Faraway, So Close: Coupled Climate and Economic Dynamics in an Agent-based Integrated Assessment Model

Abstract

In this paperwe develop the first agent-based integrated assessment model, which offers an alternative to standard, computable general-equilibrium frameworks. The Dystopian Schumpeter meeting Keynes (DSK) model is composed of heterogeneous firms belonging to capital-good, consumption-good and energy sectors. Production and energy generation lead to greenhouse gas emissions, which affect temperature dynamics in a non-linear way. Increasing temperature triggers climate damages hitting, at the micro-level, workers' labor productivity, energy efficiency, capital stock and inventories of firms. In that, aggregate damages are emerging properties of the out-of-equilibrium interactions among heterogeneous and boundedly rational agents. We find the DSK model is able to account for a wide ensemble of micro and macro empirical regularities concerning both economic and climate dynamics. Moreover, different types of shocks have heterogeneous impact on output growth, unemployment rate, and the likelihood of economic crises. Finally, we show that the magnitude and the uncertainty associated to climate change impacts increase over time, and that climate damages much larger than those estimated through standard IAMs. Our results point to the presence of tipping points and irreversible trajectories, thereby suggesting the need of urgent policy interventions.

Creating Agent-Based Energy Transition Management Models That Can Uncover Profitable Pathways to Climate Change Mitigation

“…One of the first examples of combining complex economies with climate models comes from the LAGOM model family that is able to deal with different timescales for modules and spatially distributed energy production and pollution [73][74][75] but it is not yet an IAM. The first fully fledged agent-based IAM might be the Dystopian Schumpeter meeting Keynes (DSK) model from Lamperti et al [76].…”

Agent-Based Macroeconomics

“…The model has been used to analyze labor market issues and the effects of structural reforms in Napoletano et al (2012), Dosi et al (2017d), Dosi et al (2018), Dosi et al (2017b). For an application to the analysis of the effects of climate change, see Lamperti et al (2017). For a general overview of this KS literature see Dosi et al (2017a) 13 LAGOM is not an acronym (as in the case of the other families of MABMs) but a Swedish word which means equilibrium and harmony "perhaps akin to the chinese Tao."…”

“…15 It should be mentioned that for several of the MABMs there exist also variants including additional markets, e.g. for housing and electricity, see Lamperti et al (2017), Ozel et al (2016). the behavioral rules that each type of agent (on the columns) follows in each of the different markets the agent is active (on the rows).…”

Agent-Based Model Calibration Using Machine Learning Surrogates

“…As stated by Chen et al (2012), 5 See e.g. Dosi et al (2010Dosi et al ( , 2013Dosi et al ( , 2015; Caiani et al (2016); Assenza et al (2015) and Dawid et al (2014a) on business cycle dynamics, Lamperti et al (2017) on growth, green transitions and climate change, Dawid et al (2014b) on regional convergence and Leal et al (2014) on financial markets. The surveys in Roventini (2012, 2017) provides a more exhaustive list.…”