urban or rural. The four tiers considered are: 1) top locations, 2) catchment areas, 3) average places, and 4) bottom locations. A cluster is made of one or several top locations plus the associated catchment areas. There is some similarity between our approach to identify clusters and the approaches used to define functional urban areas in advanced economies (OECD 2013, and US Bureau of Census 2011). But our approach is arguably stricter in that it uses the estimated location effects, rather than population density, as the key indicator to generate the classification of places.

We start by identifying _top locations_ , defined as the 100 places with the largest location effects. There is some arbitrariness in choosing the number 100 (about 7 percent of all places). But an advantage of this choice is that it facilitates comparisons with urban rankings generated in connection with ongoing government programs in India.

As a second step we look at all other places whose location effect is greater than one standard deviation above the mean, a threshold for better than average, with the goal of identifying which ones belong to a _cluster_ . For this, we use a recursive approach. Initially each top location is treated as a cluster, but the cluster is sequentially enlarged to encompass all places above the threshold in the same or contiguous districts. We repeat the process until there are no more places with a location effect a standard deviation above the mean whose districts are contiguous to those in the cluster. It is clear that large clusters such as Delhi-Faridabad can include several top locations, so that there are much fewer clusters than there are top locations. As for the set of places in a cluster which are not top locations, in what follows we refer to them as _catchment areas_ .

At the other end, we call _bottom locations_ the places (218 in all) whose location effect is more than one standard deviation below the mean. Again, there is some arbitrariness in the chosen threshold, but it allows us to capture a sizeable population mass in this tier. We call _average locations_ all the places that do not belong to a cluster and do not quality as bottom locations.

The average location effect for top locations is 0.409, whereas the average for bottom locations is -0.305, a difference that is statistically significant. Interpreted literally, this difference would mean that an average Indian household moving from a bottom location to a top location could expect to see its nominal household expenditure per capita more than double. The gap is obviously wider when considering the extremes of the distribution. Continuing with the hypothetical example, an average Indian household moving from a small rural area in the Malkangiri district of Orissa (the lowest location effect) to Gurgaon city in Haryana (the highest) would see its nominal household expenditure per capita increase 3.6 times.

Remarkably, among the top 100 locations there are more small urban areas (39 in all) than large urban areas (only seven). The ten small urban areas with the largest location effects are: Gurgaon in Haryana, Thiruvananthapuram, Idukki and Kottayam in Kerala, Raigarh in Mahrashtra, Gautam Buddha Nagar and Ghaziabad in Uttar Pradesh, Kachchh in Gujarat, Papum Pare in Arunachal Pradesh and Dakshina Kannada in Karnataka. The seven large urban areas that qualify as top locations are (in descending order) Mumbai in Maharashtra, Bangalore in Karnataka, Faridabad in Haryana, Thane in Maharashtra, Kolkata in West Bengal, Surat in Gujarat, and Delhi. Other large urban areas, such as Agra, Kanpur Nagar and Varanasi in Uttar Pradesh and Patna in Bihar, have location effects below the Indian average for all places, urban and rural. Even more remarkably, about half of India’s top locations are administratively rural. This suggests that location, and especially “distance to what?” matter more than administrative status.

The conclusion is similar when focusing on bottom locations. A large majority of them are rural, and 129 of them are actually small rural areas. But there are also 73 small urban areas in this group. Location, again, 22