Numerical Simulation of Economic Depression

Taiji Harashima

MPRA Paper from University Library of Munich, Germany

Abstract: In this paper, I numerically simulate the path of economy in an economic depression. It is not easy to perform a numerical simulation of the path to a steady state if households are assumed to behave by generating rational expectations. It is much easier, however, if households are assumed to behave according to a procedure based on the maximum degree of comfortability (MDC), where MDC indicates the state at which a household feels most comfortable with its combination of income and assets. The results of simulations under the supposition of this alternative procedure indicate that, if households do not strategically consider other households’ behaviors, consumption jumps upwards immediately after the shock. However, if households strategically select a Pareto inefficient path, large amounts of unutilized economic resources are generated, and the unemployment rate can rise to 30% or higher. These results seem to well match actual historical experiences during severe recessions such as the Great Depression and Great Recession.

Keywords: Economic depression; Shock; Simulation; Recession; Unemployment; Unutilized economic resources (search for similar items in EconPapers)
JEL-codes: E10 E17 E27 E32 E37 (search for similar items in EconPapers)
Date: 2024-03-21
New Economics Papers: this item is included in nep-cmp and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/120508/1/MPRA_paper_120508.pdf original version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:120508

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 ().