Agent-based macroeconomics and dynamic stochastic general equilibrium models: where do we go from here?
Dilaver, Özge, Calvert Jump, Robert ORCID: https://orcid.org/0000-0002-2967-512X and Levine, Paul ORCID: https://orcid.org/0000-0002-8639-1967 (2018) Agent-based macroeconomics and dynamic stochastic general equilibrium models: where do we go from here? Journal of Economic Surveys, 32 (4). pp. 1134-1159. ISSN 0950-0804 (Print), 1467-6419 (Online) (doi:10.1111/joes.12249)
Full text not available from this repository. (Request a copy)Abstract
Agent‐based computational economics (ACE) has been used for tackling major research questions in macroeconomics for at least two decades. This growing field positions itself as an alternative to dynamic stochastic general equilibrium (DSGE) models. In this paper, we provide a much needed review and synthesis of this literature and recent attempts to incorporate insights from ACE into DSGE models. We first review the arguments raised against DSGE in the macroeconomic ACE (macro ACE) literature, and then review existing macro ACE models, their explanatory power and empirical performance. We then turn to the literature on behavioural New Keynesian models that attempts to synthesize these two approaches to macroeconomic modelling by incorporating insights of ACE into DSGE modelling. Finally, we provide a thorough description of the internally rational New Keynesian model, and discuss how this promising line of research can progress.
Item Type: | Article |
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Uncontrolled Keywords: | agent‐based computational economics, agent‐based macroeconomics, dynamic stochastic general equilibrium models, new Keynesian behavioural models |
Subjects: | H Social Sciences > HB Economic Theory |
Faculty / School / Research Centre / Research Group: | Faculty of Business Faculty of Business > Department of International Business & Economics Faculty of Business > Institute of Political Economy, Governance, Finance and Accountability (IPEGFA) |
Last Modified: | 21 Oct 2020 11:16 |
URI: | http://gala.gre.ac.uk/id/eprint/25268 |
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