This paper presents a complex, modular, 1:1 scale model of the Hungarian residential housing market. All of the 4 million households with their relevant characteristics and all of the flats with detailed attributes like size, state and neighbourhood quality are represented, based on empirical...

This paper presents a complex, modular, 1:1 scale model of the Hungarian residential housing market. All the 4 million house‐ holds and their relevant characteristics are represented based on empirical micro‐level data coming from the Central Credit Information System, the Pension Payment...

In this paper, we have developed an agent-based Keynesian macro model that features a detailed representation of a banking system, besides households and firms, and in which fiscal, monetary and macroprudential policy regulators also operate. The banking system generates longer credit cycles on...

In this paper, relying on a time-varying parameters FAVAR model, two credit supply factors are calculated, the first of which is identified as willingness to lend, while the second as lending capacity. The impact of these two types of credit supply shocks on macroeconomic variables and their...

The high ratio of loans over 90 days past due, i.e. nonperforming mortgage loans, is the legacy of the crisis and the excessive lending that preceded it. The volume has continuously grown over the past six years and by the end of 2014 accounted for one quarter of the total mortgage portfolio,...

Crises like COVID-19 or the Japanese earthquake in 2011 exposed the fragility of corporate supply networks. The production of goods and services is a highly interdependent process and can be severely impacted by the default of critical suppliers or customers. While knowing the impact of...

Realistic credit risk assessment, the estimation of losses from counterparty's failure, is central for the financial stability. Credit risk models focus on the financial conditions of borrowers and only marginally consider other risks from the real economy, supply chains in particular. Recent...