So far we have documented an upward shift in the vote share for the government following the recollection of negative collective memories in regions more affected by the transition during the 1990s. In this section, we show how this shift in voting decisions of Russian voters has been partially driven by a simultaneous loss of votes for the liberal political opposition.
The recollection campaign depicted Russia’s liberal political opposition as responsible for the problems and difficulties during the transition period of the 1990s. Politicians such as Grigory Yavlinsky, Anatoly Chubais or Boris Nemtsov, who were both leading economic reformers during the 1990s and leading politicians of the liberal parties Yabloko and SPS during the 2000s, were singled out as representatives of the kind of “Western- style democracy” that was then often represented as being responsible for the country’s
economic decline during the 1990s. A good example to illustrate this point is a fake campaign-add that appeared in the newspaper Vecherniy Stavropol on November 23rd, 2007, that is shortly before the Duma elections that took place on December 2nd, 2007 (see Figure 2 in Appendix A.2 for the original article). In style and content, this excerpt from a regional newspaper is similar to many others that we identified for our analysis in Section 7.1. The article is designed as a campaign-add for the liberal political party SPS (Union of Right Forces):
“Forward for the Movement SPS! Back to the times of Nemtsov and Chubais! Of course, in these times: Every day the prices for products, good and services were rising. [. . . ] The economy of the country was destroyed. [. . . ] Pensions were cut and not paid. [. . . ] Salaries were cut and withhold. [. . . ] The number of poor people in Russia was growing. [. . . ] But on the other hand, we had real democracy in the country.”
To show how and to what extent this recollection campaign contributed to a decrease in votes for the liberal political opposition, we collect information on the vote share for the candidate who most closely represented the liberal agenda in the Presidential elections of 2000, 2004, 2008 and 2012.28 For Duma elections, we merge the vote share
for the two liberal parties SPS and Yabloko for the elections held in 1999, 2003 and 2007.29 In 2011, SPS did no longer compete, so here we only take the vote share
obtained by Yabloko.
In Tables 7 we document a significant and negative effect of the recollection of nega- tive collective memories on the share of votes for the liberal political opposition in both Presidential (columns 1 to 4) and Duma elections (columns 5 to 8), once the campaign to recollect memories of the 1990s started in 2003. Specifically, in column 1 we estimate a reduction of 0.057 point estimations in Presidential elections when we use our main explanatory variable, the number of times prices increased between 1990 and 1992 (or a 0.39% reduction in votes in regions with one standard deviation above the mean in inflation). This effect is quite sizeable, as it explains almost 10% of the average vote
28Specifically, we selected the following candidates as representatives of the liberal political opposition during presidential elections: Grigory Yavlinsky (2000, 5.9%), Irina Khakamada (2004, 3.9%), Andrei Bogdanov (2008, 1,3%) and Mikhail Prokhorov (2012, 8.0%).
29Yabloko (meaning ”Apple” in Russian) was founded by the liberal economist and reformer Grigory Yavlinsky in the early 1990s, represents a social-liberal agenda, and still competes in Russian elections to this day as the main representative of a European-style social-liberal political party. SPS (Union of Right Forces) was a liberal-conservative party founded in 1999 and dissolved in 2008. It was founded by a number of “young reformers” from the 1990s, in particular Anatoly Chubais, Boris Nemtsov, and Yegor Gaidar, and is associated with the free market reforms and privatizations of the transition period.
share the liberal political opposition secured in the four Presidential elections between 2000 and 2012. In absolute terms, this is higher than the effect we obtained for the government candidate in Presidential elections. Using the same explanatory variable, in column 5 we obtain a similar result for the vote share of the liberal opposition in Duma elections: one standard deviation above the mean in inflation during the early 1990s predicts a reduction of 0.58% in the vote share for the liberal opposition.
We obtain similar estimates for our alternative measures of disruption during the 1990s, namely the reduction in the production of bread, steel and cement, as well as the increase in crime. The effect when looking at the increase in the crime rate during the early 1990s is especially sizeable, with a reduction of 1.27% in the vote share for the liberal opposition in regions where the increase in crimes between 1990 and 1995 was one standard deviation above the mean. In other words, people in regions with high levels of insecurity during the 1990s were significantly less likely to vote for SPS and Yabloko, once they were reminded about difficulties of the transition period.
In Table 8 we also look at the additional effect of local and regional newspapers, as well as the level of media control on the vote share for the liberal political opposition. In almost all our specifications, we find a negative, significant and sometimes quite substantial additional propagation effect of negative memories being recalled in local and regional newspapers on the vote share for the liberal opposition. It thus seems to be the case that especially for Duma elections, the recollection campaign in newspapers worked even better to discredit the liberal opposition than it worked for encouraging people to vote for the government. Finally, as expected the degree of government control over the media also had an additional negative effect on the vote share for the liberals, although here the effect is not significant for Duma elections.
9
Conclusion
During the early 2000s, Slobodan Milosevic in Serbia, Eduard Shevardnadze in Georgia, Viktor Yanukovich in Ukraine and Askar Akayev in Kirgyzstan lost power in a series of popular protests that became known as “color revolutions.” During these revolutions, often young and pro-Western protesters used colorful symbols and organized, nonviolent resistance to oust governments that were seen as corrupt, authoritarian, as well as linked to the respective country’s Communist past.
As early as 2003, and until today Russia’s ruling elites have been concerned that a similar revolution might also take place in Russia. In a speech to Russia’s Security Council in November 2014, President Vladimir Putin underlined that Russia has to use
all available means to prevent a similar revolution from occurring:
“We see what tragic consequences the wave of so-called colour revolutions led to. For us this is a lesson and a warning. We should do everything necessary so that nothing similar ever happens in Russia.”30
In this paper, we document one strategy in particular that has been used by Russia’s ruling elites to lower the desire of the Russian population for political change. We show how the Russian government uses its control over the media to remind the Russian population about the economic and social difficulties of the 1990s. These difficulties are then described as an outcome of the kind of “Western-style democracy” that Russian and Western refomers tried to implement in Russia during the transition from Communism. The “Western-style democracy” of Russia’s 1990s is then often explicitly equated with to the kind of liberal economic and political institutions the protesters during the color revolutions aspire to, with both being described as leading to economic chaos and social decline.
In our paper, we show how the campaign is successful in mobilizing the Russian population for the regime. We also document that the recollection of negative collective memories to mobilize political support works better in regions that have been more severely affected by the transition of the 1990s. Finally, we document a strong negative effect of the recollection campaign on political support for the liberal political opposition. Our paper contributes to a new strand of literature that shows how authoritarian regimes in the 21st century no longer rely on violence and repression, but on subtler methods of political control (see e.g. Guriev and Treisman 2015 for a theoretical frame- work). In these “new authoritarian regimes” government control over information and the media has begun to play a particularly important role in securing political support for the regime. The authoritarian turn in politics worldwide will make sure that study- ing and understanding these methods of popular control will remain relevant for many years to come.
30https://www.telegraph.co.uk/news/worldnews/europe/ukraine/11243521/Vladimir-Putin-we- must-stop-a-Ukraine-style-coloured-revolution-in-Russia.html
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Table 1: Summary Statistics
mean sd min max N Panel A – Unit of Observation: Region
Prices (1992 - 1990 %) 25.41 6.79 10.90 52.60 78 Bread Production (1995 - 1990 %) 40.35 19.20 -28.17 100.00 82 Crime (1995 - 1990 %) 55.26 31.85 -18.17 143.65 72 Cement Production (1995 - 1990 %) 24.76 32.76 -1.20 100.00 82 Steel Production (1995 - 1990 %) 55.33 30.33 0.00 100.00 82 Panel B – Unit of Observation: Region × Presidential election year UR Vote % 65.05 11.81 25.01 99.76 345 Liberals Vote % 4.12 3.10 0.02 20.40 332 Grp (ln) 11.58 1.56 6.38 16.18 341 With Income Below Cost of Living (%) 23.81 14.38 5.60 94.30 328 Unemployed (%) 9.17 6.06 0.00 53.30 344 Employees in Public Education 22878.16 18033.21 0 91812 344 Employees in Other Public Services 69266.05 62367.50 0 414900 350 Number of Registered Crimes 32406.95 30885.02 345 211914 344 State Investments in Fixed Capital (%) 25.20 18.44 0.30 100.00 344 Panel C – Unit of Observation: Region × Duma election year
UR Vote % 38.06 26.69 0.00 99.48 346 Liberals Vote % 6.25 5.54 0.00 28.85 333 Grp (ln) 11.43 1.51 7.55 16.11 334 With Income Below Cost of Living (%) 25.05 13.82 5.70 90.50 323 Unemployed (%) 10.11 7.07 0.00 55.80 346 Employees in Public Education 22747.95 18158.69 0 92291 346 Employees in Other Public Services 69726.27 62507.27 0 423000 350 Number of Registered Crimes 33386.10 32084.67 158 230631 346 State Investments in Fixed Capital (%) 25.31 18.01 0.70 100.00 344
Note. In Panel A, bread, cement, and steel production are rescaled so as higher percentages mean a larger reduction between 1990 and 1995.
Figure 2: Regional distribution of the number of times prices increased between 1990 and 1992.
Table 2: Reactivation of collective memories on the pro-government vote share — Baseline and flexible estimates
Dependent variable is vote share for the government in %
Presidential Elections Duma Elections
(1) (2) (3) (4) (5) (6) (7) (8) hyperinf l 90s × post2003 0.540∗∗∗ 0.564∗∗∗ 1.802∗∗∗ 0.665∗∗∗ (0.050) (0.081) (0.087) (0.096) hyperinf l 90s × year2004 0.656∗∗∗ 0.370∗∗∗ (0.049) (0.071) hyperinf l 90s × year2008 0.589∗∗∗ 0.037 (0.054) (0.115) hyperinf l 90s × year2012 0.374∗∗∗ -0.230 (0.053) (0.148) hyperinf l 90s × year2003 1.352∗∗∗ 0.520∗∗∗ (0.070) (0.095) hyperinf l 90s × year2007 2.328∗∗∗ 0.762∗∗∗ (0.104) (0.178) hyperinf l 90s × year2011 1.726∗∗∗ -0.227 (0.094) (0.246)
Controls No Yes No Yes No Yes No Yes
Macroregion FE × Trend No Yes No Yes No Yes No Yes
Region FE Yes Yes Yes Yes Yes Yes Yes Yes
Observations 312 311 312 311 312 309 312 309
R2 0.504 0.712 0.604 0.760 0.711 0.882 0.853 0.934
The dependent variable is the vote share for the government candidate in Presidential Elections in columns 1-4 and for United Russia in Duma Elections in columns 5-8. Even columns include GRP (ln), share of people below the poverty line, unemployment rate, average annual number of employees in public sector, investments in capital by the State. Standard errors in parentheses are clustered at the region level.∗p < 0.10,∗∗p < 0.05,∗∗∗p < 0.01
Table 3: Reactivation of collective memories on the pro-government vote share — 2SLS estimates
Dependent variable is the pro-government vote share in %
Presidential Elections Duma Elections
(1) (2) (3) (4) (5) (6)
OLS 2SLS first stage OLS 2SLS first stage
hyperinf l 90s × post2003 0.564∗∗∗ 0.729∗∗∗ 0.665∗∗∗ 0.956∗∗∗
(0.081) (0.076) (0.096) (0.098)
dist to M oscow × post2003 3.535∗∗∗ 3.587∗∗∗
(0.159) (0.144)
Kleinbergen-Paap F statistics 496.885 624.055
Controls Yes Yes Yes Yes Yes Yes
Macroregion FE × Trend Yes Yes Yes Yes Yes Yes
Region FE Yes Yes Yes Yes Yes Yes
Observations 311 303 303 309 301 301
R2 0.712 0.693 0.950 0.882 0.893 0.952
The dependent variable is the vote share for the government candidate in Presidential Elections in columns 1-3 and for United Russia in Duma Elections in columns 4-6. All the columns include GRP (ln), share of people below the poverty line, unemployment rate, average annual number of employees in public sector, investments in capital by the State. Standard errors in parentheses are clustered at the region level. ∗ p < 0.10,∗∗p < 0.05,∗∗∗p < 0.01
Table 4: Reactivation of collective memories on the pro-government vote share — Alternative measure of disruptiveness in the 1990s
Dependent variable is the pro-government vote share in %
Presidential Elections Duma Elections
(1) (2) (3) (4) (5) (6) (7) (8) bread 90s × post2003 0.298∗∗∗ 0.392∗∗∗ (0.032) (0.047) crime 90s × post2003 0.138∗∗∗ 0.105∗∗ (0.021) (0.041) steel 90s × post2003 0.116∗∗∗ 0.190∗∗∗ (0.023) (0.038) cement 90s × post2003 0.143∗∗∗ 0.141∗∗∗ (0.027) (0.050)
Controls Yes Yes Yes Yes Yes Yes Yes Yes
Macroregion FE × Trend Yes Yes Yes Yes Yes Yes Yes Yes
Region FE Yes Yes Yes Yes Yes Yes Yes Yes
Observations 324 287 324 324 319 287 319 319
R2 0.699 0.621 0.600 0.601 0.887 0.869 0.871 0.860
The dependent variable is the vote share for the government candidate in Presidential Elections in columns 1-4 and for United Russia in Duma Elections in columns 5-8. All the columns include GRP (ln), share of people below the poverty mline, unemployment rate, average annual number of employees in public sector, investments in capital by the State. Standard errors in parentheses are clustered at the region level.∗p < 0.10,∗∗p < 0.05,∗∗∗p < 0.01
Table 5: Summary statistics
mean sd min max N Economic Crash 1990s (headlines) 14.85 18.44 1 163 992 Crime 1990s (headlines) 17.28 24.21 1 238 1018 F all Soviet U nion (headlines) 30.11 34.99 1 321 1043 Economic Crash 1990s (newspapers) 5.309 4.805 1 50 992 Crime 1990s (newspapers) 5.371 4.739 1 57 1018 F all Soviet U nion (newspapers) 7.064 6.791 1 71 1043 media control 3.219 0.875 1 5 1144 media control fsg 1.986 0.681 1 3 1055
5 10 15 20 Economic Crash 1990s 2000 2004 2008 2012 year 5 10 15 20 25 Crime 1990s 2000 2004 2008 2012 year 15 20 25 30 35 40
Fall of the Soviet Union
2000 2004 2008 2012 year