Measuring the Impact of Asset Complementarities: the case of rural Peru

In previous research efforts, we have shown that what seem to be sizable geographic differences in poverty rates in rural Peru can be almost fully explained by taking into account the spatial concentration of households with readily observable non-geographic characteristics-in particular, public and private assets. This does not mean that geography is not an important determinant of income inequality, but that its influence on poverty, expenditure level, and growth differentials arises through a spatially uneven provision of public infrastructure. However, the exact type, critical mass, and combination of public and private assets needed to move out of poverty have not been sufficiently studied. Our analysis tries to carry out further research in this area to contribute to more effective targeting of poverty alleviation efforts. We consider three types of public infrastructure and services in particular: a) " traditional infrastructure " such as transportation, sewer systems, water, electricity which do not generate positive network externalities; b) "human-capital-generating public services" that are capable of creating mobile private assets, such as schooling and health services and c) "information and communication technologies", such as telephone or Internet, all of which generate network externalities. Using the Peruvian LSMS data of 2000 and additional modules developed under this research effort we quantify the differential impact on poverty of each of these types of investments, as well as the interaction effect between so-called traditional types of infrastructure and those which generate network externalities.