In this paper we consider the problem of uncertainty related to growth through innovations. We study a stylized, although rich, growth model, in which the stochastic innovations follow a Bayesian nonparametric model, and provide the full taxonomy of the asymptotic equilibria. In most cases the variability around the average aggregate behaviour does not vanish asymptotically: this requires to accompany usual macroeconomic mean predictions with some measure of uncertainty, which is readily yielded by the adopted Bayesian nonparametric approach. Moreover, we discover that the extent of the asymptotic variability is the result of the interaction between the rate at which the economy creates new sectors and the concavity of returns in sector specific technologies.

Innovation, growth and aggregate volatility from a Bayesian nonparametric perspective

LIJOI, ANTONIO;MULIERE, PIETRO;PRUENSTER, IGOR;
2016

Abstract

In this paper we consider the problem of uncertainty related to growth through innovations. We study a stylized, although rich, growth model, in which the stochastic innovations follow a Bayesian nonparametric model, and provide the full taxonomy of the asymptotic equilibria. In most cases the variability around the average aggregate behaviour does not vanish asymptotically: this requires to accompany usual macroeconomic mean predictions with some measure of uncertainty, which is readily yielded by the adopted Bayesian nonparametric approach. Moreover, we discover that the extent of the asymptotic variability is the result of the interaction between the rate at which the economy creates new sectors and the concavity of returns in sector specific technologies.
2016
2016
Lijoi, Antonio; Muliere, Pietro; Pruenster, Igor; Taddei, Filippo
File in questo prodotto:
File Dimensione Formato  
EJS_2016.pdf

non disponibili

Tipologia: Documento in Post-print (Post-print document)
Licenza: NON PUBBLICO - Accesso privato/ristretto
Dimensione 302.94 kB
Formato Adobe PDF
302.94 kB Adobe PDF   Visualizza/Apri

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/11565/3991290
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 1
social impact