The debt trap: a two-compartment train wreck

Marc Artzrouni () and Fabio Tramontana

MPRA Paper from University Library of Munich, Germany

Abstract: We aim to shed light on the debate among policy-makers trying to find prescriptions that will take troubled economies out of their debt trap. We do this with a highly stylized two-compartment dynamic model consisting of the stocks of money in Government and Society. The dynamics of the system are described by a simple four-parameter linear system of two differential equations. The solutions are investigated in closed form and provide precisely quantified "escape conditions" from the debt trap: receipts must be slightly larger than outlays and there must be sufficient annual inflows of funds into the system. The model fits the data for the U.S. between 1981 and 2012 with a coefficient of correlation of 0.996. The model is used to extrapolate the two stocks beyond 2012 with three escape scenarios which shed light on monetary flows needed to take the U.S. economy out of its debt trap.

Keywords: Compartmental model; debt; system of differential equations; dynamical system; fiscal policy. (search for similar items in EconPapers)
JEL-codes: C51 C62 C63 E61 H63 (search for similar items in EconPapers)
Date: 2013-06-13
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/47578/1/MPRA_paper_47578.pdf original version (application/pdf)
https://mpra.ub.uni-muenchen.de/50347/9/MPRA_paper_50347.pdf revised 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:47578

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 ().