Economics at your fingertips  

Genetic Algorithm Learning in a New Keynesian Macroeconomic Setup

Cars Hommes (), Tomasz Makarewicz, Domenico Massaro and T. Smits
Additional contact information
T. Smits: SEO Economic Research

No 15-01, CeNDEF Working Papers from Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance

Abstract: In order to understand heterogeneous behaviour amongst agents, empirical data from Learning-to-Forecast (LtF) experiments can be used to construct learning models. This paper follows up on Assenza et al. (2013) by using a genetic algorithms (GA) model to replicate the results from their LtF experiment. In this GA model individuals optimise an adaptive, a trend following and an anchor coefficient in a population of general prediction heuristics. We replicate experimental treatments in a New-Keynesian environment with increasing complexity and use Monte Carlo simulations to investigate how well the model explains the experimental data. We find that the model is able to replicate the three different types of behaviour in the treatments using one GA model. The research furthermore shows that heterogeneous behaviour can be explained by an adaptive, anchor and trend extrapolating component and therewith contributes to the existing literature in the way that GA can be used to explain heterogeneous behaviour in LtF experiments with different types of complexity.

New Economics Papers: this item is included in nep-cbe and nep-cmp
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed

Downloads: (external link) ... ro.pdf?1420795088061 (application/pdf)

Related works:
Journal Article: Genetic algorithm learning in a New Keynesian macroeconomic setup (2017) 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:

Access Statistics for this paper

More papers in CeNDEF Working Papers from Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance Dept. of Economics and Econometrics, Universiteit van Amsterdam, Roetersstraat 11, NL - 1018 WB Amsterdam, The Netherlands. Contact information at EDIRC.
Bibliographic data for series maintained by Cees C.G. Diks ().

Page updated 2019-07-15
Handle: RePEc:ams:ndfwpp:15-01