EDUCATION, NEIGHBORHOOD EFFECTS AND GROWTH: AN AGENT-BASED MODEL APPROACH

Tanya Araãšjo () and Miguel St. Aubyn ()
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Tanya Araãšjo: ISEG (School of Economics and Management), Technical University of Lisbon (TULisbon), Rua do Quelhas, 6 1200-781 Lisboa, Portugal
Authors registered in the RePEc Author Service: Tanya Vianna de Araújo ()

Advances in Complex Systems (ACS), 2008, vol. 11, issue 01, pages 99-117

Abstract: Endogenous, ideas-led growth theory and the literature on agent-based modeling with neighborhood effects are crossed. In an economic overlapping generations framework, it is shown how social interactions and neighborhood effects are of vital importance in the endogenous determination of the long run number of skilled workers and therefore of the growth prospects of an economy. Neighborhood effects interact with the initial distribution of skilled agents across space and play a key role in the long run stabilization of the number of skilled individuals. Our model implies a tendency toward segregation, with a possibly positive influence on growth, if team effects operate. The long run growth rate is also shown to depend on the rate of time preference. Initial circumstances are of vital importance for long run outcomes. A poor initial education endowment will imply a long run reduced number of skilled workers and a mediocre growth rate, so there is no economic convergence tendency. On the contrary, poor societies will grow less, or will even fall into a poverty trap, and will diverge continuously from richer ones.

Keywords: Agent modeling; economic growth; education; human capital; neighborhood effects; poverty trap (search for similar items in EconPapers)
Date: 2008

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Working Paper: Education, Neighbourhood Effects and Growth: An Agent Based Model Approach (2005)
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