Working Paper: CEPR ID: DP10492
Authors: Tiago V. V. Cavalcanti; Chryssi Giannitsarou
Abstract: We study the interactions and dynamics of human capital, growth and inequality by explicitly embedding networks into a standard endogenous growth model with overlapping generations. The human capital of a household depends on investment in education and on average human capital of the household's network neighborhood. Network structure is crucial for both the long run outcomes and the transition of otherwise identical economies. Network cohesion above a certain threshold eliminates differences across households and leads to long run equality, while below the threshold, inequality is high and persists more often. During transition, (i) high overall growth is achieved when the network has high degree centralization and the most degree central node has high initial human capital and (ii) high individual household growth is achieved when the household has low human capital relative to its neighborhood and is located in a neighborhood that has high average human capital relative to the whole economy.
Keywords: growth; human capital; inequality; local externality; networks
JEL Codes: D62; D85; E24; O40
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| high network cohesion (D85) | eliminates differences across households (G59) |
| eliminates differences across households (G59) | leads to long-run equality (D63) |
| high network cohesion (D85) | leads to long-run equality (D63) |
| high degree centralization (H77) | high overall growth (O40) |
| high initial human capital (central node) (J24) | high overall growth (O40) |
| low human capital (household) relative to high average human capital (neighborhood) (R20) | higher individual household growth (R20) |
| affluent neighborhoods (R20) | faster growth (O49) |
| lower network cohesion (D85) | higher long-run growth (O49) |
| lower network cohesion (D85) | higher inequality (D31) |