# 1. Introduction

As production diversifies away from agricultural activities into manufacturing and services, the economic landscape evolves too. Urbanization is the most obvious manifestation of this change. But the spatial transformation goes beyond the emergence and growth of cities, as rural areas also densify and the boundaries between urban areas and the countryside become blurred. Policy makers in developing countries are increasingly interested in the implications of this spatial transformation. However, there is limited empirical evidence available to rigorously answer their queries. Case studies about specific cities abound, and there is also a wealth of benchmarking exercises across different administrative levels, including metropolitan areas, states or districts. There are also lessons from urban studies conducted in advanced economies, where urbanization was completed decades ago. But there are few systematic studies on the contribution the rural-urban transformation makes to economic growth and poverty reduction in countries that are still in the process of urbanizing.

Much of the available evidence on the relationship between locations and prosperity in developing countries comes from poverty analysis, and especially from the literature on poverty maps. These poverty maps provide a succinct measure of average household expenditure (or income) per capita in real terms across space, at a fairly disaggregated level. Building on theories of consumption they use household surveys, whose samples are small but rich in information, to estimate the relationship between household expenditure per capita and household characteristics. The set of characteristics considered are those that can also be found in population censuses. The estimated relationship is then used to predict household per capita expenditures at disaggregated spatial levels, based on local household characteristics as reported by population censuses (Demombynes et al. 2002, Elbers, Lanjouw and Lanjouw 2003, Hentschel, Lanjouw et al. 2000).

Despite the use of the word “map”, these analyses remain focused on using household characteristics to predict household expenditure, rather than on understanding location effects. Some location characteristics are generally introduced in the empirical analysis, but this is mainly to reduce biases in the prediction of household expenditures per capita. Efforts to unpack the contribution locations make to poverty prevalence have remained fairly aggregated, using the region or the province as the spatial unit of analysis, or distinguishing between urban and rural areas taken altogether (Kanbur and Venables, 2005).

Admittedly, this strand of literature includes analyses of the growth in household expenditures per capita which explicitly focus on local “poverty traps”. The use of panel data in these analyses allows controlling for unobservable household characteristics which could be spatially correlated, and whose impact could therefore be wrongly construed as a location effect. The analyses also introduce a range of location characteristics at the fairly disaggregated levels, including topography, remoteness, density of rural roads, and local human development indicators. Many of these characteristics are shown to contribute significantly to the growth in household expenditures per capita, which is interpreted as evidence that geographic capital can influence the productivity of a household's own capital (Ravallion and Jalan 1999, and Jalan and Ravallion 2002). But these analyses are restricted to farm households in rural areas, so that they are more informative about bottom locations than about the broader rural-urban transformation.

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