How v Yanukouvich Won 2010 Election

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DOI: 10.1177/08883254103885602011 25: 47East European Politics and Societies

Erik S. HerronUkraine's 2010 Presidential Election

How Viktor Yanukovych Won : Reassessing the Dominant Narratives of

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Authors Note: The author thanks participants in the conference Ukraines 2010 Presidential Election:What We Learned at George Washington University for comments, and especially Paul DAnieri for extensive suggestions. He also thanks Serhij Vasylchenko, Rhonda Houser, and Michael Lynch for techni-cal assistance and Maksym Palamarenko for valuable feedback. All errors or omissions are the responsi-

bility of the author.

East European Politics andSocieties

Volume 25 Number 1February 2011 47-67

2011 SAGE Publications10.1177/0888325410388560

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How ViktorYanukovych WonReassessing the Dominant Narrativesof Ukraines 2010 Presidential ElectionErik S. HerronUniversity of Kansas, Lawrence

This article explores two prominent narratives through an analysis of election data. Thefirst narrative is that Yanukovychs win was legitimate. While fraud may have been

present, its scale was small and it was not decisive. The second narrative suggests thatUkraines major operational political cleavage separates eastern and western regions,rendering the central region of the country a crucial prize for candidates to secure vic-tory in presidential contests.

Keywords: Ukraine; election; president; fraud

Introduction

Ukraines 2010 presidential election produced a significant setback for the politicalforces behind 2004s Orange Revolution. The loss in 2010 was not the first electoraldefeat, as the 2006 parliamentary election yielded a plurality win for Viktor Yanukovychs Party of Regions and ultimately a successful, but short-lived, anti-crisiscoalition. But the loss of the presidency to the politician associated with electoralfraud in 2004 was a particularly stinging blow with potentially far-reaching con-

sequences. Press accounts and political observers assessments suggest that theYanukovych victory may be a harbinger for significant modifications to Ukrainesdomestic and foreign policy orientation. Early policy decisions by the Yanukovychadministrationnotably the alteration of coalition formation procedures and theextension of Russias lease on port facilities in Sevastopollend support to this con-clusion. More time must elapse, however, to fully assess the accuracy of the narrativedeclaring the election results to be a reversal of the Orange Revolution.

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48 East European Politics and Societies

Two other prominent narratives associated with the 2010 election are ripe for evaluation. Both of these narratives speak to the present and future status of Ukrainian

political competition, but their assessment relies solely on analysis of election pro-cesses. The first narrative is that Yanukovychs win was legitimate. While fraudmay have been present, its scale was small and it was not decisive, in contrast tothe second round of the 2004 presidential election. The second narrative suggeststhat Ukraines major operational political cleavage separates eastern and westernregions, 1 rendering the central region of the country a crucial prize for candidates tosecure victory in presidential contests. Winning strategies must take this dynamic intoaccount.

This article explores the two narratives through an analysis of election data. Election

results provide rich source material that can be assessed at several levels: macro-regional units, 2 oblasts, electoral districts, and polling stations. 3 The first section presentsan analysis of election quality, focusing on evidence of anomalous outcomes. Thesecond section assesses voting in both rounds of competition to gain insight into can-didate strategies. The third section presents a unified model of election performancethat accounts for features associated with both narratives. The article concludes witha discussion of the political narratives and the implications of the election for politicalcompetition in Ukraine.

Quality of the Election Process

Ukraines 2010 presidential election was the third consecutive national ballot thatmet international standards for free and fair competition, and its administration waswidely praised by international monitoring groups. The election received a largely

positive assessment from the Organization for Security and Cooperation in Europe 4 and also the Commonwealth of Independent States. 5 Receiving praise from these twoorganizations is notable because they have often been at odds in their interpretations

of election results from the post-Soviet region. Domestically, the Tymoshenko campaign alleged that falsification helped propel Yanukovych to victory in the decisiveround. 6 The campaign filed several complaints 7 but ultimately dropped its challengeto the results. While the response by the international community and Ukrainian citi-zens suggests that the election was perceived to be legitimate, what is the basis for this conclusion?

Rigorous evaluations of election quality defy simple dichotomous measures. Indeed,the likelihood that fraud is present, especially in elections involving millions of voters,is reasonably high. While manipulation of the counting or compilation process is not

always due to sinister intent, it seems to be an omnipresent feature of elections. Thus,the main question in the assessment of election quality does not revolve around the presence or absence of fraud but rather the scope, scale, and impact of improper influences on the casting, counting, and compiling of votes.



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Herron / How Viktor Yanukovych Won 49

A substantial literature on the quality of elections has emerged, focusing on variousmethods to detect data anomalies. Forensic accountants point to the need for a series

of data interrogation tests to assess data quality and caution against the reliance ona single evaluative tool. Following their lead, the analysis in this section draws uponthe election quality literature to assess data along several dimensions. First, the dataare assessed at the national and regional levels according to a mathematical prin-ciple (Benfords Law) that facilitates the identification of anomalous results. Second,data analysis turns to the role of turnout in the production of results. High levelsof turnout have been associated with fraud, as unusually high turnout may reflectefforts to stuff the ballot box. 8 High turnout is especially suspect when combined withunanimousor near-unanimousresults in favor of a single candidate or party. 9

While unanimous results are not definitive proof of fraudespecially in small pollingstations located in areas associated with a candidates core supportersunanimousresults that account for large numbers of voters may be suspect. Third, data on ballotinvalidation are assessed as invalid ballots have also been associated with fraud. 10 High levels of ballot invalidation can represent attempts to undermine vote acquisi-tion by a particular party or candidate. Low levels of ballot invalidation can representattempts to stuff the ballot box. Fourth, scholarship has noted that in some electionsof suspicious quality, candidates in two-round elections inexplicably lost votesfrom the first to the second round. 11 To account for this issue, the section addresses

decay in support across the two rounds for both candidates, identifying the fre-quency, size, and impact of outcomes in which candidates vote totals decreased fromthe first to second round.

Benfords Law

Benfords Law is a concept from the mathematics literature that has been appliedto the study of elections. Rediscovered by, and named for, Frank Benford, the principledescribes how digits are distributed in naturally occurring datasets. Benford noted and

empirically tested the proposition that digits are not uniformly distributed. For example,the first digit of any nonzero number could range from 1 to 9. In his assessment of datasets from diverse fields of inquiry, Benford found that the probability that the firstdigit is a 1, for example, is not equal to the probability that the first digit is a 9. In fact,the likelihood that 1 is the first digit is greatest, and the probability declines to 9. 12 This discovery permits the evaluation of large datasets for the presence of anomalies.The approach has been applied widely to financial data, and some scholars 13 haveextended the use of Benfords Law to the assessment of election data. 14 The nullhypothesis is that data conform to the contours of a Benford-type distribution, and

thus do not bear the hallmarks of manipulation.In Ukraines 2010 election, first- and second-digit tests reveal that the nullhypothesis cannot be rejected at the national level and in most macro-regions.

Neither candidates results exceed the critical chi-squared values when they are

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aggregated at the national level, in contrast, for example, to Yanukovychs results inthe 2004 election. 15 In one case, Yanukovychs results in the East, the test data

exceed the critical value, and the null hypothesis may be rejected. In two cases,Tymoshenkos results in Crimea and the Eastcentral region, the null hypothesis may be rejected only at the .10 level of confidence. 16

While manipulation of the vote potentially explains anomalous outcomes, variationin polling station size is an alternate explanation that could account for some of theregional results. The mean size of polling stations in the East is 1,023 (with a standarddeviation of 537). By contrast, the mean size of polling stations in the West is 697(with a standard deviation of 535). In the areas of core support for the candidates where results are likely to be strongestpolling stations serving Yanukovychs core

supporters are larger than those serving Tymoshenkos core supporters and morelikely to yield ones as the first digit.The results of tests derived from Benfords Law reveal anomalous results but not

evidence of widespread fraud. The overall condition of election data suggests thatthey are naturally produced, providing initial support for the legitimacy narrative.

High Turnout and Unanimous/Near-UnanimousPolling Station Results

Another potential marker of problematic elections is high levels of turnout,especially when higher turnout consistently benefits one candidate over another.High turnout also has a more benign interpretation: superior mobilization efforts.At the national level, Tymoshenkos votes are positively correlated with turnout,while Yanukovychs votes and against all votes are negatively associated with higher turnout. 17

In cases of egregious falsification, one may find polling stations reporting complete turnout and unanimous voting for a single candidate or party. While full turnoutis not definitive evidence of fraud, it is especially unusual in polling stations with a

large number of registered voters. If polling stations further report that only onecandidate received support, the outcomes are more difficult to explain benignly. InUkraines 2002 parliamentary election, for example, twenty-nine polling stationsreported unanimous turnout and support. While the number of polling stations wassmall, the impact was significant. In one district in Luhansk Oblast, votes from these

polling stations proved to be decisive: unanimous support elevated a candidate fromthe proregime For United Ukraine bloc into the seat. 18

In 2010, many polling stations (478) reported 100 percent turnout in the secondround. 19 However, these polling stations tended to be small, with fewer than one

hundred registered voters. Although Yanukovych won a majority of votes in 289of these polling stations (to Tymoshenkos 189), Tymoshenko secured more votes(55,770) than Yanukovych (42,853).



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Fifteen polling stations recorded unanimous votes for one of the candidates. Ten polling stations recorded 100 percent of the vote for Tymoshenko. All were located in

Lviv or Ternopil, and the largest had 108 voters. Five polling stations gave Yanukovych100 percent of the vote. They were also small, ranging from 12 to 24 voters, and werelocated in Donetsk, Luhansk, and Odesa. Unlike the results in 2002, where unanimousresults were produced in large polling stations, and were decisive in at least one dis-trict, unanimous precincts produced little advantage for either campaign. Regardlessof the mechanism by which these results were produced, neither campaign garneredenough votes in stations with complete turnout or unanimous support to affect theoverall results of the election.

Both candidates also enjoyed near-unanimous results in many polling stations.

Tymoshenko garnered 95 percent or more votes in 746 polling stations (accountingfor 469,493 total voters). Most of these polling stations were located in the West(Lviv, Ternopil, and Ivano-Frankivsk), but other regions were also represented(e.g., Chernighiv, Vinnytsya, Volyn). Yanukovych also benefited from highly parti-san polling stations, but stations favoring him were fewer in number. Yanukovychreceived 95 percent or more of the vote in 390 polling stations (accounting for 394,984voters) predominantly located in the East and South (Donetsk, Luhansk, Odesa). Thenumber of votes in near-unanimous polling stations (864,477, or 3.4 percent) wasnearly equivalent to the gap between the two candidates. But neither candidate

disproportionately benefited from these precincts. Just over 54 percent of the voterscasting ballots in stations strongly supporting one candidate were associated with polling stations favoring Tymoshenko, and 46 percent were associated with pollingstations favoring Yanukovych. Once again, the overall impact of anomalous resultswas minimal, lending further support to the legitimacy narrative.

Invalid Ballots

In any election, some voters cast ballots that are invalidated. Invalidation may result

from unintentional errors (e.g., voters mismark the ballot), or intentional invalidation(e.g., voters make clear that their real intent is to cast an invalid ballot through themarks they place on the ballot). 20 While researchers have not fully investigated thenormal range of ballot invalidation, it likely varies by institutional features (e.g., com-

plexity and stability of election rules, ballot design, and technology used to record thevote) and social features (e.g., levels of voter literacy, and civic education).

A challenge to the evaluation of ballot invalidations effects, however, is that if invalidation is used as a means to falsify the vote, both high and low levels of inval-idation could be suspect. 21 High levels of invalidation could be associated with efforts

to reject ballots associated with a competitor. Low levels of invalidation could be associated with efforts to stuff the ballot box. Both of these processes could be atwork simultaneously. 22



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The analysis of invalid ballots begins by assessing the correlation between candidate performance in the second round and levels of invalid ballots, using polling-station-level

data. The results indicate that votes for Yanukovych and Tymoshenko, measured asthe proportion of votes received, are not statistically linked to the level of ballotinvalidation. Correlation coefficients are not significant at the .05 level, nor even atthe more relaxed .10 level.

More polling stations reported perfection in the completion of ballots than highlevels of invalidation. In the second round, 3,734 (11 percent) polling stations reportedno invalid ballots. Tymoshenko performed better in these polling stations, receiving,on average, 56 percent of the vote to Viktor Yanukovychs 40 percent. 23 Polling sta-tions reporting no invalid ballots were unequally distributed across the country, with

many located in the West.24

By contrast, three hundred polling stations reported a level of invalid ballots threeor more standard deviations above the mean, accounting for less than 1 percent of thetotal voting results. These polling stations were also distributed unequally acrossthe country, but the performance of candidates does not statistically differ in them. 25

Another way to assess invalid ballots is to investigate change between the tworounds of competition. While the ballot was simpler in the second round because vot-ers confronted fewer choices, and lower error rates are not unreasonable to anticipateunder these circumstances, wide swings in voter competency are unlikely. In some

polling stations, however, invalid ballot rates dropped substantially. Between the tworounds, 632 polling stations (around 1.9 percent) recorded improvements in ballotcompletion greater than 5 percent (that is, the difference in invalid ballots was equiv-alent to 5 percent or greater of the number of ballots cast in the second round). 26 Fewer polling stations (221) revealed 5 percent or greater increase in the invalidationrates between rounds. In these polling stations, voters became less capable of com-

pleting ballots. 27 Both candidates vote accumulation in the second round was nega-tively correlated to the change in ballot invalidation rates. 28

In general, the level of invalid ballots is unconnected statistically with candidate

performance. The only exception is in polling stations reporting no invalid ballots; inthese cases, Tymoshenko performed better than Yanukovych. While the ballot invali-dation differential revealed some unusual cases in which completion rates improved,or declined, at relatively high rates, invalid differentials affected the candidates in asimilar manner. Overall, Tymoshenko may have benefited disproportionately fromvotes in polling stations reporting no invalid ballots, but this anomaly does not falsifythe legitimacy narrative.

Decay in Support

Some scholarship has raised questions about the likelihood of candidates losingvotes in multiround competitions. 29 In two-round competition, surviving candidatesare generally expected to enjoy an increase in their vote totals, assuming that they



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are able to mobilize core voters and gain some support from first-round losers. InUkraine, the total number of voters increased between the first and second rounds,although some polling stations experienced a decline in the number of voters casting

ballots. Because the second round was decisive, the election was highly contentious,

and both campaigns made efforts to mobilize core supporters and supporters of first-round losers, we would generally expect the number of ballots cast for the twocandidates to increase.

Both candidates, however, experienced some decay in voting support between thetwo rounds. Tymoshenko lost 2 percent or more votes in 34 precincts. Some pre-cincts witnessed substantial vote decay, and many were located in the East. 30 Whilethe vote decay in these polling stations is suspicious, the nationwide vote loss in these

precincts was 4,752 and would not have affected the overall outcome of the election.Compiling and assessing data at the district level, Tymoshenko experienced a net loss

in only one district406 votes in district 109 in Luhansk Oblast (see Figure 1).Viktor Yanukovych lost 2 percent or more votes between rounds in fifteen pollingstations, several of which were in his areas of strength. 31 The total loss in these pollingstations amounted to 530 votes. Compiling and assessing data at the district level,

Figure 1Tymoshenko Vote Differential

Note: The map identifies the increase or decrease in votes acquired at the district level in the secondround, using the first round as a baseline.



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Yanukovych lost votes in four of the five districts located in Ternopil Oblast, account-ing for 12,184 votes (see Figure 2). His vote loss in individual polling stations wassmaller than the 2 percent threshold reported above, but the cumulative effect acrossTernopil was substantial. While vote decay is suspicious, it was locally concentratedand not large enough to be decisive.

Both candidates experienced some loss in votes across the two rounds, contraryto expectations. The total amount of vote loss was small, and was concentrated inthe areas of their opponents greatest strength.

Summary

The assessments in this section yielded anomalous outcomes, and some outcomesdisproportionately benefited one candidate. Notably, Tymoshenkos superior per-formance in polling stations reporting no invalid ballots and higher levels of votedecay for Yanukovych in Ternopil, raise questions about the potential for votemanipulation to have produced these outcomes. Even if anomalous results are attrib-utable to fraud, these outcomes were not systematic, widespread, or decisive, lend-ing support to the legitimacy narrative.

Given that the data generally do not point to fraud, the next section will adopt amore benign interpretation of the outcomes, privileging mobilization as the underly-ing cause for changes in performance between the first and second rounds.

Figure 2Yanukovych Vote Differential

Note: The map identifies the increase or decrease in votes acquired at the district level in the secondround, using the first round as a baseline.



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East-West Divide in Elections

Studies of previous Ukrainian elections have noted that political cleavages, reflectedin geographic divides, particularly influenced the dynamics of campaigning andvoting. 32 In 2010, several candidates showed regional bases of strength; Yanukovychin the East, Tymoshenko in the West, as well as Serhiy Tihipko in districts locatedin the South and Eastcentral regions, Arseniy Yatseniuk in the Southwest, and Viktor Yushchenko in the West. The results of the initial round of competition indicate the

persistence of regional dynamics, with more acute competition among candidates inthe western territories.

Tymoshenko emerged from the first round with a significant deficit in votes;

she trailed Yanukovych by 2,526,832 (or 10.3 percent of the total votes cast inthe first round). First-round losers garnered 8,793,198 votes; Tymoshenkos defi-cit amounted to 28.7 percent of these votes. Assuming that the composition of voters was constant in the runoff, Tymoshenko would have to gain just over 64.4 percent of the votes allocated to first-round losers to win the second-roundcompetition.

According to some polling data, Tymoshenko was poised to pick up a higher proportion of first-round losers support, but close to half were uncommitted toa second-round candidate. A Kyiv International Institute of Sociology poll, held

before the first round, asked respondents to identify whom they would support if asecond round were held between Yanukovych and Tymoshenko. While it is poten-tially problematic to project these data to the second round, as respondent prefer-ences may change and the number of respondents indicating support for many minor candidates was quite small, the results suggest that Tymoshenko would cut her deficit by approximately 500,000 votes, with 4.2 million of the remaining votersuncommitted.

This assessment points to multifaceted strategies for the second round: mobilizecore voters to ensure that they return to the polls, engage first-round abstainers, woo

supporters of first-round losers, and demobilize the opposition. To make up her deficit,Tymoshenko would need to gain in densely populated areas, particularly in the centraland eastern regions of the country.

This section analyzes data aggregated at the macro-regional, oblast, district, and polling station levels to assess how effectively the candidates managed to acquirevotes in the quest to win the second round. First, the section addresses turnout data to

better understand if the candidates were able to mobilize supporters in regions of core support. Second, the section focuses on regions where first-round losers werestrong performers and assesses how the competitors performance changed in those

areas. Third, the section addresses the crucial role of central regions, presenting somecounterfactual evidence to illustrate how Ukraines center can be decisive in electoralcompetition.



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Mobilizing Core Voters

A critical starting point in the candidates second-round strategies was to ensurethat core voters participated in voting. Overall turnout improved, increasing from66.76 to 69.15 percent nationally. Given that the second round was expected to beclose, voters had strong incentives to participate.

Assuming a benign interpretation of turnout figures, both candidates seem tohave been successful in activating their strongest supporters. Figures 1 and 2 displaysecond-round vote gains for both candidates. The previous section highlightedvote decay visible on the maps. However, the maps also illustrate that both cam-

paigns acquired votes in their regions of core support. In addition, Yanukovychsand Tymoshenkos areas of strength are characterized by higher turnout than other regions of the country.

Both campaigns seem to have succeeded, at least marginally, in mobilizing voters.The largest increases in turnout were in Donetsk (7.3 percent), followed by Ivano-Frankivsk (4.7 percent), Ternopil (4.7 percent), Crimea (4.0 percent), and Luhansk (3.4 percent). Notably, the most intense areas of turnout increase were in Donetsk, suggest-ing that the Yanukovych campaign was especially successful at supplementary mobi-lization. The figure also shows that turnout declined in some regions, notably districtsin Dnipropetrovsk, Zakarpattya, Odesa, Poltava, Kherson, Chernivtsy, and Kyiv City.

Polling-station-level data reveal additional information about turnout. Increases inturnout varied across Ukraine, with the average polling station recording a 2.2 percentincrease in the second round. Around 10.4 percent (3,504) of Ukraines polling sta-tions recorded turnout increases one or more standard deviations from the mean. 33 This elevated level of increased turnout was especially associated with polling sta-tions in Donetsk, where 41 percent of polling stations reported turnout increases oneor more standard deviations from the national mean. Other regions were also associ-ated with heightened turnout at the polling station level: Ivano-Frankivsk (23 percentof polling stations), Ternopil (16 percent), Crimea (16 percent), Lviv (12 percent),Vinnytsya (12 percent), Luhansk (10 percent), Odesa (10 percent), and Chernighiv(9 percent). Among the regions with the lowest proportion of polling stationsreporting results more than one standard deviation from the mean were Kyiv City(2 percent), Poltava (3 percent), Kherson (3 percent), Zaporizka (4 percent), andSevastopol (4 percent).

If one focuses on the vote differential between rounds, the candidates successesin enhancing support in core regions becomes clearer. On average, Tymoshenkogained 175.54 votes at the polling-station-level across Ukraine. 34 At the level of electoral districts, her gains were largest in Lviv and Ternopil, followed by districts inIvano-Frankivsk, Kyiv City, and Volyn. Her performance was weakest in Donetsk and Luhansk. 35 On average, Yanukovych gained 143.23 votes in polling stations acrossthe country. His strongest gains were in his regions of most intense supportDonetsk and Luhanskas well as in Dnipropetrovsk, Kharkiv, and Odesa. 36



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Based on the evidence aggregated at the polling station, district, and regionallevels, both candidates seem to have been successful in mobilizing voters in areas of

their core support: Yanukovych in the East (Donetsk and Luhansk) and Tymoshenkoin the West (Ivano-Frankivsk, Lviv, and Ternopil).

Capturing Votes from First-Round Losers

Another critical component to second-round success, especially for Tymoshenko,was to woo supporters of candidates who lost in the first round of competition. Whilesupporters of some candidates (e.g., Petro Symonenko) were unlikely to be compatiblewith Tymoshenko, voters who selected other candidates (e.g., Arseniy Yatseniuk andViktor Yushchenko) might be more likely to support her candidacy.

The prize sought by both candidates was the constituency that selected SerhiyTihipko. Tihipko did not endorse either candidate in the intervening period betweenthe two rounds, but both candidates made efforts to connect with voters who cast

ballots for him. Neither candidate, however, proved to be fully effective in garneringvotes in the micro-regions where Tihipko was strongest.

Correlation coefficients using the complete set of all polling station results suggestthat Tymoshenko was least effective at attracting Tihipko voters across all of Ukraine.Tihipko performance is negatively correlated with Tymoshenkos second-round votes,whereas Tihipko performance is positively correlated with Yanukovychs second-round votes. 37 Most notably, however, the correlation between Tihipko performanceand against all voting is particularly strong.

If the analysis focuses where Tihipko manifested particular strengthDnipropetrovsk and Odesathe story becomes more nuanced. In Dnipropetrovsk, Tihipko support is

positively associated with Tymoshenko outcomes in the second round and negativelyassociated with Yanukovych outcomes. The correlation with against all voting iseven higher. 38 In Odesa, the contenders performance differs: Tymoshenkos votes arenegatively associated with Tihipkos, outcomes and Yanukovychs results are not sta-tistically significant. Against all voting is once again strongly, and positively, associ-ated with regions of Tihipkos strength in the first round. 39

Support for Yatseniuk, Yushchenko, and Symonenko generally falls in line withexpectations. Yatseniuks outcomes are positively correlated with Tymoshenko, nega-tively with Yanukovych, and positively with against all votes. 40 Yushchenkos out-comes are positively associated with Tymoshenko and negatively with Yanukovychand against all voting. 41 Symonenkos outcomes are negatively associated withTymoshenko and positively with Yanukovych and against all voting. 42

Both campaigns attracted voters in areas associated with compatible first-roundlosers. The tendency of areas associated with Yushchenko and Yatseniuk support tolean toward Tymoshenko, and those associated with Symonenko to lean towardYanukovych, also corresponds with expected regional differences. However, the dis-

position of micro-regions that showed strong support for Tihipko was less consistent.



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The Decisive Center?

Central regions are generally considered to be crucial sources of support for candidates striving to win the presidential election. In the second round of the2010 election, eastern and southern regions reliably backed Yanukovych and accountfor 30 percent of the votes cast in the second round. Tymoshenkos western region of core support comprises only 12 percent of the vote. 43

Central regions together produced 54 percent of the vote, led by the Northcentral(23 percent) and followed by the Eastcentral (17 percent) and Westcentral (14 percent)regions. Tymoshenkos vote exceeded Yanukovychs in the Northcentral and Westcentralregions, but her margin of victory was not adequate to overcome his strength in theEastcentral region, containing the critical urban areas of Kharkiv and Dnipropetrovsk.If their performance were reversed in the Eastcentral region alone, Tymoshenko wouldhave won the election. Indeed, if she had evenly split the vote in the Eastcentral region,Tymoshenko would have been victorious.

Despite the perceived importance of voters in the center, mobilization efforts seemto have failed to engage voters in several critical districts. Despite the overall increasein voter participation in the decisive second round, urban districts in Dnipropetrovsk and Kyiv, and districts in Poltava, posted turnout declines from the first round of com-

petition. In the South, urban districts in Odesa and districts in Kherson registeredturnout declines as well. 44 While it is unclear how to interpret these drops in turnout,several occurred in districts that recorded relatively strong support for Tihipko in thefirst round. It is plausible that some voters who selected Tihipko were registering aprotest vote, rendering them less likely to support one of the two main candidatesin the second round.

While one could develop several counterfactual scenarios in which Tymoshenkocould secure victory, central regions feature prominently in the most plausible hypo-thetical cases. Indeed, any presidential candidate relying on core support in Ukraineswestern regions faces a significant challenge if the primary competitor draws coresupport from Ukraines eastern and southern regions. A successful strategy requirescandidates to make substantial inroads in the center as even highly mobilized corevoters in the West are not adequate to produce a win. Candidates relying on coresupport in the East and South also must acquire votes in the center but face a lessdaunting challenge than their western rivals.

Summary

The results in this section suggest that the regional cleavage narrative also findssupport, as the two major candidates drew upon core support in Ukraines far easternand western regions. Both campaigns faced the task of mobilizing core voters, attractingvoters who supported first-round losers, and extending support in central regions.



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This challenge was especially acute for Tymoshenko, who was burdened with a2.5 million vote deficit in the first round of competition. Core voters in eastern and

western regions were engaged, evidenced by increases in turnout. Tymoshenko andYanukovych also performed well in regions that supported compatible first-roundlosers. But neither candidate was successful in systematically attracting voters in regionswhere Tihipko was most effective. Some districts where Tihipko performed best werealso located in the center, an area crucial for second-round success.

Overall Assessment of the 2010 Presidential Election

The preceding sections assessed factors associated with the two dominant narra-tives explaining outcomes of the presidential election. The first section addressed the

possibility that the process of election administration was infected by improper effortsto alter the accurate casting, counting, or compilation of election returns. The secondsection addressed how the competitors organized their efforts in the runoff, touchingupon the crucial role of the center. This section of the article brings together elementsof both assessments to develop a general model explaining candidate performance inthe decisive second round.

The dependent variable assesses the performance of both candidates, and theagainst all option, measured by the proportion of votes received at the pollingstation level. The independent variables address the two election narratives notedthroughout the article. Turnout, measured as the proportion of registered voters whocast a ballot, is associated with both election quality and mobilization arguments.Invalid ballots, measured as the proportion of ballots disqualified from the votecount, also address election quality issues. The performance of first-round losers,represented by the proportion of votes cast for Tihipko, Yatseniuk, Yushchenko, andSymonenko, addresses political explanations of the runoff. The final set of indepen-dent variables accounts for region and is a series of dummy variables representingmacro-regional units. 45 The models also include a set of interaction terms that mea-sure the relative effects of region on turnout and Tihipko performance.

Several analytical techniques were applied to the data 46 and produced results thatcomply with expectations. Turnout exerts a statistically significant, positive effect onTymoshenkos second-round performance, as does the first-round performanceof Yushchenko and Yatseniuk. Relative to the Northcentral region, Tymoshenko

performs better in the West and substantially worse in the East and Eastcentralregions. Yanukovychs performance is positively associated with first-round supportfor Symonenko, as well as the East and Eastcentral regions. Polling stations yieldingelevated against all votes are associated with stronger support first-round losers,especially Tihipko.



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The relative effects of interactive terms uncover important dynamics. Table 1shows the predicted results for Tymoshenko and Yanukovych generated throughsimulations based on the models including all explanatory variables. 47 In Table 1,values for most independent variables are held at zero; turnout and location vary asspecified on the table. For example, the first cell in the table shows the predictedresult for a polling station in Crimea with 50 percent turnout. Under these condi-tions, we would expect Tymoshenko to secure 32 percent of the vote on average, andYanukovych 68 percent. At higher levels of turnout, we would expect to see poorer

performance by Tymoshenko and better performance by Yanukovych. While Crimea

is generally associated with Yanukovych support, rendering this outcome unsurpris-ing, elevated turnout is associated with stronger Yanukovych performance only inthis region.

Increases in turnout are associated with stronger Tymoshenko performance in allother regions except the South. As turnout varies from 50 to 90 percent, Tymoshenko

Table 1Predicted Polling-Station-Level Results,

Varying Turnout and Macro-Region50%

Turnout60%

Turnout70%

Turnout73% Turnout

(Mean)80%

Turnout90%

Turnout

CrimeaTymoshenko .3207 .3089 .2971 .2930 .2853 .2735Yanukovych .6809 .6895 .6980 .7009 .7065 .7150

EastTymoshenko .0374 .0530 .0686 .0739 .0841 .0997Yanukovych .9637 .9458 .9280 .9219 .9101 .8923

Eastcentral

Tymoshenko .1719 .1918 .2117 .2185 .2316 .2515Yanukovych .8308 .8074 .7841 .7760 .7607 .7374

NorthcentralTymoshenko .6337 .6394 .6450 .6470 .6507 .6564Yanukovych .3651 .3583 .3514 .3491 .3446 .3378

SouthTymoshenko .3167 .3121 .3074 .3058 .3027 .2981Yanukovych .6806 .6798 .6790 .6787 .6782 .6774

WestTymoshenko .7570 .7731 .7892 .7947 .8052 .8213Yanukovych .2295 .2203 .2111 .2080 .2019 .1927

WestcentralTymoshenko .6526 .6724 .6923 .6991 .7121 .7320Yanukovych .3396 .3217 .3037 .2976 .2858 .2679

SouthwestTymoshenko .4097 .4603 .5110 .5284 .5617 .6123Yanukovych .5868 .5368 .4867 .4695 .4367 .3866

Note: Cell entries are predicted probabilities generated via Clarify. All explanatory variables, except for those featured in the table, are set to zero.



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is expected to enjoy better performance in the East (the expected value at 90 percent

is 6.2 percentage points higher than at 50 percent), Eastcentral (8.0), Northcentral(2.3), West (6.4), Westcentral (7.9), and Southwest (20.3). Even in Yanukovychs coreregion (East), higher levels of turnout are associated with stronger Tymoshenko

performance. While Tymoshenkos relative gains are higher as turnout increases, theabsolute effect of turnout in this region still benefits Yanukovych.

An increase of 40 percentage points in turnout raises Tymoshenkos vote acqui-sition by 6.2 percentage points, on average, in the East. If, for example, we beginwith Tymoshenkos predicted performance in the East (3.74 percent) and apply itto a polling station with 1,000 registered voters, she would receive roughly 19 votes

to Yanukovychs roughly 482 votes.48

If turnout in this hypothetical polling stationincreased to 90 percent, Tymoshenko would receive roughly 90 votes to Yanukovychs803. Tymoshenkos share of the vote increases, but the absolute effect of increasedturnout benefits Yanukovych, who would receive 321 additional votes to Tymoshenkos71. Increased turnout benefited Tymoshenko in relative terms across most of the

Table 2Predicted Polling-Station-Level Results,

Varying Tihipko Support and Macro-Region0% Tihipko 10% Tihipko 20% Tihipko 30% Tihipko

CrimeaTymoshenko .2930 .2131 .1332 .0533Yanukovych .7009 .7603 .8196 .8790

EastTymoshenko .0739 .0953 .1167 .1380Yanukovych .9219 .8858 .8498 .8137

EastcentralTymoshenko .2185 .2446 .2707 .2967

Yanukovych .7760 .7281 .6802 .6323 Northcentral

Tymoshenko .6470 .6295 .6120 .5945Yanukovych .3491 .3396 .3302 .3207

SouthTymoshenko .3058 .2785 .2512 .2239Yanukovych .6787 .6911 .7034 .7157

WestTymoshenko .7947 .7035 .6122 .5210Yanukovych .2080 .2648 .3217 .3786

Westcentral

Tymoshenko .6991 .6729 .6468 .6206Yanukovych .2976 .3064 .3151 .3239Southwest

Tymoshenko .5284 .5669 .6053 .6438Yanukovych .4695 .4064 .3433 .2802

Note: Cell entries are predicted probabilities generated via Clarify. All explanatory variables, except for those featured in the table, are set to zero.



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country, but the effects of turnout increases in absolute terms tended to benefitYanukovych.

The intensity of variation in turnouts effect is smaller than the influence of Tihipkos performance. Table 2 displays predicted outcomes for Tymoshenko and Yanukovych,varying Tihipkos performance and region. Turnout is held constant at the nationalmean in this table, and all other factors are held at zero. Higher values for Tihipkosfirst-round performance are positively associated with Tymoshenkos second-round

performance in the East, Eastcentral, and Southwest regions. Tihipkos performanceis positively associated with Yanukovychs second-round performance in Crimea,South, West, and Westcentral regions. To continue the example from above, in ahypothetical polling station with 1,000 registered voters in the East, a 30 percentage

point difference for Tihipko is associated with a 6.4 percentage point difference for Tymoshenko, slightly higher than the yield for a 40-point swing in turnout.Second-round outcomes are split in Tihipkos regions of strength, with Tihipko

performance positively associated with Tymoshenko votes in the Eastcentral regionand Yanukovych in the South. But stronger Tihipko performance is also associatedwith stronger second-round candidate performance in the opponents core regions(Tymoshenko in the East and Yanukovych in the West). This outcome is consistentwith an interpretation of Tihipko support as a reflection of protest in the first round.Voters who did not support Tymoshenko in the West, or Yanukovych in the East, may

have found Tihipko to be a viable alternative in the first round. These voters may haveexhibited one of many behaviors in the second roundvoting for the rival of the can-didate they opposed, voting against all, or abstaining.

Summary

The general models of election performance provided additional support to bothnarratives. Regional variation in turnout was compatible with an explanation basedon mobilization. Regions associated with strong performance by first-round losers

matched second-round expectations: Tymoshenko tended to receive more votes inmicro-regions where Yatseniuk and Yushchenko performed well, and Yanukovychtended to receive more votes where Symonenko performed well. Neither candidatesystematically attracted voters in micro-regions where Tihipko performed well,

but both candidates and against all votes were associated with Tihipko support insome regions.

Conclusions

The analysis points to several conclusions about political narratives and the stateof Ukraines electoral politics. While the elections produced anomalous results, theywere not one-sided. In some cases they appear to marginally benefit Tymoshenko,



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and in other cases they appear to marginally benefit Yanukovych. Because the anom-alies were not systematic, widespread, or decisive, it is reasonable to conclude that

Yanukovychs win was based on competition in a credibly free and fair environment.This interpretation supports the legitimacy narrative.The legitimacy of Yanukovychs victory suggests that the Ukrainian political

market remains reasonably competitive, a legacy of the Orange Revolution. If politicalactors accept the consequences of real electoral competition (i.e., the potential for lossesand alternation in power), the process represented by the 2010 presidential election

bodes well for democratic consolidation in Ukraine. The progress represented by the2010 presidential election could be undermined if impediments to free and fair com-

petition emerge in the form of restrictions on contestation or participation prior to

the next election cycle. Upcoming local elections will be a first test of the legitimacynarratives robustness.Competition also revealed the persistence of regional divisions, with both cam-

paigns mobilizing core supporters and attracting votes in areas associated with first-round losers. The Tymoshenko campaign benefited from relative gains in mobilizationacross much of the country, but these gains were inadequate to overcome the first-round deficit. While registering improvements in the decisive round, Tymoshenkosfailure points to the challenges of mounting an electoral strategy primarily based onwestern core support.

The analysis suggests that a candidate who appeals to the center and can attractvotes in the West could be a formidable challenger. Tihipko positioned himself as alegitimate alternative in key regions of the center and South, evidenced by his perfor-mance in urban districts of Dnipropetrovsk, Odesa, Kharkiv, and Kyiv. The behavior of areas associated with Tihipko supporters suggests that they are a constituency seekingan alternative. In the second round, areas of Tihipko support were positively associatedwith Tymoshenko support in some districts, Yanukovych support in others, and alsorobust against all voting. If these outcomes reflect a vote of no confidence againstUkraines dominant politicians, entrepreneurial political actors may be able to carve

out a successful strategy to challenge the dominant East-West electoral divide. Tihipkohimself may have abandoned this role, however. His decision to accept a deputy prime ministers post in Mykola Azarovs government could tarnish his brand as anoutsider positioned between Tymoshenko and Yanukovych.

The election also yields potential lessons for the main rivals. The results suggestthat Yanukovych may have reached the limits of mobilization gains in his regions of core support. Attracting more consistent support from central regions of the countrycould strengthen his position in future elections. If Tymoshenko aims to return tothe prime ministers post or gain the presidency, she may benefit from studying

Yanukovychs example. After his defeat in the 2004 presidential election, Yanukovychhired a powerful political consulting firm and followed advice on how to rebuild hisimage. His subsequent campaigns for parliament and the presidency were moredisciplined, and modest changes to his behavior permitted Yanukovych to portray



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himself in a more flattering light than during the 2004 campaign. Tymoshenko mayherself benefit by reinvention that allows her to retain many of her core voters but

also extend support spatially and ideologically.

Notes

1. Analysis of earlier presidential elections has noted that Leonid Kuchma was victorious in 1994 bygarnering votes in the eastern half of the country along with central regions in the western half, and in1999 by capturing the west and some areas east of the Dnipro River.

2. The article uses eight macro-regions defined by historical, social, and political similarities (Lowell W.Barrington and Erik S. Herron, One Ukraine or Many? Regionalism in Ukraine and Its PoliticalConsequences, Nationalities Papers 32:1[2004]: 5386). The macro-regions are East (Donetsk andLuhansk), Eastcentral (Dnipropetrovsk, Kharkiv, and Zaporizka), Crimea (Crimea and Sevastopol), South(Kherson, Mykolayiv, and Odesa), Northcentral (Chernighiv, Cherkassy, Kirovohrad, Kyiv City andOblast, Poltava, and Sumy), West (Ivano-Frankivsk, Lviv, and Ternopil), Westcentral (Khmelnitsk,Rivne, Vinnytsya, Volyn, and Zhytomyr), and Southwest (Chernivtsy and Zakarpatska). For clarity, themacro-regions will be capitalized while general directional terms will not be capitalized.

3. This analysis uses data from 33,683 polling stations compiled from results provided by UkrainesCentral Electoral Commission. The total number of polling stations slightly differs between the two rounds,likely due to additional ships serving as special polling stations in Odesa during the second round. (The firstround featured 33,673 polling stations.) Analysis using polling station data must be interpreted with cautionas these data do not reveal the attitudes or behaviors of individual voters, rendering the interpretation par-ticularly vulnerable to problems of ecological inference. However, polling station data can reveal variation

in micro-regional results and can thereby provide additional insights into election dynamics.4. See http://www.osce.org/documents/odihr/2010/02/42679_en.pdf.5. See http://www.interfax.com.ua/eng/press-conference/31465/.6. Both campaigns traded allegations about fraud, especially in the first round.7. See http://www.osce.org/documents/odihr/2010/02/42816_en.pdf.8. Cf. Mikhail Myagkov and Peter C. Ordeshook, The Trail of Votes in Russias 1999 Duma and

2000 Presidential Elections, Communist and Post-Communist Studies 34:3(2001): 35370. See alsoMikhail Myagkov, Peter C. Ordeshook, and Dmitry Shakin, Fraud or Fairytales: Russia and UkrainesElectoral Experience, Post-Soviet Affairs 21:2(2005): 91-131.

9. Erik S. Herron and Paul Johnson, Fraud before the Revolution: Special Precincts in Ukraines2002 Parliamentary Election, in Ingmar Bredies, Valentin Yakushik, and Andreas Umland, eds., Aspects

of the Orange Revolution III: The Context and Dynamics of the 2004 Ukrainian Presidential Elections (Stuttgart, Germany: Ibidem-verlag, 2008).

10. A. A. Sobyanin and V. G. Sukhovolskiy, Demokratiya, Ogranichennaya Falsifikatsiyami: Vyboryi Referendumy v Rossii v 1991-1993 Gg (Moscow: Project Group for Human Rights, 1995).

11. Valentin V. Mikhailov, Osobaya Zona: Vybory v Tatarstane (Ulyanovsk, Russia: Kazan Branch of the International Assembly to Protect Rights, 2000); and Mikhailov, Kolichestvo Demokratii: AnalizVyborov Prezidenta RF 1996 G, v Regionakh, Armageddon 3:1(1999): 134-53.

12. The first-digit probabilities in the Benford distribution are 1 = .301, 2 = .176, 3 = .125, 4 = .097,5 = .079, 6 = .067, 7 = .058, 8 = .051, and 9 = .046.

13. Walter R. Mebane, Election Forensics: Vote Counts and Benfords Law (Paper presented at the2006 Summer Meeting of the Political Methodology Society, University of CaliforniaDavis, July 2006);

and Mark J. Nigrini, Monitoring Techniques Available to the Forensic Accountant, Journal of Forensic Accounting 7:2(2006): 32144.

14. Some aspects of election data present challenges to the application of Benfords Law. Data in polling stations are constrained by the lower bound of zero but an upper bound that varies from place to place, depending on the number of individuals registered. This feature of polling station data produces



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different available digits across polling stations (i.e., more 1s are available in a precinct with 2,000registered voters than in a station with 1,000 registered voters). Polling stations can also produce single-digit or zeros as results, undermining analysis of first and second digits. The application of Benfords Lawconfronts not only statistical problems, but also issues related to the interpretation of results. The presenceof anomalous data does not constitute proof of fraud. Indeed, seemingly anomalous results could be

produced in natural strongholds for candidates or by a candidates own poor performance. Lastly,Benfords Law is unlikely to identify diffuse or low scale fraud.

15. Erik S. Herron, Elections and Democracy after Communism? (New York, NY: PalgraveMacmillan, 2009).

16. In previous elections, some national-level data failed to conform to a Benford-type distribution(notably the Communist Party in 2002s constituency races and Viktor Yanukovych in the third round of the 2004 presidential election). Nonconforming results were present in the East, Eastcentral, South, and

Northcentral regions in past elections, but this analysis was conducted at the oblast level (see ibid.).17. The correlation coefficients are all significant at the .05 level and are .1800 for Tymoshenko,

.1536 for Yanukovych, and .3142 for against all.18. The decisive votes were cast in prisons (Herron and Johnson, Fraud before the Revolution).19. The distribution of polling stations reporting 100 percent turnout is as follows: 12 in Crimea,

15 in Vinnytsya, 8 in Volyn, 53 in Dnipropetrovsk, 88 in Donetsk, 6 in Zhytomyr, 1 in Zakarpatska,20 in Zaporizka, 8 in Ivano-Frankivsk, 9 in Kyiv Oblast, 8 in Kirovohrad, 43 in Luhansk, 27 in Lviv,8 in Mykolaivsk, 53 in Odesa, 15 in Poltava, 13 in Rivne, 11 in Sumska, 12 in Ternopil, 25 in Kharkiv,6 in Kherson, 9 in Khmelnitsk, 4 in Cherkaska, 3 in Chernivets, 4 in Chernighiv, 13 in Kyiv City, and3 in Sevastopol.

20. For example, the author has witnessed polling station commissions evaluate ballot papers withtext such as they are all thieves written on the paper in lieu of a recorded vote.

21. Sobyanin and Sukhovolskiy, Demokratiya, Ogranichennaya Falsifikatsiyami .22. In the second round of the 2004 presidential election, the author observed a polling station com-mission deem ballots with additional marks valid for Viktor Yanukovych, but analogous ballots invalid for Viktor Yushchenko.

23. The results of a paired two-sample t -test indicated that the outcomes are significantly different:t = 19.54.

24. Polling stations with low levels of ballot invalidation were distributed in the following way:76 in Crimea, 240 in Vinnytsya, 228 in Volyn, 47 in Dnipropetrovsk, 196 in Donetsk, 232 in Zhytomyr,29 in Zakarpattya, 81 in Zaporizka, 90 in Ivano-Frankivsk, 133 in Kyiv Oblast, 142 in Kirovohrad,105 in Luhansk, 333 in Lviv, 122 in Mykolaivsk, 156 in Odesa, 172 in Poltava, 122 in Rivne, 123 inSumska, 259 in Ternopil, 132 in Kharkiv, 91 in Kherson, 227 in Khmelnitsk, 137 in Cherkaska, 22 in

Chernivets, 136 in Chernighiv, 39 in Kyiv City, 10 in Sevastopol, and 54 abroad.25. Polling stations with high levels of ballot invalidation were distributed in the following way:

12 in Crimea, 14 in Vinnytsya, 5 in Volyn, 17 in Dnipropetrovsk, 11 in Donetsk, 16 in Zhytomyr, 11 inZakarpattya, 8 in Zaporizka, 14 in Ivano-Frankivsk, 27 in Kyiv Oblast, 12 in Kirovohrad, 11 in Luhansk,10 in Lviv, 6 in Mykolaivsk, 27 in Odesa, 14 in Poltava, 10 in Rivne, 11 in Sumska, 5 in Ternopil, 11 inKharkiv, 7 in Kherson, 11 in Khmelnitsk, 10 in Cherkaska, 7 in Chernivets, 7 in Chernighiv, 5 in KyivCity, and 1 in Sevastopol.

26. Polling stations reporting 5 percent or greater improvements in ballot completion were distrib-uted in the following way: 12 in Crimea, 28 in Vinnytsya, 13 in Volyn, 49 in Dnipropetrovsk, 19 inDonetsk, 23 in Zhytomyr, 36 in Zakarpattya, 30 in Zaporizka, 10 in Ivano-Frankivsk, 33 in Kyiv Oblast,19 in Kirovohrad, 23 in Luhansk, 24 in Lviv, 23 in Mykolaivsk, 48 in Odesa, 32 in Poltava, 22 in Rivne,

20 in Sumska, 20 in Ternopil, 26 in Kharkiv, 15 in Kherson, 36 in Khmelnitsk, 25 in Cherkaska, 9 inChernivets, 22 in Chernighiv, 14 in Kyiv City, and 1 in Sevastopol.

27. Polling stations reporting 5 percent or greater increase in the ballot invalidation rate were distrib-uted in the following way: 7 in Crimea, 13 in Vinnytsya, 4 in Volyn, 12 in Dnipropetrovsk, 11 in Donetsk,13 in Zhytomyr, 3 in Zakarpattya, 7 in Zaporizka, 5 in Ivano-Frankivsk, 22 in Kyiv Oblast, 7 in Kirovohrad,



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9 in Luhansk, 6 in Lviv, 3 in Mykolaivsk, 21 in Odesa, 14 in Poltava, 7 in Rivne, 9 in Sumska, 4 inTernopil, 9 in Kharkiv, 4 in Kherson, 7 in Khmelnitsk, 8 in Cherkaska, 3 in Chernivets, 6 in Chernighiv,6 in Kyiv City, and 1 in Sevastopol.

28. Correlation coefficients are significant at the .05 level and are .107 for Tymoshenko and .142for Yanukovych.

29. Cf. Mikhailov, Osobaya Zona .30. Polling stations reporting 2 percent or greater vote loss for Tymoshenko were distributed in the

following way: 1 in Cherkaska, 1 in Dnipropetrovsk, 6 in Donetsk, 1 in Ivano-Frankivsk, 2 in Kharkiv,1 in Kyiv Oblast, 13 in Luhansk, 1 in Mykolaivsk, 1 in Odesa, 2 in Poltava, 1 in Sevastopol, 1 in Sumska,and 3 in Zaporizka.

31. Polling stations reporting 2 percent or greater vote loss for Yanukovych were distributed in thefollowing way: 1 in Chernighiv, 1 in Dnipropetrovsk, 4 in Donetsk, 2 in Kharkiv, 2 in Luhansk, 1 in Odesa,1 in Sevastopol, and 3 in Zaporizka.

32. Cf. Ralph S. Clem and Peter Craumer, Shades of Orange: The Electoral Geography of Ukraines2004 Presidential Elections, Eurasian Geography and Economics 46:5(2005): 36485; and Paul Kubicek,Regional Polarisation in Ukraine: Public Opinion, Voting and Legislative Behaviour, Europe-AsiaStudies 52:2(2000): 27394. See also Clem and Craumer, Orange, Blue and White, and Blonde: TheElectoral Geography of Ukraines 2006 and 2007 Rada Elections, Eurasian Geography and Economics 49:2(2008): 127-51.

33. Three hundred ninety polling stations showed gains in turnout three or more standard deviationsfrom the mean; 1,059 showed gains two or more standard deviations from the mean.

34. This figure includes results for polling stations located abroad.35. Tymoshenkos district-level gains (measured by raw votes) are 3 standard deviations from the

mean in 5 districts (4 in Lviv, 1 in Ternopil), 2 to 3 standard deviations from the mean in 6 districts

(2 in Ivano-Frankivsk, 3 in Kyiv City, 1 in Volyn), 1 to 2 standard deviations from the mean in 20 districts(1 in Khmelnitsk, 6 in Kyiv City, 4 in Lviv, 4 in Ivano-Frankivsk, 1 in Rivne, 1 in Vinnytsya, 1 in Sumska,1 in Chernivets, 1 in Kyiv Oblast), 0 to 1 standard deviation from the mean in 50 districts, 0 to 1 standarddeviation from the mean in 134 districts, and beyond 1 standard deviation from the mean in 11 districts(2 in Donetsk, 9 in Luhansk).

36. Yanukovychs district-level gains (measured by raw votes) are greater than 2 standard deviations fromthe mean in 9 districts (1 in Kharkiv, 3 in Odesa, 2 in Donetsk, 1 in Dnipropetrovsk, 2 in Luhansk), 1 to 2standard deviations from the mean in 32 districts (7 in Dnipropetrovsk, 2 in Sevastopol, 6 in Kharkiv, 2 inMykolaivsk, 4 in Zaporizka, 3 in Crimea, 1 in Luhansk, 6 in Donetsk, 1 in Odesa), 0 to 1 standard deviationsfrom the mean in 52 districts, 0 to 1 standard deviations from the mean in 100 districts, and beyond 1standard deviations from the mean in 33 districts (1 in Zakarpattya, 2 in Vinnytsya, 2 in Khmelnitsk, 3 in

Rivne, 5 in Ternopil, 4 in Volyn, 8 in Lviv, 6 in Ivano-Frankivsk, 1 in Chernivets, 1 in Sumska).37. The correlation coefficients are all significant at the .05 level. They are .2458 for Tymoshenko,

.1944 for Yanukovych, and .6126 for against all votes.38. The correlation coefficients are all significant at the .05 level. They are .0986 for Tymoshenko,

.2931 for Yanukovych, and .7214 for against all votes.39. The correlation coefficients for Tymoshenko and against all votes are significant at the .05 level.

They are .1594 for Tymoshenko and .4352 for against all votes.40. The correlation coefficients are all significant at the .05 level. They are .5150 for Tymoshenko,

.5295 for Yanukovych, and .1575 for against all votes.41. The correlation coefficients are all significant at the .05 level. They are .5638 for Tymoshenko,

.5545 for Yanukovych, and .1249 for against all votes.

42. The correlation coefficients are all significant at the .05 level. They are .4061 for Tymoshenko,.4025 for Yanukovych, and .0526 for against all votes.

43. The Southwest is not included in Tymoshenkos areas of support due to results in Zakarpattya,which have been attributed to the involvement of Viktor Baloha.



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44. Southwestern districts in Chernivtsy and Zakarpattya also registered turnout declines.45. The Northcentral region is excluded as the comparison category.46. The data were analyzed using regression with robust standard errors and seemingly unrelated

regression (SUR). In the former approach, the data were also clustered by district to account for error correlation. Supplementary tables with full results are available at http://vse-na-vybory.blogspot.com.

47. The interpretation of the table requires several caveats. The results are point predictions but areaccompanied by confidence intervals. Thus, the point estimates are an approximation. Moreover, as notedin the text, other explanatory variables are held at zero to emphasize the independent effects of turnoutand region on results.

48. Values do not sum to 500 due to rounding.

Erik S. Herrons research focuses on political institutions, especially elections and political parties.He has traveled extensively in Eastern Europe and Eurasia, including a semester as a Fulbright scholar in Ukraine. He has also been an international observer for seven elections in Azerbaijan, Georgia,Russia, and Ukraine. He has authored many articles, chapters, and books about electoral politics in the

post-communist region.

How v Yanukouvich Won 2010 Election

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