Endogenous growth model with Bayesian learning and technology selection

Authors: Fu, W. and Le Riche, A.

Journal: Mathematical Social Sciences

Volume: 114

Pages: 58-71

ISSN: 0165-4896

DOI: 10.1016/j.mathsocsci.2021.10.003

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.

Source: Scopus