Economics at your fingertips  

Endogenous growth model with Bayesian learning and technology selection

Wentao Fu and Antoine Le Riche

Mathematical Social Sciences, 2021, vol. 114, issue C, 58-71

Abstract: We introduce Bayesian learning and technology selection into a two-sector endogenous growth model with physical and human capital and study their impact on steady state welfare and stability properties. We show that there are two balanced growth paths that are locally determinate: one corresponding to the good new technology selection, the other sticking to the old technology selection. The equilibrium selection is driven by Bayesian learning and the true quality of the new technology could remain unlearned with a positive probability. We establish that, at steady state, the rate of achieving a high Total Factor Productivity (TFP) in the good new technology has a positive impact on the growth rate of the economy, the GDP and the physical to human capital ratio.

Keywords: Bayesian learning; Technology selection; Endogenous growth (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

DOI: 10.1016/j.mathsocsci.2021.10.003

Access Statistics for this article

Mathematical Social Sciences is currently edited by J.-F. Laslier

More articles in Mathematical Social Sciences from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

Page updated 2022-11-07
Handle: RePEc:eee:matsoc:v:114:y:2021:i:c:p:58-71