Russia generates lots of statistical data, including annual, quarterly, and monthly indicators made available via various channels, such as the Federal State Statistics Service (Rosstat) website, the Central Statistics Database, the Interdepartmental Statistical Information System, and numerous statistical books, periodicals, bulletins, and guidebooks. In addition, much of the data collected is used as 'raw material' for calculating indicators for publication.
However, Russian statistics are of very poor quality – scarce, inaccurate, or missing – according to Vladimir Bessonov, Head of the HSE's Laboratory for Research in Inflation and Growth.
Individual indicators are not comparable, time series are broken or interrupted even for the most important variables, such as GDP, inflation, industrial production, and investment, which makes statistical data misleading rather than helpful. Thus, the observed declines in investment in early 2002 and in 2011 did not reflect the effects of the economic crisis, but were actually caused by changes in the methodology used for assessing the value of investments. The same reason was at least partially behind the inflation leap in the first half of 2013 and the concurrent economic slowdown. Statistical publications show only chunks of data from recent years, while little is left of decade-old statistics.
In his study on the limitations of Russian statistics entitled 'Russian Statistics: What Do They Preserve for History?' Bessonov explores two critical questions: what kind of statistics are really useful and what can be done to ensure that current statistics can be used as meaningful historical data in the future.
According to Bessonov, the lack of data comparability over time is a serious drawback of Russian statistics that tend to present fragmented numbers rather than consistent time series.
As a result, the comparability of economic data over time is lost, making it impossible to analyse available statistics for economic trends. Thus, data on GDP production broken down by sector is only available since 1995, while earlier estimates dating back to 1991 but collected using outdated methodology were discarded without any attempt to recalculate those retrospective estimates using current methodology or to link the older and newer time series.
Even worse is the situation with monthly and quarterly figures reflecting important dynamics and short-term trends. Such data are essential for analyzing crises and abrupt changes in the economy, Bessonov explains.
Data from previous periods are not always published, making it impossible to construct long time series. In 2012, month-on-month data show a 13% growth in agricultural production compared to 2011, but year-on-year data suggest a 4,8% drop over the same period.
"Current Russian statistics, at least in terms of economic growth data, are unlikely to be used in the future as historical statistics reflecting today's Russia," Bessonov says. “New data continuously emerge, while older data are no longer comparable or simply lost."
In fact, economists can only observe current developments in Russia through a narrow time window of just a few years, covering only short-term trends, while decades-long processes and longer time frames are hardly observable if at all," Bessonov notes.
He doubts that these limitations will make it possible in the future to properly analyse business cycles, let alone long-term trends, of the Russian economy. The shallow temporal depth of Russian statistics also limit reliable long-term projections of Russia's socio-economic development.
Limitations of Russian statistics are due mainly to the Soviet legacy and also to transitional challenges. Inherited from the old Soviet system, Russian statistics continue to focus on annual economic growth indicators (required for reporting) and treat short-term statistics as secondary (who cared about the domestic market conjuncture in Soviet times anyway?).
"Soviet statistics were used primarily for monitoring the implementation of economic plans; thus, they were not designed to capture economic conjuncture or to build long time series of comparable indicators," Bessonov explains. In fact, even the idea of market conjuncture would imply that certain economic processes could unfold independently of government control – hardly a politically acceptable idea in the Soviet Union at that time."
By the start of market reforms at the end of the 1980s and in the 1990s, the country's statistical system, including the training of statisticians and economists, was not prepared to handle the tasks required by a market economy, such as constructing long time series of comparable indicators.
In the post-Soviet era, statistics have assumed a key role in providing macroeconomic analysis and forecasting, but continuing instability and drastic changes in the economy required frequent updates of statistical methods and have favoured a short-term focus.
"Economy is evolving, it is never static. Therefore, statistics should seek to describe a never-ending process of change rather than a series of fragmented states, and its methods should be able to adapt to change, while allowing for data comparability over time,”says Bessonov.