Policy Research Working Paper 7473

# **Abstract**

Policy makers in developing countries, including India, are increasingly sensitive to the links between spatial transformation and economic development. However, the empirical knowledge available on those links is most often insufficient to guide policy decisions. There is no shortage of case studies on urban agglomerations of different sorts, or of benchmarking exercises for states and districts, but more systematic evidence is scarce. To help address this gap, this paper combines insights from poverty analysis and urban economics, and develops a methodology to assess spatial performance with a high degree of granularity. This methodology is applied to India, where individual household survey records are mapped to “places” (both rural and urban) below the district level. The analysis disentangles the contributions household characteristics and locations make to labor earnings, proxied by nominal household expenditure per capita. The paper shows that one-third of the variation in predicted labor earnings is explained by the locations where households reside and by the interaction between these locations and household characteristics such as education. In parallel, this methodology provides a workable metric to describe spatial productivity patterns across India. The paper shows that there is a gradation of spatial performance across places, rather than a clear rural-urban divide. It also finds that distance matters: places with higher productivity are close to each other, but some spread their prosperity over much broader areas than others. Using the spatial distribution of this metric across India, the paper further classifies places at below-district level into four tiers: top locations, their catchment areas, average locations, and bottom locations. The analysis finds that some small cities are among the top locations, while some large cities are not. It also finds that top locations and their catchment areas include many high-performing rural places, and are not necessarily more unequal than average locations. Preliminary analysis reveals that these top locations and their catchment areas display characteristics that are generally believed to drive agglomeration economies and contribute to faster productivity growth.

This paper is a product of the Office of the Chief Economist, South Asia Region. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at yli7@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team