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In this work, we explore the relationship between monetary poverty andproduction combining relatedness theory, graph theory, and regression analysis.We develop two measures at product level that capture short-run and long-runpatterns of poverty, respectively. We use the network of related products (orproduct space) and both metrics to estimate the influence of the productivestructure of a country in its current and future levels of poverty. We foundthat poverty is highly associated with poorly connected nodes in the PS,especially products based on natural resources. We perform a series ofregressions with several controls (including human capital, institutions,income, and population) to show the robustness of our measures as predictors ofpoverty. Finally, by means of some illustrative examples, we show how ourmeasures distinguishes between nuanced cases of countries with similar povertyand production and identify possibilities of improving their current povertylevels.

Identifying poverty traps based on the network structure of economic output