This review presents machine learning (ML) approaches from an applied economist's
perspective. We first introduce the key ML methods drawing connections to econometric …

With its update of the Bioeconomy Strategy and the Green Deal, the European Commission
committed itself to a transformation towards a sustainable and climate-neutral European …

Recently, transformer architectures for graphs emerged as an alternative to established
techniques for machine learning with graphs, such as (message-passing) graph neural …

Which policies can increase the resilience of the financial system to climate risks? Recent
evidence on the significant impacts of climate change and natural disasters on firms, banks …

Efficiently calibrating agent-based models (ABMs) to real data is an open challenge. This
paper explicitly tackles parameter space exploration and calibration of ABMs by combining …

This work nests the Agent-Based macroeconomic perspective into the earlier history of
macroeconomics. We discuss how the discipline in the 70's took a perverse path relying on …

In this work we develop an agent-based model that offers an alternative to standard,
computable general equilibrium integrated assessment models (IAMs). The Dystopian …

We analyse the double materiality of climate physical and transition risks in the euro area
economy and banking sector. First, by tailoring the EIRIN Stock-Flow Consistent behavioural …

In this paper we employ an agent-based integrated assessment model to study the
likelihood of transition to green, sustainable growth in presence of climate damages. The …

Despite significant expansion in recent years, the literature on quantitative and data-driven
approaches to economic agent-based model validation and calibration consists primarily of …