Working Paper: NBER ID: w18470
Authors: Alessandra Fogli; Laura Veldkamp
Abstract: Does the pattern of social connections between individuals matter for macroeconomic outcomes? If so, where do these differences come from and how large are their effects? Using network analysis tools, we explore how different social network structures affect technology diffusion and thereby a country's rate of growth. The model also explains how different social networks may emerge endogenously in response to the prevalence of infectious disease. Initial differences in disease prevalence can produce different network structures, leading to divergent levels of income. We compare calibrated model predictions with data. The model and data agree that a one-standard-deviation increase in our index of network diffusion speed results in output growth that is 1/2% higher per year.
Keywords: growth; development; technology diffusion; economic networks; social networks; pathogens; disease
JEL Codes: E02; O1; O33
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| different network structures (D85) | income levels (J31) |
| social networks shaped by disease prevalence (Z13) | divergent income levels among countries (F40) |
| collectivist networks (D70) | slower diffusion of technology (O33) |
| individualist networks (D85) | faster technology adoption (O33) |
| higher degrees of mobility and network connections (J62) | quicker dissemination of ideas and germs (O36) |
| quicker dissemination of ideas and germs (O36) | enhanced productivity and economic growth (O49) |
| feedback loops between disease prevalence and network structures (D85) | persistence of networks (D85) |
| initial differences in disease prevalence (I14) | different network structures (D85) |
| social connections (Z13) | macroeconomic outcomes (E66) |