Does Inequality Hamper Innovation and Growth?
39 Pages Posted: 8 Jun 2016 Last revised: 23 Feb 2017
Date Written: May 31, 2016
Abstract
The paper builds upon the Agent Based-Stock Flow Consistent model presented in Caiani et al. (2015) to analyze the relationship between income and wealth inequality and economic development. For this sake, the original model has been amended under three main dimensions: first, the households sector has been subdivided into workmen, office workers, researchers, and executives which compete on segmented labor markets.
Conversely, firms are now characterized by a hierarchical organization structure which determines, according to firms’ output levels, their demand for each type of workers. Second, in order to account for the impact of income and wealth distribution on consumption patterns, different households classes - also representing different income groups - have diversified average propensities to consume and save. Finally, the model now embeds technological change in an evolutionary flavor, affecting labor productivity evolution in the consumption sector through product innovation in the capital sector, where firms invest in R&D and produce differentiated vintages of machineries.
The model is then calibrated using realistic values for both income and wealth distribution across different income groups, and their average propensities to consume. Results of the simulation experiments suggest that more progressive tax schemes and labor market policies aiming to increase low and middle workers’ coordination, and to support their wage levels, concur to foster economic development and to reduce inequality, though the latter seem to be more effective under both respects. The model thus provides some evidence in favor of a wage-led growth regime, where improvements of middle-low levels workers’ conditions create positive systemic effects, which eventually trickle up also to high income-profit earners households.
Keywords: Innovation, Inequality, Agent Based Macroeconomics, Stock Flow Consistent Models
JEL Classification: D63, E03, E21, O11
Suggested Citation: Suggested Citation