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What Explains the African Vote? Department of Political Science UC San Diego Clark C. Gibson James D. Long Using Exit Poll Data from Kenya to Explore Ethnicity.

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Presentation on theme: "What Explains the African Vote? Department of Political Science UC San Diego Clark C. Gibson James D. Long Using Exit Poll Data from Kenya to Explore Ethnicity."— Presentation transcript:

1 What Explains the African Vote? Department of Political Science UC San Diego Clark C. Gibson James D. Long Using Exit Poll Data from Kenya to Explore Ethnicity and Government Performance in Vote Choice

2 What Explains the African Vote? What are the determinants of voter choice in the December 2007 Kenyan elections?

3 Plan of talk 1.Back story: Six months of silence 2.Theory: Approaches to African voting behavior. 3.Background: Kenya’s 2007 election context. 4.Data: Exit poll. 5.Tests and results: a.) descriptive and cross tabs b.) multivariate tests c.) survey experiment 6. Wrap-up

4 1.Back story Six months of silence

5 Kenya: The Mysterious Exit Poll AllAfrica.com 1/15/8 What's Really Going On in Kenya? And why didn't a U.S.-funded group release its exit-poll data? Slate Magazine, 1/2/08 “IRI will not release any polling results unless and until we are confident in the integrity of the data.” International Republican Institute 1/15/08 Kenyan president lost election, according to U.S. exit poll McClatchey newspapers 1/14/08

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7 Kenya winner lost, U.S. poll indicates Belated tally suggests election was stolen Chicago Tribune 7/9/08 U.S. Ambassador Ranneberger: “…it is my understanding that this ‘exit poll’ was part of a training exercise and was never intended for publication.” America.gov 3/8/08 Testify before the Kriegler Commission 7/15/08

8 Exit Poll Results: Presidential Race N = 5,495 Margin of error = 1.32 Raila 46.07% Kibaki 40.17% Kalonzo 10.22%

9 2. Theory: Approaches to explaining voting behavior in Africa

10 Approaches to voting behavior in Africa  Identity/Expressive voting (Horowitz) Elections become ethnic head counts May even vote against their policy preferences  Policy voting (Hechter, Bates, Bratton, Mattes) Co-ethnics care about same policies Giving your co-ethnic a break on policy evaluation Can be observationally equivalent to identity

11 Identity and policy are incomplete explanations for Kenya’s electoral outcomes Kibaki’s (Kikuyu) and Raila’s (Luo) groups cannot win election alone. Must at least have coalitions. Some ethnic groups split their presidential votes. Leaders from same ethnic groups join multiple coalitions.

12  Government performance Retrospective evaluations – throw the rascals out (Fiorina) Prospective evaluations – who will do best looking forwards (Fearon) Spatial voting – select the candidate nearest to you on the issues (Downs)  But ethnicity means something in Africa Approaches to voting behavior in Africa

13 Applying theory to Africa Not clear what “performance” means in the African context. What is the relationship between ethnicity and performance? Do voters use an ethnic filter on this info as akin to party ideology in the U.S.? Observational equivalence of theoretical predictions.

14  Information (Popkin, Ferree, Dawson) Like policy, but less direct link between interests and behavior Uncertainty pushes voter to seek cognitive shortcuts: Leaders (co-ethnic or not gives information) Past performance of ethnic groups Campaigns / issues Parties Approaches to voting behavior in Africa

15 Argument: Government performance affects African (Kenyan) voting behavior Kenyan elections clearly not ethnic headcounts Information comes from: –Ethnicity – hardcore –Ethnic filters – policy history / filters (including retrospective and prospective thinking) –Government performance –(Candidates, campaigns, and issues only indirectly tested in this paper)

16 Hypotheses Hypothesis 1. (Identity voting) If a voter has a co- ethnic candidate, she will vote for that candidate (if possible). Hypothesis 2. (Policy voting) a.Co-ethnics are more forgiving for poor policy performance (in this paper) b.Co-ethnics vote to secure favored policy (not). Hypothesis 3. (Government performance) If a voter believes that the government has performed well, she will be more likely to vote for the incumbent.

17 3. Background: Kenya’s 2007 election context

18 Background: Ethnic groups Kikuyu22% (President Kibaki’s group) Luhya14% Luo13% (Odinga’s group) Kalenjin12% Kamba11% (Musyoka’s group) Kisii 6% Meru6% Other African 15%, Non-African 1%

19 Background: The Players Mwai Kibaki (Kikuyu) running for a second term; Kikuyu long dominant in Kenyan politics Raila Odinga (Luo) is main challenger Musyoka (Kamba) a distant third All three candidates members of the same coalition in 2002! 2007 is fourth multiparty election (1992, 1997, 2002)

20 Background: The Issues High expectations for Kibaki after 2002 victory Economy grows (7%) Delivers free primary education, promises free secondary Shuffling of ECK Rendition of Muslims Raila says Kibaki unfulfilled promises, failed performance Failures in reform, corruption, poverty, unemployment, service delivery Majimbo (federalism)

21 4. Data: Exit poll

22 UCSD, International Republican Institute (IRI), Strategic Research with USAID grant to study determinants of the Kenyan vote. Allows researches to match attitudes and government evaluations with vote choice.

23 5,495 surveys, nationally representative: 8/8 provinces; 69/71 districts; 179/210 constituencies. Good for provincial estimates (“25% in 5 provinces” rule). Multi-stage cluster sampling proportionate to size, using final ECK published registration. Random selection of polling stations within constituencies, random selection of respondents (every 5 th person).

24 Demographics Process and timing of voting Performance of local, parliamentary, and central government Attitudes about policies, issues and ethnicity Vote choice for local, MP, president

25 5. Tests: a.) descriptive and cross tabs

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31 State of the nation's economy (by vote)

32 Is it more important for candidates to have experience or new ideas? (by vote)

33 Which issue matters most to your presidential vote?

34 5. Tests: b.) multivariate

35 Logit Model for Kibaki Vote VariableModel 1Model 2Model 3Model 4 Govt Services 1.09*** 1.933*** Promises 2.497*** 2.718*** Economy 0.987*** 1.784*** Security0.023 0.459*** 0.403*** 0.399*** Health0.189* 0.36*** 0.408*** 0.295** Family's econ0.236* 0.399*** 0.226* 0.293* Kikuyu 2.835*** 2.732*** 2.464*** Luo -2.846*** -2.853*** -2.657*** Kamba -1.641*** -1.682*** -1.835*** N 5479 5483 5484 5482 Pseudo-R2 0.43 0.45 0.4 0.52 sig * p<0.05; ** p<0.01; ***p<0.001 Coefficients shown. Constants and controls suppressed.

36 Good Performance Evaluations Bad Performance Evaluations Kikuyu.99 (.986,.993).575 (.511,.633) Non-Kikuyu.877 (.849,.902).083 (.074,.093) Predicted Probabilities of a Vote for Kibaki (confidence intervals)

37 Government Services on Vote for Kibaki coefficientsstandard errors Services2.411***0.101 Kikuyu3.092***0.135 Luo-2.967***0.34 Kamba-1.713***0.235 Services*Kikuyu-1.005***0.246 Services*Luo-0.5220.698 Services*Kamba-0.0850.321 N= 5493 Pseudo R20.4292

38 Kibaki’s Promises on Vote for Kibaki coefficientsstandard errors Promises3.362***0.11 Kikuyu2.975***0.158 Luo-2.753***0.385 Kamba-0.907***0.212 Promises*Kikuyu-1.428***0.24 Promises*Luo-0.2870.634 Promises*Kamba-1.813***0.309 N= 5492 Pseudo-R20.5145

39 Family Economy on Vote for Kibaki coefficientsstandard error Family Economy1.245***0.101 Kikuyu3.176***0.131 Luo-3.386***0.339 Kamba-1.462***0.167 F/Economy*Kikuyu-0.882***0.243 F/Economy*Luo0.5540.696 F/Economy*Kamba0.0160.354 N=5494 Pseudo-R20.3467

40 5. Tests: c.) survey experiment

41 Survey experiment Percent all respondents saying very or somewhat likely to vote for that candidate; random assignment of ethnicity and performance Good Performer Bad Performer Kikuyu70.37%21.05 % Luo71.92%21.52 %

42 Survey experiment Percent all respondents saying very or somewhat likely to vote for that candidate; random assignment of ethnicity and performance Good Performer Bad Performer Kikuyu70.37%21.05 % If respondent K= 79% if L = 62% Luo71.92%21.52 % If respondent K= 75%, if L = 76%

43 Survey experiment Percent all respondents saying very or somewhat likely to vote for that candidate; random assignment of ethnicity and performance Good Performer Bad Performer Kikuyu70.37%21.05 % If respondent K= 79% if L = 62% Luo71.92%21.52 % If respondent K= 75%, if L = 76%

44 6. Wrap up: What Explains the African Vote?

45 Hundreds of millions of $ spent on democracy promotion – be we don’t even know what motivates African voters! Ethnicity Performance through filters Performance Future work – Ghanaian elections (December 2007) – South African elections (Spring 2008) – Campaign speeches

46 "IRI is the sole funder, producer, and/or source of the exit poll"

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48 Model 1Model 2Model 3Model 4Model 5 Services1.926*** 0.101 Promises2.672*** 0.1 National Economy1.779*** 0.102 Security0.405***0.347***0.345*** 0.0950.1010.096 Health0.302**0.239*0.347*** 0.0920.0960.093 Family Economy0.302*0.2120.119 0.1180.1270.118 Employment-0.333***-0.276***-0.212**-0.193*-0.225** 0.0580.0740.0820.0880.081 Experience1.213***1.274***1.121***1.035***1.124*** 0.0590.0770.0850.0910.084 Kikuyu3.133***2.834***2.464***2.727*** 0.1150.1230.1360.123 Luo-3.355***-2.912***-2.665***-2.943*** 0.2970.3 0.294 Kamba-1.514***-1.659***-1.900***-1.709*** 0.1540.1640.2080.174 Age0.065***0.053**0.047*0.053** 0.0160.0180.0190.018 Income0.04-0.059-0.008-0.051 0.0310.0340.0370.033 Male-0.161* -0.177*-0.154 0.0740.0810.0870.08 Education-0.089**-0.100** -0.094** 0.0320.0350.0370.036 Urban-0.512***-0.493***-0.404***-0.485*** 0.0820.0910.10.091 Constant-0.680***-0.917***-1.488***-1.867***-1.447*** 0.0480.1170.1350.1450.133 Pseudo R20.06720.38180.47730.54020.468 N54955493548354825484 * p<0.05; ** p<0.01; *** p<0.001 Prospective and Retrospective Votes for Kibaki

49 Raila VotersKalonzo Voters Employment-0.211.014* 0.2250.419 Family Economy-0.810***-0.19 0.220.418 Majimbo1.798***1.241** 0.2570.464 Corruption0.957***2.04*** 0.240.429 Education-2.082***-0.388 0.2360.427 Constitution1.8481.7** 0.3210.528 age-0.047**-0.018 0.0150.022 income-0.174***-0.157*** 0.0290.04 male0.239***0.014 0.0680.099 urban0.622***0.021 0.0720.111 education0.0350.117** 0.0290.043 _cons0.497*-1.729*** 0.2290.428 Kibaki Voters as base outcome N=5298 p<0.05* p<0.01** p<.001*** Multinomial Logit Vote Choice Model

50 Total NairobiCoast North- eastern EasternCentral Rift Valley WesternNyanza Raila Exit Poll46.0754.5567.16767.182.5454.6372.6883.42 Official44.143.9659.3747.5151.8964.6665.8282.33 Difference (Official-Poll) -1.97-10.59-7.79-28.49-2.18-0.6510.03-6.86-1.09 Kibaki Exit Poll40.1733.0824.581742.5491.9141.1724.1714.67 Official46.3847.6933.1250.5350.2596.8733.4732.1616.88 Difference (Official-Poll) 6.2114.618.5433.537.714.96-7.77.992.21 Kalonzo Exit Poll10.226.587.2746.853.51.872.481.02 Official8.928.066.532.3443.70.651.390.690.28 Difference (Official-Poll) -1.31.48-0.67-4.66-3.15-2.85-0.48-1.79-0.74 Other/RTA Exit Poll3.530.581.0603.432.052.330.660.89 Official0.6100.1 % registered voters 1008.928.242.2116.6115.323.4910.9514.23 Poll sample54955174721009058281285604784 Margin of error1.324.314.519.83.263.412.733.993.5 Difference between exit poll and official results

51 Religion and Gender

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53 Education

54 Income

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56 Urban vs. Rural

57 Party Identification (58% say party member; 38% say no)

58 Logit Model for Kibaki Vote VariableModel 1Model 2Model 3Model 4 Govt Services 1.09*** 1.933*** 0.1010.098 Promises 2.497*** 2.718*** 0.0870.097 Economy 0.987*** 1.784*** 0.1020.099 Security0.023 0.459*** 0.403*** 0.399*** 0.1020.0930.0950.1 Health0.189* 0.36*** 0.408*** 0.295** 0.093 0.0950.0960.097 Family's econ0.236* 0.399*** 0.226* 0.293* 0.12 0.1130.1140.126 Kikuyu 2.835*** 2.732*** 2.464*** 0.120.1190.133 Luo -2.846*** -2.853*** -2.657*** 0.3040.2940.313 Kamba -1.641*** -1.682*** -1.835*** 0.1580.1660.191


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