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Unemployment Expectations in an Agent-Based Model with Education

  • Luca Gerotto
  • Paolo Pellizzari
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10978)

Abstract

Why are unemployment expectations of the “man in the street” markedly different from professional forecasts? We present an agent-based model to explain this deep disconnection using boundedly rational agents with different levels of education. A good fit of empirical data is obtained under the assumptions that there is staggered update of information, agents update episodically their estimate and there is a fraction of households who always and stubbornly forecast that the unemployment is going to raise. The model also sheds light on the role of education and suggests that more educated agents update their information more often and less obstinately fixate on the worst possible forecast.

Keywords

Agent-based modeling Bounded rationality Unemployment expectations 

References

  1. 1.
    Carroll, C.D., Hall, R.E., Zeldes, S.P.: The buffer-stock theory of saving: some macroeconomic evidence. Brookings Papers Econ. Act. 1992(2), 61–156 (1992)CrossRefGoogle Scholar
  2. 2.
    Hegselmann, R., Krause, U.: Opinion dynamics and bounded confidence models, analysis, and simulation. J. Artif. Soc. Soc. Simul. 5(3) (2002)Google Scholar
  3. 3.
    Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Rev. Modern Phys. 81(2), 591 (2009)CrossRefGoogle Scholar
  4. 4.
    Hegselmann, R., König, S., Kurz, S., Niemann, C., Rambau, J.: Optimal opinion control: the campaign problem. J. Artif. Soc. Soc. Simul. 18(3) (2015)Google Scholar
  5. 5.
    Carroll, C.D.: The epidemiology of macroeconomic expectations. In: Blume, L.E., Durlauf, S.N. (eds.) The Economy as an Evolving Complex System, III: Current Perspectives and Future Directions, pp. 5–29. Oxford University Press, Oxford (2006)Google Scholar
  6. 6.
    Rabin, M.: Psychology and economics. J. Econ. Lit. 36(1), 11–46 (1998)Google Scholar
  7. 7.
    Camerer, C.F.: Progress in behavioral game theory. J. Econ. Perspect. 11(4), 167–188 (1997)CrossRefGoogle Scholar
  8. 8.
    Branch, W.A.: The theory of rationally heterogeneous expectations: evidence from survey data on inflation expectations. Econ. J. 114(497), 592–621 (2004)CrossRefGoogle Scholar
  9. 9.
    Axtell, R.L., Epstein, J.M.: Coordination in Transient Social Networks: An Agent-Based Computational Model of the Timing of Retirement, pp. 161–183. Brookings Institution Press, Washington DC (1999)Google Scholar
  10. 10.
    Moro, A., Pellizzari, P.: A computational model of labor market participation with health shocks and bounded rationality. Knowl. Inf. Syst. 54(3), 617–631 (2018)CrossRefGoogle Scholar
  11. 11.
    Lusardi, A., Mitchell, O.S.: Financial literacy around the world: an overview. J. Pension Econ. Financ. 10(4), 497–508 (2011)CrossRefGoogle Scholar
  12. 12.
    Souleles, N.S.: Expectations, heterogeneous forecast errors, and consumption: micro evidence from the Michigan consumer sentiment surveys. J. Money Credit Bank. 36(1), 39–72 (2004)CrossRefGoogle Scholar
  13. 13.
    Easaw, J., Golinelli, R., Malgarini, M.: What determines households inflation expectations? Theory and evidence from a household survey. Eur. Econ. Rev. 61, 1–13 (2013)CrossRefGoogle Scholar
  14. 14.
    Epstein, J.M.: Why model? J. Artif. Soc. Soc. Simul. 11(4), 12 (2008)Google Scholar
  15. 15.
    Epstein, J.M.: Generative Social Science: Studies in Agent-Based Computational Modeling. Princeton University Press, Princeton (2006)CrossRefGoogle Scholar
  16. 16.
    Capistrán, C., Timmermann, A.: Disagreement and biases in inflation expectations. J. Money Credit Bank. 41(2–3), 365–396 (2009)CrossRefGoogle Scholar
  17. 17.
    Wilensky, U.: NetLogo (1999). http://ccl.northwestern.edu/netlogo/. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL
  18. 18.
    Conlisk, J.: Why bounded rationality. J. Econ. Lit. 34, 669–700 (1996)Google Scholar
  19. 19.
    Baddeley, M.: Herding, social influence and economic decision-making: socio-psychological and neuroscientific analyses. Philos. Trans. Roy. Soc. Lond. B: Biol. Sci. 365(1538), 281–290 (2010)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of EconomicsCa’ Foscari UniversityVeniceItaly

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