EconPapers    
Economics at your fingertips  
 

A tractable overlapping generations structure for quantitative DSGE models

Robert Kollmann ()

Economics Letters, 2022, vol. 221, issue C

Abstract: This paper develops a novel tractable overlapping generations (OLG) structure whose aggregate equations resemble a model of an infinitely lived representative agent, except that there are no aggregate transversality conditions in the OLG economy. The main assumptions are complete markets and time-invariant (but age-dependent) consumption shares of age-groups. The tractability of the OLG structure here distinguishes it from conventional OLG models — the present structure is suitable for quantitative dynamic stochastic general equilibrium (DSGE) macro models. Importantly, the OLG structure here maintains key predictions of standard OLG models, namely the possibility of low real interest rates and of equilibrium indeterminacy.

Keywords: Overlapping generations; DSGE models (search for similar items in EconPapers)
JEL-codes: C6 E1 E3 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S016517652200372X
Full text for ScienceDirect subscribers only

Related works:
Working Paper: A Tractable Overlapping Generations Structure for Quantitative DSGE Models (2022) Downloads
Working Paper: A Tractable Overlapping Generations Structure for Quantitative DSGE Models (2022) Downloads
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:ecolet:v:221:y:2022:i:c:s016517652200372x

DOI: 10.1016/j.econlet.2022.110898

Access Statistics for this article

Economics Letters is currently edited by Economics Letters Editorial Office

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

 
Page updated 2025-03-19
Handle: RePEc:eee:ecolet:v:221:y:2022:i:c:s016517652200372x