Estimation of heuristic switching in behavioral macroeconomic models

This is a pre-print of an article published in the Journal of Economic Dynamics and Control (2023). The final authenticated version is available online at DOI: doi.org/10.1016/j.jedc.2022.104585

29 Pages Posted: 22 Mar 2021 Last revised: 11 Jun 2023

See all articles by Jiri Kukacka

Jiri Kukacka

Charles University - Institute of Economic Studies; Academy of Sciences of the Czech Republic

Stephen Sacht

University of Kiel

Date Written: December 2, 2022

Abstract

This paper addresses the issue of empirical validation of macroeconomic models with behavioral heuristics and a nonlinear switching mechanism. Heuristic switching is an important feature of modeling strategy since it uses simple decision rules of boundedly rational heterogeneous agents. The simulation study shows that the proposed simulated maximum likelihood method well identifies behavioral effects that remain hidden under standard econometric approaches. In the empirical application, we estimate the structural and behavioral parameters of the US economy. We are specifically able to reliably identify the intensity of choice that governs the models' nonlinear dynamics. Our empirical results thus lay the foundation for studying monetary and fiscal policy in a behavioral macroeconomic framework.

Keywords: behavioral heuristics, heuristic switching model, intensity of choice, simulated maximum likelihood

JEL Classification: C53, E12, E32, E71

Suggested Citation

Kukacka, Jiri and Sacht, Stephen, Estimation of heuristic switching in behavioral macroeconomic models (December 2, 2022). This is a pre-print of an article published in the Journal of Economic Dynamics and Control (2023). The final authenticated version is available online at DOI: doi.org/10.1016/j.jedc.2022.104585, Available at SSRN: https://ssrn.com/abstract=3792139 or http://dx.doi.org/10.2139/ssrn.3792139

Jiri Kukacka (Contact Author)

Charles University - Institute of Economic Studies ( email )

Opletalova 26
Prague 1, CZ-11000
Czech Republic

HOME PAGE: http://ies.fsv.cuni.cz/en/contacts/people/58305408

Academy of Sciences of the Czech Republic ( email )

Pod Vodarenskou vezi 4
Prague 8, CZ-18200
Czech Republic

HOME PAGE: http://www.utia.cas.cz/people/kukacka

Stephen Sacht

University of Kiel ( email )

Olshausenstr. 40
D-24118 Kiel, Schleswig-Holstein 24118
Germany

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