publications

My publications span environmental economics, political economy, and innovation studies, with a current focus on green technological change and climate-policy institutions.

Working Papers

1. Directed technological change and general purpose technologies: can AI accelerate clean energy innovation?

   Pia Andres, Eugenie Dugoua, and Marion Dumas

   GRI Working Paper, 2022 Abstract

   Transitioning away from dirty and towards clean technologies is critical to reduce carbon emissions, but the race between clean and dirty technologies is taking place against the backdrop of improvements in general-purpose technologies (GPT) such as information and communication technologies (ICT) and artificial intelligence (AI). We show how, in theory, a GPT can affect the direction of technological change and, in particular, the competition between clean and dirty technologies. Second, we use patent data to show that clean technologies absorb more spillovers from AI and ICT than dirty technologies and that energy patenting firms with higher AI knowledge stocks are more likely to absorb AI spillovers for their energy inventions. We conclude that ICT and AI have the potential to accelerate clean energy innovation.

Key Publications

1. Decarbonizing a Complex System

   Marion Dumas, and Pia Andres

   In The Economy as an Evolving Complex System IV, 2025 Abstract

   Meeting the challenge of climate-change mitigation involves a rapid and comprehensive transformation of the global economy away from high-emitting production systems toward low-carbon ones. This chapter illustrates how complex-systems approaches are uniquely well suited to understanding the drivers, barriers, and risks arising from such a technological transformation. We first consider the dynamics at play in growing new technological systems. We contrast two empirically well-documented cases (solar photovoltaics and electric vehicles) to show the central importance of technological interdependencies in shaping the dynamics of innovation and in crafting effective policy strategies. In particular, we argue that promoting low-carbon technologies that are less modular may require a more targeted and coordinated approach than is standard in innovation policy. We then turn to the dynamics at play in phasing out old technological systems. A central question is whether the progress of low-carbon technologies can on its own displace fossil-fuel-based technologies without policies that actively phase out or discourage these technologies. We highlight the different feedback processes that are key to answering this question (including the interaction between changes in technology costs, the rebound effect and the green paradox, and the role of heterogeneous expectations), some areas where better modeling is needed, and open policy questions. Finally, we argue that accounting for the heterogeneous nature of capital assets, skills, and regional capabilities, as well as understanding systemic interdependencies, is essential to anticipating disruption and stranding and crafting policies to mitigate transition risks.

2. Coordination dynamics between fuel cell and battery technologies in the transition to clean cars

   Eugenie Dugoua, and Marion Dumas

   Proceedings of the National Academy of Sciences of the United States of America, 2024 Abstract

   Significant progress reconciling economic activities with a stable climate requires radical and rapid technological change in multiple sectors. Here, we study the case of the automotive industry’s transition to electric vehicles, which involved choosing between two different technologies: fuel cell electric vehicles (FCEVs) or battery electric vehicles (BEVs). We know very little about the role that such technological uncertainty plays in shaping the strategies of firms, the efficacy of technological and climate policies, and the speed of technological transitions. Here, we explain that the choice between these two technologies posed a global and multisectoral coordination game, due to technological complementarities and the global organization of the industry’s markets and supply chains. We use data on patents, supply-chain relationships, and national policies to document historical trends and industry dynamics for these two technologies. While the industry initially focused on FCEVs, around 2008, the technological paradigm shifted to BEVs. National-level policies had a limited ability to coordinate global players around a type of clean car technology. Instead, exogenous innovation spillovers from outside the automotive sector played a critical role in solving this coordination game in favor of BEVs. Our results suggest that global and cross-sectoral technology policies may be needed to accelerate low-carbon technological change in other sectors, such as shipping or aviation. This enriches the existing theoretical paradigm, which ignores the scale of interdependencies between technologies and firms.

3. When does reputation lie? Dynamic feedbacks between costly signals, social capital and social prominence

   Marion Dumas, Jessica L Barker, and Eleanor A Power

   Philosophical Transactions B, 2021 Abstract

   Performing a dramatic act of religious devotion, creating an art exhibit, or releasing a new product are all examples of public acts that signal quality and contribute to building a reputation. Signalling theory predicts that these public displays can reliably reveal quality. However, data from ethnographic work in South India suggests that more prominent individuals gain more from reputation-building religious acts than more marginalized individuals. To understand this phenomenon, we extend signalling theory to include variation in people’s social prominence or social capital, first with an analytical model and then with an agent-based model. We consider two ways in which social prominence/capital may alter signalling: (i) it impacts observers’ priors, and (ii) it alters the signallers’ pay-offs. These two mechanisms can result in both a ’reputational shield,’ where low quality individuals are able to ’pass’ as high quality thanks to their greater social prominence/capital, and a ’reputational poverty trap,’ where high quality individuals are unable to improve their standing owing to a lack of social prominence/capital. These findings bridge the signalling theory tradition prominent in behavioural ecology, anthropology and economics with the work on status hierarchies in sociology, and shed light on the complex ways in which individuals make inferences about others. This article is part of the theme issue ’The language of cooperation: reputation and honest signalling’.

4. Green product innovation in industrial networks: A theoretical model

   Eugenie Dugoua, and Marion Dumas

   Journal of Environmental Economics and Management, 2021 Abstract

   Previous studies have modeled green technological change as innovations in the process of production (e.g., abatement technologies or energy sources). But greening the economy also requires changing products. The automotive industry, for example, needs to massively deploy alternative-fuel vehicles. Product manufacturing occurs within supply-chain networks, and developing new products typically requires complementary investments by suppliers. We study the incentives for green product innovation in industrial networks and how policies can affect them. We follow the industrial organization theory of product differentiation, and model green product innovations as upgrades in product quality where inputs from suppliers are essential for upgrading quality. We show that suppliers can be innovation bottlenecks and render policy instruments less effective. We provide an explicit mechanism for the role of institutions that help actors coordinate on the long-term direction of innovation. We discuss how our results help organize several findings from case studies in the automotive industry.

5. Taking the law to court: Citizen suits and the legislative process

   Marion Dumas

   American Journal of Political Science, 2017 Abstract

   The institution of citizen suits is a decentralized form of public participation that allows citizens to influence the implementation of public laws in courts. How does this institution influence policymaking? This article proposes a model of citizen suits. It then analyzes how this institution influences legislative decisions. The legislature bargains to choose the budget, distributive spending, and spending on an ideologically contested public good (e.g., health care or environmental protection). I find that citizen suits enable courts to forge a compromise between opponents and proponents of the public good by responding to the diverse claims of citizens. Anticipating the mobilization of citizens in courts, legislators in turn craft more socially efficient bills, with less distributive spending, which better represent the distribution of preferences for the public good compared to when citizens have no role in the implementation of legislation.

All Other Outputs

1. A methodology for comprehensive national climate damage assessments applied to the UK

   James Rising, Ritika Khurana, Simon Dietz, and 6 more authors

   Nature Climate Change (accepted), 2026 Abstract

   Climate change has very wide-ranging economic impacts. Comprehensive economic assessments are therefore needed, yet existing estimates remain fragmented, incomplete, and deeply uncertain. This paper develops an emulation methodology to achieve a much more complete economic valuation of climate risks. We apply it to the United Kingdom, which provides a test case due to the availability of many modeled and expert elicitation estimates. The approach provides channel-specific estimates, quantifies climatic and socioeconomic uncertainties, disaggregates to 406 local areas, and crucially includes understudied impacts such as spillovers from other regions and missing risks. While current warming produces welfare losses equivalent to 2% of GDP [95% CI of 1%-4%], damages grow rapidly under the baseline scenario and reach 10% of GDP [2% to 20%] by the end of the century. Comprehensiveness matters: half of the expected total damages and the greatest uncertainties come from catastrophic and missing risks.

2. Text as Data in Environmental Economics and Policy

   Eugenie Dugoua, Marion Dumas, and Joëlle Noailly

   Review of Environmental Economics and Policy, 2022 Abstract

   AbstractThere is growing interest in using text as data in social science research, particularly in economics. The availability of large amounts of digitized text material such as social media posts, newspapers, firms? annual reports, and patents, combined with new computer techniques, makes it increasingly possible for researchers to use this type of information. The aim of this article is to discuss the potential of these techniques for the field of environmental economics and policy.

3. Systematic shifts in scaling behavior based on organizational strategy in universities

   Ryan C Taylor, Xiaofan Liang, Manfred D Laubichler, and 3 more authors

   PloS One, 2021 Abstract

   To build better theories of cities, companies, and other social institutions such as universities, requires that we understand the tradeoffs and complementarities that exist between their core functions, and that we understand bounds to their growth. Scaling theory has been a powerful tool for addressing such questions in diverse physical, biological and urban systems, revealing systematic quantitative regularities between size and function. Here we apply scaling theory to the social sciences, taking a synoptic view of an entire class of institutions. The United States higher education system serves as an ideal case study, since it includes over 5,800 institutions with shared broad objectives, but ranges in strategy from vocational training to the production of novel research, contains public, nonprofit and for-profit models, and spans sizes from 10 to roughly 100,000 enrolled students. We show that, like organisms, ecosystems and cities, universities and colleges scale in a surprisingly systematic fashion following simple power-law behavior. Comparing seven commonly accepted sectors of higher education organizations, we find distinct regimes of scaling between a school’s total enrollment and its expenditures, revenues, graduation rates and economic added value. Our results quantify how each sector leverages specific economies of scale to address distinct priorities. Taken together, the scaling of features within a sector along with the shifts in scaling across sectors implies that there are generic mechanisms and constraints shared by all sectors, which lead to tradeoffs between their different societal functions and roles. We highlight the strong complementarity between public and private research universities, and community and state colleges, that all display superlinear returns to scale. In contrast to the scaling of biological systems, our results highlight that much of the observed scaling behavior is modulated by the particular strategies of organizations rather than an immutable set of constraints.

4. Detecting ideology in judicial language

   Marion Dumas

   In Law as data: Computation, text, and the future of legal analysis, 2020
5. Developing a sustainability science approach for water systems

   Christa Brelsford, Marion Dumas, Edella Schlager, and 20 more authors

   Ecology & Society, 2020 Abstract

   We convened a workshop to enable scientists who study water systems from both social science and physical science perspectives to develop a shared language. This shared language is necessary to bridge a divide between these disciplines’ different conceptual frameworks. As a result of this workshop, we argue that we should view socio-hydrological systems as structurally co-constituted of social, engineered, and natural elements and study the “characteristic management challenges” that emerge from this structure and reoccur across time, space, and socioeconomic contexts. This approach is in contrast to theories that view these systems as separately conceptualized natural and social domains connected by bi-directional feedbacks, as is prevalent in much of the water systems research arising from the physical sciences. A focus on emergent characteristic management challenges encourages us to go beyond searching for evidence of feedbacks and instead ask questions such as: What types of innovations have successfully been used to address these challenges? What structural components of the system affect its resilience to hydrological events and through what mechanisms? Are there differences between successful and unsuccessful strategies to solve one of the characteristic management challenges? If so, how are these differences affected by institutional structure and ecological and economic contexts? To answer these questions, social processes must now take center stage in the study and practice of water management. We also argue that water systems are an important class of coupled systems with relevance for sustainability science because they are particularly amenable to the kinds of systematic comparisons that allow knowledge to accumulate. Indeed, the characteristic management challenges we identify are few in number and recur over most of human history and in most geographical locations. This recurrence should allow us to accumulate knowledge to answer the above questions by studying the long historical record of institutional innovations to manage water systems.

6. Text as observational data

   Marion Dumas, and Jens Frankenreiter

   In Law as data: Computation, text, and the future of legal analysis, 2020
7. Asking about social circles improves election predictions

   M Galesic, W Bruin, M Dumas, and 3 more authors

   Nature Human Behaviour, 2018 Abstract

   Election outcomes can be difficult to predict. A recent example is the 2016 US presidential election, in which Hillary Clinton lost five states that had been predicted to go for her, and with them the White House. Most election polls ask people about their own voting intentions: whether they will vote and, if so, for which candidate. We show that, compared with own-intention questions, social-circle questions that ask participants about the voting intentions of their social contacts improved predictions of voting in the 2016 US and 2017 French presidential elections. Responses to social-circle questions predicted election outcomes on national, state and individual levels, helped to explain last-minute changes in people’s voting intentions and provided information about the dynamics of echo chambers among supporters of different candidates. Galesic et al. show that election poll questions that ask participants about the voting intentions of their social contacts, in addition to their own intentions, improve predictions of voting in the 2016 US and 2017 French presidential elections.

8. Computational Data Sciences and the Regulation of Banking and Financial Services

   Sharyn O’Halloran, Marion Dumas, Sameer Maskey, and 2 more authors

   In From Social Data Mining and Analysis to Prediction and Community Detection, 2017 Abstract

   The development of computational data science techniques in natural language processing (NLP) and machine learning (ML) algorithms to analyze large and complex textual information opens new avenues to study intricate policy processes at a scale unimaginable even a few years ago. We apply these scalable NLP and ML techniques to analyze the United States Government’s regulation of the banking and financial services sector. First, we employ NLP techniques to convert the text of financial regulation laws into feature vectors and infer representative “topics” across all the laws. Second, we apply ML algorithms to the feature vectors to predict various attributes of each law, focusing on the amount of authority delegated to regulators. Lastly, we compare the power of alternative models in predicting regulators’ discretion to oversee financial markets. These methods allow us to efficiently process large amounts of documents and represent the text of the laws in feature vectors, taking into account words, phrases, syntax, and semantics. The vectors can be paired with predefined policy features, thereby enabling us to build better predictive measures of financial sector regulation. The analysis offers policymakers and the business community alike a tool to automatically score policy features of financial regulation laws to and measure their impact on market performance.

9. Political competition and renewable energy transitions over long time horizons: A dynamic approach

   Marion Dumas, James Rising, and Johannes Urpelainen

   Ecological Economics, 2016 Abstract

   Climate change mitigation requires sustainable energy transitions, but their political dynamics are poorly understood. This article presents a general dynamic model of renewable energy policy with long time horizons, endogenous electoral competition, and techno-political path dependence. We calibrate the model with data on the economics of contemporary renewable energy technologies. In doing so, we discover transition dynamics not present in economy-energy models, which ignore politics, or in formal political economy models, which ignore long-term technological dynamics. We show that the largest effects of partisan ideology on policy occur when the competing parties disagree on the importance of energy policy. In these cases, the less ideological party appeases the more ideological one, while the more ideological party attempts to appease the electorate. The results demonstrate that political dynamics could have large effects on the development of renewable energy and carbon dioxide emissions over time, influencing the ability of countries to reach various climate mitigation trajectories.

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