Internal Rationality, Learning and Imperfect Information

Abstract

We construct, estimate and explore the monetary policy consequences of a New Keynesian (NK) behavioural model with bounded-rationality and heterogeneous agents. We radically depart from most existing models of this genre in our treatment of bounded rationality and learning. Instead of the usual Euler learning approach, we assume that agents are internally rational (IR) given their beliefs of aggregate states and prices. The model is inhabited by fully rational (RE) and IR agents where the latter use simple heuristic rules to forecast aggregate variables exogenous to their micro-environment. We find that IR results in an NK model with more persistence and a smaller policy space for rule parameters that induce stability and determinacy. In the most general form of the model, agents learn from their forecasting errors by observing and comparing them with those under RE making the composition of the two types endogenous. In a Bayesian estimation with fixed proportions of RE and IR agents and a general heuristic forecasting rule we find that a pure IR model fits the data better than the pure RE case. However, the latter with imperfect rather than the standard perfect information assumption outperforms IR (easily) and RE-IR composites (slightly), but second moment comparisons suggest that the RE-IR composite can match data better. Our findings suggest that Kalman-filtering learning with RE can match bounded-rationality in matching persistence seen in the data.

Fiscal stimulus in expectations-driven liquidity traps

“…Branch (2004Branch ( , 2007). Other works with similar heterogeneous expectations frameworks include Elton et al (2017), Massaro (2013) and Deák et al (2017). In terms of micro-foundations and aggregation of heterogeneous expectations the current paper is also related to these three papers.…”

Beliefs formation and the puzzle of forward guidance power

“…1 1 Opposed with the Euler learning approach of most of the literature, agents are assumed to be internally rational, i.e., they optimize given their beliefs of aggregate states and prices and face a …xed cost of being fully rational. Deak et al (2016), Jump and Levine (2017) for details.…”

On the Estimation of Behavioral Macroeconomic Models via Simulated Maximum Likelihood

“…As a result, various approaches advocate the design of optimal policy strategies within a behavioral model framework, while the alternative explanation of expectation formation has rapidly gained attention in macroeconomics in recent years. That is in large part due to both existing suspicions regarding the rational expectation paradigm and the availability of powerful computers that enable extensive numerical simulations of macroeconomic models (Hommes, 2006;Windrum et al, 2007;Fagiolo et al, 2007;LeBaron and Tesfatsion, 2008;De Grauwe, 2011, 2012Deák et al, 2017;Gabaix, 2017).…”

“…For example, the moment conditions are replaced by simulated counterparts, and more accurate estimation can be obtained through long simulations of behavioral variables (Franke, 2009;Franke and Westerhoff, 2012;Jang and Sacht, 2016;Grazzini and Richiardi, 2015;Franke, 2018). In particular, if prior distributions of macroeconomic variables are widely accepted, then we can rely on Bayesian inference in parameter estimation (Grazzini et al, 2017;Deák et al, 2017). The Bayesian approach is particularly relevant for the estimation of macroeconomic models because the sample size is often not large enough to ensure asymptotic statistical properties.…”

“…They report uninformative estimates for the degree of switching, where the posterior mean is centered around its pseudo-true value but the corresponding posterior distribution does not depart significantly from the prior one. Deák et al (2017) also use Bayesian estimation to compare forecasting errors under rational expectations (RE) with those under bounded rational (BR) and learning in a New Keynesian behavioral model. Jang and Sacht (2016) and Jang and Sacht (2018) consider both the purely forward-looking and hybrid version of the NKM.…”