Using Administrative Data To Enhance Policymaking In Developing Countries Tax Data And The National Accounts

Statistical agencies worldwide are increasingly turning to new data sources, including administrative data, to improve statistical coverage. Administrative data can significantly enhance the quality of national statistics and produce synergies with tax administration and other government agencies, supporting better decision making, policy advice, and economic performance. Compared to economic censuses and business surveys, administrative data are less burdensome to collect and produce more timely, detailed, and accurate data with better coverage. This paper specifically explores the use of value added tax and income tax records to enhance the compilation of national accounts statistics.

Statistical agencies worldwide are increasingly turning to new data sources, including administrative data, to improve statistical coverage. Administrative data can significantly enhance the quality of national statistics and produce synergies with tax administration and other government agencies, supporting better decision making, policy advice, and economic performance. Compared to economic censuses and business surveys, administrative data are less burdensome to collect and produce more timely, detailed, and accurate data with better coverage. This paper specifically explores the use of value added tax and income tax records to enhance the compilation of national accounts statistics.

Federal government statistics provide critical information to the country and serve a key role in a democracy. For decades, sample surveys with instruments carefully designed for particular data needs have been one of the primary methods for collecting data for federal statistics. However, the costs of conducting such surveys have been increasing while response rates have been declining, and many surveys are not able to fulfill growing demands for more timely information and for more detailed information at state and local levels. Innovations in Federal Statistics examines the opportunities and risks of using government administrative and private sector data sources to foster a paradigm shift in federal statistical programs that would combine diverse data sources in a secure manner to enhance federal statistics. This first publication of a two-part series discusses the challenges faced by the federal statistical system and the foundational elements needed for a new paradigm.

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.

It is generally difficult to measure revenue not collected due to noncompliance, but a growing number of countries now regularly produce and publish estimated revenue losses. Good tax gap analysis enables the detection of changes in taxpayer behavior by consistent estimates over time. This Technical Note sets out the theoretical concepts for personal income tax (PIT) gap estimation, the different measurement approaches available, and their implications for the scope and presentation of statistics. The note also focuses on the practical steps for measuring the PIT gap by establishing a random audit program to collect data, and how to scale findings from the sample to the population.

This Handbook intends to inform Data Providers and researchers on how to provide privacy-protected access to, handle, and analyze administrative data, and to link them with existing resources, such as a database of data use agreements (DUA) and templates. Available publicly, the Handbook will provide guidance on data access requirements and procedures, data privacy, data security, property rights, regulations for public data use, data architecture, data use and storage, cost structure and recovery, ethics and privacy-protection, making data accessible for research, and dissemination for restricted access use. The knowledge base will serve as a resource for all researchers looking to work with administrative data and for Data Providers looking to make such data available.

Transparency in government operations is widely regarded as an important precondition for macroeconomic fiscal sustainability, good governance, and overall fiscal rectitude. Notably, the Interim Committee, at its April and September 1996 meetings, stressed the need for greater fiscal transparency. Prompted by these concerns, this paper represents a first attempt to address many of the aspects of transparency in government operations. It provides an overview of major issues in fiscal transparency and examines the IMF's role in promoting transparency in government operations.

This report examines the opportunities of enhancing access to and sharing of data (EASD) in the context of the growing importance of artificial intelligence and the Internet of Things. It discusses how EASD can maximise the social and economic value of data re-use and how the related risks and challenges can be addressed. It highlights the trade-offs, complementarities and possible unintended consequences of policy action – and inaction. It also provides examples of EASD approaches and policy initiatives in OECD countries and partner economies.