This study has been conducted by the Cedar (Center for data and research on Russia) team for the Known Unknowns project with the support of the Boris Nemtsov Foundation and the Ideas for Russia initiative. The sources used include monitoring data from the To Be Precise project.
One of the problems created by Russia’s full-scale invasion of Ukraine in 2022 has been the increasingly limited availability and reliability of official Russian statistics. There had been certain challenges concerning the use of official data before, but it was after the outbreak of war that a number of new restrictions were introduced, affecting both availability and quality of government statistics.
For example, Russian authorities have restricted access to official data on foreign trade. Oil and natural gas production figures do not get published anymore. Over the past two years, at least 35 Russian government bodies have closed certain statistical indicators to the public. Almost 500 datasets have disappeared from the official websites of federal agencies alone. In some cases, entire statistical platforms stopped functioning.
Officials tend to justify restrictions on data availability by the need to protect the Russian economy from sanctions. Some experts, however, lean toward other explanations. One reason for the restrictions might be the desire to gloss over the impact that the war has had on Russian society and the state’s resilience.
For researchers and journalists working on Russia-related topics, the increasingly limited availability and reliability of data has become a serious issue. Experts have said as much in the recently published report of the Known Unknowns project, produced by the Ideas for Russia initiative with support from the Boris Nemtsov Foundation for Freedom. The report identified reduced reliability and availability of statistical data as one of the main challenges facing people studying and reporting on Russia since 2022.
This is a particularly acute issue because after the full-scale invasion of Ukraine official statistics have often become the only source of Russia-related data for many scholars, analysts, and journalists who had previously been able to retrieve information through other means. Many of these people can no longer work in Russia, collect data directly, or interact with Russians in person. Opportunities to obtain information about Russia have now either disappeared altogether or been significantly reduced.
Any government data should be treated with caution, even more so in authoritarian regimes. There are many reasons for this. Some distortions in official figures arise naturally — for instance due to data collection difficulties. Other data is distorted intentionally, in order to meet KPIs on paper or compete for bureaucratic resources. Further challenges may occur at the interpretation stage, when an indicator is claimed to reflect something that it does not.
However, it is also important to avoid the idea that all Russian official data is always falsified and that the country has become impenetrable for an outside observer. Russia, unlike North Korea or the Soviet Union, does not seek to close itself off from the outside world completely (at least not yet). Despite wartime censorship, Russia still has plenty of high-quality open data — more than some other countries that are generally more democratic. What matters is how to properly use this data.
The present guide to the do’s and don’ts of official Russian statistics is designed to help with this task. It contains information that will help researchers, journalists, and experts dealing with Russia-related topics to better navigate those state-provided statistical indicators which are still available. It thus raises awareness of distortion risks for particular indicators and helps understand which data can or cannot be trusted, to what extent and for what reasons.
For the first edition of the map, we selected 30 indicators that are used to assess the demographic, social, and economic situation in modern Russia. For each of these indicators, we conducted an expert review, taking into account various aspects, from the completeness of the methodology and the quality of primary data to manipulation susceptibility and the relationship to resource allocation.
The assessment results were then validated by at least one, and more often several, experts on the subject matter.
For each indicator, we noted ‘red flags’ — potential issues that require special attention. These include:
- Sharp changes in methodology;
- Discrepant data from different sources;
- Abnormal jumps in regional data;
- Data inaccessibility or publishing issues;
- Confirmed cases of indicator manipulation;
- Poor record keeping or low quality of primary data;
- Sloppy data interpretation.
Based on the results of our study, we assigned reliability scores to all indicators. There are three levels of reliability:
Green — for reliable indicators,
Yellow — for indicators that can be trusted under certain conditions,
Red — for unreliable indicators.