New chairman of the Statistical Advisory Board elected: Münnich sets new standards!
Ralf Münnich from the University of Trier was elected chairman of the Statistical Advisory Board. Importance for official statistics.

New chairman of the Statistical Advisory Board elected: Münnich sets new standards!
On June 17, 2025, the University of Trier announced that Ralf Münnich, Professor of Economic and Social Statistics, was elected as the new Chairman of the Statistical Advisory Board of the Federal Statistical Office. This decision followed the 72nd meeting of the Advisory Board, which took place on May 22, 2025. Münnich, a member of the advisory board and representative of the German Statistical Society since 2017, has an outstanding reputation in the scientific and statistical community. His research focuses on statistical survey methodology, data quality and microsimulations.
The election of Münnich to lead the committee is not only a personal success, but also underlines the importance of the Statistical Advisory Board, which has advised the Federal Statistical Office on fundamental issues since 1953. In this context, Dr. Andrea Schultz from the Office for Statistics and Elections of the City of Leipzig was elected deputy chairwoman. The expertise of these two people should help to further increase the quality and relevance of official statistics.
Recommendations for the further development of official statistics
As early as March 2025, the Statistical Advisory Board made recommendations for the further development of official statistics. These recommendations are a response to current challenges and changing user needs. Particular attention is paid to the need for precise and reliable data, especially in times of global crises. The Advisory Board emphasizes that official statistics play a central role in fact-based decisions in politics, the economy and society.
Some important points of the recommendations are:
- Modernisierung der rechtlichen und organisatorischen Rahmenbedingungen.
- Anpassung des Bundesstatistikgesetzes.
- Vorantreiben des Forschungsdatengesetzes.
- Einführung einer mittelfristigen Programm- und Finanzplanung für das Statistische Bundesamt.
- Maßnahmen zur Gewährleistung der Qualität der amtlichen Statistik.
- Stärkere Verknüpfung von Statistiken mit Register- oder Verwaltungsdaten.
- Erschließung neuer Datenquellen.
These measures are intended not only to ensure the quality of official statistics, but also to reduce bureaucracy and optimize the use of existing data. The importance of combining data from different statistical systems such as census and microcensus is also discussed.
Quality in official statistics
The quality of statistical data is of crucial importance in official statistics. The statistical offices are leading providers of qualitative statistical information in Germany. A quality manual developed by the federal and state statistical offices describes a framework for ensuring data quality. It serves both as a guide for the production of official statistics and as a source of information for users to better understand the management of the quality of statistical results.
Chapter 5 of the handbook contains several hundred “quality guidelines for the statistical production process” that describe concrete procedures for all phases of the implementation of official statistics. These guidelines are binding for all specialist statistics and ensure the consistent implementation of quality standards.
In addition, the statistical offices also observe international quality standards, which have been incorporated into a code of conduct for European statistics. This Code has been regularly updated since its inception in 2005, 2011 and 2017 to reflect changing needs.
The Statistical Advisory Board and the new leadership decisions under Ralf Münnich's leadership will play a crucial role in the future design and perception of official statistics. Their work will not only improve the quality and availability of data in Germany, but will also serve as an international example of how high quality standards can be successfully implemented.