Our paper estimates and compares behavioral New-Keynesian DSGE models derived under two alternative ways to introduce heterogeneous expectations. We assume that agents may be either short-sighted or long-horizon forecasters. The difference does not matter when agents have rational expectations, but it does when a fraction of them form beliefs about the future according to some heuristics. Bayesian estimations show that a behavioral model based on short forecasters fits the data better than one based on long forecasters. Long-horizon predictors exhibit very poor predictive ability, whereas the short forecasters’ model also outperforms the rational expectation framework. We show that the superiority is due to its ability to capture heterogeneous consumers’ expectations. Finally, by Monte-Carlo-filtering mapping, we investigate the indeterminacy regions to complement existing literature.

Bounded-rationality and heterogeneous agents: Long or short forecasters? / Beqiraj, Elton; DI BARTOLOMEO, Giovanni; DI PIETRO, Marco; Serpieri, Carolina. - (2018). [10.2760/244931]

Bounded-rationality and heterogeneous agents: Long or short forecasters?

Beqiraj Elton;Di Bartolomeo Giovanni;Di Pietro Marco;Serpieri Carolina
2018

Abstract

Our paper estimates and compares behavioral New-Keynesian DSGE models derived under two alternative ways to introduce heterogeneous expectations. We assume that agents may be either short-sighted or long-horizon forecasters. The difference does not matter when agents have rational expectations, but it does when a fraction of them form beliefs about the future according to some heuristics. Bayesian estimations show that a behavioral model based on short forecasters fits the data better than one based on long forecasters. Long-horizon predictors exhibit very poor predictive ability, whereas the short forecasters’ model also outperforms the rational expectation framework. We show that the superiority is due to its ability to capture heterogeneous consumers’ expectations. Finally, by Monte-Carlo-filtering mapping, we investigate the indeterminacy regions to complement existing literature.
2018
978-92-79-81858-5
File allegati a questo prodotto
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1425189
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact