Heterogeneous Expectations and Micro-Foundations in Macroeconomics ✶ ✶We are grateful to the editors, Cars Hommes and Blake LeBaron, as well as Guillaume Rocheteau and three anonymous referees for many helpful comments.

Branch, William A.; McGough, Bruce

doi:10.1016/bs.hescom.2018.03.001

Cited by 15 publications

(6 citation statements)

References 60 publications

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“…the chapters in the Handbook of Computational Economics, Vol. 4, Heterogeneous Agent Modeling (Hommes and LeBaron, 2018), in particular the chapter of Branch and McGough (2018) on the micro-foundations of heterogeneous agents macro models and the recent survey on behavioral macroeconomics provided in Hommes (2021).…”

Section: Related Literaturementioning

confidence: 99%

Rational vs. Irrational Beliefs in a Complex World

Boehl,

Hommes

2024

Preprint

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Section: Related Literaturementioning

confidence: 99%

Rational vs. Irrational Beliefs in a Complex World

Boehl,

Hommes

2024

Preprint

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“…3 This observation was first coined as 'magic' 1 This approach is also reminiscent of modifications that have been made to basic modern macroeconomic models to take account of what Angeletos and Lian (2016) describe as "the potential fragility of workhorse macroeconomic models to relaxations of common knowledge". See Kirman (2006) for an overview of the role of heterogeneity in economics, Branch and McGough (2018) for a discussion of the role of heterogeneous expectations in macroeconomics, and Bookstaber and Kirman (2018) on the difficulties with building both theoretical and computational models of heterogeneous agents even when the nature of the heterogeneity is known and understood. 2 See also McKelvey et al (2000) and Weizsäcker (2003) for earlier investigations of equilibrium models of games played by non-homogenous agents.…”

Section: Introductionmentioning

confidence: 99%

Relaxing the symmetry assumption in participation games: a specification test for cluster-heterogeneity

Kirman¹,

Laisney

Pezanis-Christou

2023

Exp Econ

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We propose a novel approach to check whether individual behaviour in binary-choice participation games is consistent with the restrictions imposed by symmetric models. This approach allows in particular an assessment of how much cluster-heterogeneity a symmetric model can tolerate to remain consistent with its behavioural restrictions. We assess our approach with data from market-entry experiments which we analyse through the lens of ‘Exploration versus Exploration’ (EvE, which is equivalent to Logit-QRE) or of Impulse Balance Equilibrium (IBE). We find that when the symmetry assumption is imposed, both models are typically rejected when assuming pooled data and IBE yields more data-consistent estimates than EvE, i.e., IBE’s estimates of session and pooled data are more consistent than those of EvE. When relaxing symmetry, EvE (IBE) is rejected for 17% (42%) of the time. Although both models support cluster-heterogeneity, IBE is much less likely to yield over-parametrised specifications and insignificant estimates so it outperforms EvE in accommodating a model-consistent cluster-heterogeneity. The use of regularisation procedures in the estimations partially addresses EvE’s shortcomings but leaves our overall conclusions unchanged.

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“…The challenge posed by the wilderness is clearly demonstrated by the sheer size of literature on behavioural macroeconomics and the huge number of equilibria proposed. Surveys include References [6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Reinforcement Learning in a New Keynesian Model

et al. 2023

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We construct a New Keynesian (NK) behavioural macroeconomic model with bounded-rationality (BR) and heterogeneous agents. We solve and simulate the model using a third-order approximation for a given policy and evaluate its properties using this solution. The model is inhabited by fully rational (RE) and BR agents. The latter are anticipated utility learners, given their beliefs of aggregate states, and they use simple heuristic rules to forecast aggregate variables exogenous to their micro-environment. In the most general form of the model, RE and BR agents learn from their forecasting errors by observing and comparing them with each other, making the composition of the two types endogenous. This reinforcement learning is then at the core of the heterogeneous expectations model and leads to the striking result that increasing the volatility of exogenous shocks, by assisting the learning process, increases the proportion of RE agents and is welfare-increasing.

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Heterogeneous Expectations and Micro-Foundations in Macroeconomics ✶ ✶We are grateful to the editors, Cars Hommes and Blake LeBaron, as well as Guillaume Rocheteau and three anonymous referees for many helpful comments.

Cited by 15 publications

References 60 publications

Rational vs. Irrational Beliefs in a Complex World

Rational vs. Irrational Beliefs in a Complex World

Relaxing the symmetry assumption in participation games: a specification test for cluster-heterogeneity

Reinforcement Learning in a New Keynesian Model

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