Gian Pietro Bellocca , Pilar Poncela , Esther Ruiz
{"title":"Extreme temperatures and the profitability of large European firms","authors":"Gian Pietro Bellocca , Pilar Poncela , Esther Ruiz","doi":"10.1016/j.jclimf.2025.100068","DOIUrl":"10.1016/j.jclimf.2025.100068","url":null,"abstract":"<div><div>In this paper, we analyze the impact of temperature exposure on earnings per share of large European firms over the 21st century using panel data models. Our findings reveal that earnings are sensitive to extreme temperatures in a large proportion of sectors. Depending on the particular quarter of the year and sector, we observe impacts on profitability, which can be positive, negative, or both. Most of the effects of extreme temperatures are observed during the milder seasons of spring and autumn. Furthermore, we find a steady increase in investments in sectors that are negatively impacted by extreme temperatures, which grew from around 16 % in 2015 to more than 23 % in 2022. Finally, we find a higher percentage of sectors affected by exposure to extreme temperatures in Europe than that observed in other similar studies for the US.</div></div>","PeriodicalId":100763,"journal":{"name":"Journal of Climate Finance","volume":"11 ","pages":"Article 100068"},"PeriodicalIF":0.0,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143935997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Did we open the flood gates? climate risk and infrastructure loans probability of default","authors":"Abderrahim Assab","doi":"10.1016/j.jclimf.2025.100066","DOIUrl":"10.1016/j.jclimf.2025.100066","url":null,"abstract":"<div><div>I provide a novel approach to estimating asset-level expected damage from flooding for 952 airports, ports, and power plants globally. This study contributes to the understanding of climate risks in infrastructure finance by focusing on the impact of flood damage on loan default probabilities—a critical aspect for investors and policymakers managing climate adaptation in high-risk areas. Using multivariate regression models with sectoral and geographic controls, I find that the expected damage from flood increases the probability of default on infrastructure project finance loans and that the presence of stringent flood adaptation standards decreases it. A standard deviation increase in the expected damage from flood increases the probability of default by one percent, while the presence of enforced flood adaptation standards leads to a 4 percent decrease in the probability of default. I find that the effect of expected damage from floods is higher for long-maturity loans, as well as projects including financial risk mitigation mechanisms such as Power Purchase Agreements. I also find that flood adaptation standards decrease probability of default only when these are enforced. The presence of non-enforced flood management policies leads to an increase in probability of default. These findings have important implications for project finance as an instrument to finance infrastructure and infrastructure as a distinct financial asset class.</div></div>","PeriodicalId":100763,"journal":{"name":"Journal of Climate Finance","volume":"11 ","pages":"Article 100066"},"PeriodicalIF":0.0,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143899236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Greenhouse gas emissions and bank lending in Japan","authors":"Koji Takahashi , Junnosuke Shino","doi":"10.1016/j.jclimf.2025.100067","DOIUrl":"10.1016/j.jclimf.2025.100067","url":null,"abstract":"<div><div>This paper examines the effect of firms’ greenhouse gas (GHG) emissions on bank loans, using matched bank-firm data from Japanese listed companies between 2006 and 2018. Previous research suggests that climate risks priced in corporate bonds or syndicated loans are statistically significant but economically minor. This paper explores bank lending behavior by focusing on loan amounts, which we consider to have a more direct influence on firms’ investment decisions. Our findings indicate that banks significantly reduce loans to firms with higher GHG emissions. Moreover, this effect of GHG emissions on Japan’s bank loans appears to have been present even before the signing of the Paris Agreement, which existing literature identifies as the point where GHG emissions began to be factored into the pricing of debt instruments as a component of credit risk. Finally, banks with higher leverage and lower ROA are more likely to reduce loans to firms with high GHG emissions.</div></div>","PeriodicalId":100763,"journal":{"name":"Journal of Climate Finance","volume":"11 ","pages":"Article 100067"},"PeriodicalIF":0.0,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143855608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Spillovers between hydrogen, nuclear, and AI sectors: The impact of climate policy uncertainty and geopolitical risks","authors":"Adnan Aslam","doi":"10.1016/j.jclimf.2025.100065","DOIUrl":"10.1016/j.jclimf.2025.100065","url":null,"abstract":"<div><div>This study investigates the spillover effects between hydrogen energy, nuclear energy, and artificial intelligence (AI) sectors in the context of the global clean energy transition, with a particular focus on the impact of climate policy uncertainty (CPU) and geopolitical risks (GPR). Employing the TVP-VAR extended joint connectedness approach, the findings show a high connectedness that indicates significant spillovers among these sectors. Hydrogen energy emerges as a dominant transmitter of shocks, reflecting its sensitivity to regulatory changes and fluctuating demand. However, nuclear energy acts as a stabilising force that offers hedging opportunities and resilience against market turbulence. The AI sector exhibits strong connectedness, primarily as a net receiver of shocks, driven by its dependency on clean energy sources and vulnerability to energy market volatility. Using the GARCH-MIDAS framework, the study identifies a temporal asymmetry in market responses to CPU and GPR. CPU triggers immediate but short-lived disruptions, while GPR induces delayed yet persistent effects that intensify cross-sector spillovers over time. These results underline the vulnerabilities of sectors reliant on regulatory clarity and geopolitical stability. This study provides practical insights for investors, policymakers, technology, and energy companies to better manage systemic risks at the crossroads of clean energy, technological innovation, and uncertainty.</div></div>","PeriodicalId":100763,"journal":{"name":"Journal of Climate Finance","volume":"11 ","pages":"Article 100065"},"PeriodicalIF":0.0,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143737771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Rural credit market imperfection in financing climate change adaptation: Evidence from Pakistan","authors":"Muhammad Nawaz , Misak Avetisyan","doi":"10.1016/j.jclimf.2025.100062","DOIUrl":"10.1016/j.jclimf.2025.100062","url":null,"abstract":"<div><div>With the increasing negative consequences of climate change on agriculture, adaptation has emerged as a viable alternative to mitigation. Adaptation strategies for farmers heavily dependent on availability of credit financing from formal, semi-formal and informal lenders. However, there has been limited access to the credit for adaptation because of inefficiency and inequity in credit markets, caused mostly by the variations in farmer’s socio-economic status. Therefore, in this study we analyze the inefficiency and inequity measures of credit market imperfection by utilizing field data of 400 wheat growing farmers from various agro-ecological zones in Pakistan. In this study we find presence of imperfection in credit markets for financing climate change adaptation strategies. Only 36 % and 37 % of farmers have access to loans from formal (banks) and semi-formal lenders (MFIs), respectively, while 95 % of farmers have access to credit from informal lenders contributing to inequity issues in credit markets. The findings further suggest that 75 % of farmers use ‘personal security’ for loans and travel from far-off areas to get credit which may strengthen the imperfection of credit markets in allocating and financing loans for climate vulnerable farmers. Climate vulnerable farmers mostly use the climate and non-climate adaptation strategies that include ‘better and expensive seed’ (57 %) and the ‘use of tractor’ (83 %). The results of our regression analysis suggest that marginal and small farmers have limited access to credit from all types of lenders, which negatively affects their ability to invest in climate change adaptation strategies. Application cost (registration and trip to lenders) reduces the access to credit and ability to invest in climate adaptations. Finally, credit market imperfection can be minimized for climate vulnerable farmers through direct provision of agricultural inputs at local markets.</div></div>","PeriodicalId":100763,"journal":{"name":"Journal of Climate Finance","volume":"10 ","pages":"Article 100062"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143548875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Probabilistic forecasting of transition towards sustainable energy production","authors":"Victor E. Gluzberg , Yuri A. Katz","doi":"10.1016/j.jclimf.2025.100063","DOIUrl":"10.1016/j.jclimf.2025.100063","url":null,"abstract":"<div><div>It is observed that cumulative production of electricity by renewable technologies increases exponentially with time, while the unit cost exponentially decreases. However, the exponential growth of <em>annual</em> production even by a sustainable technology will eventually flatten due to saturation of the global market. This should result in a linear growth of <em>cumulative</em> production with a passage of time. To capture this qualitative picture, we introduce the novel model of cumulative production by a sustainable technology with negative feedback in the different form than in the traditional logistic model. To account for irregularity of technological progress, we utilize the method of cumulant expansion that allows to make probabilistic forecasts for the unit cost, which do not depend on the specific model of underlying stochastic processes and a scenario of the future production growth. The derived results demonstrate that during the period of initial exponential growth of production, the effective rate of decrease of the unit cost is slightly lower than its average value. The respective confidence interval is growing linearly with the square root of the forecasting horizon. In the long run, the model of sustainable production forecasts the power law decline of the expected unit cost with time. In this regime, the forecasting error of the logarithm of the unit cost is slowly growing as the square root of the logarithm of the forecasting horizon. To illustrate the method, we make probabilistic forecasts for prices of solar photovoltaic modules up to 2060.</div></div>","PeriodicalId":100763,"journal":{"name":"Journal of Climate Finance","volume":"10 ","pages":"Article 100063"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143509118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Henk Jan Reinders , Dirk Schoenmaker , Mathijs van Dijk
{"title":"Climate risk stress testing: A critical survey and classification","authors":"Henk Jan Reinders , Dirk Schoenmaker , Mathijs van Dijk","doi":"10.1016/j.jclimf.2025.100061","DOIUrl":"10.1016/j.jclimf.2025.100061","url":null,"abstract":"<div><div>We conceptually investigate Climate Risk Stress Testing (CRST) exercises to assess the impact of climate-related shocks on financial system stability. We distinguish between climate, economic, and financial modeling steps, and classify CRST exercises into six types of climate shocks and four different approaches (macro-financial, micro-financial, non-structural, and disaster risk). We identify several key limitations in current CRST approaches: (i) neglect of certain climate shock types (Green Swan and Minsky-type events); (ii) overreliance on macro models (with low sectoral and spatial granularity); (iii) incomplete modeling (lack of feedback effects); and (iv) limited scope (subset of causal channels and asset classes). We argue that these limitations may lead to significant underestimation of potential system-wide financial losses and offer suggestions for improving CRST approaches. They have also led CRST exercises to diverge from the traditional stress testing objective of capital adequacy.</div></div>","PeriodicalId":100763,"journal":{"name":"Journal of Climate Finance","volume":"10 ","pages":"Article 100061"},"PeriodicalIF":0.0,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143454599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Dynamic connectedness and portfolio strategies: Insights from fintech, robotics, renewable energy, and green bonds in China","authors":"Nader Naifar","doi":"10.1016/j.jclimf.2025.100060","DOIUrl":"10.1016/j.jclimf.2025.100060","url":null,"abstract":"<div><div>This study investigates the dynamic interactions between fintech, robotics, renewable energy, and green bonds in China's market, focusing on sectoral spillovers, their determinants, and optimal portfolio strategies. While prior research has often examined these sectors in isolation, their interconnected dynamics within China's green finance framework remain underexplored. Employing an extended joint connectedness approach and quantile regression techniques, this study analyzes the interdependencies among these sectors and evaluates the influence of macroeconomic factors, including Chinese sovereign credit risk, the Yuan-Dollar exchange rate, and global volatility indices. The findings highlight fintech's fundamental role in return transmission and the robotics sector's pronounced sensitivity to external shocks. Moreover, the study demonstrates the feasibility of a minimum connectedness portfolio strategy, which optimizes investment outcomes by leveraging reduced intersectoral correlations during environmental policy shifts. These insights offer valuable guidance for investors, policymakers, and financial advisors, emphasizing the strategic importance of fostering cross-sectoral collaboration to drive technological advancement, job creation, and environmental sustainability in China's market.</div></div>","PeriodicalId":100763,"journal":{"name":"Journal of Climate Finance","volume":"10 ","pages":"Article 100060"},"PeriodicalIF":0.0,"publicationDate":"2025-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143135552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Portfolio selection from risk transfer mechanisms in a time of crisis for renewable energy markets","authors":"Yu-Ann Wang , Chia-Lin Chang","doi":"10.1016/j.jclimf.2024.100059","DOIUrl":"10.1016/j.jclimf.2024.100059","url":null,"abstract":"<div><div>This study investigates risk transmission in financial markets, focusing on investor’s hedging decisions and how risk moves between renewable and fossil fuel energy assets within energy ETFs during the Global Financial Crisis (GFC) and the COVID-19 pandemic. A novel approach is introduced to assess how the volatility of a single energy asset affects the risk of an entire energy portfolio, providing valuable insights for policymakers, investors, and energy producers in managing financial risk. The analysis focuses on three major renewable energy ETFs (solar, wind, and hydro) and three major fossil fuel energy ETFs (oil, coal, and natural gas). During the COVID-19 crisis, asset combinations like (solar, coal), and (wind, coal), were found to effectively minimize losses. Although not ideal for solar-related risks, the (solar, oil) combination proved advantageous, particularly oil-related shocks. The study also finds that combining solar with oil and wind with oil was effective in mitigating losses during the GFC and before the COVID-19 pandemic. In non-crisis periods, asset combinations such as (solar, oil) or (solar, coal) offer robust risk management strategies. This research highlights the interconnectedness of energy assets and the importance of using crisis-specific forecasting models, which significantly improve forecasting accuracy. Further research could explore similar impacts from events like the Russia-Ukraine war, which could affect energy markets.</div></div>","PeriodicalId":100763,"journal":{"name":"Journal of Climate Finance","volume":"10 ","pages":"Article 100059"},"PeriodicalIF":0.0,"publicationDate":"2024-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143135553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Corporate carbon emission effectiveness and corporate green transformation: Based on a quasi-natural experiment from China","authors":"Xin Yun, Yang Hu","doi":"10.1016/j.jclimf.2024.100056","DOIUrl":"10.1016/j.jclimf.2024.100056","url":null,"abstract":"<div><div>Green finance policies serve as a critical driver for the green transformation of enterprises, significantly influencing the environmental decision-making of corporate leaders. Publicly listed companies disclose carbon reduction data through various channels, including corporate social responsibility reports, sustainability reports, and corporate bylaws. This aggregation of information enhances market transparency and strengthens the interconnectedness between listed companies and the market, thereby enriching the external information environment for these firms. Such data dissemination facilitates the implementation of incentive-compatible market governance mechanisms within companies, thereby promoting their green transformation efforts. This study employs the Carbon Emission Disclosure (Cid) and a Difference-in-Differences (DID) model to examine the impact of carbon reduction measures on the green transformation of listed companies before and after the establishment of green finance pilot zones, utilizing data from 2008 to 2021. We analyze how these enhance corporate governance, increase media attention, stimulate government research and development investments, and ultimately influence the green innovation and overall productivity of these enterprises. Our findings indicate that the effects of these processes depend on factors such as the degree of marketization within the industry, company size, and geographic location. Empirical results provide robust support for the implementation of green finance pilot zone policies in China and offer policy recommendations for publicly listed companies to enhance energy conservation, emission reduction, and green development.</div></div>","PeriodicalId":100763,"journal":{"name":"Journal of Climate Finance","volume":"10 ","pages":"Article 100056"},"PeriodicalIF":0.0,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143135554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}