Social inequality and voter turnout - evidence from EU elections Daniel Horn TÁRKI GINI Year-One Conference February 4-5. 2011. Milan

Social inequality and voter turnout - evidence from EU

electionsDaniel Horn

TÁRKIGINI Year-One ConferenceFebruary 4-5. 2011. Milan

Inequality and turnout Daniel Horn 2

Introduction

• Why people vote?– Individual explanations

• rational choice (Downs 1957, Tulock 1967, Riker and Ordershook 1968, Muller 2003)

• social capital (Putnam 2000), social status (Lijphart 1997)• civic resources (Verba, Schlotzman, Brady 1995)

– Macro explanations (see e.g. Geys 2006)• socio economic (population size, - stability, - concentration, -

homogenity)• political variables (closeness, campaign spendings, fragmentation)• institutional variables (electoral system, compulsory voting,

concurrent elections, registration requirements)

But how does inequality associate with voter turnout? Does higher inequality drive more people to cast a vote? Or does it hinder this form of political participation?


Additional motivation

• The link between inequality and redistribution is thought to be well established (Meltzer and Richard 1981).– lower income people prefer more redistribution– higher turnout is likely to be driven by higher turnout

of lower income people, who demand more redistribution (the median voter is moving to the „left”)

– thus the association between inequality and redistibution is mediated by voter turnout (see Lacrinese 2007)

So the association between inequality and voter turnout is interesting as a part of the governmental redistribution topic as well.


Possible explanations

• Three possible ways of asociation bw/ inequality and voter turnout– negative – positive– none (less interesting)


Possible explanations - negative

• Changing political agenda (Solt 2010, Schattschneider 1960)– rich are better able to set the political agenda. When social

inequality is high, this „advantage” is higher, hence voter turnout of the poor is lower

• Social norms (Lister 2007)– institutions (such as the welfare state) influence social norms,

and hence individual behavior. In more equal societies (c.f. universalist welfare states) we should observe higher levels of political participation

• Reverse causation – class bias (Muller and Stratmann 2003, but see the logic of Meltzer and Richard 1981)– Upper classes (rich) participate more (Lijphart 1997). Lower

voter turnout benefits upper classes, which leads to socially unjust policies and thus social inequality.


Possible explanations - positive

• Heterogeneity increases voter turnout (Zimmer 1976)– If the government performs redistributive actions, homogeneous

groups with high political power can gain much (many homogeneous groups = heterogeneous society)

• Or alternatively:– If social tensions are high, relatively homogeneous groups of

people (poor, elderly, students… etc.) are easier to mobilize (citation needed!)

– „societies with deep divisions between social groups that are linked to specific parties are more likely to see high turnout than societies in which the decline of cleavage politics has reduced the importance of these links” (Franklin et al., 1992, citation from van der Eijk et al 1996).


Empirical evidence so far:

Solt (2010): US Gubernatorial Elections

– Individual dataset (~240 thousand, in 6 elections 1978-2000)

– post-tax Gini as income inequality

All negative! Increasing inequality associates with decreasing voter turnout.

Lister (2007) – Comparative Welfare States dataset: Macro data for 15 countries, 1963-1993.

Mueller and Stratmann (2003) – Macro level data for 76 countries, 1960-1990.


Data• 5 European elections (European Election Survey 1989-2009 – PIREDEU

database)• Disadvantage: „second-order election” (Reif and Schmitt 1980)

– turnout is lower than in national parliamentary elections, affected by• the closeness of the next parliamentary election• complusory voting• and other „endogeneous” factors, like pro-European feeelings

– and continuously falling (1979: 63%, 1989: 58,5%, 1999: 49,4%, 2009: 43%)

but– it seems that „voters go to the polls because of a desire for political influence.

Moreover there is no evidence of different processes at work in different countries.” (Franklin, van der Ejik and Oppenhuis 1996, p. 330)

– and „The second-order election model implies that it is more likely that national elections will effect European elections than vice-versa, but in reality we find influences running in both directions.” (van der Eijk et al. 1996)

• Advantage:– similar everywhere (smaller institutional effects)

• must be PR system (~UK)• can only be subdivided to regions if this does not affect the PR nature• maximum 5% threshold

– taken at the same time– no unexpected effects (e.g. early elections)


Data (individual level)

• European Election Study– phone interviews– after elections– approx. 150.000 individuals in 5 years (~3000

people/country until 1994; ~1000 in 1999, 2004 – 2009 is in preparation)

– questions about participation and individual background (no income) – and much more

(controls: age, sex, education, class, settlement, church, voted last parl. elect.)


Data (country level)• National data

– Next election in days/365 (wikipedia)– Compulsory voting (IDEA, www.idea.int)– GDP/capita (Eurostat 1995-2004) and Nationmaster (WDI

database - 1989)– Nationality – consider herself belong to other nationality (EES

2009)– Inequality

• (post-tax) Gini for each year (Eurostat - SILC)• pre-tax Gini (Social Situation Observatory Annual Montioring Report

2009)– Gini indices of the distribution of equivalent household market income

among the working age 2004

• MDMI (Lancee - v. d. Werfhorts 2011)• poverty - Population at risk of poverty or social exclusion 2005

(Eurostat) (Bulgaria 2006, Romania 2007)

http://www.idea.int/


Voter turnout - EES

EES study Mean Std. Dev. Freq.1989 0,74 0,44 105031994 0,72 0,45 123571999 0,70 0,46 129802004 0,60 0,49 267902009 0,71 0,45 26908Total 0,68 0,47 89538

No weights

EES study Mean Std. Dev. Freq. Obs.1989 0,58 0,49 13278 105031994 0,56 0,50 15794 123571999 0,54 0,50 16823 129802004 0,43 0,50 37418 26790Total 0,50 0,50 83313 62630

With weights


Own calculationsDescriptive

AT

CY

CZ

DK

EE

ESFI

FR

GR

HU

IE

IT

LU

LV

NL

PL

PT

SE

SISK

UK

.2.4

.6.8

1tu

rnou

t

20 25 30 35 40Gini

year=2004


Own calculationsLowess smoothing

.4.5

.6.7

.8

20 25 30 35 40Gini

real voting probability of votingfixed effects


Methods

• Pooled logit with clustered standard errors• two 2-step probits

– fixed effect:• 1st step: individual controls and country fixed marginal

effects • 2nd step: country controls and inequality indicators

– separate country regressions• 1st step: individual controls for each country and probabilities

are predicted (for 42 year old middle class women, who live in mid-size settlement, with 12 years of education, and voted in parl. elections.)

• 2nd step: country controls and inequality indicators

• Multilevel mixed effect logit (no weighting)


Base model

All variables here are included in each regression below.

ORs (se)age 1.021** (0.00173)female 0.897** (0.0261)educ==up to 14 years 0.927 (0.0981)educ==15 years 0.783** (0.0558)educ==16 years 0.886+ (0.0642)educ==17 years 0.873* (0.0588)educ==19 years 0.910 (0.0714)educ==20 years 1.070 (0.0790)educ==21 years 1.089 (0.0796)educ==22 years and more 1.402** (0.121)educ==still studying 1.353** (0.141)go to church 1.552** (0.101)settlement, rural area/village 1.116** (0.0462)settlement, large town 1.077 (0.0521)Working class 0.866** (0.0419)Upper class 1.063 (0.0647)1989 2.138** (0.576)1994 1.869** (0.428)2004 1.054 (0.238)Voted in parl. elections 4.182** (0.456)Compulsory voting 2.611** (0.577)distance from the next national elections, years 0.771** (0.0569)% of other nationalitis 1.009 (0.00805)Constant 0.0860** (0.0264)Observations 55,423Robust clustered se in parentheses** p<0.01, * p<0.05, + p<0.1

Country level variables


Pooled logit

vote vote vote votegdp 1.007* 1.006* 1.008** 1.008**

(0.00306) (0.00267) (0.00230) (0.00216)gini 1.088** 1.796** 1.082** 1.369

(0.0261) (0.390) (0.0192) (0.281)gini^2 0.992* 0.996

(0.00359) (0.00345)Constant 0.00431** 3.80e-06** 0.00713** 0.000257**

(0.00394) (1.23e-05) (0.00480) (0.000747)

Observations 55,423 55,423 55,148 55,148

Pooled logitWeighted Non-weighted (plus2009)

Robust clustered se in parentheses** p<0.01, * p<0.05, + p<0.1


Pooled logit – other indicatorsODDS RATIOS (1) (2) (3) (4) (9) (10) (7) (8)

Gini 1.088** 1.796**(0.0261) (0.390)

Gini^2 0.992*(0.00359)

pre-tax Gini 1.089** 0.852(0.0361) (0.594)

pre-tax Gini^2 1.003(0.00817)

MDMI 1.039** 1.258**(0.0103) (0.0888)

MDMI^2 0.998**(0.000742)

Poverty 1.059* 1.246**(0.0239) (0.0748)

Poverty^2 0.997**(0.000927)

Constant 0.00431** 3.80e-06** 0.000886** 0.143 0.00801** 0.000116** 0.0116** 0.00124**(0.00394) (1.23e-05) (0.00151) (2.129) (0.00568) (0.000191) (0.0112) (0.00147)

Observations 55,423 55,423 41,862 41,862 55,423 55,423 55,423 55,423Robust clustered se in parentheses** p<0.01, * p<0.05, + p<0.1

2step probit


ATAT

BEBEBE

CY

CZ

DKDKDK DK

EE

FI FI

FRFRFRFR

DEDE

GRGRGRGR

HU

IEIEIEIE

ITITIT

LV

LULULU

NLNLNL

PTPTPT PT

SK

SI

ESESESES

SE SE

UKUKUK UK

.2.4

.6.8

1F

ixe

d-e

ffect

s

20 25 30 35 40Gini


AT

AT

CZ

DK

FI

FI

FR

FR

HU

IE

IE

LVLT

NL NL PL

PT

PT

SKSI

ES

ES

SE

SE UK

UK

.2.4

.6.8

pre

dic

ted

pro

bab

ility

20 25 30 35 40Gini

separate country regressions

Quick tests of „negative” theories


Social norms• universal welfare state -> more equal and higher

turnout

DKDKDK DK DK

FI FI FINLNLNL NLNL

SE SE SE

.2.4

.6.8

1fix

ed-

effe

cts

20 25 30 35 40Gini


.2.4

.6.8

1C

ount

ry fi

xed

effe

cts

(by

cla

ss)

20 25 30 35 40Gini

Working classMiddle class

Upper class

fractional-polynomial prediction

Changing political agenda /Class biasIf inequality increases rich are more likely to vote than the poor


Conclusion

• „conventional” results for the base model (compulsory voting, voted last election… etc.)– so results for european „second-order” elections work as first-

order elections• but unconvetional results for the inequality dimesion:

– Inequality and voter turnout associates positivelyor

in a quadratic relation– Negative association is less likely to hold

• Social norms theory does not explain low levels of turnout for universal welfare states (e.g. Sweden, Finland, Denmark, Netherlands)

• Political agenda/ Class bias theories does not explain coparatively higher rising levels of turnout for the working class

– Theories of positive association are yet to be confirmed


Questions

• Whether it is due to– the quality of the data– the „second-order” nature of the EU elections– the fact that aggregate data works differently

than individual (ecological fallacy)– the fact that US inequality is higher (cf. Solt

2010) and very low inequality and very high inequality both predicts low turnout compared to the middle

are all open to further research.

Thank you for your attention!

Daniel Horn

[email protected]


AUSTRIABELGIUM

CYPRUS

CZECH REPUBLIC

DENMARK

ESTONIA

FINLANDFRANCE

GREECE

HUNGARY

IRELAND

ITALY

LATVIALITHUANIA

LUXEMBOURG

NETHERLANDS

POLAND

PORTUGAL

SLOVAKIA

SLOVENIA

SPAIN

SWEDEN UK

50

100

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250

GD

Pp

c a

s %

of E

U2

7

20 25 30 35 40Gini

year=2004


Note: ----------- X=Y line

AUSTRIA

BELGIUM

CYPRUS

CZECH REPUBLIC

DENMARK

ESTONIA

FINLAND FRANCE

HUNGARY

IRELAND

LITHUANIA

LUXEMBOURGNETHERLANDS

POLAND

SLOVAKIASLOVENIA

SWEDEN

UK

20

30

40

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60

pre

-tax

Gin

i

20 25 30 35 40(post-tax) Gini

year=2004


AUSTRIA

BELGIUM

CYPRUS

CZECH REPUBLIC

DENMARK

ESTONIA

FINLANDFRANCE

GREECE

HUNGARY

IRELANDITALY

LATVIA

LITHUANIA

LUXEMBOURGNETHERLANDS

POLAND

PORTUGAL

SLOVAKIA

SLOVENIA

SPAIN

SWEDEN

UK

10

20

30

40

50

pov

ert

y

20 25 30 35 40(post-tax) Gini

year=2004


AUSTRIA

BELGIUM

CYPRUS

CZECH REPUBLIC

DENMARK

ESTONIA

FINLAND FRANCE

GREECE

HUNGARY

IRELAND

ITALY

LATVIA

LITHUANIA

LUXEMBOURG

NETHERLANDS

POLAND

PORTUGAL

SLOVAKIA

SLOVENIA

SPAIN

SWEDEN

UK

30

40

50

60

70

80

MD

MI

20 25 30 35 40(post-tax) Gini

year=2004


ODDS RATIOS (1) (2) (3) (4) (5) (6) (7) (8)

Gini 1.022* 1.095(0.00815) (0.0842)

Gini^2 0.999(0.00130)

pre-tax Gini 1.025+ 0.888(0.0137) (0.183)

pre-tax Gini^2 1.002(0.00249)

MDMI 1.010** 1.051+(0.00327) (0.0277)

MDMI^2 1.000(0.000268)

Poverty 1.020* 1.077**(0.00773) (0.0207)

Poverty^2 0.999**(0.000331)

Constant 0.806 0.307 0.516 9.712 0.986 0.401 0.949 0.456*(0.213) (0.338) (0.308) (41.46) (0.164) (0.252) (0.232) (0.141)

year fixed effects y y y y y y y yObservations 55 55 39 39 55 55 55 55R-squared 0.654 0.663 0.674 0.684 0.703 0.729 0.656 0.738Robust clustered se in parentheses** p<0.01, * p<0.05, + p<0.1

Dependent variable: Country fixed effects (Weighted GLS)

Country fixed effects


Separate country regressions

ODDS RATIOS (1) (2) (3) (4) (5) (6) (7) (8)

Gini 1.021* 1.076(0.00718) (0.0849)

Gini^2 0.999(0.00129)

pre-tax Gini 1.019 1.441*(0.0135) (0.199)

pre-tax Gini^2 0.996*(0.00150)

MDMI 1.009** 1.020(0.00208) (0.0149)

MDMI^2 1.000(0.000139)

Poverty 1.009 1.058*(0.00890) (0.0252)

Poverty^2 0.999+(0.000370)

Constant 0.723 0.350 0.515 0.000276* 0.815 0.637 0.995 0.519(0.193) (0.421) (0.339) (0.000863) (0.130) (0.250) (0.433) (0.236)

year fixed effects y y y y y y y yObservations 26 26 21 21 26 26 26 26R-squared 0.470 0.480 0.402 0.588 0.582 0.590 0.274 0.446Robust seeform in parentheses** p<0.01, * p<0.05, + p<0.1


Multilevel logitODDS RATIOS 1 2 3 4 5 6 7 8

Gini 1.107** 1.094(0.0124) (0.0871)

Gini^2 1.000(0.00132)

pre-tax Gini 0.999 1.593(0.0351) (0.772)

pre-tax Gini^2 0.995(0.00551)

MDMI 1.002 1.096(0.0130) (0.111)

MDMI^2 0.999(0.000984)

Poverty 0.979+ 0.962(0.0117) (0.0593)

Poverty^2 1.000(0.000870)

Constant 0.00688** 0.00819** 0.0614+ 2.84e-06 0.120** 0.0148+ 0.276** 0.353(0.00289) (0.00994) (0.0941) (2.97e-05) (0.0771) (0.0360) (0.117) (0.340)

year fixed effectsObservations 55,148 55,148 39,349 39,349 53,245 53,245 55,148 55,148R-squared 27 27 19 19 24 24 27 27se in parentheses** p<0.01, * p<0.05, + p<0.1


Changing political agenda /Class bias

• If inequality increases rich are more likely to vote than the poor

ODDS RATIOS (1) (2) (3) (4) (5) (6)

Compulsory vote 1.261** 1.235* 1.241* 1.223* 1.188* 1.184*(0.0914) (0.0923) (0.0977) (0.102) (0.0862) (0.0877)

Time until next election 0.973 0.969+ 0.974 0.971 0.971 0.971(0.0171) (0.0165) (0.0178) (0.0172) (0.0169) (0.0169)

% of other nationality 0.997 0.995 0.997 0.996 0.999 0.999(0.00373) (0.00336) (0.00423) (0.00410) (0.00416) (0.00414)

GDP/capita in % of EU27 1.002* 1.002* 1.002* 1.002* 1.001 1.001(0.000616) (0.000574) (0.000682) (0.000662) (0.000610) (0.000624)

Gini 1.024** 1.121 1.022* 1.091 1.008 1.025(0.00817) (0.0795) (0.00882) (0.0925) (0.00714) (0.0750)

Gini^2 0.998 0.999 1.000(0.00120) (0.00143) (0.00125)

Constant 0.733 0.207 0.768 0.308 1.362 1.079(0.194) (0.210) (0.217) (0.373) (0.346) (1.110)

year fixed effectsObservations 55 55 55 55 55 55R-squared 0.697 0.712 0.634 0.642 0.476 0.477Robust seeform in parentheses** p<0.01, * p<0.05, + p<0.1

Dependent variable: Country fixed effects (Weighted GLS)

Lower class Middle class Upper class

Documents

Social inequality and voter turnout - evidence from EU elections Daniel Horn TÁRKI GINI Year-One Conference February 4-5. 2011. Milan