Tag: Putin

Trending? Social Media Attention on Russia’s War in Ukraine

20240218 Social Media Attention on Russia Image 01

Russia’s invasion of Ukraine is one of the most important geopolitical events of the 21st century. For almost two years, international news outlets have been covering the war, often providing daily or even hourly updates. But what is the level of public interest and public engagement in countries around the world? When does the war capture an international audience’s attention and what are the events that supplant it? This brief uses data on X (formerly Twitter) trends in 62 countries to address these questions.

The competition for attention is a defining feature of our information landscape. From the relentless stream of social media updates to the myriad of news articles vying for our clicks, individuals are constantly bombarded with information, each competing for a slice of their limited attention. Amidst this cacophony of voices, certain topics rise to the forefront, capturing the collective consciousness and dominating public discourse.

Russia’s war in Ukraine has, for obvious reasons, commanded significant media coverage over the past two years. It has been described as a hybrid war, where conventional military tactics are increasingly combined with non-traditional methods. This includes an information war, fought with narratives to manipulate people’s perceptions, spread falsehoods, or enlist support. To a large extent, this information war has taken place on social media. On the one hand, social media platforms have been used to spread disinformation and propaganda. For example, we’ve seen the spread of false narratives about the causes of the war, the actions of the different parties involved, and the suffering of the Ukrainian people. But on the other hand, social media has also been used to counter this disinformation, with fact-checking initiatives and grassroots efforts to promote accurate information.

This policy brief analyses the prominence of the war in social media discourse. While the content on traditional media outlets provides a snapshot of the supply of information, platforms like X/Twitter offer a unique window into the broader population’s demand for that information and how they evolve over time. Whether or not hashtags related to Russia’s war in Ukraine are trending in a given country, depends not just on the public’s interest in the war relative to other events in the news, but also on the level of interest relative to sport, music, television, and cats. By tracking the prevalence of trending hashtags, we can gain insights into the public’s engagement with Russia’s war in Ukraine, going beyond traditional media narratives and high-level governmental discussions to uncover the conversations and sentiments that shape broader public opinion.

The X/Twitter data suggest that in most countries, social media attention in the Russian war on Ukraine has been short-lived and sporadic. On February 24, 2022, Ukraine-related hashtags were trending in 100 percent of the countries in our dataset. Two weeks later, on March 9, 2022, they were trending in only 3 percent of the countries. We find that geographical proximity to the conflict is a strong predictor of social media interest. Related hashtags trend most frequently in Eastern, Central and Northern Europe. We also document spikes in interest around events that link a country to the war in Ukraine: announcements of military assistance or visits by Ukraine’s President Volodymyr Zelenskyj. Finally, we compare the hashtags trending in NATO countries to those trending in countries that either sided with Russia or abstained from voting in a critical UN resolution and show significant differences between the two groups.

Data and Methodology

The source for our dataset is archive.twitter-trending.com – a website that records trending hashtags on X/Twitter across countries and over time. We scrape this website to collect (i) the five highest volume topics in each country on each day and (ii) the five longest-trending topics in each country on each day (these two categories can overlap). Our sample consists of the 62 countries available on the website and covers the timeframe July 2021 to December 2023. From this, we construct a country-by-day panel dataset with 55,862 observations.

We identify 11 topic categories that collectively account for the overwhelming majority of trending topics related to Russia’s war in Ukraine. These topics and their relative frequency are shown in Figure 1. The three dominant categories are “Ukraine”, “Russia” and ”Putin”. We use Google’s translation software to translate non-English tweets which account for a significant fraction of the dataset.

Figure 1. Frequency of hashtags in 11 category topics.

Note: This chart shows the number of times topics assigned to our 11 war-related categories were among the top five longest trending topics (in orange) or the top five highest volume topics (in blue) in any country on any day in our dataset. The source are data scraped from archive.twitter-trending.com

Figure 1 shows that it is more common for war-related topics to be among the highest volume topics on a given day than among the longest trending topics. This suggests that these topics attract a lot of interest in a narrow timeframe (e.g. when news breaks) but are relatively less likely to remain prominent over a whole day. Despite this difference, we find that the distinction between highest-volume and longest-trending does not affect any of the patterns we observe when comparing across countries or time. For simplicity, the results shown below all use the highest-volume measure.

It is important to acknowledge the limitations of the X/Twitter data. Firstly, the population actively using X/Twitter is not representative of the overall population. Secondly, the composition of users may differ across countries which complicates cross-country comparisons. Trending hashtags provide an indicator of public interest that is informative only because we do not have high frequency, nationally representative surveys that are comparable across countries. Finally, we are only able to observe the top-five hashtags in a country on any given day. In principle, a war-related topic could increase in absolute volume from one day to the next, while still being crowded out of the top five.

Geographic Variation in Attention

Social media attention to the war in Ukraine varies greatly across countries. The map in Figure 2 shows the proportion of days when any hashtag from the considered categories was among the top-five most tweeted, for each country in the database since the start of the war. Interest has, on average, been higher in Europe as well as in Anglo-Saxon countries. In contrast, other regions of the world exhibited less sustained interest, as indicated by the lower frequency of related hashtags among the top-five most tweeted topics.

Figure 2. Prevalence of war-related hashtags.

Note: The map shows the share of days on which war-related hashtags (in our 11 categories) were among the top five highest volume topics on X/Twitter between 24/02/2022 and 18/12/2023. Countries in white are not among the 62 countries in the dataset. The source are data scraped from archive.twitter-trending.com

To some extent, this heterogeneity is explained by distance. Figure 3 plots the frequency of war-related trends against geographical proximity to the conflict zone (represented by the distance from each country’s capital to the city of Kharkiv in eastern Ukraine, a major point of focus during the ongoing war). The relationship is clearly negative, suggesting that physical distance from the crisis reduces the intensity of online discourse and public interest. Unsurprisingly, the number of related trends is highest in countries directly or indirectly involved in the conflict – Ukraine, Russia, and Belarus – as well as in Latvia which borders both Russia and Belarus.

Figure 3. Frequency of war-related hashtags and distance from Kharkiv.

Note: The chart shows the log of the distance from each country’s capital city to the city of Kharkiv in km on the x-axis and the logged frequency of war-related topics among the top five highest volume topics in that country between 24/02/2022 and 18/12/2023 on the y-axis. The source are data scraped from archive.twitter-trending.com

Variation in Attention Over Time

Over the past two years, the war has sustained a relatively high intensity. By contrast, global attention on X/Twitter has been more sporadic, spiking around specific events. This is shown in Figure 4, which plots the day-to-day variation in the number of battle events as recorded by the Armed Conflict Location & Event Data Project (ACLED) (in blue) as well as the share of countries where war-related tweets are trending (in orange). Attention was highest at the time of the invasion in February 2022 and the days of the Wagner Group rebellion in June 2023. Overall, the correlation between twitter trends and conflict intensity is positive but relatively weak.

Figure 4. Frequency of war-related hashtags and intensity of conflict.

Note: The chart shows the number of daily battle events in Ukraine as classified by ACLED on the left axis (in blue) and the share of countries where war-related topics were trending on the respective day on the right axis (in orange). The sources are ACLED’s Ukraine conflict monitor and data scraped from archive.twitter-trending.com

Attention also reacts to other major global events. Figure 5 compares the number of top-five trending hashtags related to the categories of interest in each country on two specific dates: February 24, 2022, the day of Russia’s full-scale invasion of Ukraine, and October 7, 2023, the day of a Hamas terror attack on Israel. On the day of the Russian invasion, the majority of countries in our sample exhibited the highest value. In contrast, on the day of the Hamas attack, related hashtags were trending almost nowhere outside Ukraine and Russia, indicating that global attention and engagement with this new ongoing crisis significantly overshadowed the focus on the situation in Ukraine. This shift in attention demonstrates how breaking news can capture the public’s interest and divert focus from ongoing crises, affecting the level of engagement on social media and potentially influencing the global response and discourse surrounding these events.

Figure 5. Map of prevalence of war-related hashtags on two different dates.

Note: The maps show the share of the top five highest volume topics on twitter related to Russia’s war on Ukraine. The map on the left shows 24/02/2022 – the day of Russia’s invasion. The map on the right shows 07/10/2023 – the day of a Hamas terror attack on Israel. Countries in white are not among the 62 countries in the dataset. The source are data scraped from archive.twitter-trending.com

While some events impact attention globally, others affect the salience of the conflict for a specific country. Figure 6 shows that people pay more attention to the war when there is a tangible connection to their own country. The panel on the left shows that war-related topics were more likely to trend in a country around the days where the country announced an aid package for Ukraine (military, financial or humanitarian). It shows an increasing trend in the preceding days and a peak on the day of the announcement. The panel on the right shows that war-related topics were more likely to trend in a country around the days of a visit from President Zelenskyj. This effect is large in magnitude but only lasts for around three days.

Figure 6. Likelihood of hashtags trending in relation to country-specific event.

Note: The charts show variation in the share of countries where at least one war-related topic was among the top five highest volume topics on days relative to a specific event. In the left chart, day 0 represents the day on which a country’s government announces an aid package for Ukraine. In the right chart, day 0 represents the day on which President Zelenskyj arrived in a country for an official visit. The source for these charts are: (i) the Kiel Institute’s Ukraine Support Tracker (Trebesch et al., 2023), (ii) Wikipedia’s list of official visits by President Zelenskyj and (iii) data scraped from archive.twitter-trending.com

While the events above act as drivers of attention, it is also interesting to consider what causes war-related topics to drop out of the top five trending topics. We distinguish between two reasons why war-related hashtags could stop trending: (i) a loss of interest that results in a reduction in the absolute number of related tweets (ii) the rise of other topics that displace war-related tweets from the top five. Figure 7 focuses on days where war-related topics dropped out and compares the volume of tweets on the last day where they were in the top five, to the threshold they would have had to surpass in order to make the top five on the subsequent day. In cases where the threshold is lower than the previously observed volume of tweets (a ratio of less than 1), the topic would have kept trending had it sustained its volumes, and one can conclude there was an absolute loss of interest. In cases where the ratio is greater than one, it is possible that the topic sustained its previous volume of tweets but was crowded-out by the rise of a new trending topic. Figure 7plots the histogram of this ratio. 73 percent of the cases are in the first category (loss of attention) and 27 percent are in the possible crowding out category. This provides further evidence to suggest that attention to the war on social media is typically fleeting.

Figure 7. Loss of attention vs crowding out.

Note: The sample are country-days where war-related topics were among the top five highest-volume topics but then dropped out of the top five the next day. The chart provides a histogram of the ratio of the threshold for making the top five on the subsequent day to the highest volume of tweets of a war-related topic. Values below 1 (in blue) indicate that the volume was above the next day’s threshold and the topic declined in absolute terms. Values above 1 (in orange) indicate that the volume was below the next day’s threshold. The source are data scraped from archive.twitter-trending.com

We also examine the content of discussions on the first day after war-related hashtags drop out of the top five. The word cloud in Figure 8 suggests that on such days, people primarily discuss entertainment topics like music and football.

Figure 8. Word cloud of hashtags trending on days war-related categories drop out.

Note: The figure provides a word cloud of trending topics on country-days where no war-related topic was among the top five highest volume topics, but at least one war-related topic had been in the top five on the previous day. The source are data scraped from archive.twitter-trending.com

Content and Context of War-Related Discourse

In addition to providing insight into the level of engagement, hashtag analysis can also reveal the content and context of popular discourse surrounding the war. By examining words trending on the same days as those from our 11 categories, we can gain a better understanding of the topics people are discussing and how the conversation varies across different regions. Figure 9 illustrates this through word clouds, showing the language used in NATO countries on the left and in countries that abstained or voted against the United Nations General Assembly Resolution ES-11/1 on the right. This resolution, dated March 2, 2022, condemned the brutal invasion of Ukraine and demanded that Russia immediately withdraw its forces and comply with international law.

This exercise allows us to compare the dominant themes and narratives in these two groups of countries and observe any differences in public perception and discourse regarding the conflict. The prevalence of cryptocurrency and NFT (non-fungible tokens) references in the word cloud on the right is suggestive of how economic interests and alternative financial systems could be relevant for the positions of countries that abstained or voted against the resolution, and how this might affect their involvement or response to the conflict. On the left, words like “NATO”, ”Biden”,  and ”Trump” clearly stand out, suggesting that these topics are central to the discourse on the war in NATO countries. This could indicate a focus on geopolitical alliances, international cooperation, and the role of key political figures in shaping the response to the conflict. Interestingly, “Putin” is very prominent in the left word cloud while “Russia” and “Russian” are more prominent on the right. This could indicate that Putin is seen and discussed as the primary antagonist in NATO countries.

Figure 9. Word cloud of hashtags in NATO countries vs Russia-friendly countries.

Note: These word clouds represent topics that trend on days where at least one war-related topic is trending in the respective country. The cloud on the left shows NATO countries. The cloud on the right shows countries that either abstained or voted against United Nations General Assembly Resolution ES-11/1. The source are data scraped from archive.twitter-trending.com

Conclusion

This brief uses X/Twitter trends as a barometer of public interest in Russia’s war in Ukraine. We show how attention fluctuates over time in response to developments in the conflict, to other breaking news, and to local events that make the conflict salient for a domestic audience. We also provide descriptive evidence on the variation across geographical regions and among different groups of countries. Additionally, we analyse the instance where Ukraine-related topics stop trending and find suggestive evidence that this is typically due to a gradual loss of interest rather than crowding out by new distracting trends.

Public attention and engagement drive policy in democratic countries, and the sustained support of its democratic allies is vital for Ukraine during this critical time. Understanding the patterns and influences of public attention is crucial for developing effective strategies to sustain engagement and support. This can be achieved for example by regularly highlighting the ongoing significance and bearing of Russia’s war against Ukraine, even as other events dominate the headlines. Emphasizing the impact of the conflict on individuals and communities, as well as its broader implications for international relations and global security, can help sustain public interest and engagement.

References

  • ACLED. Ukraine Conflict Monitor. https://acleddata.com/ukraine-conflict-monitor/
  • Trebesch, C., Antezza, A., Bushnell, K., Bomprezzi, P., Dyussimbinov, Y., Frank, A., Frank, P., Franz, L., Kharitonov, I., Kumar, B., Rebinskaya, E., Schade, C., Schramm, S., and Weiser, L. (2023). The Ukraine Support Tracker: Which countries help Ukraine and how? Kiel Working Paper, 2218, 1-75.
  • Twitter Trending Archive. Scraped on ##/12/2023. https://archive.twitter-trending.com/

Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

Insights and Research Shared at the 2023 FREE Network Retreat

FREE network retreat Image from the conference

The 2023 FREE Network Retreat, an annual face-to-face event for members of the FREE Network, gathered its representatives to share and exchange research ideas and to discuss its institutes’ respective work and joint efforts within the Network. An academic session highlighted multiple overarching areas of interest and opportunities for research collaboration and included a plenary session on topics ranging from theoretical underpinning of Vladimir Putin’s regime to climate change beliefs and to consumer behaviour in credit markets. A session addressing the respective institute’s work during the last year also demonstrated the importance and relevance of the FREE Network’s joint initiatives on gender, democracy and media, and climate change and environment: FROGEE, FROMDEE and FREECE. This brief gives a short outline of the plenary session and an overview of some further topics covered during the conference.  

The Academic Day

The Academic Day consisted partly of a plenary session and partly of an academic session. The academic session was outlined to demonstrate the wide spectrum of research interests within the network and to promote and highlight the opportunities for research collaboration. Designed as a series of poster sessions, each organized around a common research theme, it allowed for an exchange of ideas between presenting researchers and the audience while displaying the overlap of the various research interests across the institutes. At the same time, the poster session combined the broad range of topics within 10 overarching subjects (trade, gender, migration and education, public economics, energy, labor, political economy and development, macro, conflict, and theory and auctions).

The plenary session further illustrated the wide variety of topics the FREE Network researchers’ work on. During the plenary session, three distinguished presentations were held, summarized in what follows.

“Why Did Putin Invade Ukraine? – A Theory of Degenerate Autocracy”

Firstly, Konstantin Sonin, Professor at the University of Chicago Harris School of Public Policy, gave a presentation of his working paper (with Georgy Egorov, Northwestern University) in which the Russian full-scale invasion of Ukraine is explained through a theoretical framework on dictators’ decision-making in degenerate autocracies.

Sonin outlined how the beliefs about Ukraine in Kremlin, prior to the invasion, were factually wrong. For example, Kremlin believed that Ukraine, despite plenty of facts pointing in the opposite direction, lacked a stable government and had an incapable army. Further, it was believed that the US and Europe wouldn’t care about Ukraine and that Russian troops would be welcomed as liberators – the latter exemplified by the fact that Russia sent police and not the army during the first phase of the invasion. He also stressed that the decision to invade Ukraine is likely to have disastrous consequences for Vladimir Putin, his regime, and for Russia as a whole. This is, however, not the first example of a disastrous decision made by a leader of an autocratic regime, leading up to the question: What explains such choices that should not rationally have been made? And how can leaders make them in highly institutionalized environments where they are surrounded by councils and advisors who are supposed to possess the best expertise?

The model presented by Sonin assumes a leader in such highly institutionalized environment that wishes to stay in power and whose decisions are based on input from subordinates. The subordinates differ in level of their expertise and the leader thus chooses the quality of advice that he receives through his choice of subordinates.  In turn, while giving advice to the leader, the subordinate considers two factors: the vulnerability of the leader and their own prospects should the leader fall. In equilibrium there is a tradeoff as competent subordinates are also less loyal (since a more competent person might know when to switch alliances and have better prospects if the regime changes).

The leader also has access to repression as an instrument. Repression decreases his changes to be overthrown but raises the stakes for a potential future power struggle, as a leader with a history of repression is more likely to be repressed by his successor.

This interaction creates a feedback loop. If a dictator chooses repression, he feels more endangered, and he then chooses a more loyal subordinate who is less likely to deceive him for personal gain under a potential new regime. However, this leads to the appointment of less competent subordinates whereafter the information that flows to the leader becomes less and less reliable – as illustrated by Kremlin’s beliefs about Ukraine prior to the war.

There are three types of paths in equilibrium, Sonin explained; 1. “stable autocracy”, with leaders altering in power and choosing peaceful paths without repressions 2. “degenerate autocracy” – where the incumbent and opponent first replace each other peacefully and then slide into the repression-based change of power (until one of them dies and the story repeats), and 3. “consecutive degenerate autocracy” – where each power struggle is followed by repression.

Concluding his presentation, Sonin highlighted that in a degenerate autocracy such as Russia, individual decisions by the leader are rarely crucial due to the high level of institutionalization. However, as shown by the model, the leader is inevitably faced with a situation where he is surrounded by incompetent loyalists feeding him bad intel and setting him up to make disastrous decisions – most recently displayed in Vladimir Putin’s decision to invade Ukraine.

“Facing the Hard Truth: Evidence from Climate Change Ignorance”

Pamela Campa, Associate Professor at Stockholm Institute of Transition Economics, gave the conference’s second presentation, which detailed her work (with Ferenc Szucz, Stockholm University) on climate change skepticism.

Campa opened her talk with the current paradox regarding climate change, where, in the scientific community there is a strong consensus about the existence of climate change, but in society at large, skepticism is largely prevalent. This can be exemplified by one quarter of the US population not believing in global warming in 2023, and Europeans not believing in the fact that humans are the main driver of climate change.

According to Campa, the key question to answer is therefore “Why does ignorance about climate change persist among the public – in spite of the overwhelming evidence?”. One possible explanation may be a deficit in comprehension; people simply don’t understand the complexity of climate change and thus follow biased media and/ or politicians more or less sponsored by lobbyists. However, research have shown scientifical literacy to be quite uncorrelated with climate change denial, contradicting the above explanation. The second hypothesis, and of focus in the study, instead revolve around the concept of information avoidance. To test the hypothesis that people actively avoid climate change information, the authors key in on coal mining communities in the US having been exposed to negative shocks in the form of layoffs. These communities are of interest given their strong sense of identity and the fact that they are directly affected by the green transition. Arguably, a layoff shock would negatively affect not only their economy, but also pose a threat to their perceived identity. Given the context, it can thus be assumed that these communities to a larger extent would avoid information on climate change and information post-shock to restore the threatened identity.

The authors consider US counties experiencing mass layoff (more than 30 percent of mining jobs lost between 2014 and 2017) as treated counties, finding that in these counties, learning about climate change is 30 to 40 percent lower than in counties having experienced no mass layoffs. To account for the fact that the layoff itself may cause changes in learning, the authors also consider an instrument variable analysis in which gas prices are exploited as instrument for the layoffs – once again displaying the fact that people in affected communities believe climate change to be caused by humans to a lesser extent, when compared to counties in which no mass layoffs had occurred.

Interestingly, when controlling with other industries with somewhat similar characteristics (such as metal mining), the drop in climate change learning disappears, feeding in the notion of “identity-based information avoidance”.

The lack of support for and consensus among the public of the ongoing climate change and its drivers might pose a threat for the green transition as well as reduce personal effort to reduce the carbon footprint, Campa concluded.

“Consumer Credit with Over-Optimistic Borrowers”

In the plenary session’s last presentation, Igor Livshits, Economic Advisor and Economist at the Federal Reserve Bank of Philadelphia, presented his working paper (with Florian Exler, University of Vienna, James MacGee, Bank of Canada and Michèle Tertilt, Mannheimer University) on consumer credit and borrower’s behaviour.

There has been much debate on whether and how to regulate consumer credit products to limit misuse of credit. In 2009/2010 several initiatives and regulations (such as the 2009 Credit Card Accountability Responsibility and Disclosure Act) were introduced with the aim of protecting consumers and borrowers from arguments that sellers of credit products exploit lack of information and cognitive capacity of borrowers. There is however a lack of evaluation of such arguments and subsequent regulations, which Livshits explained to be the motivation behind the paper.

The paper differentiates between over-optimistic borrowers (behaviour borrowers) and rational borrowers (rationalists). While both types face the same risks, behaviour borrowers are more prone to shocks and are at the same time unaware of these worse risks (i.e., they believe they are rationalists). Focusing on these types of borrowers, the paper introduces a model in which the lenders endogenously price credit based on beliefs about the borrower type. Households decide whether to spend or save and if to file for bankruptcy in an environment in which they are faced with earning shocks and expense shocks.

In this structural model of unsecured lending and default, Livshits finds that behavioral borrowers’ “risky” behaviour negatively affects rationalists since both types are pooled together and, thus rationalists are overpaying to cover for the behaviour borrowers. A calibration of the model also suggests that behavioral borrowers borrow too much and file for bankruptcy too little and too late.

Livshits argued that the model does not provide evidence of the notion that borrowers need protection from lenders, but rather that borrowers need to be protected from themselves. In fact, had behaviour borrowers been made aware of the fact that they are overly optimistic about the actual state of their future incomes, they would borrow 15 percent less.

To address the increased risks behaviour borrowers take at the cost of rationalists, policies such as default made easier, taxation on borrowing, financial literacy efforts and score-dependent borrowing limits could all be considered. Such policies may lower debt and reduce bankruptcy filings but as they may also reduce welfare and exhibit scaling difficulties.

Updates from the Institutes

During the Retreat, the respective institutes shared the previous year’s work, and updates within the FREE Network’s three joint projects were also presented. These go under the acronyms of FROMDEE (Forum for Research on Media and Democracy in Eastern Europe), FREECE (Forum for Research on Eastern Europe; Climate and the Environment) and FROGEE (Forum for Research on Gender Economics in Eastern Europe), and address areas of great relevance in Eastern Europe and the Caucasus. Researchers from all FREE Network institutes work on these topics, with the most recent policy paper written in coordination by SITE, KSE and CenEA (with expert Maja Bosnic, Niras International Consulting). The policy paper focuses on the gender dimension of the reconstruction of Ukraine – putting emphasis on the necessity of gender budgeting principles throughout the various parts of reconstruction.  An upcoming joint research paper will consider the effects of gasoline price increase on household income across the Network’s countries, written under the FREECE umbrella.

The three themes of gender, media and democracy, and environment and climate are not only purely research topics within the institutes. They also reflect developments and challenges that the institutes to a various extent face in the respective contexts in which they operate. The work focusing on the reconstruction of Ukraine is an excellent example of an area that encompasses all three.

Another example of the relevance of the three themes features prominently in one of the institutes’ most tangible contribution to their respective societies: their education programs. Nataliia Shapoval, Vice President for Policy Research at Kyiv School of Economics (KSE), emphasized how KSE has – amid Russia’s war on Ukraine – managed to greatly expand. Over the past year, KSE has launched 8 new bachelor’s and master’s programs, some of which are directly targeted at ensuring postwar reconstruction competence. On a similar note, Lev Lvovskiy, Academic Director at the Belarusian Research and Outreach Center (BEROC) mentioned the likelihood of next year being able to offer students a bachelor’s program in economics and several business courses in Vilnius – BEROC’S new location. BEROC’s effort in providing quality education in economics to Belarus’ exile youth is considered a fundamental investment in the future of the country – providing a competent leading class capable of installing democracy and fair elections in Belarus once the current regime is gone. The emphasis on education was further highlighted by Salome Gelashvili, Practice Head, Agriculture & rural policy at the International School of Economics Policy Institute (ISET-PI) who not only mentioned the opening of a master’s program in Finance at ISET but also the fact that an increasing number of students who’ve recently graduated from PhD’s abroad are now returning to Georgia. Such investments into education are necessary to counter Russian propaganda in the region all three agreed, emphasizing the need to continually stem Russia’s negative influence in the region. This investment into education is also important to hinder countries from sliding away from democratic values – realized in Belarus and threatening in Georgia.

To further delve into the issues of democratic backsliding, a tendency that has been recently observed not only in the region but also more widely across the globe, FROMDEE will organize an academic conference in Stockholm on October 13th, 2023.

Concluding Remarks

The 2023 FREE Network Retreat provided a great opportunity for the Networks’ participants to jointly take part of new research and to share experiences, opportunities, and knowledge amongst each other. The Retreat also served as reminder of the importance of continuously supporting economic and democratic development, through research, policy work, and networking, in Eastern Europe and the Caucasus.

List of Presenters

Disclaimer: Opinions expressed in policy briefs and other publications are those of the authors; they do not necessarily reflect those of the FREE Network and its research institutes.

The Russian economy under Putin (so far)

20121229 Accountability in Russia Image 02

Russians are heading to the polling booths on March 18, but where will the economy head after Putin has been elected president again? This brief provides an overview of the economic progress Russia has made since 2000 as well as an economic scorecard of Putin’s first three tenures in the Kremlin and uses this to discuss what can be expected for the coming six years. Although significant growth has been achieved since 2000, all of this came in the first two tenures of Putin in the Kremlin on the back of increasing oil prices. In order to generate growth in his upcoming presidential term, Putin and his team will need to address the significant needs for reforms in the institutions that form the basis for modern market economies. Otherwise, Russia will continue to be hostage to the whims of the international oil market and eventually lose most of its exports and government revenues as the world moves towards a carbon free future. Perhaps this is beyond the scope of Putin as president, but not beyond the horizon of young Russians that will be casting their votes on Sunday and in future elections.

Let’s assume that Putin will be elected president again on March 18 (for once a very realistic assumption made by an economist). What will this mean for the Russian economy in the coming six years given what happened during his previous and current tenures in the Kremlin? To assess the future as well as to understand Putin’s power and popularity, this brief starts by looking back at the economic developments in Russia since Putin first became president.

Although many different factors enter the power and popularity function of Putin, economic developments have a special role in providing the budget constrain within which the president can operate. A higher income level means more resources to devote to any particular sector, project, voting group or power base. This is not unique to Russia, but sometimes forgotten in discussions about Russia, that often instead only focus on military power or control of the security apparatus and media. These are of course highly relevant dimensions to understand power and popularity in Russia, but so is economic development, particularly in the longer run.

Russia’s economy in the world

The economic greatness and progress of a country is usually assessed in terms of the size of the economy, how much growth that has been generated, and how well off the citizens are relative to the citizens of other countries. So, by our common indicator gross domestic product (GDP), has Russia become a greater and more powerful country since Putin first became president? Table 1 shows two things, the absolute level of GDP measured in USD at market exchange rates and the rank this gives a country in a sample of 192 countries in the world that the IMF collects data on (this brief is too short for a long discussion of the most relevant GDP measure, but GDP at market exchange rates makes sense when comparing the economic strength of countries in a global context, Becker 2017 provides a discussion of alternative measures as well). When Putin become president for the first time in 2000, the value of domestic production was estimated at $279 billion, which implied a 19th place in the world rankings of countries’ GDP. In 2016, almost three presidential terms of Putin later, Russia’s GDP had increased by 4½ times to $1281 billion and its ranking improved to 12th place in the world. This clearly is an impressive record by most standards. However, the Russian economy is still the smallest economy of the BRIC countries and corresponds to only 7 percent of the US economy in 2016. In other words, impressive progress by Russia but the country is (still) not a global superpower in the economic arena.

Table 1. Russia in the world (GDP in USD bn)

Source: IMF (2017)

For the average Russian, income per capita is a measure more closely connected to consumption and investment opportunities or ‘welfare’. Progress in this area is also more likely to affect how individuals assess the performance of its political leaders. Of course, progress in terms of overall GDP and GDP per capita is closely linked unless something unusual is happening to population growth. Therefore, it is not surprising that GDP per capita also increased by around 4½ times between 2000 and 2016 (Table 2). This is the first order effect of the economic development in Russia, but in addition, citizens of Russia moved up from a world income rank of 92nd to 71st. This has implications when Russian’s compare themselves with other countries and can in itself provide a boost of national pride.

It also directly affects opportunities and status for Russians visiting other countries. Being at place 71 may not be fully satisfactory to many, but we should remember that due to the rather uneven income distribution in Russia, many of the people that travel abroad are far higher up on the global income ranking than what this table indicate. Nevertheless, Russia is far behind the Western and Asian high-income countries in terms of GDP per capita. And although the picture would look less severe if purchasing power parity measures are used, the basic message is the same; Russia has still a lot of catching up to do before its (average) citizens enjoy the economic standards of high-income countries.

Table 2. Russian’s in the world (GDP/capita)

Source: IMF (2017)

The macro scorecard of Putin

So what generated the impressive 4½ times increase in income in USD terms from 2000 to 2016 and can we expect high growth during Putin’s next six years in office? The short answer to the first question is the rise in international oil prices and to the second question, we don’t know. Table 3 provides a comparison of different economic indicators for Putin’s two first terms in office compared with his current term (where GDP data ends in 2016 so the sample is cut short by a year). It is evident that the impressive growth over the full period is entirely due to the strong growth performance in the first two presidential tenures. Rather than generating growth in the most recent period, the economy has shrunk. This is explained by the evolution of international oil prices, which quadrupled in the first eight years and instead halved in the more recent period. These swings in oil prices have also been accompanied by significant shifts in foreign exchange reserves, the exchange rate, and the value of the stock market.

In Becker (2017) I discuss in more detail the importance of international oil prices in understanding the macro economic development in Russia. In particular, it is important to note that it is changes in oil prices that correlate with GDP growth and other macro variables and that the problems with predicting oil prices makes it very hard to make good predictions of Russian growth.

Table 3. A macro scorecard of Putin in office

Source: Becker (forthcoming)

Policy conclusions

To break the oil dependence and take control of the economic future of Russia, the president will need to implement serious institutional reforms that constitute the basis for a modern, well-functioning market economy in his next term. Otherwise, Russia will continue to be hostage to unpredictable swing in international oil prices and nobody—including the president, the central bank, the IMF and financial markets—will be able to predict where the Russian economy is heading in the next couple of years.

Figure 1. Reforms (still) needed

Source: World Bank (2017)

In the longer run, the prediction is much easier. With the world moving towards a green economy, the price of oil will see a structural decline that will rob Russia (and other oil exporters) of most of its export and government revenues. The reforms which basically every economist agree are needed are related to market institutions and Figure 1 provides a clear illustration of key reform areas. The progress during Putin’s years in office has been modest at best. Swedish institutions in 2016 have been added to the figure as a comparison and it is clear that the institutional gap between Russia and Sweden is significant. Of course, all countries are different, but Russian policy makers that are interested in reforming its economy are most welcome to Sweden for a discussion of what we have done to build our institutions.

References

  • Becker, T. (2017). ‘Macroeconomic Challenges’, in Rosefielde, S., Kuboniwa, M., Mizobata, S. and Haba K. (eds.) The Unwinding of the Globalist Dream: EU, Russia and China, Singapore: World Scientific Publishing.
  • Becker, T. (forthcoming), ‘Russia’s economy under Putin and its impact on the CIS region’, Chapter 2 in T. Becker and S. Oxenstierna (eds.) Perspectives on the Russian Economy under Putin, London: Routledge.
  • IMF (2017), World Economic Outlook database, April 2017 edition available at http://www.imf.org/external/pubs/ft/weo/2017/01/weodata/index.aspx
  • World Bank (2017), Worldwide Governance Indicators (WGI), 2017 update available at http://info.worldbank.org/governance/wgi/index.aspx#home

Putin and the Modernization of Russia – a Chimera?

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Vladimir Putin is once more the Russian President and a new government has been formed consisting of most of the same faces and mentality. Putin’s victory looks complete – yet there is a very real risk that it will be Pyrrhic. Even if the ‘managed’ political and economic system – rooted in a lack of competition and openness – that has been his defining project can remain stable, it will continue to sap the country’s vitality. In the election campaign, even Putin acknowledged the country’s lack of modern and competitive industries, as well as a business environment plagued by corruption, cronyism and excessive regulation. Yet, in calling for further modernisation of the economy, Putin has also called for more of the same policies, notably a central role for the Russian state in supporting new industries and technological leadership; a newly established State Corporation for Siberia and the Far East is a case in point. 

However, this very model has so far achieved very limited results. Oil and gas still account for nearly 70% of total merchandise exports and around half of the federal budget. While relying on publicly funded and managed entities – such as Rusnano – to shepherd the economy into more diversified and more productive spaces, particularly in high-tech activities, has also yielded a relatively meagre harvest. Rusnano itself has already acknowledged the limited portfolio of innovative projects to fund.

In the arena that provides the most compelling metric of competitiveness – export markets – relatively few Russian firms compete in international markets and very few do in higher value added trade. Ricardo Hausmann (2007) has argued that the products that a country exports also reflect the proximity of products and their reliance on similar sets of inputs, such as physical assets and knowledge or skills. Near the start of Russia’s transition it has been calculated that Russia had comparative advantage in only 156 out of 1242 product lines when using a 4-digit SITC classification. Most were natural resources. In contrast, China had comparative advantage in 479 product lines. And as regards proximity, few of Russia’s export products were closely connected to other products, meaning that there was limited scope for enhancing exports. Yet, by 2010 our research shows that there has been an increased concentration on natural resource exports. The contraction of manufacturing has, further, been associated with a fall in the number of Russian product lines with comparative advantage to 103. In contrast, the number for China increased in 2010 to 513. So, despite Putin’s rhetoric, the Russian export basket has become even more concentrated since the mid-1990s. Moreover, the ability to shift into proximate products, as well as diversify into new ones, remains very restricted. This is due to several factors.

A common diagnosis is that failings in the business environment are to be blamed. This is not a new complaint. While the options for limiting these constraints may not be straightforward but the broad policy direction and options are well understood. The challenge is in enforcement. In this – as also with improving governance and further reducing the role of public ownership – improvement is only likely to start with serious political commitment. That is still lacking.

But modernising the economy depends on much more than a good business climate. Critically, it depends on what sorts of skills and knowledge are available to the economy. Yet, even here where many have believed that Russia is relatively favourably situated, on closer inspection, the situation turns out to be far more problematic. In fact, our evidence indicates deterioration in the quality of both skills and education over time, including limitations on the supply of high quality management. Evidence from surveys suggests that Russian firms face problems in finding workers with the appropriate skill profile. While this may be the situation for existing firms, it seems likely that potential entrants to new, diversified activities may, if anything, face even steeper constraints. To understand whether this is indeed the case, the leading – 270 – recruitment firms in Russia were surveyed using face-to-face interviews in 23 locations in Russia, including Moscow and St. Petersburg. This included a small experiment looking at skills availability for work in more innovative activities, such as web technology aimed at social networking and marketing. The aim was to see whether innovative activities faced more binding constraints when trying to hire.

The results of this survey are unequivocal. Not only are there widespread skill gaps for all types of skills, but it takes firms a much longer time to fill vacancies for skilled personnel. This is particularly true for relatively innovative activities. Recruiting managers or high level professionals in the major Russian cities on average takes 3-5 times longer for innovative activity. Even in Moscow, recruiting a manager or high level professional would take between 3-4 times longer; the gap was yet greater in the Urals, Siberia and the Far East.

Moreover, looking at the sorts of skills that are lacking for each type of potential recruit (e.g., a manager); recruiters also report an absence of basic or essential skills. For example, lack of problem solving and management skills were overwhelmingly the most commonly cited limitations for managers, with high level professionals most commonly lacking both problem solving and practical skills. Among the consequences, many firms decide to postpone launching new products and/or modernizing plant.

In short, our evidence shows not only widespread skill shortages but also major barriers on the availability of personnel for firms wishing to establish new or relatively innovative activity. At the same time, anecdotal evidence also suggests that among the thin layer of top talent – likely to be essential for high tech and other innovative activities – many prefer to emigrate. In contrast, Russia fails to attract talent from other countries, not least because of a restrictive migration regime.

The last decade has seen an emphasis on modernising and diversifying Russia. The results have been depressingly limited. Yet Putin and his government propose more of the same. In effect, they are continuing to take a huge gamble by relying on a mix of energy prices and publicly funded industrial policy to paper over the structural weaknesses of the economy. As this article has shown, what Russia currently produces and exports – and the underlying skills and knowledge – provide a very weak base for achieving the goals of modernisation.

References

  • Denisova, I., and S.Commander, S.Commander and I. Denisova (2012), ‘Are skills a constraint on firms? New evidence from Russia’, EBRD and CEFIR/NES, mimeo
  • Hausmann, R., and Klinger, B., (2007), “The Structure of the Product Space and the Evolution of Comparative Advantage”, CID Working Paper No. 146
  • Volchkova, N., Output and Export Diversification: evidence from Russia, CEFIR Working Paper, 2011

 

Presidential Elections in Russia: Massive Vote Fraud Ensures that Legitimacy is in Doubt, but the Policy Direction is not

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The March 4th, 2012, elections formally returned Vladimir Putin, the paramount leader of Russia since 1999, to the presidency. Despite Draconian restrictions on entry, financing, campaigning by other candidates, Putin’s dominance of TV, blatant use of state employees and funds to his own advantage, and significant vote fraud, the victory was underwhelming in the end. While the official tally was only 63.6 percent in Putin’s favor, estimates of his vote share by independent observers relying on networks of tens of thousands of volunteers were in the range of 49-57 percent of the turnout; even lower.  (If his share was truly below 50 percent, a run-off vote would have to take place between Putin and the runner up) The second major outcome of the elections was the successful attempt by civic society to ensure a fair vote count in Russia’s largest city and capital, Moscow, where Putin’s official vote share (45 percent) on March 4th was the same that United Russia achieved in the December 4th parliamentary elections. (Generally, Putin polls much higher than United Russia.) The third outcome was the emergence of Mikhail Prokhorov, a billionaire with negligible experience in politics, as a major political force representing large cities and young educated voters.

The Success of Civic Society in Moscow and Vote Fraud Elsewhere

The central issue in the wake of the March 4th elections is the extent of fraud organized by the incumbent. Massive fraud during the December 4th parliamentary elections generated mass protests in response. In total, hundreds of thousands of Muscovites took part in four large rallies held during this winter. (No political rallies of comparable size, except for the state-sponsored pro-Putin ones, have taken place during the last 15 years.) A similar discrepancy between the actual vote and official returns was expected to generate even larger protests this time round.

Despite dozens of reported and video-documented cases of organized groups brought in to Moscow to vote multiple times and the presence of tens of thousands of observers, public outrage after massive vote fraud in the parliamentary elections last December is likely to have prevented the most outrageous and blatant forms of fraud during these elections. No less important, it is also likely that they generated less directly observable forms of electoral manipulation. Not surprisingly, for Moscow, the vote count by Citizen Observer, Golos, and other independent and highly respected observer organizations nearly coincided with the official election results, certified by the widely despised Central Election Commission (CEC). (Since December, the name of the head of CEC, Vladimir Churov, has become a synonym for incompetence and of fawning loyalty to the incumbent.) This does not mean, however, that no fraud took place outside the capital.

Figure 1. Cross-plot of the United Russia (Putin) vote share vs. turnout in the December 4, 2011, parliamentary elections and the March 4, 2011, presidential elections in Moscow. (Courtesy of Alexei Zakharov, HSE and Citizen Observer, using the CEC data.)


A side effect of the fair vote count on March 4th, 2012, in Moscow was that it highlighted the extensive centrally-organized fraud in parliamentary elections held on December 4th, 2011. (See the December 2011 issue of the FREE Policy Brief for a snap analysis of the parliamentary elections.) Figure 1 shows that the suspicious-looking relationship between the turnout and the Putin-led United Russia Party, highly visible in December (top figure), completely disappeared in March (bottom figure). Thus, the strong correlation between turnout and the United Russia vote share is a result of ballot-stuffing rather than anything else (theoretically, such a correlation might be caused by some socio-demographic characteristics of United Russia’s supporters). Similarly, Figure 2 exhibits a “normal” (Gaussian) distribution of total votes for United Russia/Putin by turnout (this is what should be expected theoretically, and is consistently observed in democratic elections around the world) on March 4th (bottom figure) and an unusual distribution, a result of changed voting protocols on December 4th (top figure).

Figure 2. Number of ballots by turnout in the December 4, 2011, parliamentary elections, and the March 4, 2011, presidential elections in Moscow. (Courtesy of Maxim Pshenichnikov using the CEC data.) Note the spikes on 70,75,70,85, and 90 percentiles on the left graph, a result of “targeting” by election officials. 

Outside Moscow, the situation was different. Across the country, independent observers documented ballot stuffing and manipulation of local vote returns. St. Petersburg, the second largest city in Russia with a population of just over 4 million and the cradle of the “Putin’s team”, is a case in point. The preliminary estimates, based on a (nearly random for these purposes) sample of 269 polling stations (which is about 12 percent of the total number of station in the city), shows that the actual vote share for Putin was 50 percent rather than the officially reported 65 percent, while for Prokhorov it was 22 percent instead of 14 percent, and for Zyuganov 15 percent instead of 11 percent in the official tally. These estimates are based on the comparison between the official results as certified by the Central Electoral Commission with official copies of vote protocols signed by accredited observers and members of local electoral commissions at the polling stations. In other words, the discrepancy is a result of vote fraud at the level of the territorial electoral commission instead of more conventional forms of fraud, such ballot-stuffing at polling stations.

New Faces of Russian Politics

Three of the four competitors against Putin on March 4th were veterans of Russian politics. The Communist party Chairman, Gennady Zyuganov, lost presidential elections to Boris Yeltsin in 1996, Putin himself in 2000, and to Dmitry Medvedev, Putin’s figurehead “heir,” in 2008. (In 2004, the communists ran a minor candidate). Vladimir Zhirinovsky, a perennial nationalist candidate for presidency since 1991, has maintained a parliamentary faction for his one-man party for 20 years, but has never come close to winning the presidency. Sergei Mironov, a former Putin ally (in 2004 he ran for presidency with the announced goal “to help Putin win presidency”), was the main beneficiary of the December 4th, 2011, vote when many people supported his party primarily for the reason that parties they would have otherwise voted for were banned from participation. By official tally, Zyuganov got 17.2 percent (2nd place), Zhirinovsky 6.2 percent (4th place), and Mironov 3.9 percent (5th place). Despite the fact that these three have been on the ballot for a long time, they have never succeeded in presenting a genuine alternative choice for Russian voters at the polls and therefore posed no serious threat to Putin’s authority.

Mikhail Prokhorov, the 2nd richest person in Russia according to Forbes, ran a campaign that was watched warily by both Putin in Kremlin and Putin’s opponents in the liberal camp, and came in 3rd place with an official total of 8.0 percent. In Moscow, his result was even more impressive with 22 percent of the vote, second only to Putin’s 45 percent. While Prokhorov certainly benefited from the absence of Grigory Yavlinsky, who failed to clear the (unheard of in democratic countries) requirement to collect 2 000 000 signatures, and other liberal politicians, his results exceeded the previous combined returns of the liberal parties and candidates in parliamentary and presidential elections in 2000. The success of his candidacy have raised doubts on a long-held assumption in Russian politics that a rich, not to mention very rich, candidate has no chance of gaining traction in popular vote.

Another new face in Russian politics, Alexei Navalny has a law degree, business background, and was a member of the leadership in the Yabloko party (expelled in 2007) before becoming a famous blogger and shareholder activist in the beginning of 2010.  His blog (navalny.livejournal.com) is now one of the most popular blogs in Russia, with more than 66,000 followers. A major boost to its popularity was the “Rospil” project that focused on protecting minority shareholders of large state-owned companies (and, by extent, on the management of the taxpayers’ property by the Putin government). Navalny used his blog to organize large-scale petitioning and litigation campaigns related to corruption in state-controlled companies.  As a result of these activities, Navalny was described by the BBC in 2011 as “arguably the only major opposition figure to emerge in Russia in the past five years.”  (Obviously the BBC has not foreseen the rise of Prokhorov.) After December 4th, 2011, Navalny became a major leader of the protests and organizers of election observers.

“Staying the Course”

President-elect Vladimir Putin will start his new 6-year term in difficult times. The election raised questions about his true legitimate level of popular support, yet there is little doubt that he does not face any viable alternative challengers in the near future. Given that Putin has proven himself extremely rigid in the choice of policy and personnel (he would not get rid of close subordinates even if wide-spread corruption allegation would make them a visible drag on his popularity), the new government is not expected to be radically different from the current one (which features most of the ministers serving for 5-10 years in their current capacity). His anointed prime-minister is not a new face either. Dmitry Medvedev, who served as Russia’s president for the last 4 years, is not expected to bring forward any major policy changes.

Fortunately for Putin the opposition is not organized and cannot settle on any particular message or alternative policy direction, let alone viable leader. The protest movement during the winter of 2011-12 was characterized more by decentralized leadership, featuring a number of prominent literature, arts, and entertainment figures. With its goal to ensure fair elections, it has, however, united a very diverse group of smaller movements ranging from radical young communists to libertarians despite its not having provided an alternative leader to Putin.  In the end, the outcome of the March 2, 2012, presidential election has ended the myth of a significant Putin majority, casted considerable doubt on his legitimacy and has shown that Russians seem hungry for a change. It has, however, also left a big question mark on what the opposition’s next steps are and who the alternative could be.

A Resonant Signal: the Russian Parliamentary Elections of December 2011

FREE Network Policy Brief | A Resonant Signal: the Russian Parliamentary Elections of December 2011

Days before December 4, prospects of electoral democracy in Russia looked bleak. Consolidation of the authoritarian rule of Vladimir Putin, Russia’s paramount leader since 1999, adoption of non-democratic electoral laws and politically-motivated law enforcement, constant harassment of media, civil society organizations, and election observers, and outright involvement of the government in the electoral process gave little hope that elections would make the political leadership accountable. The courts and electoral officials were used to prevent most opposition leaders from registering a party or participating in elections; opposition financial supporters had been driven into exile. Parliamentary elections in December 2007 and presidential elections in March 2008 were marred by such irregularities that many observers, myself included, had stopped counting. However, the outcome of December 4, 2011 will arguably have a major impact on future political developments in Russia.

Firstly, the official results of United Russia, the party that is led by Vladimir Putin and had a constitutional majority in the previous parliament, showed a significant drop in support for the current political leadership among the general public. Despite overwhelming presence on state-controlled TV channels, significant support by government officials, and outright vote fraud, the official results show the ruling party deserted by more than a quarter of its supporters (12.8 million out of 44.7 million who voted for United Russia in 2007).

Secondly, those who turned out to vote (the turnout was significantly lower than at previous parliamentary elections) showed obvious discontent with Putin/United Russia policy and, possibly, with the way elections were conducted. In particular, millions of Russians voted for Just Russia, a party with no charismatic leader and a platform that is not substantively different from that of United Russia.

Thirdly – and perhaps most importantly – there was a visible and dramatic upsurge of voter activism on the Election Day. Without any large-scale centrally organized campaign, hundreds of volunteers went to polling stations to work as election observers. They witnessed, prevented and/or reported hundreds of violations by electoral officials via social networks (despite coordinated DDoS attacks on the most important networks and popular news sites on the Election Day) and via You Tube. By December 5, some of the You Tube clips showing electoral fraud had more than 1,000,000 hits.

Reported Results and Corrections for Voter Fraud

As is always the case in a semi-democratic state, result of the official count may deviate significantly from how people actually voted. In Russia, the parliament is formed by representatives of political parties: voters vote for party lists, rather than for individual candidates. The officially announced results were: 49.5 percent for United Russia, 19.2 for Communist party, 13.2 for Just Russia, and 11.7 for the Liberal Democrats (Vladimir Zhirinovsky). Other parties, including Yabloko, the only liberal-leaning party that was allowed to participate in elections, fell short of the 7 percent required to enter parliament. However, the observations of international observers concur with those of opposition parties and independent Russian observers: ballot stuffing in favor of United Russia was witnessed/recorded and was widespread; electoral laws, draconian in themselves, were grossly violated by state officials, including police, at polling stations. In a number of cases, the elections results certified by local election boards do not coincide with the data presented by the central electoral commission, with every major discrepancy being in favor of United Russia.

Results obtained by the Citizen Observer project, which brought about 500 Moscovites to 160 polling stations as observers, give an impression of the scale of the fraud. Unfortunately, the project did not use a randomized distribution of observers, which would make the sample statistically representative of the whole of Moscow. However, Moscow districts have demonstrated fairly homogenous voting patterns in the last two decades, and there is no reason to think that any major change in this pattern occurred, so the report offers a fairly reliable estimate of election fraud. Averaging across polling stations where the observers did not report any serious violations, the Communist party won 25.3 percent of votes, United Russia 23.4, Just Russia and Yabloko 17.6 percent each, and the Liberal Democrats 12.5 percent. Turnout was 49 percent.

I would therefore estimate the effects of irregularities at 10 percentage points, i.e. the real share of votes cast for United Russia nationwide would be 39 percent rather than the reported 49 percent. But it would be reasonable to suppose the effect of irregularities at between 7 and 15 percentage points, so real votes for United Russia would be between 34 and 42 percent of votes cast. It is conceivable that the real share of votes cast for the Communist Party in Moscow (19.4 percent in official returns) was close to that of United Russia; it is not inconceivable that the Communists won the majority of real (not “counted”) votes by Moscovites.

Explanations

Following such a major surprise, any explanation offered only three days after the event risks being way off mark. Public opinion surveys predicted a significantly larger plurality for United Russia. (Personally, I have doubts about the quality of surveys of electoral intentions by major Russian polling firms. I find it particularly disturbing that, in the past, such firms have proved good at predicting – supposedly based on voter intentions – the reported results, rather than the results as adjusted by a realistic estimate of electoral fraud.)

The most obvious explanation for the United Russia setback is economic. Russia suffered more than any other G20 country as a result of the world financial crisis in 2008-09: an EBRD Transition Report 2011 found, based on an extensive survey of Russian citizens, that 38 percent of households had to cut their food consumption as a result of the crisis (11 percent of West European households were affected the same way). This is a major impact. In a democracy, such economic impact alone would most probably result in loss of power for the incumbent leadership.

Another explanation is growing discontent among Russians with the harshness of Putin’s administration and with rampant corruption. When oil prices were rising and real incomes were growing by double digits, the Russian public exhibited markedly high tolerance even when political decisions ran contrary to the will of the majority (for example, no opinion survey in five years showed majority approval of the abolition of regional gubernatorial elections, which was a cornerstone of Putin’s political changes) or when they had to pay substantial corruption premiums in the marketplace. In harder times, people are less willing to have their wishes ignored or to tolerate high and rising prices.

Consequences

In the Yeltsin era, such an outcome of parliamentary elections (even by the official count, United Russia lost almost 13 million votes as compared to 2007) would have triggered a major change in the composition of the cabinet. In 2011, there is even more reason for such a change: a number of prominent cabinet members, who had remits to run United Russia slates in specific provinces led their slates to dismal results (low 30s by the official count). However, low mobility in the upper echelons of the Russian elite during the last decade suggests that drastic changes in the near future are unlikely.

More important than the loss of seats in parliament for United Russia is the possibility that Vladimir Putin, the current prime minister with de facto presidential powers and the head of United Russia, is no longer assured a safe victory in March 2012 presidential elections, which looked a foregone conclusion just a couple of months ago. He is still arguably the favorite, even if (very improbably) there is no ban on opposition candidates participating in the elections (in 2008, the field was restricted to three contenders, all of them effectively pseudo-candidates; in 2004, other candidates were de facto prohibited from raising money for the campaign, while the incumbent had the full capacity of the state at his disposal). With a ban on opposition participation, he is the overwhelming favorite. However, we do not rule out an initiative by the government to make outcome of presidential elections even more secure in the near future by a major crackdown on the opposition.