Published
07/22/2025, 17:59On 22 July, a working meeting between the Chairman of the National Statistics Committee, Baktybek Kudaibergenov, and representatives of the World Bank took place at the National Statistics Committee of the Kyrgyz Republic.
The delegation was led by Grigory Kisunko, Senior Public Sector Specialist and Co-Head of the World Bank Mission. Apichok Kotikula, Project Manager for the Modernisation of Tax Administration and Statistical System, also participated in the talks.
During the meeting, the parties discussed the interim results of the project, noting the results already achieved in the first half of 2025. In particular, as part of the modernisation of the statistical system, a new business process model has been introduced, a National Quality Assurance Framework for Official Statistics has been implemented, and statistical reporting forms have been optimised and reduced.
In addition, mechanisms for using administrative data sources are being actively developed, and work is underway to strengthen institutional capacity in the areas of metadata management, preparation and conduct of the upcoming census, as well as geospatial data statistics and environmental statistics.
World Bank representatives highly appreciated the current progress of the National Statistics Committee, noting the steady progress of the project. It was emphasised that the level of implementation achieved requires a review of the current status of the project with a view to upgrading its assessment.
The parties confirmed their interest in further constructive cooperation, noting the importance of transparency and coordination of actions for the successful achievement of the set goals. Baktybek Kudaibergenov expressed confidence that the activities planned for 2025 will be successfully implemented through joint efforts.
It should be noted that the project to modernise Kyrgyzstan's statistical system is a key element of the country's digital transformation. It aims to improve the quality of official statistics, develop modern approaches to data collection and processing, and strengthen user confidence in statistical information.