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Understanding Revenue Administration: An Initial Data Analysis Using the Revenue Administration Fiscal Information Tool

Author

Listed:
  • Mrs. Andrea Lemgruber
  • Mr. Andrew R Masters
  • Mr. Duncan Cleary

Abstract

During the past few years, the Fiscal Affairs Department (FAD) has developed the Revenue Administration Fiscal Information Tool (RA-FIT), a tax and customs data gathering initiative. This paper, the first of its kind internationally given the number of countries covered, analyzes the results of the first round of RA-FIT data for 85 countries. It begins the process of making summarized cross-country information available to revenue administrations, in particular in developing economies, to help them improve their performance. Topics covered include performance measurement, institutional arrangements, and core operations of tax and customs administration. RA-FIT is in its second round of data gathering, now via an online portal; these data will be analyzed and in future made available to participating countries and technical assistance partners/donors through an online dissemination platform.

Suggested Citation

  • Mrs. Andrea Lemgruber & Mr. Andrew R Masters & Mr. Duncan Cleary, 2015. "Understanding Revenue Administration: An Initial Data Analysis Using the Revenue Administration Fiscal Information Tool," IMF Departmental Papers / Policy Papers 2015/006, International Monetary Fund.
  • Handle: RePEc:imf:imfdps:2015/006
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    Citations

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    Cited by:

    1. Mukherjee, Sacchidananda, 2017. "Changing Tax Capacity and Tax Effort of Indian States in the Era of High Economic Growth, 2001-2014," Working Papers 17/196, National Institute of Public Finance and Policy.
    2. Ma Jun, 2018. "The reform of vertical arrangements of tax administrative agencies in China," Journal of Tax Reform, Graduate School of Economics and Management, Ural Federal University, vol. 4(3), pages 223-235.
    3. Roel Dom, 2017. "Semi-Autonomous Revenue Authorities in Sub-Saharan Africa: Silver Bullet or White Elephant," Discussion Papers 2017-01, University of Nottingham, CREDIT.

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