Yongyang Cai, Professor in Department of Agricultural, Environmental and Development Economics at The Ohio State University. His research focuses on dynamic and stochastic integration of climate and the economy; integration of regional food, energy, water systems, and economy; and computational methods in economics. He has published peer-reviewed papers in leading academic journals, including Journal of Political Economy, Journal of the European Economic Association, Quantitative Economics, Journal of the Association of Environmental and Resource Economists, Journal of Environmental Economics and Management, Nature Climate Change, Proceedings of the National Academy of Sciences, and Operations Research. He is a co-investigator on several research projects funded by the National ScieAnce Foundation and USDA. He currently serves as an Associate Editor at Climatic Change, and an editorial board member at Computational Economics. Prior to joining OSU, Cai was a Senior Research Scientist at the Becker Friedman Institute and the Center for Robust Decision Making on Climate and Energy Policy of the University of Chicago, as well as a Visiting Fellow at the Hoover Institution of Stanford University. In 2021, he received the Erik Kempe Award in environmental and resource economics. 

Abstract: 

Climate change poses systemic risk to the financial system. Of particular concern is the compounding of climate and market risks, an episode in which climate and market shocks materialize concurrently, generating substantial losses through their interaction. We aim to quantify the systemic risk of a sector under both standalone and joint climate–market stress. We measure systemic risk using the conditional expected shortfall (CoES), given the occurrence of a tail event that is sufficiently general to encompass both standalone and joint climate–market distress scenarios. We conduct an extreme value analysis of CoES that reveals how systemic risk is amplified by the underlying tail dependence structure among market, climate, and sectorspecific risks. Using market-based risk factors to construct both market and climate stress scenarios, we estimate CoES for key sectors of the economy. Our results show that (i) analyzing climate and market shocks separately leads to a substantial underestimation of systemic risk; (ii) sectoral systemic importance exhibits pronounced time variation, with different sectors emerging as systemically important at different periods; and (iii) a decomposition of systemic risk into marginal and dependence contributions uncovers marked differences across sectors, with some sectors driven primarily by marginal effects and others by dependence effects.

Kwangmin Jung is an associate professor in the Department of Industrial and Management Engineering at Pohang University of Science and Technology (POSTECH), Korea. He is also the director of the master's program in Management Science and leads the Actuarial Modeling, Insurance and Risk Management (AIRM) research group at POSTECH. Prior to joining the faculty of POSTECH, he was the Robb B. Kelley distinguished visiting assistant professor at Drake University in the U.S. His research explores the intersection of actuarial science, risk management, and insurance, with a particular focus on studying emerging systemic risks (cyber, AI, and climate), capital market solutions for risk transfer, and insurance operations. He has published his academic findings at leading journals in these fields, including Journal of Risk and Insurance, Insurance: Mathematics and Economics, North American Actuarial Journal and ASTIN Bulletin. His work has been recognized with several awards, including Han Dong Ho Best Paper Prize by Korea Insurance Academic Society in 2022, the IAA AFIR-ERM Research Paper Prize in 2019 and the SCOR Actuarial Prize for Asia-Pacific in 2018. He received his Ph.D. in Finance from the University of St. Gallen, Switzerland. 

Gbenga is a Professor and Chair of Finance at the University of Edinburgh, where he also directs the University’s flagship FinTech research centre, the Edinburgh Centre for Financial Innovations, and the NatWest Group-funded Centre for Purpose-Driven Innovation in Banking. He is an elected Fellow of both the UK’s Academy of Social Sciences and the Royal Society of Edinburgh, Scotland’s national academy; a Fellow at Australia’s Rozetta Institute; and a Member of the Bank of England and HM Treasury's Central Bank Digital Currency Academic Advisory Group. He was also a Council Member of the World Economic Forum’s Global Future Council on the Future of Resilient Financial Systems for the 2023-2024 term, and the Deputy Scientific Director of the European Capital Markets Cooperative Research Centre. His current research sits at the intersection of the economics of financial markets and data science with applications to practice and policy. His research reports have been published by various bodies, such as the Bank for International Settlements, the UK's Financial Conduct Authority, and the UK Houses of Parliament's All Party Parliamentary Corporate Governance Group. Gbenga's research papers have been published extensively in the leading international academic journals, and have been featured in the international media, including The New York Times, The Economist, Financial Times, Forbes, and Bloomberg. He is the author (with Andros Gregoriou) of the research monograph 'Carbon Markets: Microstructure, Pricing & Policy', published in 2018 by Palgrave Macmillan, and translated into the Chinese (Mandarin) language in 2022. 

Mike Ludkovski is a Professor of Statistics and Applied Probability at University of California Santa Barbara where he co-directs the Center for Financial Mathematics and Actuarial Research. Among his research interests are renewable energy and groundwater markets, machine learning for quantitative finance, and mortality analysis. He serves on 5+ Editorial Boards and his research has been supported by NSF, DOE, ARPA-E and CAS.  He holds a Ph.D. in Operations Research and Financial Engineering from Princeton University and has held visiting positions at London School of Economics and Paris Dauphine University.

Title: Switching Games of Deep Decarbonization

Abstract: We study a continuous-time game model of competitive transition to green technology between two emitting sectors. Each sector controls its productive capacity through net investment and chooses when to irreversibly adopt a non-emissive technology.  Their interaction is mediated by a common emission pressure index whose drift increases with the production of sectors that remain brown.  Once a sector switches, it ceases to contribute to this pressure, thereby changing both the dynamics and the dimension of the continuation game.  We characterize stationary Markov Nash equilibria recursively across technology regimes. Notably in the both-brown regime we study the resulting non-zero-sum stopping-and-control game. For an empirical case study, we calibrate the model to the EU industrial sectors. Numerical results show that strategic interaction delays decarbonization relative to a social planner benchmark. Finally, we compute sector-specific carbon-tax equivalents of the transition incentives generated by the emission pressure index. This is joint work with Rene Aid (Paris Dauphine) and Jisu Yu (UCSB).

Andrea Macrina is Professor of Mathematics at the University of Ottawa and University College London (UCL), and Honorary Professor at the University of Cape Town (UCT) in the African Institute of Financial Markets and Risk Management. In 2012, Dr Macrina launched the Financial Mathematics MSc Programme at UCL, of which he was programme director for twelve years until September 2024. In 2014, he co-founded the Financial Mathematics Team Challenge (FMTC), an international research student workshop held annually at UCT. Dr Macrina is a recipient of the Fields Research Fellowship and Elliott-Yui Distinguished Visitor of The Fields Institute for Research in Mathematical Sciences.

Prof. Macrina held a Senior Lectureship followed by a Readership in the Department of Mathematics, University College London, an Adjunct Professorship at the Department of Actuarial Science of the University of Cape Town, a Lectureship in Financial Mathematics in the Department of Mathematics, King's College London, a one-year Visiting Research Associate Professorship in the Institute of Economic Research, Kyoto University, and a six-month Research Fellowship at ETH Zurich. Read more about him.

Christina Nikitopoulos is an Associate Professor at the UTS Business School with expertise in energy finance, sustainable finance, renewable energy, and commodity markets. Christina’s projects in sustainable finance address the challenges of fossil fuel divesting, green bonds screening and the effects of climate transition risk on sovereign bond markets. This research analyses dynamic portfolio construction strategies accounting for the demographic attributes of investors, such as performance tracking, risk tolerance, and management structure, as well as, divestment schedules and re-investing, to inform of optimal carbon reduction practices in equity and bond portfolios. Her research also quantifies the significance of climate transition risk factors as determinants of sovereign bond markets. Christina also leads several projects addressing energy transition and the impact of renewable energy generation on electricity price dynamics in Australia. These studies offer insights and recommendations of practical relevance to policymakers, energy providers, and consumers and inform debates regarding system’s security and reliability and optimal courses of action to facilitate energy transition. Christina has been awarded two Australian Research Council grants and many internal and industry research grants, including the UTS Strategic Research Accelerator Program 2024. Christina publishes in leading finance journals including the Journal of Banking & Finance, Energy Economics, Quantitative Finance, Journal of Commodity Markets and Energy Policy.  She is a member of the Commodity and Energy Markets Association (CEMA), the Academic Female Finance Committee (AFFECT), the International Association of Energy Economics (IAEE), Financial Research Network (FIRN), and the Australian Accounting & Finance Association of Australia and New Zealand (AFAANZ). 

Matteo Malavasi is a Lecturer at the UNSW School of Risk and Actuarial Studies. He holds a PhD in Actuarial Studies and Business Analytics from Macquarie University in cotutelle with University of Bergamo, Italy. His research interests are multidisciplinary, including climate change, climate risk, cyber risk, risk analytics, risk management, actuarial studies, data science, computational method for economics and finance, and applied probability.  

Eric Ofosu-hene is a Senior Lecturer in Accounting and Finance at Leeds Business School, Leeds Beckett University (UK). He Chairs the Sustainability - Demography Mortality and Morbidity Working Party of the Institute and Faculty of Actuaries (UK), where he leads and drives research strategy on the impact of climate change on mortality and morbidity. He has consulted for several organisations in both the public and private sectors drawing on Enterprise Risk Management and Pensions Management expertise. His research work is at the intersection of actuarial science, finance and climate change and has published in leading journals including Energy Economics, Annals of Actuarial Science and others. Eric holds a PhD in Actuarial Science from University of Kent, a double Master of Science degrees with distinction in Actuarial Management and Actuarial Science from Heriot-Watt University and is a Qualified Accountant with the Association of Chartered Certified Accountants (UK).   

Pavel Shevchenko is a Professor in the Department of Actuarial Studies and Business Analytics and Co-Director of the Centre for Emerging Risks at Macquarie Business School. Prior to joining Macquarie University in August 2016, he worked at CSIRO Australia (1999-2016) holding the position of a Senior Principal Research Scientist (2012-2016). Since 1999, Prof Shevchenko has worked in the area of risk analytics, leading research and industry commercial projects on: modelling of operational and credit risks; longevity and mortality, retirement products; option pricing; insurance; modelling commodities and foreign exchange; and the development of relevant numerical methods and software. 

He is currently associate editor of international journals (Asia-Pacific Journal of Risk and Insurance, RISKS and Journal of Operational Risk) and member of the Retirement Incomes Working Group in the Institute of Actuaries of Australia. Prof Shevchenko has published extensively in academic journals, consulted for major financial institutions, and is a frequent presenter at industry and academic conferences. His publication records include three research monographs, over 100 journal papers, and over 80 technical reports.

Adam Solomon is an Assistant Professor of Finance at the NYU Stern School of Business. His research focuses on the intersection of public finance, financial economics, and climate finance. He studies the design, provision, and regulation of (public and private) insurance and how this interacts with changing climate risk and other market frictions. He received his PhD in Economics from MIT and his undergraduate degrees in Mathematics and Economics from UNSW in Sydney, Australia.

After earning his PhD in statistics from the University of Science and Technology of China in 2001, he has worked at different places around the world including the University of Hong Kong (2001), the University of Amsterdam (2002-2004), Concordia University (2004-2005), and the University of Iowa (2006-2019). At the University of Iowa, he was promoted to Full Professor in 2012 and conferred an Endowed Chair in 2014. He joined UNSW Business School under the SHARP (Strategic Hires and Retention Pathways) scheme in July 2017.

His expertise span insurance, finance, and risk management. Recently, he has been working on various emerging topics including:

• Modeling, measuring, and managing catastrophe risks [awarded ARC DP200101859]

• Systemic risk and financial networks [awarded ARC DP220100090]

• Decision making under uncertainty [awarded ARC DP250100078]

• Pricing in incomplete markets

• Climate change and insurance

He has been Principal Investigator/Lead Chief Investigator of various major external grants, including (in reverse order): 3 from ARC of Australia, 1 from NSF of the US, 2 CAE research grants from the Society of Actuaries, and 1 from NSERC of Canada. His research has resulted in an H-index of 44 according to Google Scholar. He has graduated over a dozen PhD students who are now working in academia or industry around the world.

Currently, he serves as an Editor of the journal Insurance: Mathematics and Economics, and an Associate Editor of several other journals including Applied Stochastic Models in Business and Industry and Science China Mathematics. He is an Elected Member of the International Statistical Institute. Internally at UNSW Sydney, he serves as Co-Director of the Innovations in Risk, Insurance and Superannuation (IRIS) Knowledge Hub.

Prof Tanja Tippett is an applied mathematician who lectures on the MCom in Risk Management of Financial Markets. Tanja has extensive industry experience in asset management and insurance, specialising in asset-liability matching, risk management, credit risk management and fixed income strategies. 

Presentation title: A risk framework for climate-economic models impacted by stochastic uncertainty

Authors: Tanja Tippett, joint work with Andrea Macrina and Thomas McWalter

Abstract. Integrated assessment models (IAMs) are widely used to evaluate interactions between economic activity and climate change, yet most applications remain deterministic and therefore provide limited information about the range and severity of possible climate-economic outcomes. We developed a model-agnostic adaptive stochastic framework for IAMs that preserves the underlying deterministic structure while allowing uncertainty to propagate through the coupled climate-economic system. Monte Carlo simulation generates probability distributions for climate and economic outcomes, while receding-horizon re-optimisation allows mitigation and consumption decisions to adapt as uncertainty is progressively resolved. The framework is applied to DICE-2016 and DICE-2023. Despite incorporating additional sources of climate uncertainty, DICE-2023 generally produces narrower atmospheric carbon and temperature distributions than DICE-2016, demonstrating that uncertainty propagation depends critically on model architecture rather than solely on the magnitude of uncertain inputs. The resulting distributions are evaluated using a climate-economic risk framework combining threshold and tail-risk measures with climate-economic solvency, which assesses the capacity of the economy to absorb climate damages and mitigation expenditure while maintaining consumption and investment. Marginal social values additionally identify the uncertain drivers with the greatest influence on welfare, demonstrating that the drivers of outcome uncertainty need not coincide with those of welfare significance. Our research extends deterministic IAM analysis from expected trajectories to distributions of climate-economic outcomes and adaptive policy responses. By integrating uncertainty propagation, dynamic re-optimisation, tail risk, economic resilience, and welfare sensitivity, it provides a richer basis for climate policy evaluation under uncertainty.

Dr. Chi Truong is a Senior Lecturer in Actuarial Studies and Business Analytics at Macquarie Business School, Macquarie University. His research interests focus on risk quantification and management, especially disaster risk, systemic risk, and operational risk. He has extensive experience in developing dynamic factor models for risk management, and evaluating risk mitigation strategies under climate change uncertainty.

His work has been published in leading journals, including European Journal of Operational Research, Conservation Biology, Journal of Financial Stability, Applied Energy, Energy Policy, North American Actuarial Journal, Journal of Environmental Management, Annals of Operations Research, Environmental and Resource Economics, Weather and Climate Extremes, Agricultural Water Management, Canadian Journal of Agricultural Economics.

Dr. Truong serves as reviewer for numerous top-tiered journals, including European Journal of Operational Research, Energy Economics, American Journal of Agricultural Economics, Journal of Economic Dynamics and Control, International Journal of Production Economics, ASTIN Bulletin, Environmental and Resource Economics, Journal of Environmental Management.

He has secured research funding from major organizations, including the Asian Development Bank, the Commonwealth Bank of Australia, Society of Actuaries (USA), Toyota, and the National Climate Change Adaptation Research Facility. His research has been awarded with ABARE Prize and Research Excellence Publications Award at Macquarie University.

Brad Archer is a senior public sector executive with over 30 years’ experience, including 15 years in roles leading on climate change policy advice and analysis in Australia. He has extensive experience working on climate change, renewable energy and energy market issues. In February 2026, he commenced as head of the Gas and Liquid Fuels Division in the Federal Department of Climate Change, Energy, Environment and Water.  During 2018-2026, he was Chief Executive Officer at Climate Change Authority overseeing the development of independent, evidence-based advice on emissions reduction targets, sectoral decarbonisation, and climate policy settings.  Previously, he was head of the International Climate Change and Energy Innovation Division in the Australian Government Department of the Environment and Energy, where his responsibilities included advising on clean energy innovation, Australia’s greenhouse gas inventory, and international climate change policy. Mr Archer has been working on climate change policies for the Australian Government since early 2011. Prior to this he worked on a range of issues in the Treasury, which he joined in 1991. Mr Archer has qualifications in economics and information management.

Professor Mark Lawrence brings deep insight into the links between climate change, energy transition and global financial systems. He is currently Professor of Practice at the University of Adelaide and is the former Expert Principal at McKinsey and Chief Risk Officer at ANZ Bank, having spent over 30 years leading global financial risk management practices across the Americas and the Asia-Pacific. Today, Mark is focused on the most urgent and far-reaching risk of all: climate risk.

Dr Richard Matear is a senior climate scientist in the Climate Intelligence program of CSIRO Environment.  Richard has 30 years of experience investigating how rising greenhouse gases impact our climate.   His research utilises models and observations to understand the mechanisms driving climate variability and change and its implications for our future climate.  Richard currently leads CSIRO's future climate and hazard activity in the Australia Climate Service. In this role, he is working to ensure our climate intelligence is used to inform Australia's first National Climate Risk Assessment and helps guide Australia’s Climate Adaptation Plans.  Richard is also involved in efforts to demonstrate ocean-based negative emission technologies to remove carbon dioxide from the atmosphere and mitigate climate change.  

Rade Musulin is a Principal at Finity Consulting in Sydney, Australia, where he leads the Climate Risk practice. Previously he served as the Chief Executive Officer of FBAlliance Insurance, Chief Operating Officer of Aon Benfield Analytics Asia Pacific, and Vice President Operations, Public Affairs, and Reinsurance for the Florida Farm Bureau Insurance Companies.

Rade serves as Vice-Chair of the International Actuarial Association’s Resource and Environmental Working Group and was Vice President – Casualty for the American Academy of Actuaries from 2016 – 2018. He has a long history of volunteer service, including roles with the Actuaries Institute of Australia, American Academy of Actuaries, Casualty Actuarial Society, and International Actuarial Association. He is a past Chair of the Board of the Florida Insurance Council and of the Advisory Council of the Florida Hurricane Catastrophe Fund.

His main areas of interest include how changing population demographics affect catastrophe exposure, climate change adaptation, applications of catastrophe models for disaster planning in developing countries, building code development, and community resilience. Rade has maintained close ties with academic institutions, including being a lecturer for undergraduate classes in actuarial science, risk management, and political science. 

David Orsmond is Professor of Economics, Macquarie Business School and Director of Policy and Communications, Centre for Applied Artificial Intelligence at Macquarie University. He previously worked at the Reserve Bank of Australia, holding senior positions in the Financial Stability and Economic Analysis Departments. Dr Orsmond also spent an extended period at the International Monetary Fund working on economic stabilisation and technical assistance issues across numerous countries. He has written on a range of topics, including the emergence of artificial intelligence, regulatory policies in the financial sector, China’s economy and the mining sector. He holds a PhD from Duke University, a Bachelor of Economics (Hons) from the University of Sydney and completed studies in economic policy at the Kiel Institute for the World Economy in Germany.

Stefan Trück is a Professor of Business Analytics and Director of the Transforming Energy Markets Research Centre at Macquarie University. Previously, he has held positions at Queensland University of Technology and Karlsruhe Institute of Technology in Germany where he received a PhD in Business Engineering. Stefan’s research interests focus on risk management, financial econometrics and business analytics. His is a world leading expert in the area of electricity markets and energy finance, while his research also comprises the areas of and commodity markets, credit risk, systemic risk, emissions trading, climate change economics and international financial markets. He has published in many high impact journals. He has also worked in various consulting projects in the area of energy and financial risk for organisations such as Deutsche Bank, Deutsche Bundesbank, Australian Energy Market Commission, Saudi Electricity and Co-Generation Regulatory Authority, Maybank, CRC Limited, just to name a few. He also has received various research grants, including two Discovery Grants from the Australian Research Council (ARC) plus an ARC Future Fellowship, one of the most prestigious awards for mid-career researchers in Australia.

Aqib Ahmed is a PhD Candidate in Applied Mathematics and Quantitative Finance at Reykjavik University, supervised by Heidar Eyjolfsson, in Iceland. His research focuses on stochastic control, stochastic numerical methods, self-exciting jump processes, mean-field systems, and derivative pricing, with applications to climate and energy finance. His doctoral work develops stochastic models and computational methods for pricing and risk management under self-exciting dynamics, as well as stochastic control methods for heterogeneous interacting systems. He holds a master's degree in quantitative finance and Applied Mathematics from Universite Paris Cite and an engineering degree in applied mathematics from ESILV. He previously worked as a quantitative analyst in model validation at Bpifrance and in financial tools development at Lazard. He is also a teaching assistant in derivative pricing and in data mining and machine learning at Reykjavik University.

Presentation title: Pricing Derivatives under Self-Exciting Dynamics: A Finite-Difference and Transform Approach

Authors: Aqib Ahmed (presenting author) and Heidar Eyjolfsson, Reykjavik University

ABSTRACT

We study the pricing of derivatives written on accumulated marks, such as weather derivatives or aggregate loss claims, under a self-exciting marked point process. The jump intensity mean-reverts between events and rises at each event by an amount proportional to the mark, so that the state process is piecewise deterministic. The discounted pricing equation is a backward partial integro-differential equation in two spatial dimensions. We remove one dimension through an exponential transform in the accumulated mark, which diagonalises the translation operator and reduces the problem to a family of one-dimensional equations along a Bromwich contour. For Gamma-mixture mark laws, the nonlocal term is approximated by generalised Gauss-Laguerre quadrature, and the reduced equations are solved backward in time with a stable IMEX finite-difference scheme. We establish a term-by-term global error bound and validate the method against Monte Carlo benchmarks.

Asma is a PhD candidate in the Department of Land and Property Management at Lincoln University, New Zealand, under the supervision of Professor Graham Squires. Her research examines how flood risk affects housing market values across New Zealand's major cities, using spatial analysis and Geographically Weighted Regression. Asma is interested in climate-related hazards, property markets, and geospatial methods for risk assessment. She holds an MPhil in which she used geospatial techniques to assess two decades of soil salinization and its impact on wheat production in Gujranwala, Pakistan.

Presentation title: Flood Risk and Housing Market Values: A Spatial Analysis of Auckland, Wellington, and Christchurch Using Geographically Weighted Regression

ABSTRACT

Residential property is one of the most directly affected assets and climate related hazards are an increasingly important source of financial risk. Flood risk is increasingly being seen in New Zealand housing values, and recent years have seen an increase in the frequency and severity of flooding. This research examines the link between flood risk and house values for the three largest cities in New Zealand Auckland, Wellington and Christchurch. It merges property-level data from 2017 to 2021 at the suburb level, with flood hazard maps and uses Geographically Weighted Regression (GWR) to account for local variation in the relationships between flood exposure and property values. GWR differs from global regression models, which assume a single and uniform relationship, and can identify the spatial variability in the relationship between flood risk and property value, highlighting which housing markets are most sensitive to flood exposure. The study reveals these spatial patterns across suburbs and cities, offering fresh insights into the pricing of environmental risk in property markets. The results will show the utility of spatially explicit approaches in the evaluation of climate risk in property markets, with implications for property valuation, insurance, lending and flood risk management.

Hadi is a PhD Candidate in Finance at the UTS Business School Finance Discipline Group, with research and teaching interests in financial econometrics, time series analysis, interest rate modelling, financial machine learning, and quantitative trading. He has nearly ten years of experience as a financial market analyst and portfolio manager across diverse institutions. Hadi has instructed courses on derivatives pricing, capital markets fundamentals, and market microstructure analysis in both financial and educational settings. Holding a master's degree in industrial management and operations research from the University of Tehran and a bachelor's degree in mechanical engineering from Shiraz University, he is currently focused on applying statistical machine learning techniques to explore the dynamics of the green bonds market.

Shawn Yang is a PhD candidate in the School of Risk and Actuarial Studies at UNSW Sydney, supervised by Prof. Qihe Tang, A/Prof. Katja Ignatieva, and A/Prof. Han Li. His research focuses on insurance and climate change, systemic risk in reinsurance networks, and electricity price forecasting. He has published in the field of operations research and has prior industry experience in quantitative finance and risk management. His work on economic impacts of climate change is supported by the 2025–2026 UNSW Business School Sustainable Development Goals (SDGs) Research Grant.

Presentation title: Bayesian Learning of Regional Economic Impacts of Climate Change

Authors: Shawn Yang (presenting author) and Qihe Tang, UNSW Sydney

Abstract: We develop a Bayesian learning framework to analyze the deep uncertainty surrounding the economic impacts of climate change across multiple regions. We disaggregate GDP losses from climate damages to capture regional heterogeneity and incorporate spatial dependence to reflect cross-regional correlations. The framework enables joint learning across regions by leveraging shared information. By characterizing the dynamics of uncertainty reduction, we estimate the years required to reach target confidence levels in damage assessments across regions and sectors. The results indicate that joint learning among regions with similar damage functions reaches target confidence levels sooner than individual learning. Our empirical analysis is based on the FUND dataset and on the Representative Concentration Pathways (RCPs) adopted by the Intergovernmental Panel on Climate Change (IPCC).