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Fiscal federalism: data analytics perspective

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dc.contributor.author Singh, Nitin.
dc.date.accessioned 2020-06-11T06:19:11Z
dc.date.available 2020-06-11T06:19:11Z
dc.date.issued 2020-03
dc.identifier.citation Singh, N. (2020). Fiscal federalism: data analytics perspective. World Economics, 21(1), 153-164. en_US
dc.identifier.uri https://www.world-economics-journal.com/Journal/Papers/Fiscal%20Federalism%20Data%20Analytics%20Perspective.details?ID=779
dc.identifier.uri http://idr.iimranchi.ac.in:8080/xmlui/handle/123456789/648
dc.description.abstract Goods and service tax (GST) is a value-added tax which is levied on goods and services sold and consumed domestically within a country. Although GST is paid by customers it is remitted to the government by the businesses selling the goods and services. The implementation of GST in India is a relatively new development that has impacted on fiscal transfers. The Fifteenth Finance Commission of India is currently deliberating on its terms of reference to determine fiscal transfers from the centre to state governments for the period 2020/1 to 2024/5. The GST Network (GSTN) has been established to provide information technology infrastructure to taxpayers, central and state governments, dealers and all stakeholders. Evidently, there are substantial opportunities to leverage data emanating from GSTN. In such a context, the role of data analytics becomes prominent in monitoring tax administration, mitigating tax evasion, leveraging digitisation and designing fiscal federal policy. The implications presented in this article are relevant to any country having a federal structure that has implemented GST in some form or another. en_US
dc.language.iso en en_US
dc.publisher World Economics en_US
dc.subject IIM Ranchi en_US
dc.title Fiscal federalism: data analytics perspective en_US
dc.type Article en_US
dc.volume 21 en_US
dc.issue 1 en_US


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