Age Dependency ratio</td><td>-0.010***<br>(0.004)</td><td>-0.003<br>(0.005)</td><td>-0.007**<br>(0.004)</td><td>-0.011***<br>(0.004)</td></tr><tr><td>Unemployment Rate</td><td>-0.016***<br>(0.005)</td><td>-0.030***<br>(0.005)</td><td>-0.018***<br>(0.005)</td><td>-0.019***<br>(0.005)</td></tr><tr><td>Democracy</td><td>-0.014<br>(0.035)</td><td>-0.049<br>(0.033)</td><td>-0.019<br>(0.034)</td><td>-0.016<br>(0.035)</td></tr><tr><td>Country FE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Time FE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Observations</td><td>724</td><td>539</td><td>663</td><td>690</td></tr><tr><td>R<sup>2</sup></td><td>0.7613</td><td>0.7953</td><td>0.7730</td><td>0.7694</td></tr></tbody></table>

Notes: This table reports robustness checks of our baseline estimates using alternative samples. The variable of interest is the fiscal rules index (ranging from 0 to 1), and the dependent variable is environmental spending, measured as a share of GDP. Columns [1] and [6] reproduce the baseline estimates for comparison. Columns [2]–[5] sequentially exclude EU member states, the Global Financial Crisis (2008–2009), and the Kyoto Protocol first commitment period (2008–2012). Columns [7]–[9] exclude the Paris Agreement period (2016–2021), the post-COVID-19 period, and countries that have adopted and subsequently broken fiscal rules (Canada, Iceland). All regressions include the constant (not reported). Robust standard errors are in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1.
findings are not driven by any specific country and are robust to potential outliers.

## 5.3 Alternative measures

As outlined in Subsection 3, our main outcome variable is environmental spending as a share of GDP, which provides information on how much economic effort and resources are devoted to environmental protection relative to the size of the economy as a whole. This also allows for assessing how different governments prioritize environmental protection based on their economic capacity. However, it does not catch a potential composition effect of the fiscal rule on public spending. To account for that, we use environmental spending as a share of total expenditures. Results are reported in Column [2] of Table A.4 and reveal that fiscal rules still reduce environmental spending. Nonetheless, the estimated coefficient is larger in magnitude than that obtained in the baseline model (-0.136 versus -0.263), likely reflecting differences in the scaling of the two outcome measures. These results suggest that our findings are not driven by the measure of our outcome variable.

Next, we use an alternative measure for our right-hand-side variable. Our baseline approach follows previous studies (see, among others, Bergman and Hutchison, 2015; Gootjes et al., 2021; Gootjes and De Haan, 2022) and uses a fiscal rules index that includes flexibility features. However, the consideration of the flexibility of fiscal rules remains a debated issue in the literature. On the one hand, some scholars argue that incorporating flexibility into fiscal rules may be desirable when designing optimal fiscal frameworks. Rigid fiscal rules can constrain policymakers during economic downturns and may incentivize inefficient, procyclical fiscal policies. Consequently, fiscal rules that account for the business cycle and exclude certain spending from expenditure ceilings are considered more effective in promoting sound fiscal management (Guerguil et al., 2017). On the other hand, Schaechter et al. (2012) claim that flexibility measures should not be incorporated into the overall fiscal rules index, as flexible rules may not be suitable for all countries and can introduce additional challenges for effective implementation and monitoring. To account for that, we exclude flexibility features from the fiscal rules index in Column [3] of Table A.4. The new coefficients remain close to our main estimates.

## 5.4 Alternative methods

From an econometric perspective, we conduct additional sensitivity analyses using alternative estimation methods to account for potential endogeneity concerns. In particular, we re-estimate the benchmark model employing an Instrumental Variables (IV) approach and a Generalized
Method of Moments (GMM) estimator.

**IV estimates.** The OLS estimations conducted thus far rely on the assumption that fiscal rules are uncorrelated with the error term in Equation 2. The country fixed effects included in our specifications help mitigate endogeneity concerns by accounting for time-invariant, country-specific factors. The set of additional control variables, included as a robustness check, further reduces bias arising from omitted factors that vary over time and are potentially correlated with both fiscal rules and environmental spending. Nevertheless, unobserved time-varying factors, such as the government's fiscal stance, other reforms, or political determinants, may still not be fully captured. If these factors are correlated with fiscal rules, their omission would induce a mechanical correlation between our estimated coefficient $\beta_1$ and the error term, potentially leading to an underestimation, in absolute value, of the true effect of fiscal rules. Instrumental variables are well-suited to addressing this issue. A first approach would be to rely on an internal instrument, that is, to instrument the fiscal rules index with its lagged value (see, among others, Debrun et al., 2008; Arezki and Brückner, 2011; Guerguil et al., 2017). A second approach would be to employ an external instrument. Our empirical strategy employs both instruments simultaneously. The external instrument builds on, among others, Caselli and Reynaud, 2020; Ardanaz et al., 2021; Balvir, 2023; López-Villavicencio and Zoumenou, 2025, exploiting regional variation in the strengthening of fiscal rules as an exogenous source of variation in domestic fiscal rule strength.17 Specifically, we construct a variable capturing the average strength of fiscal rules in regional peer countries. This approach draws on the policy diffusion literature, which emphasizes that reforms in neighboring countries can exert strong spillover effects on domestic policymaking, through mechanisms such as imitation, peer pressure, learning, or competition (see, among others, Meseguer, 2005; Dobbin et al., 2007; Shipan and Volden, 2008; Buera et al., 2011). Consistent with the above discussion, our identifying assumption is that the strength of fiscal rules in regional peer countries influences the strengthening of domestic fiscal rules but does not directly affect domestic environmental spending, conditional on our vector of controls. To reinforce our exclusion restriction, we include regional debt and regional economic growth as additional controls in our core IV estimates, ensuring that the estimated effect of fiscal rules is not confounded by regional economic dynamics that could independently influence environmental spending.

Our IV results are reported in Table 4. Panel B of Column [2] presents the first-stage estimates, where the strength of fiscal rules is instrumented with its one-year lagged value and the regional average strength of fiscal rules. Both instruments are positively correlated with fis-

<footnote>17For instance, Balvir (2023) shows that countries may adopt national fiscal rules strategically by imitating reforms in neighboring countries to signal credibility to international markets.</footnote>
cal rule strength, and the Kleibergen-Paap F-statistic (217.7) far exceeds the Staiger and Stock (1997) rule of thumb value of 10, indicating that our instruments are not weak. Similarly, the Hansen test of overidentifying restrictions is not rejected. Turning to the second stage, Panel A of Column [2] shows that fiscal rules exert a negative effect on environmental spending. More importantly, the coefficient estimated using instrumental variables is nearly twice as large as that obtained from the baseline OLS estimates (-0.23 versus -0.13), suggesting a slight underestimation of our main effects by OLS. Finally, the results remain robust when regional fiscal and economic conditions are accounted for, whether sequentially or simultaneously, as shown in Columns [3] to [5].

**System GMM estimates.** Next, we re-estimate our benchmark model using the two-step system-GMM dynamic panel estimator proposed by Blundell and Bond (1998).<fnref n="18" /> Unlike the IV approach, the system-GMM estimator relies primarily on internal instruments (in levels and differences) and allows us to account for the persistence of the dependent variable while mitigating the Nickell bias (Nickell, 1981) that arises from the correlation between lagged dependent variables and the error term. This feature is particularly important since fiscal policy variables are well-known to be strongly persistent. Thus, the system-GMM approach provides a more robust framework for capturing the dynamic nature of environmental spending, which both the OLS and IV analyses fail to consider.<fnref n="19" /> Results are reported in Column [6] of Table 4. The strength of fiscal rules appears to exert a significantly negative effect on environmental spending, with short-term effects very close to the OLS estimates. Importantly, the long-run effect, calculated by adjusting the short-run coefficient using the autoregressive parameter of environmental spending, is seven times larger, equivalent to 0.48 percent of GDP.<fnref n="20" />

# 6 Heterogeneity

In this section, we explore some heterogeneous effects, including the type of fiscal rules and economic and political factors.

<footnote n="18">¹⁸The two-step system-GMM estimator combines equations in levels and first differences into a single system, using lagged levels and differences of the explanatory variables as instruments. Compared to the standard difference-GMM estimator, system-GMM improves efficiency by exploiting additional moment conditions. To mitigate the risk of instrument proliferation highlighted by Roodman (2009), we collapse the instrument matrix (with the collapse option in xtabond2) and restrict the number of lags to four. Moreover, to address the downward bias of standard errors in finite samples, we apply the finite-sample correction proposed by Windmeijer (2005). The two instruments used in our IV estimation, the lagged value of fiscal rules strength and the regional average strength of fiscal rules, are also incorporated in the GMM framework as external instruments.</footnote>

<footnote n="19">¹⁹We reorganize our panel data into nine sub-periods of three non-overlapping years (see, among others, Combes et al., 2015; Docquier et al., 2016 for a similar approach). This strategy filters out short-term noise unrelated to the effects of interest and mitigates the risk of spurious regressions.</footnote>

<footnote n="20">²⁰($\frac{0.143}{1-0.849}$)×0.51</footnote>
<table><caption>Table 4: Robustness check: Alternative methods</caption><thead><tr><th rowspan="3">Environmental Spending (% of GDP)</th><th colspan="5">Panel A: Second-stage equation</th><th rowspan="3">System GMM<br>[6]</th></tr><tr><th colspan="5">IV—2SLS</th></tr><tr><th>[1]</th><th>[2]</th><th>[3]</th><th>[4]</th><th>[5]</th></tr></thead><tbody><tr><td>Fiscal Rules</td><td>-0.130***<br>(0.037)</td><td>-0.217***<br>(0.043)</td><td>-0.213***<br>(0.043)</td><td>-0.210***<br>(0.044)</td><td>-0.210***<br>(0.043)</td><td>-0.143**<br>(0.057)</td></tr><tr><td>Output gap</td><td>0.024<br>(0.019)</td><td>0.022<br>(0.019)</td><td>0.022<br>(0.019)</td><td>0.022<br>(0.019)</td><td>0.022<br>(0.019)</td><td>0.130<br>(0.085)</td></tr><tr><td>Debt-to-GDP</td><td>0.003***<br>(0.001)</td><td>0.003***<br>(0.001)</td><td>0.003***<br>(0.001)</td><td>0.003***<br>(0.001)</td><td>0.003***<br>(0.001)</td><td>-0.001<br>(0.001)</td></tr><tr><td>Trade Openness</td><td>0.001<br>(0.001)</td><td>0.001<br>(0.001)</td><td>0.001<br>(0.001)</td><td>0.002<br>(0.001)</td><td>0.002<br>(0.001)</td><td>-0.004*<br>(0.002)</td></tr><tr><td>Age Dependency ratio</td><td>-0.010***<br>(0.004)</td><td>-0.011***<br>(0.004)</td><td>-0.011***<br>(0.004)</td><td>-0.011***<br>(0.004)</td><td>-0.011***<br>(0.004)</td><td>0.017<br>(0.011)</td></tr><tr><td>Unemployment Rate</td><td>-0.016***<br>(0.005)</td><td>-0.017***<br>(0.005)</td><td>-0.017***<br>(0.005)</td><td>-0.017***<br>(0.005)</td><td>-0.017***<br>(0.005)</td><td>0.006<br>(0.019)</td></tr><tr><td>Democracy</td><td>-0.014<br>(0.035)</td><td>-0.017<br>(0.034)</td><td>-0.019<br>(0.034)</td><td>-0.019<br>(0.034)</td><td>-0.019<br>(0.034)</td><td>-0.070<br>(0.065)</td></tr><tr><td>Regional Debt</td><td></td><td></td><td>0.001<br>(0.002)</td><td></td><td>0.000<br>(0.003)</td><td></td></tr><tr><td>Regional Growth</td><td></td><td></td><td></td><td>-0.010<br>(0.010)</td><td>-0.009<br>(0.013)</td><td></td></tr><tr><td>Lag. Environmental Spending</td><td></td><td></td><td></td><td></td><td></td><td>0.849***<br>(0.190)</td></tr><tr><td>Country FE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td></td></tr><tr><td>Time FE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td></td></tr><tr><td>Kleinberg-PaaprRk test</td><td></td><td>217.70</td><td>210.86</td><td>224.53</td><td>217.62</td><td></td></tr><tr><td>Stock-Wright p-value</td><td></td><td>0.00</td><td>0.00</td><td>0.00</td><td>0.00</td><td></td></tr><tr><td>Hansen. p-val.</td><td></td><td>0.25</td><td>0.26</td><td>0.43</td><td>0.41</td><td>0.36</td></tr><tr><td>AR(1) p-val.</td><td></td><td></td><td></td><td></td><td></td><td>0.09</td></tr><tr><td>AR(2) p-val.</td><td></td><td></td><td></td><td></td><td></td><td>0.87</td></tr><tr><td>Num of countries</td><td></td><td></td><td></td><td></td><td></td><td>31</td></tr><tr><td>Num of instruments</td><td></td><td></td><td></td><td></td><td></td><td>26</td></tr><tr><td>Observations</td><td>724</td><td>724</td><td>724</td><td>724</td><td>724</td><td>174</td></tr><tr><td>R<sup>2</sup></td><td>0.7613</td><td>0.1586</td><td>0.1599</td><td>0.1620</td><td>0.1621</td><td></td></tr></tbody></table><table><thead><tr><th colspan="5">Panel B: First-stage equation</th></tr><tr><th>Instruments</th><th colspan="5"></th></tr></thead><tbody><tr><td>Lag Fiscal Rules Index</td><td>0.728***<br>(0.058)</td><td>0.728***<br>(0.058)</td><td>0.728***<br>(0.058)</td><td>0.729***<br>(0.058)</td><td></td></tr><tr><td>Contiguity</td><td>0.443***<br>(0.152)</td><td>0.446***<br>(0.147)</td><td>0.433***<br>(0.136)</td><td>0.436***<br>(0.136)</td><td></td></tr></tbody></table>

**Notes:** This table reports robustness checks for our baseline estimates using alternative estimation methods. The variable of interest is the fiscal rules index (ranging from 0 to 1), and the dependent variable is environmental spending, measured as a share of GDP. Column [1] of Panel A reports the baseline estimates for comparison. Column [2] reports instrumental-variables estimates, where the fiscal rules index is instrumented by its lagged value and the regional average fiscal rules index (contiguity). Columns [3] and [4] extend these IV estimates by adding regional debt-to-GDP and regional growth, respectively. Column [5] presents two-step system GMM estimates, using non-overlapping five-year average sub-periods to reduce short-term noise and account for the dynamic persistence of environmental spending. All regressions include the constant (not reported in the table), Robust standard errors are in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1.

## 6.1 Does the level of environmental spending matter?

Our main findings estimate the average effect of fiscal rules, thereby overlooking potential heterogeneity across the distribution of environmental spending. It is therefore important to ask whether governments tend to reduce such spending when it is at a moderate or high level, or
even when it is already low. To capture this heterogeneity, we employ a quantile regression approach. The intuition behind this technique is that fiscal rules may have varying effects depending on the initial level of environmental spending. The results, reported in Columns [3]–[5] of Table A.5, indicate that the effect of fiscal rules is negative and statistically significant across the entire distribution of environmental spending. However, we observe differences in magnitude: countries with low levels of environmental spending, located in the bottom quartile of the distribution, reduce such spending less than countries with moderate or high levels (50th and 75th percentiles of the distribution). This finding suggests that governments are more inclined to cut environmental spending when it is already at a moderate or high level. Consequently, the initial level of environmental spending plays a crucial role in government decisions regarding the extent of reductions.

## 6.2 Types of fiscal rules

Do the types of fiscal rules matter? Our fiscal rule strength index captures a broad range of information, including the type of fiscal aggregate targeted by the rules. We investigate whether different types of fiscal rules have distinct effects by re-estimating our benchmark specification. As noted in Subsection 3.2, balanced budget rules (BBR) are the most prevalent in our sample and across the study period, followed by debt rules (DR) and expenditure rules (ER), while revenue rules (RR) remain the least developed. BBR set a numerical ceiling or target for the government's budget balance, whereas DR impose explicit limits on the stock of government debt to ensure convergence to a debt target (Schaechter et al., 2012). Under BBR and DR, high debt or deficit levels may increase debt-servicing costs or threaten budget balance, prompting governments to prioritize fiscal stability over environmental programs. ER directly constrain government spending by limiting total, primary, or current expenditures, which may pressure governments to cut discretionary spending across all sectors, including environmental initiatives. Environmental programs may therefore compete with other spending priorities, resulting in underfunding or budget reductions. RR set ceilings or floors on revenues to enhance collection and prevent excessive taxation. While RR are not directly tied to debt control, capping revenues restricts the maximum funds available, potentially reducing resources for environmental projects. Results in Table 5 indicate that only ER and DR significantly reduce environmental spending (Columns [1]–[2]), with qualitatively similar effects.
<table><caption>Table 5: Heterogeneity: Type of fiscal rules</caption><thead><tr><th rowspan="2">Environmental Spending (% of GDP)</th><th colspan="4">Type of Rules</th></tr><tr><th>Expenditure Rules<br>[1]</th><th>Debt Rules<br>[2]</th><th>Balanced Budget Rules<br>[3]</th><th>Revenue Rules<br>[4]</th></tr></thead><tbody><tr><td>Type of Rules</td><td>-0.114**<br>(0.054)</td><td>-0.126*<br>(0.066)</td><td>-0.027<br>(0.062)</td><td>-0.075<br>(0.090)</td></tr><tr><td>Output gap</td><td>0.025<br>(0.019)</td><td>0.027<br>(0.019)</td><td>0.027<br>(0.019)</td><td>0.027<br>(0.019)</td></tr><tr><td>Debt-to-GDP</td><td>0.003***<br>(0.001)</td><td>0.003***<br>(0.001)</td><td>0.003***<br>(0.001)</td><td>0.003***<br>(0.001)</td></tr><tr><td>Trade Openness</td><td>0.001<br>(0.001)</td><td>0.001<br>(0.001)</td><td>0.001<br>(0.001)</td><td>0.001<br>(0.001)</td></tr><tr><td>Age Dependency ratio</td><td>-0.008**<br>(0.004)</td><td>-0.010***<br>(0.003)</td><td>-0.010***<br>(0.004)</td><td>-0.009**<br>(0.004)</td></tr><tr><td>Unemployment Rate</td><td>-0.015***<br>(0.005)</td><td>-0.017***<br>(0.005)</td><td>-0.015***<br>(0.005)</td><td>-0.015***<br>(0.005)</td></tr><tr><td>Democracy</td><td>-0.014<br>(0.035)</td><td>-0.017<br>(0.035)</td><td>-0.012<br>(0.037)</td><td>-0.010<br>(0.035)</td></tr><tr><td>Country FE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Time FE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Observations</td><td>724</td><td>724</td><td>724</td><td>724</td></tr><tr><td>R<sup>2</sup></td><td>0.7586</td><td>0.7589</td><td>0.7573</td><td>0.7575</td></tr></tbody></table>

Notes: This table reports heterogeneity analyses by type of fiscal rule. The dependent variable is environmental spending, measured as a share of GDP. Column [1] reports results using the Expenditure-Rules Index, Column [2] uses the Debt-Rules Index, Column [3] the Balanced Budget-Rules Index, and Column [4] the Revenue-Rules Index. All regressions include the constant (not reported). Robust standard errors are in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1.

## 6.3 Do economic and political environments matter?

This section examines potential sources of heterogeneity in the effect of fiscal rules by considering the following heterogeneity factors: past fiscal conditions, the Kyoto Protocol (KP), environmental regulations, and elections. Countries with sound past fiscal conditions, characterized by low deficits, sustainable debt levels, and prudent fiscal management, may enjoy greater credibility and flexibility in complying with fiscal rules. A strong fiscal track record reduces the need for drastic adjustments when rules are enforced, as governments are already perceived as fiscally responsible. In this context, environmental expenditures are less likely to be treated as expendable, allowing governments to maintain such spending without undermining fiscal sustainability. Hence, sound past fiscal conditions may mitigate the negative effect of fiscal rules on environmental spending by providing governments with more fiscal space and credibility. Another important factor is the Kyoto Protocol (KP), an international environmental agreement committing signatory countries to reduce greenhouse gas emissions and adopt climate-friendly policies. By joining the KP, governments not only signal their willingness to integrate environmental concerns into national policy but also accept external monitoring and accountability.
ity mechanisms. This international commitment strengthens the credibility of environmental policy objectives and raises the reputational and diplomatic costs of reducing environmental spending. Consequently, the KP can mitigate the negative effect of fiscal rules on environmental expenditures, as governments are compelled to allocate resources to meet their international obligations and avoid non-compliance. Furthermore, stringent environmental policies create a binding institutional and regulatory framework that makes it difficult for governments to drastically reduce environmental spending, even under fiscal constraints. These policies not only impose legal obligations for emission abatement and mitigation but also stimulate the adoption of green technologies by altering firms' opportunity costs and encouraging consumers to demand environmentally friendly goods through financial incentive measures (Jaffe et al., 2005; Ahmed, 2020). Although the effectiveness of such policies in promoting innovation remains debated, their presence nonetheless limits the scope for expenditure cuts. Consequently, stringent environmental regulations tend to mitigate the negative impact of fiscal rules on environmental spending, as governments face both domestic and international pressures to sustain environmental investments. Finally, electoral dynamics also play a role. As suggested by the political budget cycle theory, incumbent governments tend to reallocate spending before elections toward politically salient and visible sectors such as social transfers, wages, or subsidies to maximize electoral support (see, among others, Nordhaus, 1975; Rogoff, 1990; Shi and Svensson, 2006; Brender and Drazen, 2013). Environmental protection, by contrast, is a public good whose benefits are neither immediately visible nor easily targeted to specific groups of voters, unlike pork-barrel spending (Lizzeri and Persico, 2001; Boly et al., 2023). This creates a trade-off: the more resources are devoted to politically advantageous projects, the fewer remain for environmental concerns, resulting in their under-provision. Consequently, elections can amplify the adverse effect of fiscal rules on environmental spending, as fiscal constraints interact with short-term political incentives to further reduce allocations to the environment.

The results are reported in Table A.6. Column [4] shows that elections amplify the negative effects of fiscal rules, while Columns [1] to [3] show that past sound fiscal conditions, the Kyoto Protocol, and stringent environmental policies help mitigate these adverse effects, in line with the above discussion.

# 7 Doing better with less? From expenditure cuts to efficiency

There is a follow-up question: Does a reduction in public spending necessarily lead to suboptimal use, that is, low efficiency of resources allocated to the environmental sector? Public expenditure efficiency assesses the performance of the public sector in delivering goods and services
relative to the resources employed. Higher efficiency implies that governments achieve more
with less, that is, they limit resources while maximizing public service provision. The efficiency
of public spending has been a central concern of fiscal policy for decades and remains partic-
ularly relevant today, given rising public deficits exacerbated by events such as the COVID-19
pandemic, the war in Ukraine, and current geopolitical tensions. Empirical evidence from sec-
tors such as education, health, public administration, and infrastructure indicates that many
advanced and developing countries have considerable room to improve expenditure efficiency
(e.g., see Afonso et al., 2005; Apeti et al., 2024; Afonso et al., 2024; Apeti et al., 2025; Bambe
and Ouedraogo, 2025). Accordingly, reductions in environmental spending driven by stricter
fiscal rules may not necessarily result in suboptimal resource use. On the contrary, constrained
resources may incentivize governments to reduce fiscal waste in the environmental sector. This
waste can take two forms: active waste, referring to corruption in public procurement and a
lack of transparency in the management of environmental funds, and passive waste, including
large-scale “white elephant” investments that consume substantial environmental funds without
yielding meaningful gains, as well as waste arising from negligence or cost overruns (Bandiera
et al., 2009). Building on this and Apeti et al. (2025), who show that fiscal rules enhance the
efficiency of public spending in education, health, infrastructure, and administration, this sec-
tion extends our previous analysis by estimating the effect of fiscal rules on the efficiency of
environmental spending.

We adopt a recent methodology for computing environmental expenditure efficiency, that is, a stochastic frontier analysis (SFA) following Kumbhakar et al. (2015). This approach allows for mitigating the usual limitations of nonparametric methods by accounting for measurement errors and unobserved heterogeneity across units (see Apeti et al., 2024). Efficiency is estimated based on the relative distance of inefficient observations from an ideal frontier, defined by the best-performing country-year observations in the sample. We use the Environmental Performance Index (EPI)<fnref n="21" /> as the outcome variable and environmental expenditures as a percentage of GDP as the input. Since environmental performance may not respond instantaneously to spending, we consider two efficiency scores to capture the potential lagged effect of spending on efficiency. *Efficiency 1* is calculated using environmental expenditures in periods *t* and *t* − 1, while *Efficiency 2* is calculated using expenditures in periods *t*, *t* − 1, and *t* − 2. The outcome is

<footnote n="21">²¹This is a composite indicator based on 40 metrics across 11 categories, capturing progress in environmental health, climate mitigation, and ecosystem protection. We do not use the OECD's Environmental Policy Stringency Index (EPSI) for two reasons. First, the EPI is an outcome-based measure, whereas the EPSI assesses the strictness of environmental policies according to criteria such as the stringency of air and water quality standards, the use of economic instruments (taxes, subsidies), the scope of pollution source regulation, and the strength of climate policies. Second, EPI provides more comprehensive coverage of the countries and period in our sample, whereas the EPSI dataset contains a non-negligible number of missing observations.</footnote>
regressed on the inputs to obtain an environmental expenditure efficiency score, which by construction ranges from 0 to 1, with higher values indicating greater efficiency.<fnref n="22" /> As illustrated in Figure A.1, we observe a steadily increasing efficiency of environmental spending over our study period and across our sample. We report an average efficiency index (*Efficiency 1*) of 0.25, indicating substantial room for improvement in the management of environmental expenditures. In other words, for the same level of environmental spending, advanced economies could theoretically increase environmental outcomes by nearly 75%.<fnref n="23" /> By comparison, the efficiency of environmental spending in advanced economies remains considerably lower than that observed in other sectors (education, health, infrastructure, and administration) as identified by Apeti et al. (2024), which averages around 0.71.

The results presented in Columns [1]-[2] of Table 6, where the two efficiency indicators are considered respectively, show a positive and statistically significant effect of fiscal rules on the efficiency of environmental spending. By multiplying the estimated coefficient in the first column by the mean value of the fiscal rules index, we find that these rules increase the efficiency of environmental spending by approximately 0.023 units (or 2.3 percentage points), which represents about 9% of the sample mean efficiency. The results remain robust for the second efficiency score, reported in Column [2]. Finally, in Columns [3]-[4], we replicate our estimation using the IV approach instead of OLS, as in the first two columns. The IV estimates are slightly larger than the OLS estimates but remain qualitatively consistent, confirming the robustness of our findings. These results support our previous hypothesis: while fiscal rules exert downward pressure on environmental spending, they also appear to foster more efficient management of these expenditures.

$$Y_{it} = \alpha_0 + f(X_{it}; \beta) + v_{it} - u_{it} - \eta_i, \quad (3)$$

where $v_{it} \sim N(0, \sigma^2)$ captures noise, $u_{it} \sim N^+(0, \sigma^2)$ is time-varying inefficiency, and $\eta_i$ is persistent inefficiency. Estimation proceeds in three steps. First, we estimate $\beta$ and the predicted inefficiencies using a random-effects regression. Second, persistent technical inefficiency (PTE) is computed from $\eta_i$, with PTE = $\exp(-\eta_i)$. Third, residual technical inefficiency (RTE) is obtained from model residuals, and overall technical efficiency (OTE) is calculated as OTE = PTE $\times$ RTE, following Jondrow et al. (1982). This procedure disentangles time-persistent and residual inefficiencies while ignoring sampling variability in $\beta$ and $\eta_i$.

<footnote n="22">²²Let $Y_{it}$ denote a measure of environmental output, proxied by the Environmental Performance Index (EPI). in country $i$ at time $t$, and $X_{it}$ the input, i.e., environmental expenditures as a percentage of GDP. The model is specified as follows:</footnote>

<footnote n="23">²³The results are largely similar for *Efficiency 2*.</footnote>
<table><caption>Table 6: Fiscal rules and environmental spending efficiency</caption><thead><tr><th rowspan="2">Environmental Spending Efficiency</th><th colspan="2">OLS Estimates</th><th colspan="2">IV Estimates</th></tr><tr><th>Efficiency 1<br>[1]</th><th>Efficiency 2<br>[2]</th><th>Efficiency 1<br>[3]</th><th>Efficiency 2<br>[4]</th></tr></thead><tbody><tr><td>Fiscal Rules</td><td>0.047***<br>(0.016)</td><td>0.042**<br>(0.018)</td><td>0.091***<br>(0.018)</td><td>0.096***<br>(0.021)</td></tr><tr><td>Output gap</td><td>0.002<br>(0.008)</td><td>0.000<br>(0.009)</td><td>0.005<br>(0.008)</td><td>0.004<br>(0.008)</td></tr><tr><td>Debt-to-GDP</td><td>-0.001**<br>(0.000)</td><td>-0.001**<br>(0.000)</td><td>-0.001***<br>(0.000)</td><td>-0.001***<br>(0.000)</td></tr><tr><td>Trade Openness</td><td>-0.001<br>(0.001)</td><td>-0.000<br>(0.001)</td><td>-0.000<br>(0.000)</td><td>-0.000<br>(0.001)</td></tr><tr><td>Age Dependency ratio</td><td>0.003**<br>(0.002)</td><td>0.003*<br>(0.002)</td><td>0.003**<br>(0.002)</td><td>0.003*<br>(0.002)</td></tr><tr><td>Unemployment Rate</td><td>0.005**<br>(0.002)</td><td>0.004*<br>(0.002)</td><td>0.005**<br>(0.002)</td><td>0.005**<br>(0.002)</td></tr><tr><td>Democracy</td><td>0.057***<br>(0.012)</td><td>0.055***<br>(0.014)</td><td>0.059***<br>(0.012)</td><td>0.058***<br>(0.013)</td></tr><tr><td>Country FE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Time FE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Kleinberg-PaaprRk test</td><td></td><td></td><td>141.66</td><td>88.53</td></tr><tr><td>Stock-Wright p-value</td><td></td><td></td><td>0.00</td><td>0.00</td></tr><tr><td>Hansen. p-val.</td><td></td><td></td><td>0.76</td><td>0.93</td></tr><tr><td>Observations</td><td>454</td><td>411</td><td>454</td><td>411</td></tr><tr><td>R<sup>2</sup></td><td>0.5643</td><td>0.5465</td><td>0.4668</td><td>0.4467</td></tr><tr><th colspan="5" style="text-align: center;">First-Stage</th></tr><tr><td>Fiscal Rules</td><td></td><td></td><td></td><td></td></tr><tr><td>Lag Fiscal Rules</td><td></td><td></td><td>0.723***<br>(0.066)</td><td>0.702***<br>(0.071)</td></tr><tr><td>Contiguity</td><td></td><td></td><td>0.491**<br>(0.239)</td><td>0.634*<br>(0.355)</td></tr></tbody></table>

**Notes:** This table reports the results of the effect of fiscal rules on the efficiency of environmental spending. The efficiency scores and the fiscal rules index range between 0 and 1. To capture the potential lagged effect of spending on efficiency, *Efficiency 1* is calculated using environmental expenditures in periods *t* and *t* − 1, while *Efficiency 2* is calculated using expenditures in periods *t* and *t* − 2. All regressions include the constant (not reported). Robust standard errors are in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1.
# 8 Conclusion and discussion

The urgency of addressing climate challenges to limit global warming to 1.5 °C requires rapid and substantial reductions in emissions, as well as significant investment in the environmental sector to support the green transition. This situation poses a dual challenge for governments in advanced economies: maintaining fiscal discipline while financing initiatives aimed at combatting climate change. While such investments can generate positive spillover effects, including job creation, the development of new technologies, and support for economic growth, they may also conflict with fiscal sustainability objectives, particularly in contexts where many countries struggle to reduce budget deficits. This challenge is even more pronounced in countries that have adopted strict fiscal rules designed to limit excessive spending and deficits. In this context, this paper investigates whether fiscal rules constrain environmental expenditure, employing a panel of 31 advanced economies over the period 1995–2021.

Our OLS estimates indicate that strengthening fiscal rules reduces environmental expenditures, and the effect is statistically and economically significant. Our main findings remain robust when we include a series of additional controls, use alternative subsamples and subperiods, or address potential endogeneity of fiscal rules using instrumental variable methods and the system GMM estimator. We also highlight several sources of heterogeneity in the effect of fiscal rules: the reduction in environmental expenditures is more pronounced when initial spending levels are moderate or high; only expenditure and debt rules significantly decrease environmental spending; and fiscal responsibility laws and electoral periods tend to amplify the negative effects of fiscal rules. Conversely, strong past fiscal conditions, the Kyoto Protocol, and stringent environmental policies mitigate these adverse impacts. Finally, we extend our analysis by examining the effect of fiscal rules on the efficiency of environmental spending. The results indicate that, although stronger fiscal rules exert a negative impact on the level of spending, they tend to enhance its efficiency, suggesting a more optimal allocation of environmental resources under fiscal rule frameworks.

Our findings carry significant implications for public policy. While fiscal rules tend to constrain environmental spending, they also appear to promote greater efficiency in its management, encouraging governments to allocate resources more productively and minimize waste. This suggests that under fiscal rule frameworks, limited resources are directed toward the most impactful environmental initiatives, enabling governments to achieve more with less and maximize the effectiveness of environmental expenditures. These findings are consistent with existing literature showing that fiscal rules or stringent rules are associated with lower total public spending (Potrafke, 2025) and better management of overall public spending based on sectors
such as education, health, public administration, and infrastructure (Apeti et al., 2025), leading to better macroeconomic performance such as higher growth and productivity (Afonso and Jalles, 2013; Castro, 2011; Ash et al., 2025; Chrysanthakopoulos et al., 2025; Potrafke, 2025).

Preserving existing rules is vital in the sense that it does not lead to a cascade of exemp-
tions, making the rule a mere ornament that ultimately amounts to nothing. Indeed, the ease
with which some expenditure can be excluded under fiscal rules, as is currently the case with
the environment, could trigger discussions about other arrangements using the same arguments
for pressing needs such as defense and pensions, for example. A more assertive position in our
analysis is that, before implementing an exemption policy, effectiveness analyses should be pro-
vided to prevent misleading exclusions that create a feeling of endless flexibility and rewriting
of the fiscal rule, weakening its framework and credibility. In other words, we must learn to
live with the rules and avoid considering exemptions at the slightest opportunity. When asked
what the ideal level of environmental spending might reasonably expect to bring benefits to
the environment, the answer is, as with total government spending, it depends. Improving the
quality of environmental spending shows that what we are observing in level of environmen-
tal spending is a discipline effect for rigorous management of such spending to achieve better
results, since environmental spending can be subject to manipulation and moral hazard by gov-
ernments. This provides a framework in which the environment is protected through prudent
financial management without excessive debt, which can create fiscal instability and challenge
the fiscal rules framework. Although the decision to exclude environmental spending from bud-
getary rules is the responsibility of each country, it does not appear to be a pressing objective,
as these rules do not seem to reduce the impact of government intervention in the environment
but, rather, improve its effectiveness. What seems to emerge from this is that environmental
spending should at least be protected within a framework of fiscal rules with the introduction
of a green spending rule, for instance, that sets spending limits as in the case of standard public
spending, with an efficiency criterion, since exclusion could give rise to excessive spending and
reckless behavior by greedy governments that would exploit the gap between immediate action,
i.e., the implementation of spending, and the effects, which are generally medium- or long-term
improvements in environmental quality.

However, our analysis has some limitations. The IMF Climate Change Indicators do not
distinguish between current environmental expenditures and environmental investment. Con-
sequently, we are unable to assess potential compositional effects within total environmental
spending. Future research should explore how governments operating under fiscal rules allo-
cate resources between current expenditures and environmental investments. Nonetheless, we
believe that our study provides valuable insights into the ongoing debate on fiscal rules and
green investment. Moving forward, we believe that examining the determinants of environmen-
tal spending, along with a comprehensive assessment of the efficiency of such expenditures,
constitutes a promising avenue for future research in this area.
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Online Appendix

Fiscal discipline vs. green priorities: Do fiscal rules shape environmental spending?
# 1 Sample composition and descriptive statistics

<table><caption>Table A.1: Sample</caption><tr><td>Australia</td><td>Japan</td><td>Austria</td><td>Latvia</td><td>Belgium</td></tr><tr><td>Lithuania</td><td>Canada</td><td>Luxembourg</td><td>China, P.R.: Hong Kong</td><td>Malta</td></tr><tr><td>Cyprus</td><td>Netherlands, The</td><td>Czech Rep.</td><td>Norway</td><td>Denmark</td></tr><tr><td>Portugal</td><td>Estonia, Rep. of</td><td>Singapore</td><td>Finland</td><td>Slovak Rep.</td></tr><tr><td>France</td><td>Slovenia, Rep. of</td><td>Germany</td><td>Spain</td><td>Greece</td></tr><tr><td>Sweden</td><td>Iceland</td><td>Switzerland</td><td>Ireland</td><td>United Kingdom</td></tr><tr><td>Italy</td><td></td><td></td><td></td><td></td></tr></table>

<table><caption>Table A.2: Summary Statistics</caption><thead><tr><th></th><th>Obs</th><th>Mean</th><th>Standard deviation</th><th>Minimum</th><th>Maximum</th></tr></thead><tbody><tr><td>Environmental Spending (% of GDP)</td><td>724</td><td>0.7319</td><td>0.3441</td><td>0</td><td>1.9146</td></tr><tr><td>Fiscal Rules</td><td>724</td><td>0.5151</td><td>0.4215</td><td>0</td><td>1</td></tr><tr><td>Output gap</td><td>724</td><td>0.4931</td><td>0.5003</td><td>0</td><td>1</td></tr><tr><td>Debt-to-GDP</td><td>724</td><td>63.8039</td><td>42.9584</td><td>0.0520</td><td>262.4920</td></tr><tr><td>Trade Openness</td><td>724</td><td>1.3028</td><td>9.3011</td><td>-79.1339</td><td>56.3730</td></tr><tr><td>Age Dependency ratio</td><td>724</td><td>49.5035</td><td>6.1890</td><td>26.8735</td><td>70.2570</td></tr><tr><td>Unemployment Rate</td><td>724</td><td>7.1588</td><td>3.0192</td><td>3.5700</td><td>13.1090</td></tr><tr><td>Democracy</td><td>724</td><td>5.5677</td><td>0.8814</td><td>2</td><td>6</td></tr></tbody></table>

<table><caption>Table A.3: Unit root tests</caption><thead><tr><th rowspan="2"></th><th colspan="3">Augmented Dickey-Fuller test</th><th colspan="3">Im-Pesaran-Shin test</th></tr><tr><th>Z-Statistic</th><th>Z-P-value</th><th>Integration Order</th><th>Wtbar-Statistic</th><th>Wtbar-P-value</th><th>Integration Order</th></tr><tr><th></th><th>[1]</th><th>[2]</th><th>[3]</th><th>[4]</th><th>[5]</th><th>[6]</th></tr></thead><tbody><tr><td>Environmental Spending (% of GDP)</td><td>-2.121</td><td>0.017</td><td>I(0)</td><td>-2.955</td><td>0.002</td><td>I(0)</td></tr><tr><td>Fiscal Rules</td><td>-3.150</td><td>0.001</td><td>I(0)</td><td>-1.915</td><td>0.028</td><td>I(0)</td></tr><tr><td>Output gap</td><td>-6.211</td><td>0.000</td><td>I(0)</td><td>-8.561</td><td>0.000</td><td>I(0)</td></tr><tr><td>Debt-to-GDP ratio</td><td>-1.828</td><td>0.034</td><td>I(0)</td><td>-1.891</td><td>0.029</td><td>I(0)</td></tr><tr><td>Trade Openness</td><td>-0.353</td><td>0.361</td><td>I(1)</td><td>-1.225</td><td>0.110</td><td>I(1)</td></tr><tr><td>Unemployment Rate</td><td>-2.657</td><td>0.004</td><td>I(0)</td><td>-2.557</td><td>0.005</td><td>I(0)</td></tr><tr><td>Age Dependency ratio</td><td>-6.522</td><td>0.000</td><td>I(0)</td><td>-5.974</td><td>0.000</td><td>I(0)</td></tr><tr><td>Democracy</td><td>-5.503</td><td>0.000</td><td>I(0)</td><td>-5.242</td><td>0.000</td><td>I(0)</td></tr><tr><td>Trade Openness</td><td>-11.079</td><td>0.000</td><td>I(1)</td><td>-15.634</td><td>0.000</td><td>I(1)</td></tr></tbody></table>
<figure><img src="image_7.png" /><figcaption>Figure A.1: Average trends in environmental spending efficiency from 1995 to 2021.</figcaption></figure>

Note: *Efficiency 1* is calculated using environmental expenditures in periods *t* and *t* − 1, while *Efficiency 2* is calculated using expenditures in periods *t* and *t* − 2.

## 2 Robustness checks and heterogeneity

<table><caption>Table A.4: Robustness check: Alternative measures</caption><thead><tr><th rowspan="2">Env. Spending (% of GDP)</th><th>Baseline</th><th>Env. Spending (% of Total Exp.)</th><th>Fiscal Rules (without flexibility)</th></tr><tr><th>[1]</th><th>[2]</th><th>[3]</th></tr></thead><tbody><tr><td>Fiscal Rules</td><td>-0.130***<br>(0.037)</td><td>-0.263***<br>(0.087)</td><td></td></tr><tr><td>Fiscal Rules (without flexibility)</td><td></td><td></td><td>-0.128***<br>(0.034)</td></tr><tr><td>Output gap</td><td>0.024<br>(0.019)</td><td>0.022<br>(0.045)</td><td>0.024<br>(0.019)</td></tr><tr><td>Debt-to-GDP</td><td>0.003***<br>(0.001)</td><td>0.006***<br>(0.002)</td><td>0.003***<br>(0.001)</td></tr><tr><td>Trade Openness</td><td>0.001<br>(0.001)</td><td>0.000<br>(0.003)</td><td>0.001<br>(0.001)</td></tr><tr><td>Age Dependency ratio</td><td>-0.010***<br>(0.004)</td><td>-0.041***<br>(0.009)</td><td>-0.011***<br>(0.004)</td></tr><tr><td>Unemployment Rate</td><td>-0.016***<br>(0.005)</td><td>-0.077***<br>(0.013)</td><td>-0.017***<br>(0.005)</td></tr><tr><td>Democracy</td><td>-0.014<br>(0.035)</td><td>-0.086<br>(0.066)</td><td>-0.018<br>(0.034)</td></tr><tr><td>Country FE</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Time FE</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Observations</td><td>724</td><td>660</td><td>724</td></tr><tr><td>R<sup>2</sup></td><td>0.7613</td><td>0.7979</td><td>0.7619</td></tr></tbody></table>

Notes: This table reports robustness checks using alternative measures of both the dependent variable and the fiscal rules index. The dependent variable is environmental spending, measured as a share of GDP. Column [1] reproduces the baseline estimates for comparison. Column [2] redefines the dependent variable as environmental spending relative to total government expenditure, while Column [3] computes the fiscal rules index excluding the flexibility feature. All regressions include a constant term (not reported). Robust standard errors are in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1.
<figure><img src="image_8.png" /><figcaption>Figure A.2: Robustness check dropping one country at a time.</figcaption></figure>

**Notes:** The blue line plots the estimated effect of fiscal rules, while the shaded gray area represents the 99% confidence intervals.

<table><caption>Table A.5: Heterogeneity: Composition effects and Quantile regressions</caption><thead><tr><th></th><th>First Quartile (25%)</th><th>Second Quartile (50%)</th><th>Third Quartile (75%)</th></tr><tr><th></th><th>[1]</th><th>[2]</th><th>[3]</th></tr></thead><tbody><tr><td>Fiscal Rules</td><td>-0.105**<br>(0.052)</td><td>-0.222***<br>(0.046)</td><td>-0.201***<br>(0.054)</td></tr><tr><td>Output gap</td><td>0.010<br>(0.016)</td><td>0.002<br>(0.016)</td><td>0.006<br>(0.019)</td></tr><tr><td>Debt-to-GDP</td><td>0.002***<br>(0.001)</td><td>0.002***<br>(0.001)</td><td>0.002**<br>(0.001)</td></tr><tr><td>Trade Openness</td><td>0.001<br>(0.001)</td><td>0.001<br>(0.001)</td><td>0.001<br>(0.002)</td></tr><tr><td>Age Dependency ratio</td><td>-0.011***<br>(0.003)</td><td>-0.015***<br>(0.003)</td><td>-0.011***<br>(0.004)</td></tr><tr><td>Unemployment Rate</td><td>-0.021***<br>(0.005)</td><td>-0.020***<br>(0.005)</td><td>-0.010<br>(0.007)</td></tr><tr><td>Democracy</td><td>-0.006<br>(0.026)</td><td>0.015<br>(0.036)</td><td>0.022<br>(0.042)</td></tr><tr><td>Country FE</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Time FE</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Observations</td><td>724</td><td>724</td><td>724</td></tr></tbody></table>

**Notes:** This table presents heterogeneity analyses by outcome. Columns [1] to [3] present quantile estimates at the first, second and third quartiles, respectively. All regressions include a constant term (not reported). Robust standard errors are in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1.
<table><caption>Table A.6: Heterogeneity: The role of economic, environmental, and political factors</caption><thead><tr><th>Environmental Spending (% of GDP)</th><th>[1]</th><th>[2]</th><th>[3]</th><th>[4]</th></tr></thead><tbody><tr><td>Fiscal Rules</td><td>-0.275***<br>(0.039)</td><td>-0.197***<br>(0.048)</td><td>-0.392***<br>(0.054)</td><td>-0.121***<br>(0.038)</td></tr><tr><td>Fiscal Rules × Past Fiscal Conditions</td><td>0.265***<br>(0.038)</td><td></td><td></td><td></td></tr><tr><td>Fiscal Rules × Kyoto Protocol</td><td></td><td>0.100*<br>(0.057)</td><td></td><td></td></tr><tr><td>Fiscal Rules × Stringency Index</td><td></td><td></td><td>0.040***<br>(0.011)</td><td></td></tr><tr><td>Fiscal Rules × Elections</td><td></td><td></td><td></td><td>-0.176**<br>(0.085)</td></tr><tr><td>Country FE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Time FE</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Observations</td><td>662</td><td>724</td><td>501</td><td>724</td></tr><tr><td>R<sup>2</sup></td><td>0.8032</td><td>0.7621</td><td>0.7576</td><td>0.7626</td></tr></tbody></table>

Notes: Fiscal responsibility laws, past fiscal conditions, the Kyoto Protocol, and elections are captured using binary variables. Past fiscal conditions are measured by a dummy equal to 1 if the past debt (lagged value of debt-to-GDP ratio) is above its historical average for the country, 0 otherwise. All controls from the baseline model, as well as the heterogeneity variables in additive form, are included but not reported due to space constraints. All regressions include the constant (not reported). Robust standard errors are in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1.
# 3 Description of variables and data sources

<table><caption>Table A.7: Description of Variables and Data Sources (1/3)</caption><thead><tr><th>Variable</th><th>Definition</th><th>Source</th></tr></thead><tbody><tr><td colspan="3"><strong>Main variables</strong></td></tr><tr><td>Environmental Spending (% of GDP)</td><td>Environmental protection expenditure as share of GDP.</td><td>Climate Change Indicators, IMF</td></tr><tr><td>Fiscal Rules Strength</td><td>Index ranging from 0 to 1. Higher values indicate stronger fiscal rules.</td><td>Authors from the IMF' Fiscal Rules Dataset</td></tr><tr><td colspan="3"><strong>Baseline Controls</strong></td></tr><tr><td>Output gap</td><td>Annual gap between the actual value and the potential value of the GDP.</td><td>Authors' from WDI, World Bank</td></tr><tr><td>Trade Openness</td><td>Trade is the sum of exports and imports of goods and services measured as a share of GDP.</td><td>WDI, World Bank</td></tr><tr><td>Age dependency</td><td>Age dependency ratio (% of working-age population). It is the ratio of dependents (younger than 15 or older than 64) to the working-age population (15–64).</td><td></td></tr><tr><td>Unemployment rate</td><td>Unemployment rate (% of total labor force).</td><td></td></tr><tr><td>Debt-to-GDP ratio</td><td>Government total public debt as a share of GDP.</td><td>Kose et al. (2022)</td></tr><tr><td>Democracy</td><td>A measure of government responsiveness to its people, based on regime types (alternating democracies, dominated democracies, de facto or de jure single-party governments, autarchies). Index ranges from 0 to 6. High scores correspond to alternating democracies, low scores to autarchies.</td><td>ICRG</td></tr></tbody></table>
<table><caption>Table A.8: Description of Variables and Data Sources (2/3)</caption><thead><tr><th>Variable</th><th>Definition</th><th>Source</th></tr></thead><tbody><tr><td colspan="3"><strong>Additional Controls</strong></td></tr><tr><td>Government Fragmentation</td><td>Probability that two randomly chosen deputies from among the governing parties represent different parties. Ranges from 0 to 1.</td><td>Authors' coding</td></tr><tr><td>Government Ideology</td><td>Equals -1 for left-wing governments, 0 for centrist governments, and 1 for right-wing governments.</td><td>DPI2020, Database of Political Institutions</td></tr><tr><td>Freedom of Media</td><td>Press freedom index across three dimensions: legal constraints, political influence, and economic environment (ownership, transparency, costs, barriers, subsidies). Original index ranges from 0 (full freedom) to 100 (no freedom) and is inverted so that higher values indicate greater freedom.</td><td>Freedom House</td></tr><tr><td>Financial Development</td><td>Composite index capturing depth (size and liquidity of markets), access (ability to access financial services), and efficiency (low-cost provision). Ranges from 0 to 1.</td><td>Financial Development Index Database, IMF</td></tr><tr><td>Environmental Taxes</td><td>Environmental tax revenues as a share of GDP.</td><td>Climate Change Indicators, IMF</td></tr><tr><td>Urban Population</td><td>Urban population as a percentage of total population.</td><td>WDI, World Bank</td></tr><tr><td>Population Size</td><td>Total population (log).</td><td></td></tr><tr><td>Share of Young People (0–14)</td><td>Population aged 0–14 as a percentage of total population.</td><td></td></tr><tr><td>Share of Elderly People (65+)</td><td>Population aged 65 and above as a percentage of total population.</td><td></td></tr><tr><td colspan="3"><strong>Sample Dependence</strong></td></tr><tr><td>EU Countries</td><td>Dummy equal to 1 for EU members, 0 otherwise.</td><td>Authors' calculations</td></tr><tr><td>GFC (2008–2009) Crisis</td><td>Dummy equal to 1 in 2008–2009, 0 otherwise.</td><td>Authors' calculations</td></tr><tr><td>Global Crises</td><td>Dummy equal to 1 if a country experiences a banking, currency, or debt crisis in year t, 0 otherwise.</td><td>SBC Database, Nguyen et al. (2022)</td></tr><tr><td>Kyoto Objectives</td><td>Dummy equal to 1 for Kyoto Protocol's first commitment period (2008–2012), 0 otherwise.</td><td>Authors' calculations</td></tr><tr><td>Paris Agreement</td><td>Dummy equal to 1 for post-Paris Agreement period (2016–2021), 0 otherwise.</td><td>Authors' calculations</td></tr><tr><td>Post Covid-19</td><td>Dummy equal to 1 for the post-Covid-19 period (2020–2021), 0 otherwise.</td><td>Authors' calculations</td></tr><tr><td>Breaking Rules Countries</td><td>Dummy equal to 1 for Canada or Iceland, 0 otherwise.</td><td>Authors' calculations</td></tr></tbody></table>
<table><caption>Table A.9: Description of Variables and Data Sources (3/3)</caption><thead><tr><th>Variable</th><th>Definition</th><th>Source</th></tr></thead><tbody><tr><td colspan="3"><strong>Alternative Measures</strong></td></tr><tr><td>Environmental Spending (% of total spending)</td><td>Environmental protection expenditure as a share of total government expenditure.</td><td>Authors' calculations</td></tr><tr><td>Fiscal Rules Strength (without flexibility)</td><td>Index measuring the strength of fiscal rules, excluding the flexibility feature of the original indicator. Ranges from 0 to 1.</td><td>Authors from Fiscal Rules Dataset, IMF</td></tr><tr><td colspan="3"><strong>Heterogeneity Analysis</strong></td></tr><tr><td>Expenditure Rules</td><td>Strength of expenditure rules, ranging from 0 to 1.</td><td>Authors from Fiscal Rules Dataset, IMF</td></tr><tr><td>Debt Rules</td><td>Strength of debt rules, ranging from 0 to 1.</td><td>Authors' calculations</td></tr><tr><td>Balanced Budget Rules</td><td>Strength of balanced budget or deficit rules, ranging from 0 to 1.</td><td>Authors' calculations</td></tr><tr><td>Revenue Rules</td><td>Strength of revenue rules, ranging from 0 to 1.</td><td>Authors' calculations</td></tr><tr><td>Fiscal Responsibility Law</td><td>Dummy equal to 1 if a country has a fiscal responsibility law (FRL), 0 otherwise.</td><td>Authors' calculations</td></tr><tr><td>Past Sound Fiscal Conditions</td><td>Dummy equal to 1 if the past debt is above its historical average for the country, 0 otherwise.</td><td>Authors from Kose et al. (2022)</td></tr><tr><td>Kyoto Protocol</td><td>Dummy equal to 1 from 2005 onwards (when the Protocol entered into force), 0 otherwise.</td><td>Authors' calculations</td></tr><tr><td>Environmental Policy Stringency Index</td><td>Index capturing the degree to which 13 environmental policy instruments put an explicit or implicit price on polluting or environmentally harmful behaviour. Ranges from 0 (not stringent) to 6 (highest stringency).</td><td>OECD</td></tr><tr><td>Elections</td><td>Election timing variable from Franzese Jr (2000). Defined as <sup>M</sup>/<sub>12</sub> in an election year and <sup>12-M</sup>/<sub>12</sub> in the pre-election year, where M denotes the election month.</td><td>Authors from NELDA Dataset</td></tr></tbody></table>