Unemployment expectations in an agent-based model with education

Luca Gerotto, Paolo Pellizzari

Risultato della ricerca: Contributo in libroChapter

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.
Lingua originaleEnglish
Titolo della pubblicazione ospiteLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pagine175-186
Numero di pagine12
Volume10978
DOI
Stato di pubblicazionePubblicato - 2018

Serie di pubblicazioni

NomeLECTURE NOTES IN COMPUTER SCIENCE

Keywords

  • Agent-based modeling
  • Bounded rationality
  • Unemployment expectations

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