Economic and labour market impacts of migration in Austria: an agent-based modelling approach.

Unlabelled: This study examines the potential economic and labour market impacts of a hypothetical but plausible migration scenario of 250,000 new migrants inspired by Austria's experience in 2015. Using the agent-based macroeconomic model developed by Poledna et al. (Eur Econ Rev, 151:104306, 2023.

Revealing indirect risks in complex socioeconomic systems: A highly detailed multi-model analysis of flood events in Austria.

Cascading risks that can spread through complex systems have recently gained attention. As it is crucial for decision-makers to put figures on such risks and their interactions, models that explicitly capture such interactions in a realistic manner are needed. Climate related hazards often cascade through different systems, from physical to economic and social systems, causing direct but also indirect risks and losses.

Quantifying economic resilience from input-output susceptibility to improve predictions of economic growth and recovery.

Modern macroeconomic theories were unable to foresee the last Great Recession and could neither predict its prolonged duration nor the recovery rate. They are based on supply-demand equilibria that do not exist during recessionary shocks. Here we focus on resilience as a nonequilibrium property of networked production systems and develop a linear response theory for input-output economics.

Identifying Systemically Important Companies by Using the Credit Network of an Entire Nation.

The notions of systemic importance and systemic risk of financial institutions are closely related to the topology of financial liability networks. In this work, we reconstruct and analyze the financial liability network of an entire economy using data of 50,159 firms and banks. Our analysis contains 80.

DebtRank-transparency: controlling systemic risk in financial networks.

Nodes in a financial network, such as banks, cannot assess the true risks associated with lending to other nodes in the network, unless they have full information on the riskiness of all other nodes. These risks can be estimated by using network metrics (as DebtRank) of the interbank liability network. With a simple agent based model we show that systemic risk in financial networks can be drastically reduced by increasing transparency, i.