Lessons learned from randomized controlled experiments for energy and climate

Over the past 10 years, we have run over 10 large-scale field experiments with randomized counterfactuals focused on climate and energy. We have tested a variety of behavioral interventions to promote energy conservation, load shifting, and green technology adoption. High-frequency energy metering has allowed us to evaluate the impacts of these interventions at a high level of granularity and detail.
In this talk, we plan to report on the lessons learned accumulated over the years. We discuss issues related to internal and external validity of the main findings, summarize the main results in terms of effectiveness in reducing energy and CO2 emissions, and most important heterogeneous effects.
We highlight the challenges and opportunities of using large-scale experimental methods in combination with big data and with alternative elicitation processes. We highlight the challenges and opportunities of using large-scale experimental methods in combination with big data and with alternative elicitation processes, such as surveys or labs-in-the-field.
We conclude with a research process to make experimental methods more relevant in future IPCC assessments.