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 |