seems to be quite decisive. A vast majority of the bottom locations concentrate in the middle of India, crossing the states of Madhya Pradesh, Chhattisgarh, and Orissa from West to East. A number of bottom locations can also be found in Uttar Pradesh and Bihar, along the Ganga basin. Interestingly, most of them are not rural areas but rather small urban areas with exceptionally low location effects.

The importance of location is highlighted by the spatial distribution of clusters (Map 1). The cutoff points used in our approach lead to the identification of 17 clusters in India’s case. Geographically, these clusters can be found in the northwest towards Pakistan, in the coastal areas of the mid-west and the southwest, in some inland areas and coastal areas of the southeast, and in the northeast towards Bangladesh and China. Some of these clusters cover multiple districts and, in some cases, multiple states. For example, the cluster of Delhi, Faridabad and Gurgaon spreads across 60 districts in seven northwestern states and union territories. Similarly, the cluster of Thiruvananthapuram includes 19 districts in Karnataka, Kerala and Tamil Nadu. The cluster of Mumbai, Surat and Thane encompasses nine districts in Gujarat and Maharashtra; the cluster of Ahmadabad covers seven districts in Gujarat; and the cluster of Bangalore includes five districts in Karnataka and Tamil Nadu.

The distance indicator introduced above can be used to assess the geographic spread of a cluster. Consider a cluster whose core is in one district but whose catchment area includes several neighboring districts. The geographic spread can be measured as the maximum distance to the core from all the neighboring districts belonging to the catchment area. By this criterion, the biggest three clusters in India are those of Jodhpur, of Delhi, Faridabad and Gurgaon, and of Ahmadabad, in that order. Another way to measure the size of a cluster is based on its total population. By this metric, the largest three clusters are the one of Delhi, Faridabad and Gurgaon, the one of Thiruvananthapuram and the one of Mumbai, Surat and Thane.

By construction, clusters can include places belonging to all population size groups. Within the 17 clusters identified based on our approach there 12 large urban areas, 91 small urban areas, 45 large rural areas, and 67 small rural areas. Unfortunately, these places can only be mapped at the district level because the NSS 2011-12 does not provide information on the exact geographic position of the different population size groups within a district (Map 2). In principle, a district can include top locations, catchment areas, average locations and bottom locations. Such level of heterogeneity is uncommon given the high spatial correlation of location effects. But it can be found in practice. One salient example is the district of Thane of Maharashtra, part of the Mumbai, Surat and Thane cluster. In Thane, urban areas are among top locations, whereas small rural areas belong to bottom locations. Without going to such extremes, 34 percent of districts include places belonging to two or more different tiers.

# 7. Location and social inclusion

Assessing the relationship between location and social inclusion is not straightforward. To begin with, our location effects are estimated based on nominal household expenditure per capita, which can be seen as a proxy for labor productivity but should not be confused with a proxy for living standards. Indeed, places with higher productivity can be expected to also be characterized by higher land rents, and these in turn may create an upward pressure on the prices of non-tradable goods and services. Households living in places with high location effects may therefore enjoy higher nominal expenditure per capita, but they are also confronted with a higher cost of living.

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