The SHRUG

The Socioeconomic High-resolution Rural-Urban Geographic Platform for India (SHRUG) facilitates data sharing between researchers working on India. It is an open access repository currently comprising dozens of datasets covering India's over 500,000 villages and 8000 towns over a span of 25 years, all linked together with a set of common geographic identifiers.

Download SHRUG SHRUG Documentation The SHRUG Paper

A new model for using and sharing data.

Our goal is to make as many Indian datasets as possible speak to each other at the highest achievable granularity. Browse our data, use as much as you want, and contribute back to this effort to empower everyone to use data for the greater good.

Prior to the SHRUG, linking different Indian datasets was a hassle. The common geographic frame of SHRUG now makes it easy to share information and link data. Researchers can immediately tap into SHRUG to mine a wealth of previously unavailable socioeconomic data for the geographies that they are working on, and can then publish their own data back to SHRUG, making it available to researchers working on other topics.

What is the SHRUG?

The SHRUG is an easily linkable dataset covering a wide range of socioeconomic variables in India. Some highlights:

  • Open-source geometries at the village- and town-level based on 2011 Census polygons.
  • Socioeconomic data covering a huge range of dimensions, all linked with the same identifiers.
  • All data is available at the subdistrict, district, constituency, town, and village level.
  • The only large-scale socioeconomic data at the level of assembly constituencies.
  • Everything merges cleanly and easily.

The essential unit of observation of the shrug is the shrid, which is a village or town unit with consistent boundaries since 1991. We put in a ton of work to reconcile boundary changes across censuses. Villages and towns merge and split; shrids are aggregated units that keep the same boundaries across all periods. You can read more about how we did this in the SHRUG paper.

The variables are grouped into different modules based on the data source and subject matter, and each module can be independently downloaded from links provided below. Each download link contains flat data tables at all available geographic levels (e.g. village, town, constituency). You can merge at any geographic level you wish using the appropriate key in the core keys module. Many SHRUG variables can be interactively visualized using the SHRUG Atlas.

If you are using previous versions, we recommend you download version 2.0 or newer. v.1.5 Samosa shrid IDs do not match to 2.0 Pakora, and many other improvements have been made.

For more information, please see:

Bugs, feedback, or requests? Let us know!

Applications of the SHRUG

Where are the most impactful locations for targeting a new primary health centre in India? We want to identify places with high populations unserved by public or private health facilities. The necessary data are already linked together in the SHRUG, make it easy to find the data needed to improve allocation decisions.

How do village characteristics depend on proximity to towns? SHRUG's high-resolution data lets us map out these relationships with precision. These graphs show how (i) dependence on agriculture, (ii) consumption, and (iii) non-farm employment change as a function of distance to the nearest town with at least 100,000 people.

Units:
  • (i) Share of employment in cultivation-related activities
  • (ii) Consumption per capita (Rs)
  • (iii) Ratio of non-farm employment to total population

What are your prospects for moving up in the distribution if your family is poor? We get at this with a measure of upward mobility: it measures your expected education rank if you are born to a parent in the bottom half of the education distribution. We find that upward mobility for Muslims is way behind forward castes, SCs and STs, and is going down. [Source]

Nearly one billion people worldwide live in rural areas without access to national paved road networks. We estimated the impacts of India's $40 billion national rural road construction program using village-level microdata. Roads don't have much impact on village consumption or agricultural investments, but they do help people exit agriculture and keep their children in school longer. [Source] [Source]

Contributing to the SHRUG

contributing to SHRUG

SHRUG data is shared using the Creative Commons BY-NC-SA 4.0 International License for non-commercial use. You may use the data for your private research, on condition that you share your own data with SHRUG identifiers when your research paper is published. This makes it easier for others to find your data and cite your work. For inquiries into using the SHRUG for commercial purposes, please contact our team.

Contribute
Bugs, feedback, or data requests

Funding Partners

We are grateful to our many funding partners for supporting the work behind the SHRUG.

Commercial use & services

For commercial use of the SHRUG, as well as custom data generation requests, please contact our team for capabilities and pricing.

Contact us

info@devdatalab.org

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