Open access repository currently comprising dozens of datasets covering India's 500,000 villages, 8000 towns, and 4000 legislative constituencies using a set of a common geographic identifiers that span 25 years

The Socioeconomic High-resolution Rural-Urban Geographic Dataset on India (SHRUG) is a new administrative data source describing socioeconomic development in India. The first version of the SHRUG describes demographic, socioeconomic, firm and political outcomes at a high geographic resolution for the universe of Indian households and non-farm productive establishments, in both rural and urban India, from 1990-2013. The SHRUG is a platform for future collaboration and data sharing between researchers working with administrative data in India. We have created a set of consistent location identifiers for all geographic locations in India from 1990-2013, and establish a methodology to extend this classification to units from future data sources. Researchers working with geographic variation in India can thus benefit from linking to the SHRUG, and can benefit other researchers by making their data available to others through the SHRUG platform. In the accompanying paper, we describe the construction of the data and the strengths and weaknesses of administrative data like these for research on economic development. We then perform several validation exercises to show that the SHRUG is consistent with other data sources. Finally, we present an illustrative data exercise on recent trends in rural and urban development. This is an archive of a prior version of SHRUG (v1.3, or Harvard Dataverse version number 3.x). Harvard Dataverse v2.0 corresponds to SHRUG v1.2. For the most recent version, please go to devdatalab.org/shrug

This dataset links SHRUG's village- and town-level identifiers (shrid) to their corresponding local governance bodies using official LGD (Local Government Directory) codes from the Government of India. Each observation is matched to either a Gram Panchayat or an Urban Local Body, enabling governance-level analysis of census and economic data. The matching achieves 90.41% coverage overall, with over 95% accuracy in most major Indian states. Discrepancies are summarized in documentation. In the code folder, I have included all necessary scripts and datasets used in the creation of the dataset. Under documentation, I have also included a markdown pdf describing the steps and discrepancies encountered while creating the dataset, and a state/UT wise summary of total matching rates. The table summarizes the direction and type of the missing observations. All remaining omissions and mistakes are the author’s.

Dataset

This dataset was created by Miftahul Fahmi

Released under Other (specified in description)

Contents

Development plan "Zum Zuckmantel" of the city of Öhringen transformed according to INSPIRE based on an XPlanung data set in version 5.0.

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Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

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