Abstract
Abstract The SHRUG is an open data platform describing multidimensional socioeconomic development across 600,000 villages and towns in India. This paper presents three illustrative analyses only possible with high-resolution data. First, it confirms that nighttime lights are highly significant proxies for population, employment, per capita consumption, and electrification at very local levels. However, elasticities between night-lights and these variables are far lower in time series than in cross section, and vary widely across context and level of aggregation. Next, this study shows that the distribution of manufacturing employment across villages follows a power law: the majority of rural Indians have considerably less access to manufacturing employment than is suggested by aggregate data. Third, a poverty mapping exercise explores local heterogeneity in living standards and estimates the potential targeting improvement from allocating programs at the village—rather than at the district—level. The SHRUG can serve as a model for open high-resolution data in developing countries.
Highlights
Development and economic growth, insofar as they affect the living standards of individuals, are highly localized phenomena
This paper introduces the Socioeconomic High-resolution Rural-Urban Geographic Dataset on India (SHRUG), a multidimensional socioeconomic data platform with high geographic resolution data on demography, non-farm employment structure, political outcomes, forest cover, night lights, and administrative program operation, among other dimensions, for the universe of municipalities
We present three analyses that shed light on the distribution of economic opportunity within highly localized regions, analyses that are only possible with high resolution data like the SHRUG
Summary
Development and economic growth, insofar as they affect the living standards of individuals, are highly localized phenomena. Due to the nature of data available to researchers, analysis of development has largely occurred at an aggregate geographic scale. In India, much policy and research has been based on the National Sample Surveys, which have tracked socioeconomic change at the district level since independence. A single Indian district is home to around 2 million people, often with vast variation in living standards. This variation is demonstrated, which shows the share of variation in various development outcomes at different levels of geographic variation. The National Sample Surveys often base district statistics on fewer than 100 households per district, missing much of this microgeographic variation
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