About Statistical Business Registers

Statistical Business Registers (SBRs) are an essential element of the statistical infrastructure to support the coherence and consistency of statistics produced. SBRs provide the frame to correctly identify the target population for business surveys, to randomly select a sample of units under investigation, and to gross-up the sample of survey respondents. They also provide a rich source of statistics directly derived from SBRs and they facilitate the integration of databases thus increasing the analytical value of data.


United Nations Guidelines on Statistical Business Registers

The United Nations Guidelines on Statistical Business Registers were prepared by the United Nations Committee of Experts on Business and Trade Statistics in collaboration with the United Nations Statistics Division.

At its forty-eighth session in March 2017, the United Nations Statistical Commission stressed the continued need for capacity building activities on Statistical Business Registers in developing countries. The Commission endorsed the proposal to prepare the Guidelines on Statistical Business Registers based on existing regional guidelines, notably the ECE Guidelines for Statistical Business Registers and broadening the scope of the guidelines by addressing the specific needs of countries with less-developed statistical systems.

The United Nations Statistical Commission endorsed the draft Guidelines on Statistical Business Registers at its 50th session in March 2019.


Maturity Model for Statistical Business Registers

The maturity model for Statistical Business Registers (SBRs) was developed as a tool to assist countries in identifying areas for improvement for their SBRs. It was prepared by the United Nations Committee of Experts on Business and Trade Statistics, which recognizes, in its strategic view for business and trade statistics, the fundamental role of SBRs in the production and compilation of business and trade statistics and in supporting the development of new statistics or improving the quality and granularity of existing ones.


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