India

  • President:Droupadi Murmu
  • Prime Minister:Narendra Modi
  • Capital city:New Delhi
  • Languages:Hindi 41%, Bengali 8.1%, Telugu 7.2%, Marathi 7%, Tamil 5.9%, Urdu 5%, Gujarati 4.5%, Kannada 3.7%, Malayalam 3.2%, Oriya 3.2%, Punjabi 2.8%, Assamese 1.3%, Maithili 1.2%, other 5.9% note: English enjoys the status of subsidiary official language but is the most important language for national, political, and commercial communication; Hindi is the most widely spoken language and primary tongue of 41% of the people; there are 14 other official languages: Bengali, Telugu, Marathi, Tamil, Urdu, Gujarati, Malayalam, Kannada, Oriya, Punjabi, Assamese, Kashmiri, Sindhi, and Sanskrit; Hindustani is a popular variant of Hindi/Urdu spoken widely throughout northern India but is not an official language (2001 census)
  • Government
  • National statistics office
  • Population, persons:1,43,52,28,798 (2024)
  • Area, sq km:29,73,190
  • GDP per capita, US$:2,411 (2022)
  • GDP, billion current US$:3,416.6 (2022)
  • GINI index:32.8 (2021)
  • Ease of Doing Business rank:62

All datasets: A E G I M N R S W
  • A
    • अक्तूबर 2021
      Source: Chief Executives Board for Coordination, UN
      Uploaded by: Knoema
      Accessed On: 20 अक्तूबर, 2021
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      Agency Revenue By Government Donor for assessed revenue type
  • E
  • G
  • I
    • अगस्त 2022
      Source: International Centre for Tax and Development
      Uploaded by: Knoema
      Accessed On: 16 अगस्त, 2022
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      Data cited at: ICTD/UNU-WIDER, ‘Government Revenue Dataset’, 2018, https://www.wider.unu.edu/project/government-revenue-dataset' ICTD Government Revenue Dataset, 2018 A major obstacle to cross-country research on the role of revenue and taxation in development has been the weakness of available data. Government Revenue Dataset (GRD), developed through the International Centre for Tax and Development (ICTD), is aimed at overcoming this obstacle. It meticulously combines data from several major international databases, as well as drawing on data compiled from all available International Monetary Fund (IMF) Article IV reports. It achieves marked improvements in data coverage and accuracy, including a standardized approach to revenue from natural resources, and holds the promise of significant improvement in the credibility and robustness of research in this area. Dataset contains Central, General and merged government revenue data reported as % of GDP.
    • मई 2023
      Source: International Monetary Fund
      Uploaded by: Felix Maru
      Accessed On: 29 मई, 2023
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  • M
  • N
    • जनवरी 2024
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 20 जनवरी, 2024
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      It provides a faithful image, to the greatest extent possible, of the aggregates and balances of the general government sector in the SNA 1993 conceptual framework. In addition, it brings to light two relevant aggregates that do not belong to this conceptual frame work: the Total Revenue and the Total Expenditure of the general government sector. Unit of measure used - National currency; current prices. Expressed in millions.
  • R
    • दिसम्बर 2023
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 13 जनवरी, 2024
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      A key set of information for policy analysis is i) how much revenue is collected; ii) in what ways is it collected; iii) from which institutional units of the economy are revenues raised for each particular financing scheme; and iv) which financing schemes receive those revenues. This dataset provides information about the contribution mechanisms the particular financing schemes use to raise their revenues. Understanding the nature of the flows is of importance from the perspective of both health and public finance policy. For example, the classification of revenues make it possible to distinguish between public and private funding of health care finance. Understanding how resources are raised by financing schemes is important for many countries, as many health systems are struggling with the issue of funding. The classification of revenues of financing schemes is suitable for tracking the collection mechanisms of a financing framework. Furthermore, the new classification makes it possible to analyse the contribution of the institutional units to health financing.
  • S
    • दिसम्बर 2023
      Source: Reserve Bank of India
      Uploaded by: Raviraj Mahendran
      Accessed On: 19 दिसम्बर, 2023
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      Note: FY2017-2018, 2018-2019, 2019-2020 and 2020-21 have been considered as 2017, 2018, 2019 and 2020 respectively. Capital Disbursements and Receipts, Expenditure and Revenue of India
  • W
    • फरवरी 2022
      Source: International Monetary Fund
      Uploaded by: Knoema
      Accessed On: 06 अप्रैल, 2022
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      The IMF’s World Revenue Longitudinal Data set (WoRLD) is a compilation of government tax and non-tax revenues from the IMF’s Government Finance Statistics and World Economic Outlook, and drawing on the OECD Revenue Statistics and Revenue Statistics in Latin American and the Caribbean.