An agent-based model of trickle-up growth and income inequality - Elisa Palagi; Mauro Napoletano; Andrea Roventini; Jean-Luc Gaffard (Scuola Superiore Sant'Anna, Laboratory of Economics and Management (LEM), 2021)
We build an agent-based model to study how coordination failures, credit constraints and unequal access to investment opportunities affect inequality and aggregate income dynamics. The economy is populated by households who can invest in alternative projects associated with different productivity growth rates. Access to investment projects also depends on credit availability. The income of each household is determined by the output of the project but also by aggregate demand conditions. We show that aggregate dynamics is affected by income distribution. Moreover, we show that the model features a trickle-up growth dynamics. Redistribution towards poorer households raises aggregate demand and is beneficial for the income growth of all agents in the economy. Extensive numerical simulations show that our model is able to reproduce several stylized facts concerning income inequality and social mobility. Finally, we test the impact of redistributive fiscal policies, showing that fiscal policies facilitating access to investment opportunities by poor households have the largest impact in terms of raising long-run aggregate income and decreasing income inequality. Moreover, policy timing is important: fiscal policies that are implemented too late may have no significant effects on inequality.
Keywords: C63; D31; E63; E21; 330; Income inequality; social mobility; credit constraints; coordination failures; effective demand; trickle-up growth; fiscal policy