Climate Change Summer School : Program content

by Farid Farrokhi

This course reviews tools and insights from the trade literature to address the challenges that climate change poses to the international community. We first introduce a general equilibrium model of international trade, extended to account for international carbon supply chains and government policies. Next, we use variations of this framework to analyze how trade policy can mitigate climate change, with particular emphasis on how it can be leveraged in the design of international climate agreements. Lastly, we extend the model to include land-use dynamics and examine how trade integration impacts deforestation.

Structure

• Part 1: A Model of International Trade with Carbon Supply Chains and Government Policies
• Part 2: Linking Trade and Climate Policy
  • Unilateral Climate Policy and Climate Clubs
  • Embedding Carbon Pricing into Existing Trade Agreements

Selected key references (access the full list)

• Farrokhi F. & Lashkaripour A., 2025, “Can Trade Policy Mitigate Climate Change?”.
• Farrokhi F. & Lashkaripour A., 2024, “Can Trade Policy Help Combat Climate Change?”, Econofact.
• Farrokhi F., Lashkaripour A. & Taheri H., 2025, “A Framework for Integrating Climate Policy into Trade Agreements”.
• Farrokhi F., Kang E., Pellegrina H. & Sotelo S., 2024, “Deforestation: A Global and Dynamic Perspective”.

by Antoine Dechezleprêtre

Ambition to address environmental challenges has often been held back by the perceived costs of more stringent environmental policies on firms. Policy makers fear that differences in the stringency of environmental policies across countries would negatively affect the competitiveness of firms located in the most ambitious regions, leading to pollution havens and emissions leakage. On the other hand, policy makers have often articulated the vision that new environmental policies could actually have a positive effect on the competitiveness of regulated firms because such policies promote cost-cutting efficiency improvements and foster innovation in new technologies that may help firms achieve international technological leadership. The lectures will discuss these opposing visions from a theoretical perspective and provide an overview of the empirical literature in environmental economics that has addressed these questions, focusing on papers that have evaluated the effects of climate policies on innovation activity, firm performance (as measured by revenue, employment, etc) and carbon emissions across jurisdictions.

Structure

• Climate policy and innovation
• The impact of climate policies on competitiveness and carbon emissions
• Leakage and the EU Carbon Border Adjustment Mechanism

Selected key references

• Aghion P. et al., 2016, “Carbon Taxes, Path Dependency and Directed Technical Change: Evidence from the Auto Industry”, Journal of Political Economy, 124(1).
• Brucal A., 2021, Assessing the impact of energy prices on plant-level environmental and economic performance: Evidence from Indonesian manufacturers, OECD Environment Working Paper.
• Calel R. & Dechezleprêtre A., 2016, “Environmental Policy and Directed Technological Change: Evidence from the European Carbon Market”, The Review of Economics and Statistics, 98(1), pp 173-191.
• Dussaux D., 2020, The Joint Effects of Energy Prices and Carbon Taxes on Environmental and Economic Performance: Evidence from the French Manufacturing Sector, OECD Environment Working Paper.
• Dechezleprêtre A. et al., 2022, “Searching for carbon leaks in multinational companies”, Journal of Environmental Economics and Management, 112.
• Dechezleprêtre A., Nachtigall D. & Venmans F., 2023), “The joint impact of the European Union emissions trading scheme on carbon emissions and economic performance”, Journal of Environmental Economics and Management, 118.
• Dussaux D., Vona F. & Dechezleprêtre A., 2023, “Imported carbon emissions: Evidence from French manufacturing companies”, Canadian Journal of Economics, 56(2), pp 593-621.
• Dechezleprêtre A. et al., 2025, Carbon Border Adjustments: The potential effects of the EU CBAM along the supply chain, OECD Science, Technology and Innovation Working Paper.
• Dechezleprêtre A. & Sato M., 2017, “The impacts of environmental regulations on competitiveness”, Review of Environmental Economics and Policy, 11(2).
• Grubb M. et al., 2021, Induced innovation in energy technologies and systems: A review of evidence and potential implications for CO2 mitigation, Environmental Research Letters.
• OECD, 2021, Assessing the economic impact of environmental policies: Evidence from a decade of OECD research, OECD Publications.

by Matthew Gordon

This module will study how individuals and groups can insure against the risks of climate change and natural disasters through informal networks and technological adaptation. We will also study adaptation frictions – why moral hazard and adverse selection inhibit the ability to manage climate and disaster risks. In particular we will look at how public adaptation investments interact with private incentives. The module will cover recent studies of these topics using a variety of methodologies including structural models and reduced form causal inference.

The final lecture will look at current applications of satellite data in environmental economics. We will cover how satellite data can be used to measure deforestation, air pollution, crop yields, and more. We will also study potential pitfalls in using satellite data, and how to address common sources of bias.

Structure

• Satellite Data and Machine Learning: Applications, Biases, and Current Research
• Risk and self-insurance facing disasters
• Public Policy, Moral Hazard, and Adverse Selection

Selected key references

• Barreca A. et al., 2016, “Adapting to Climate Change: The Remarkable Decline in the US Temperature-Mortality Relationship over the Twentieth Century”, Journal of Political Economy, 124(1), pp 105-159.
• Carleton T. et al., 2022, “Valuing the Global Mortality Consequences of Climate Change Accounting for Adaptation Costs and Benefits”, Quarterly Journal of Economics, 137(4), pp 2037-2105.
• Deryugina T., Kawano S. & Levitt S., 2018, “The Economic Impact of Hurricane Katrina on Its Victims: Evidence from Individual Tax Returns”, American Economic Journal: Applied Economics, 10(2), pp 202-33.
• Jain M., 2020, “The Benefits and Pitfalls of Using Satellite Data for Causal Inference”, Review of Environmental Economics and Policy, 14(1).
• Meghir C. et al., 2022, “Migration and Informal Insurance: Evidence from a randomized controlled trial and a structural model”, Review of Economics Studies, 89(1), pp 452-480.
• Wagner K., 2022, “Adaptation and Adverse Selection in Markets for Natural Disaster Insurance”, American Economic Journal: Economic Policy, 14(3), pp 380-421.

by Katrin Millock

This module aims at understanding mobility responses to climate change and migration as a means of adaptation to climate change.

The module will focus on the main empirical methods that are used to identify the effects of climate change on migration. The spectrum of models covered will include the random utility model and its empirical counterpart (the gravity model), and general equilibrium models. We will also discuss predictions of future migration flows linked to climate change and to what extent such predictions are reliable. Participants will learn about recent approaches to better model the mechanisms underlying this specific form of adaptation, and the relation of migration to other adaptation strategies. The module thus intends to give participants an understanding of the methods currently used to predict future climate-related migration, and the remaining challenges in identifying mobility responses to climate change.

Structure

• Identifying climate migrants: going from macro flows to micro-economic evidence
• Migration as climate change adaptation: modelling the underlying mechanisms and in situ adaptation choices

Selected key references

• Albert C., Bustos P. & Ponticelli J., 2023, The effects of climate change on labor and capital reallocation, NBER Working Paper N°28995.
• Beine M., Bertoli S. & Fernandez-Huertas Moraga J., 2016, “A Practitioners’ guide to gravity models of international migration”, The World Economy, 39(4), pp 496-512.
• Burzynski M. et al., 2022, “Climate change, inequality and human migration”, Journal of the European Economic Association, 20(3), pp 1145-1197.
• Cattaneo C. et al., 2019, “Human migration in the era of climate change”, Review of Environmental Economics and Policy, 13(2), pp 189-206.
• Dallmann I. & Millock K., 2017, “Climate variability and inter-state migration in India”, CESifo Economic Studies, 63(4), pp 560-594.
• Desmet K. & Rossi-Hansberg E., 2024, “Climate change economics over time and space”, Annual Review of Economics, 16, pp 271-304.
• Liu M., Shamdasani Y. & Taraz V., 2023, “Climate change and labor reallocation: Evidence from six decades of the Indian census”, American Economic Journal: Economic Policy, 15(2), pp 395-423.
• Mahajan P. & Yang, D., 2020, “Taken by the storm: Hurricanes, migrant networks, and U.S. immigration”, American Economic Journal: Applied Economics, 12(2), pp 250-277.

by Hélène Ollivier

This course will cover the latest research on how to estimate the effects of climate change (namely, temperature and rainfall shocks) and natural disasters, taking into account interrelationships arising from trade and input-output linkages. Additionally, we will study the effects of regulation on firms, taking into account cross-dependencies among firms and within firms. Our focus is on ex post analysis and relies on model-based estimation strategies that account for these cross-dependencies. Using workhorse models from international trade and industrial organization, we will derive new implications for our understanding of the effects of climate change, local shocks, and regulation.

Structure

• The Economic Costs of Climate Change
• The Effects of Local Environmental Shocks in an Interconnected World
• The Effects of Regulation on Manufacturing Firms when Firms Compete

Selected key references

• Barrows G. et al., 2023, Equilibrium Effects of Environmental Regulation, CESifo Working Paper N°10438.
• Chen Q. et al., 2021, Regulating Conglomerates in China: Evidence from an Energy Conservation Program, NBER Working Paper N°29066.
• Bento A. et al., 2023, A Unifying Approach to Measuring Climate Change Impacts and Adaptation, NBER Working Paper N°27247.
• Burke M., Hsiang S. & Miguel E., 2015, “Global non-linear effect of temperature on economic production”, Nature, 15725.
• Feng A., Haishi L. & Wang Y., 2023, We Are All in the Same Boat: Cross-Border Spillovers of Climate Shocks through International Trade and Supply Chain, CESifo Working Paper N°10402.
• Carvalho V. et al., 2021, “Supply Chain Disruptions: Evidence from the Great East Japan Earthquake”, Quarterly Journal of Economics, 136(2), pp 1255-1321.

by Nicolas Astier

This course will cover recent empirical research on the decarbonation of energy supply. Because deep decarbonation pathways typically consist in greening electricity generation and moving as many energy uses as possible away from fossil fuels, we will focus on the electricity industry. We will first discuss how to design public policies supporting renewables (mainly wind and solar) that provide incentives to deploy them cost-efficiently. We will then turn to the integration of these installations into existing power systems and electricity industries. In particular, we will discuss some challenges raised by the increasing share of intermittent generation, drawing insights from already available empirical evidence and takeaways from recent energy crises.

Structure

• Deploying renewables cost-efficiently
• Integrating renewables into power systems
• A few lessons from recent energy crises

Selected key references

• Astier N., Rajagopal R. & Wolak F. A., 2023, “Can distributed intermittent renewable generation reduce future grid investments? Evidence from France”, Journal of the European Economic Association, 21(1), pp 367-412.
• Callaway D. S., Fowlie M. & McCormick G., 2018, “Location, location, location: The variable value of renewable energy and demand-side efficiency resources”, Journal of the Association of Environmental and Resource Economists, 5(1), pp 39-75.
• De Groote O. & Verboven F., 2019, “Subsidies and time discounting in new technology adoption: Evidence from solar photovoltaic systems”, American Economic Review, 109(6), pp 2137-2172.
• Hatem N. & Astier N., “Dynamic (Mis) allocation of Investments in Solar Energy”, Journal of the Association of Environmental and Resource Economists, forthcoming.
• Wolak F. A., 2022, “Long-term resource adequacy in wholesale electricity markets with significant intermittent renewables”, Environmental and Energy Policy and the Economy, 3(1), pp 155-220.