Dipartimento di Ingegneria Gestionale

Climate economics and modeling

About the project

This research projects investigates the economics and modeling of national and international climate policies. We use tools from behavioural economics, integrated assessment modeling, agent based modeling to evaluate climate protection strategies aimed at reducing greenhouse gases and adapting to climate change economic, environmental and social impacts.

Principal Investigators: Massimo Tavoni

Researcher team: Massimo Tavoni, Giacomo Marangoni, Arianna Galliera, Jacopo Bonan, Matteo Fontana

Funders: ERC

Duration: Till 2019

Partners: None


–          Longer description included key research questions (2000 caratteri spazi inclusi)

The objective of COBHAM is to study behavior and interactions among individuals and their impact on energy efficiency and climate change mitigation. The project aims at increasing our understanding of human behavior in relation to the environment and in developing models able to incorporate the heterogeneity and the complex dynamics of individual decision making. The project integrates different disciplines –behavioural economics, complex networks, big data analytics, integrated assessment modeling- with the objective to go beyond the standard analysis of energy and climate policies in the presence of environmental externalities, by accounting for the heterogeneity in consumers’ preferences, the role of social interactions, and the presence of behavioral tendencies and biases.

Specifically the project aim at:

  • understand and test the potential of behavioral interventions to promote energy efficiency, pro-environmental behaviour, and adoption of green technologies
  • model energy demand response using the big data coming from smart meters and devices;
  • build a behaviorally founded integrated assessment model for the assessment of climate change and energy policies.

In doing so, the project provides a richer characterization of energy demand response, to evaluate the impact of behavioural (‘nudges’) and traditional interventions on emission reductions, and to provide input to the design of new policy instruments aimed at influencing energy and environmental sustainable behavior. In order to generate robust estimates of the efficacy of these behavioral interventions, several formal methods are used.

Randomization methods such as Randomized Control Trials (RCT) and lab/web experiments allow us to evaluate the causal relations between policy interventions and pro-environmental behaviour, by comparing proper treatment and control groups. Big data analytics using the large amount of data coming from the smart meters and online platforms is used to carry out statistical analysis of energy demand response. Numerical modeling tools will allow us to assess the welfare impacts of climate and energy policies.


  1.  Ricke, Katharine, Laurent Drouet, Ken Caldeira, and Massimo Tavoni. “Country-Level Social Cost of Carbon.” Nature Climate Change, September 24, 2018, 1. https://doi.org/10.1038/s41558-018-0282-y
  2. Luderer G. et. al “Residual fossil CO 2 emissions in 1.5–2 °C pathways”, Nature Climate Change, 2018, 8:626-633
  3. Vinca, A., J. Emmerling and M. Tavoni “Bearing the Cost of Stored Carbon Leakage” May 2018, Frontiers in Energy Research 6(40):1-11
  4. Jewell et al. “Limited Emission Reductions from Fuel Subsidy Removal except in Energy-Exporting Regions.” Nature 554, no. 7691 (February 2018): 229–33. https://doi.org/10.1038/nature25467.
  5.  Rogelj, J. et al. “Scenarios towards Limiting Global Mean Temperature Increase below 1.5 °C.” Nature Climate Change, March 5, 2018, 1. https://doi.org/10.1038/s41558-018-0091-3.
  6. R B Jackson, Canadell J, Fuss S.,Milne J, Nakicenovic N. and M Tavoni 2017 ‘Focus on negative emissions’, Environmental Research Letters, Volume 12, Number 11
  7. Witajewski-Baltvilks, J., Verdolini, E. & Tavoni, M 2017 ‘Induced Technological Change and Energy Efficiency Improvements’, Energy Economics (2017). doi:10.1016/j.eneco.2017.10.032
  8. Nicolini and Tavoni 2017 ‘Are renewable energy subsidies effective? Evidence from Europe’, Renewable and Sustainable Energy Reviews 74:412-423
  9. Bonan, Pareglio and Tavoni 2017 ‘Access to modern energy: a review of barriers, drivers and impacts’, Environment and Development Economics, 1-26
  10. van Soest et. al. 2017 ‘Low-emission pathways in 11 major economies: comparison of cost-optimal pathways and Paris climate proposals’ Climatic Change 142(3):491-504 · April 2017
  11. d’Adda, Capraro and Tavoni 2017 ‘Push, don’t nudge: Behavioral spillovers and policy instruments’, Economics Letters, 154, 92–95
  12. Bosetti et. al. 2017 ‘COP21 climate negotiators’ responses to climate model forecasts’, Nature Climate Change, 7 (2017) doi:10.1038/nclimate3208
  13. Marangoni, Tavoni et. al. 2017 ‘Sensitivity of projected long-term CO2 emissions across the Shared Socioeconomic Pathways’, Nature Climate Change, doi:10.1038/nclimate3199
  14. Emmerling and Tavoni, 2017 ‘Climate Engineering and Abatement: A ‘flat’ Relationship Under Uncertainty’, Environmental and Resource Economics, doi:10.1007/s10640-016-0104-5