Heuristic Switching Model and Exploration-Exploitation Algorithm to Describe Long-Run Expectations in LtFEs: a Compariso
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Heuristic Switching Model and Exploration-Exploitation Algorithm to Describe Long-Run Expectations in LtFEs: a Comparison Annarita Colasante1
· Simone Alfarano1 · Eva Camacho-Cuena1
Accepted: 16 November 2019 © Springer Science+Business Media, LLC, part of Springer Nature 2019
Abstract We elicit individual expectations in a series of Learning-to-Forecast Experiments (LtFEs) with different feedback mechanisms between expectations and market price: positive and negative feedback markets. We implement the EEA proposed by Colasante et al. (J Evol Econ 2018b. https://doi.org/10.1007/S00191-018-0585-1). We compare the performance of two learning algorithms in replicating individual short and longrun expectations: the Exploration-Exploitation Algorithm (EEA) and the Heuristic Switching Model (HSM). Moreover, we modify the existing version of the HSM in order to incorporate the long run predictions. Although the two algorithms provide a fairly good description of prices in the short run, the EEA outperforms the HSM in replicating the main characteristics of individual expectation in the long-run, both in terms of coordination of individual expectations and convergence of expectations to the fundamental value. Keywords Expectations · Experiment · Evolutionary learning JEL Classification D03 · G12 · C91
1 Introduction The origin of heterogeneity across individual expectations and the role that it plays in shaping aggregate outcomes is an important topic in theoretical as well as empirical research in macroeconomics. Unlike the stock prices, volumes of sold books, interest rates of bonds, downloads or number of likes, which can be precisely measured and recorded in the new world where almost “everything” is now in an electronic format, expectations are not directly observable. This means that there is a significant limi-
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Annarita Colasante [email protected] University Jaume I, Castellon de la plana, Spain
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tation when it comes to fully understanding the precise role played by expectations in driving macroeconomic aggregates. One way to circumvent this problem and rigorously model the expectations of individuals is to assume consistent expectations, i.e. rational expectations, following the seminal idea of Muth (1961), which has been further developed by Lucas Jr and Prescott (1971). From a formal point of view, the main advantage of rational expectations is that agents can be rational in one way only. The argument put forward by Friedman and Friedman (1953) on the irrelevance of “irrational” individuals in the long run gives further intuitive appeal to the rationality assumption. As an alternative to the rational expectations paradigm, it certainly plays a central role in the bounded rationality assumption of economic agents introduced by Simon (1966). In the world of bounded rational agents, we typically lose the uniqueness of the behavior, as agents can be “non-rational” in many different ways. Laboratory experiments have been largely demonstrated to be an essential methodology for
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