Purpose This review characterizes the governance challenges arising from the potential deployment of solar geoengineering. The authors survey existing theoretical models that analyze the strategic incentives such technologies generate. In particular, this study examines the conditions under which the “free-driver problem”, where a single nation or small group of nations initiates solar geoengineering without the consent of the international community, might be avoided or mitigated and explores the implications for international climate governance when mitigation and solar geoengineering policies interact. Design/methodology/approach The authors focus on a subset of theoretical contributions and examine them in depth to clarify the mechanisms underlying free-driving and to explore potential solutions. Findings Overall, the literature suggests that governance mechanisms such as voting rules, transfer schemes and self-enforcing agreements can, in principle, mitigate free-driving and support stable cooperation on solar geoengineering. Theoretical models indicate that geoengineering may either undermine or strengthen incentives for mitigation and international cooperation, and under specific conditions can even facilitate the formation of large climate agreements avoiding its deployment. Originality/value By bringing together insights from public good, coalition formation and game theoretical literature, this review highlights the conditions under which cooperation can emerge and identifies key gaps for future research on the governance of solar geoengineering.
This paper contains a synthesis of the pros and cons of four alternative approaches to several aspects of the economics of species preservation, some of which dual-purpose, being liable to be simultaneously interpreted also in terms of area preservation. The first consists of a comparative assessment of preservation vs economic development. The second relies on a microeconomic approach to the analysis of area preservation under binding budget constraints. The third is borrowed from the economic policy debate about the suboptimality of the private provision of public goods, to show that the preservation of species or natural areas may rely on a time consistent tax policy designed by the government. The fourth tackles explicitly the problem of the perpetual survival of a species defined as a common good, ensured by an optimally regulated access. All of these approaches, although apparently treating particular aspects, could become an integral part of the main debate on the preservation of species and natural areas, as they offer several effective responses to problems intrinsically connected with the latter.
Transitioning to clean energy is necessary to meet the climate targets of the Paris Agreement. Accelerating decarbonisation requires improving energy efficiency and making large-scale green energy investments, inter alia in residential homes. Household energy behaviours and investment decisions are mostly suboptimal as individuals often face significant psychological barriers and are subjected to cognitive biases. Consequently, one-size-fits-all interventions, that are aimed at fostering green energy behaviours, lead to information overload and rebound effects, thereby being inefficient. A growing proposition in behavioural sciences is to personalise the delivery of behavioural interventions (BIs) to facilitate the uptake of energy-efficient behaviours. This is typically done, for example, by tailoring different BIs to individuals to overcome individual biases in the adoption of green appliances and renovations. Nonetheless, there is no clear know-how to use different statistical methods to tailor BIs. While researchers rely on various techniques to customise BIs for specific groups, this segmentation process lacks coherence overall. In this paper, we systematically review and sort the literature on statistical classification and clustering models, including machine learning methods, that have been used to optimise BIs for improving residential energy efficiency. Our review provides a holistic overview of these different methods, along with recommendations for practitioners to use them. It further highlights the role that machine learning algorithms can play in automating BIs, for example, by using sophisticated data analysis and pattern recognition to identify intricate relationships between decision-making factors. These insights can lead to highly optimised personalised strategies for increased energy efficiency.
In this paper, we survey recent econometric contributions to measure the relationship between economic activity and climate change. Due to the critical relevance of these effects for the well-being of future generations, there is an explosion of publications devoted to measuring this relationship and its main channels. The relation between economic activity and climate change is complex with the possibility of causality running in both directions. Starting from economic activity, the channels that relate economic activity and climate change are energy consumption and the consequent pollution. Hence, we first describe the main econometric contributions about the interactions between economic activity and energy consumption, moving then to describing the contributions on the interactions between economic activity and pollution. Finally, we look at the main results on the relationship between climate change and economic activity. An important consequence of climate change is the increasing occurrence of extreme weather phenomena. Therefore, we also survey contributions on the economic effects of catastrophic climate phenomena.
In recent years, the importance of Environmental, Social, and Governance (ESG) factors in shaping business sustain-ability and performance has gained significant attention. ESG is not only a measure of a company's social responsi-bility but also a crucial determinant of its long-term success. Despite the widespread recognition of ESG's importance, its impact on firm performance remains a subject of debate. In this paper, we systematically review and analyze the complex relationship between ESG and firm performance. We first introduce major ESG rating methods and agencies, followed by a synthesis of the empirical evidence on the rela-tionship between ESG and corporate financial performance, with particular emphasis on the conflicting and inconclusive findings in the literature. Subsequently, we examine the mechanisms through which ESG practices influence firm performance, focusing on legitimacy, reputation, and corpo-rate management as key pathways. Through this analysis, we aim to provide insights into how ESG can drive sus-tainable development and influence firm performance in the long run. Our study contributes to the ongoing academic discussions and practical advancements in the field of ESG by providing a structured approach to understanding the complex and multidimensional relationship between ESG and corporate performance and identifying future research directions.
Modern environmental health science has revealed the complex, nonlinear, and heterogeneous nature of air pollution's health impacts. However, the economic frameworks used for policy evaluation often rely on static, spatially uniform assumptions that fail to capture these critical realities. This paper argues that to design effective and equitable air quality management strategies for a new phase of governance challenges, a more dynamic and nuanced economic framework is essential. We synthesize recent advances from both fields to develop an integrated analytical framework built on two core new approaches. First, we propose a dual-track Benefit-Cost Analysis (BCA) that distinguishes between long-term and short-term objectives. Second, we apply this framework to a three-phase prioritization strategy based on pollution levels, demonstrating how policy priorities shift across different stages. We further examine how this framework can incorporate broader goals like climate change mitigation and social equity. Ultimately, this paper presents a context-specific approach and a more realistic framework to guide efficient and equitable air-quality policies that safeguard human health while aligning with broader climate goals.
This paper provides a historical overview of the United ence of the Parties meetings and reviews the major outcomes of the meetings up to the most recent, which took place in Dubai. We describe how climate negotiations, agreements and policies have evolved, summarise the main points reached, and highlight the key concerns of low-income countries relating to distribution and fairness - a key obstacle for many countries. We then discuss the progress made to date to address fairness issues and to reduce greenhouse gas emissions. In particular, we discuss the Just Energy Transi- tion Partnerships and the loss and damage initiatives, which provide funds to developing countries to finance the switch from fossil fuels to renewable energy and to compensate for climate damages, respectively.
The advancements in technologies such as location tracking, big data analytics, image processing, online retailing, and cloud computing, alongside innovations in artificial intelligence research, have propelled the adoption of machine learning (ML) models. These models surpass conventional econometric approaches in detecting patterns in complex, high-dimensional data, thereby enhancing predictive accuracy. In environmental economics, ML is increasingly utilized to analyze datasets from sensors, satellites, and texts, improving predictions, imputing missing values, uncovering counterfactual patterns for causal analysis, and gauging public sentiment via social media. We first present an overview of supervised, unsupervised, and causal ML models, discussing their applications so far in environmental economics, and evaluate their advantages and limitations. We then show that ML models have been used in four broad topics: (1) environmental policy evaluation, (2) environment and resource market analysis, (3) prediction of environmental outcomes, and (4) media analysis for environmental issues. We provide examples and report the gain from ML over conventional models to show the potentials of these methods in analyzing various topics. The review serves as a starting point for researchers seeking to explore the applications of ML in environmental economics.
This paper provides a review of the economics of tipping points in natural resources and climate change economics, examining recent advances in theoretical modeling and controlled experiments. We begin with the non-convexity models as a theoretical foundation, provide a typology of the resulting deterministic tipping points, and discuss their implications for management. Then, we focus on hazard rate modeling for optimal resource management with stochastic and unknown tipping points. We discuss Bayesian learning, strategic behavior among agents, and the advancement in integrated assessment modeling with multiple and interacting tipping points. Finally, we examine the new contributions of experimental economics to understanding decision-making processes in the presence of tipping points. The paper concludes by highlighting the main advances in the literature and outlining future research directions, ultimately aiming to encourage further investigation and the development of innovative tools to address global challenges.
This article confronts strands of thought in environmental ethics with environmental economics. Three approaches in ethics are addressed: that pointing to the rights of individual natural entities, the holistic approach, and the relational approach of Human and Nature. They are confronted with three strands of thought in environmental economics: the welfare economics approach, the biophysical-centric approach, the relational economic approach. The confrontation of ethics and environmental economics allow us to draw some insights both for academic research and environmental policy.
Integrating environmental, social, and governance (ESG) considerations into investment decisions has become increasingly popular. In 2020, global assets under management incorporating ESG factors reached $35 trillion, a 55% increase from 2016. Given its growing relevance within the financial and academic community, this paper analyzes the historical evolution of ESG Investing and its most recent developments. It describes the extent to which ESG considerations affect financial performance and outlines the main strategies used by investors when incorporating ESG factors into their financial decisions. This study also introduces Islamic finance, and sheds a light on the main differences, but also similarities, with ESG Investing through a novel comparative approach. Finally, we offer a summary of the main research findings on the performance of socially aware mutual funds through a comprehensive literature review of more than 40 papers (1993-2022), which we hope it will be of practical assistance to scholars and industry professionals looking to develop or refine their investment strategies.
In this article, I explain socially enforced norms mostly from an economist's perspective, how they emerge and how they diffuse through society. I then investigate the particular role that social norms play for the environment, looking at both the theoretical literature as well as the empirical results. Following that I discuss the reasons for which governmental intervention is necessary when it comes to dealing with social norms and the environment. I also place emphasis on the steps that policy-makers need to take in order to internalize both the externalities from the collective action problem, as well as the impact on the social norm. In addition, I discuss research gaps and provide suggestions for researchers that are interested in dealing with the joint study of collective action problems and social norms.
Incentives have been extensively studied in the management and policy literature, with most attention focusing on their type, magnitude, alignment, and effects.More recently, scholars paid attention to discounting issues and how these issues impact the effectiveness of incentives.Building on the nascent literature related to incentive timing, we argue that timing can offer an additional dimension to better characterize incentives and leverage their power by exploiting windows of opportunity.Using conceptual reasoning, we identify several mechanisms by which the timing of incentives can be used to increase their behavioral power.Specifically, well-timed (green) incentives can harness temporal landmarks, intermittence, immediacy and surprise effects, and intrinsic motivation reinforcement to reach environmental goals without significantly increasing the overall costs.We also indicate new avenues for further research such as designing a timing menu or considering time itself as an incentive.
There is still considerable resistance against carbon pricing-i.e. carbon taxation or cap-and-trade - in the social and policy sciences. We review its main arguments and conclude that they are not supported by the theoretical and empirical literature on instrument performance. Critics are also unable to offer alternative and feasible instruments that limit free riding in climate solutions and perform better on main evaluation criteria, namely effectiveness, efficiency, equity, and global-harmonization potential. Their argument that carbon pricing meets strong political resistance is countered by its widespread implementation already and by its ability to compensate inequitable impacts. We argue that overcoming unsubstantiated criticism on carbon pricing will lead to more consistent advice from policy experts to politicians, thus improving the feasibility of, and accelerating progress towards, globally harmonized and stringent climate policy. All in all, it might be more widely acknowledged that the remarkable feature of carbon pricing is that, if well implemented, it has a great number of advantages and few disadvantages. Rather than weakening political support by criticizing carbon pricing, critics would contribute more productively to effective global climate policy by defending proper and uniform implementation of it.
Worldwide there is an increasing trend of firms integrating social and environmentally responsible practices into their business strategy. This review aims to analyze the motivations for firms to engage in socially and environmentally responsible behavior and ways in which these motivations differ for firms in developed versus developing countries. In this context it discusses the differing role for governments and for markets in developed versus developing countries. In the developed countries, consumer, labor, and capital markets provide incentives for firms to voluntarily adopt these practices. Additionally, the threat of more stringent government regulations also motivates firms to engage in responsible behavior. Similar motivations may be weaker in developing countries where rewards for being responsible from either consumers or investors are uncertain, and environmental regulations are poorly enforced. Instead in developing countries there are other drivers of corporate social responsibility (CSR) such as pressures through the supply chain being exerted by downstream firms and consumers located in the developed countries, and MNCs in the developed countries. Firms in developing countries are also being directly required by government regulations to undertake CSR. We then assess how firms responded to these government policies, and the effectiveness of CSR initiatives in improving environmental and social goals. Finally, we discuss the limitations of relying on CSR to address pressing environmental and social problems in developing countries.
The interactions between financial development, productivity and growth have been extensively studied in the literature. However, their nature, directions and magnitudes remain unclear, and no consensus has been reached, notably in the agricultural sector. We conduct a state-of-the-art review of this topic and also present alternative environmental determinants (climate change and extreme event issues; water, soil and land management practices; waste management and circular economy) of agricultural productivity. In doing so, we show where this domain has fallen short on methodological approaches, while emphasizing the relevant feature characterizing this empirical debate. Moreover, we emphasize the heterogeneity of the linkages between financial development, productivity and growth across income groups. Along with prospects for future research, some policy recommendations are offered.
Agriculture and the entire food production system play a critical role in sustaining the human species. However, as we strive to secure our means of subsistence, our extensive use of land and water has led to the depletion of the environment and biodiversity. This raises the pressing question of whether we can sufficiently produce food to support a growing population while simultaneously mitigating the inevitable environmental impacts. This article presents a comprehensive review of the significant effects of agriculture on the environment including contributions to greenhouse emissions, land use and land-use change, and forests, impact on biodiversity, impact on water quality and quantity, and the impact of pesticide use. The article also offers a list of approaches used to measure and evaluate the impact of agriculture. The primary aim of this article is to comprehensively review the latest insights in the field and to stimulate further research in this area.
