A simple aggregate demand analysis with dynamic optimization in a small open economy

Ken-ichi Hashimoto and Yoshiyasu Ono

Economic Modelling, 2020, vol. 91, issue C, 89-99

Abstract: We develop a very simple aggregate demand analysis of a small open economy that suffers from secular demand stagnation. It looks like the conventional Keynesian cross analysis but considers dynamically optimizing behavior of households and firms, international capital movement, and the current account adjustment. We find that parameter changes that improve the current account yield an appreciation pressure on the home currency and decrease demand for the home commodity and labor. Consequently, they worsen deflation and decrease consumption and income. This result is quite opposite to that under full employment. For example, an exogenous rise in the price of the home commodity decreases employment, consumption and income. If a country owns greater foreign assets, it suffers from less employment, consumption and income.

Keywords: Aggregate demand shortage; Unemployment; Small open economy (search for similar items in EconPapers)
JEL-codes: E12 E13 E21 E24 F32 F41 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S026499931931867X
Full text for ScienceDirect subscribers only

Related works:
Working Paper: A simple aggregate demand analysis with dynamic optimization in a small open economy (2019)
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:eee:ecmode:v:91:y:2020:i:c:p:89-99

DOI: 10.1016/j.econmod.2020.04.019

Access Statistics for this article

Economic Modelling is currently edited by S. Hall and P. Pauly

More articles in Economic Modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().