Tackling climate change through energy efficiency: mathematical models for evidence-based public policy recommendations
Federico Gallo, Pierluigi Contucci, Adam Coutts, Ignacio Gallo

TL;DR
This paper introduces a new family of mathematical models based on statistical mechanics and discrete choice theory to analyze and promote energy-efficient behaviors, aiding evidence-based climate policy development.
Contribution
It presents a novel modeling framework that incorporates social interactions and tipping points to better understand and influence energy-efficient lifestyle adoption.
Findings
Models can predict adoption rates of energy-efficient products.
Social influence significantly impacts decision-making.
Identifies societal tipping points for behavioral change.
Abstract
Promoting and increasing energy efficiency is a promising method of reducing CO2 emissions and avoiding the potentially devastating effects of climate change. The question is: How do we induce a cultural or behavioural change whereby people nationally and globally adopt more energy efficient lifestyles? We propose a new family of mathematical models, based on a statistical mechanics extension of discrete choice theory, that offer a set of formal tools to systematically analyse and quantify this problem. An application example could be to predict the percentage of people choosing to buy new energy efficient light bulbs instead of the traditional incandescent versions. Through statistical evaluation of survey responses, the models can identify the key driving factors in the decision-making process; for example, the extent to which people imitate each other. These models allow us to…
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Taxonomy
TopicsEconomic and Environmental Valuation · Environmental Education and Sustainability · Urban Transport and Accessibility
