Abstract
There is an ongoing discussion concerning the relationship between social welfare and climate change, and thus the required level and type of measures needed to protect the climate. Integrated assessment models (IAMs) have been extended to incorporate technological progress, heterogeneity and uncertainty, making use of a (stochastic) dynamic equilibrium approach in order to derive a solution. According to the literature, the IAM class of models does not take all the relationships among economic, social and environmental factors into account. Moreover, it does not consider these interdependencies at the micro-level, meaning that all possible consequences are not duly examined. Here, we propose an agent-based approach to analyse the relationship between economic welfare and climate protection. In particular, our aim is to analyse how the decisions of individual agents, allowing for the trade-off between economic welfare and climate protection, influence the aggregated emergent economic behaviour. Using this model, we estimate a damage function, with values in the order 3% - 4%for 2 C temperature increase and having a linear (or slightly concave) shape. We show that the heterogeneity of the agents, technological progress and the damage function may lead to lower GDP growth rates and greater temperature-related damage than what is forecast by models with solely homogeneous (representative) agents.
Highlights
Within the regional DICE model [RICE, (Nordhaus & Boyer )], heterogeneity of regional impacts and income inequalities are investigated by Dennig et al ( ), presenting estimates on the per capita consumption of the poorest agents and showing the poorest in all regions can participate in economic growth when carbon pricing is optimal in a world with inversely proportional damage
To be able to take into account both changing capital goods prices and changing overnight investment cost, we model physical capital as the product of capacity and the overnight investment cost, whereas capital value remains a product of physical capital and the capital goods price
We present the results of three di erent analyses : . selected scenario analysis without damages
Summary
Extensions of MIND are, for instance, addressing uncertainty over selected parameters by chance constraint programming (Held et al ), heterogeneous regions (Leimbach et al ), value of learning (Lorenz et al ), and cost-risk analysis (Neubersch et al ) In the latter approach, the goal function includes a weighted sum of the welfare measure and the risk of exceeding the climate (temperature) target over the optimisation horizon. The IAM by Sche ran ( ) considers energy production technologies causing low or high carbon emissions within an adaptive optimisation process Such a modelling approach can provide decision support to negotiate admissible emission trajectories and to better understand the choices of climate politics, including multiple agents and their interdependencies. Agent-Based Models (ABMs), by contrast, “seek to provide more realistic representations of socio-economics by simulating the economy through the interactions of a large number of di erent agents, on the basis of specific rules” (Stern )
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