Income inequality, consumption, credit and credit risk in a data-driven agent-based model
MPRA Paper from University Library of Munich, Germany
The issue of income inequality occupies a prominent position in the research agenda of academic and policy circles alike, especially after the crisis of 2008, due to its potential causal link with the development of credit bubbles and therefore the emergence of financial crises. This paper examines the long-run effect of income inequality on consumption, consumer credit and non-performing loans through the means of a data-driven agent-based model. The data-driven nature of the model enhances its ability to match historical series and thus makes it suitable for policy simulations tailored for specific economies. The analysis indicates that higher income inequality has a detrimental impact on consumption and is associated with lower volumes of consumer credit. However, the ratio of non-performing loans as a share of total loans seems to be independent of income inequality.
Keywords: Income inequality; Consumption; Consumer credit; Non-performing loans; Agent-based model (search for similar items in EconPapers)
JEL-codes: C63 D31 E21 E27 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
https://mpra.ub.uni-muenchen.de/89764/1/MPRA_paper_89764.pdf original version (application/pdf)
Journal Article: Income inequality, consumption, credit and credit risk in a data-driven agent-based model (2019)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:89764
Access Statistics for this paper
More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().