How to Collaborate Effectively to Improve Data Quality and Use in Revenue Administration and Official Statistics

How to Collaborate Effectively to Improve Data Quality and Use in Revenue Administration and Official Statistics
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Volume/Issue: Volume 2021 Issue 005
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Economics- Macroeconomics , Public Finance , Taxation - General , Economics / General , data quality , RA-NSO engagement , assessment tool , taxpayer information , quality challenge , Tax administration core functions , Data collection , Information for taxpayers , Economic classification , Africa

Summary

This note outlines the interest of Revenue Administrations (RAs) and National Statistical Offices (NSOs) in the quality of data at their disposal, and how collaboration between these organizations can contribute to improving data quality. The similarities between the data collection and processing steps in revenue administration and in the production of economic statistics underlie meaningful information and data sharing. Mutually beneficial collaboration between RAs and NSOs can be achieved, particularly in efforts to improve the coverage of registers and to update register information; classify economic activity; and analyze joint data to address data shortcomings. Since there are differences in concepts and definitions used in revenue administration and official statistics, dialogue is necessary to ensure the effective use of data from the partner organization. Collaboration can improve the quality of data available to both institutions: for RAs, this can assist in realizing improved taxpayer compliance and revenue mobilization, and for NSOs, tax-administrative data sources may enable expanded coverage of the economy in official statistics and reduce timeframes required for publishing economic time series and national accounts. Together, these outcomes can enhance the policy formulation, planning, and service delivery capability of governments. To that end, this note delineates concrete steps to engender sustainable and meaningful interchange of information and data between the RA and NSO.