Hostname: page-component-848d4c4894-75dct Total loading time: 0 Render date: 2024-05-18T15:50:02.238Z Has data issue: false hasContentIssue false
  • English
  • Français

Adaptive agents may be smarter than you think: unbiasedness in adaptive expectations

Published online by Cambridge University Press:  15 April 2024

A. Palestrini ,
D. Delli Gatti ,
M. Gallegati  and
B. Greenwald
A. Palestrini*
Affiliation:
Università Politecnica delle Marche, Ancona, Italy
D. Delli Gatti
Affiliation:
Catholic University of Milan, Milan, Italy
M. Gallegati
Affiliation:
Università Politecnica delle Marche, Ancona, Italy
B. Greenwald
Affiliation:
Columbia University, New York, NY, USA
*
Corresponding author: Antonio Palestrini; Email: a.palestrini@univpm.it
Get access Rights & Permissions [Opens in a new window]

Abstract

Experimental evidence shows that human subjects frequently rely on adaptive heuristics to form expectations but their forecasting performance in the lab is not as inadequate as assumed in macroeconomic theory. In this paper, we use an agent-based model (ABM) to show that the average forecasting error is indeed close to zero even in a complex environment if we assume that agents augment the canonical adaptive algorithm with a Belief Correction term which takes into account the previous trend of the variable of interest. We investigate the reasons for this result using a streamlined nonlinear macro-dynamic model that captures the essence of the ABM.

Keywords

Adaptive expectationsBelief Correctionagent-based modelsC63D83D84E71
Type
Articles
Information
Macroeconomic Dynamics , First View , pp. 1 - 24
Copyright
© The Author(s), 2024. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Anufriev, M., Hommes, C. and Makarewicz, T.. (2019) Simple forecasting heuristics that make us smart: evidence from different market experiments. Journal of the European Economic Association 17(5), 1538–1584.CrossRefGoogle Scholar
Assenza, T., Heemeije, P., Hommes, C., Massaro, D.. (2019) Managing self-organization of expectations through monetary policy: a macro experiment. Journal of Monetary Economics 117(2021), 170–186.CrossRefGoogle Scholar
Assenza, T., Bao, T., Hommes, C. and Massaro, D.. (2014) Experiments on expectations in macroeconomics and finance. In Experiments in Macroeconomics, pp. 11–70. Emerald Group Publishing Limited.CrossRefGoogle Scholar
Branch, W. A. and McGough, B.. (2018) Heterogeneous expectations and micro-foundations in macroeconomics. Handbook of Computational Economics 4, 3–62.CrossRefGoogle Scholar
Clements, M. P. (2019) Macroeconomic survey expectations. Cham, Switzerland: Palgrave Macmillan.CrossRefGoogle Scholar
Colasante, A., Palestrini, A., Russo, A. and Gallegati, M.. (2017) Adaptive expectations versus rational expectations: evidence from the lab. International Journal of Forecasting 33(4), 988–1006.CrossRefGoogle Scholar
Dawid, H. and Gatti, D. D.. (2018) Agent-based macroeconomics. In: Dawid, H. and Gatti, D. D.. (eds.), Handbook of Computational Economics, vol. 4, pp. 63–156. Elsevier.Google Scholar
Dosi, G., Napoletano, M., Roventini, A., Stiglitz, J. E. and Treibich, T.. (2017) Rational heuristics? Expectations and behaviors in evolving economies with heterogeneous interacting agents. Economic Inquiry 58(3), 1487–1516.CrossRefGoogle Scholar
Brock, W. & Hommes, C.. (1997) A rational route to randomness. Econometrica 9(1), 1059–1095.CrossRefGoogle Scholar
Evans, G. W. and Honkapohja, S.. (2001) Learning and expectations in macroeconomics.Princeton, New Jersey: Princeton University Press.CrossRefGoogle Scholar
Hansen, L. P. and Sargent, T. J.. (2014). Uncertainty within economic models, World Scientific Series in Economic Theory.CrossRefGoogle Scholar
Heemeijer, P., Hommes, C., Sonnemans, J. and Tuinstra, J.. (2009) Price stability and volatility in markets with positive and negative expectations feedback: an experimental investigation. Journal of Economic Dynamics and Control 33(5), 1052–1072.CrossRefGoogle Scholar
Hommes, C. (2013) Behavioral rationality and heterogeneous expectations in complex economic systems. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
Hommes, C. and Zhu, M.. (2014) Behavioral learning equilibria. Journal of Economic Theory 150, 778–814.CrossRefGoogle Scholar
Kahneman, D. (2011) Thinking Fast and Slow. New York: Allen Lane and Penguin Books.Google Scholar
Muth, J. F. (1961) Rational expectations and the theory of price movements. Econometrica: Journal of the Econometric Society 29(3), 315–335.CrossRefGoogle Scholar
Palestrini, A. (2017) Expectation models in agent-based computational economics. In Introduction to Agent-Based Economics, pp. 127–142. Elsevier.CrossRefGoogle Scholar
Palestrini, A. and Gallegati, M.. (2015) Unbiased adaptive expectation schemes. Economics Bulletin 35(2), 1185–1190.Google Scholar
Poledna, S., Miess, M. G. and Hommes, C.. (2023) Economic forecasting with an agent-based model. European Economic Review 151, 104306.CrossRefGoogle Scholar
Salle, I. L. (2015) Modeling expectations in agent-based models–an application to central bank’s communication and monetary policy. Economic Modelling 46, 130–141.CrossRefGoogle Scholar
Satopää, V. A. (2017) Combining information from multiple forecasters: inefficiency of central tendency, arXiv preprint arXiv: 1706.06006.Google Scholar
Sims, C. (1998) Stickiness. Carnegie-Rochester Conference Series on Public Policy 49, 317–356.CrossRefGoogle Scholar
Sims, C. (2003) Implications of rational inattention. Journal of Monetary Economics 50(3), 665–690.CrossRefGoogle Scholar