Compulsory voting and political knowledge: testing a ‘compelled engagement’ hypothesis Jill Sheppard Centre for Applied Social Research Methods The Australian National University

Background Assumptions about compulsory voting But evidence too: turnout rate (Franklin 1999) equality between voters and non-voters engagement (Lijphart 1997) party stability (Mackerras and McAllister 1999) policy outcomes (Fowler 2013)

Compulsory voting Variations in enforcement formal sanctions (e.g. fines) informal sanctions (e.g. job exclusions) ‘compulsion’ without sanction (e.g. statute but no enforcement) “Compulsory voting” is heterogeneous

Or, in an array… Sanctions Sanctioned Unsanctioned Form of obligation Formal Sanctioned compulsion (Australia) Unsanctioned compulsion (Mexico, Venezuela) Informal Sanctions/benefits but no ‘compulsion’ (Russia) No compulsion, little pressure (NZ, US, UK…)

Research questions Does sanctioned compulsory voting have positive effects on engagement? - specifically, on political knowledge? Do any effects also occur in the absence of sanctions? - does the *idea* of compulsion matter?

Switzerland (Schaffhausen) Data and methods CSES Modules 1-4 pooled OLS and LME models (LME4 package in R) Strong sanctions (elections=15) Moderate sanctions (elections=8) No sanctions Australia Brazil Greece Uruguay Chile Mexico Belgium Italy Switzerland (Schaffhausen) Thailand Peru Degrees of enforcement come from CSES investigators’ advice Countries with voluntary voting in the sample: Albania, Austria, Bulgaria, Belarus, Canada, the rest of Switzerland, the Czech Republic, Germany, Denmark, Spain, Estonia, Finland, France, Great Britain, Croatia, Hungary, Ireland, Israel, Japan, Kyrgyzstan, South Korea, Lithuania, Montenegro, Netherlands, Norway, New Zealand, Philippines, Poland, Portugal, Romania, Russia, Serbia, Slovakia, Slovenia, Sweden, Taiwan, Ukraine and United States Iceland and Hong Kong excluded as no Polity data available for them In total, 38 countries and 95 elections

CSES information questions (examples) Australia: Australia became a federation in 1901 (T/F). The longest time allowed between Federal elections for the House of Representatives is four years (T/F). Brazil: The president has a 4 year mandate (T/F). Geraldo Alckmin belongs to the PTB (T/F). The deputies of the House of Representatives are elected by majoritarian system (T/F). Greece: Could you tell me how many parties are represented in parliament today? Based on the current electoral law, what percentage of votes constitutes the threshold for entry of a political party into parliament? (T/F) Mexico: Which are the chambers of Mexico’s Congress? Could you tell me the name of the governor of your state? On the whole, how many years does a Deputy stay on his charge? (T/F) Note measurement errors inherent to comparative design (and the CSES project more generally)

Mean responses by CV type All diffs sig (p=.00) except ‘Strong’ and ‘Weak’ for ‘Don’t know’

Partial effects by CV type Voluntary (n=122,839) No sanctions (n=11,663) Moderate sanctions (n=11,685) Strong sanctions (n=15,166) Male .28 (.01) .26 (.02) .22 (.02) Party ID (binary) .18 (.01) .10 (.02) .29 (.02) .00 (.02) Age .00 (.00) .01 (.00) .02 (.00) Education .09 (.00) .20 (.01) .09 (.01) .10 (.00) Household income .07 (.00) .03 (.01) .10 (.01) .11 (.01) Constant -.19 (.02) -.13 (.05) -.09 (.05) 1.30 (.19) Adj r2 .07 .16 .11 .26 Note lack of party ID effect in strongly enforced compulsory countries, but overall higher model fit Bit all over the shop, if anything

Interactions: education * CV Model A Model B B SE Country-level   CV (strong) .24 .06 .30 .07 CV (mod) -.32 .29 -.20 CV (weak) .16 .26 .00 Individual-level Education .68 .01 .71 Education*CV (strong) -.04 .03 Education*CV (mod) -.17 .04 Education*CV(weak) .19 Constant -1.49 0.80 .80 Residual .77 0.88 0.77 .88 Controls all modelled as fixed effects – Polity IV, days since election (for time-contingent effects of media coverage), district magnitude (as a proxy for electoral systems and consequent differences in constituent-representative linkage), party ID (which has a moderate positive effect) age (which has a positive effect), gender (being male has a strong positive effect, which is covered extensively in literature elsewhere on measurement error in knowledge studies), and household income (weak positive effect). Intercepts are modelled as random effects, controlling for clustered standard errors by election and interview mode of administration

Interactions: education * CV

Interactions: gender * CV Model A Model B B SE Country-level   CV (strong) .24 .06 .07 CV (mod) -.32 .29 -.16 CV (weak) .16 .26 .27 Individual-level Male .30 .01 .48 .04 Male*CV (strong) .02 Male*CV (mod) -.10 Male*CV(weak) -.07 Constant -1.49 0.80 -1.76 .80 Residual .77 0.88 0.77 .88 Controls all modelled as fixed effects – Polity IV, days since election (for time-contingent effects of media coverage), district magnitude (as a proxy for electoral systems and consequent differences in constituent-representative linkage), party ID (which has a moderate positive effect) age (which has a positive effect), gender (being male has a strong positive effect, which is covered extensively in literature elsewhere on measurement error in knowledge studies), and household income (weak positive effect). Intercepts are modelled as random effects, controlling for clustered standard errors by election and interview mode of administration

Interactions: gender * CV

Interactions: age * CV Model A Model B B SE Country-level CV (strong)   CV (strong) .24 .06 .03 .07 CV (mod) -.32 .29 -.03 CV (weak) .16 .26 .27 Individual-level Age .01 .00 .04 Age*CV (strong) Age*CV (mod) Age*CV(weak) Constant -1.49 0.80 -1.76 .80 Residual .77 0.88 0.77 .88 Controls all modelled as fixed effects – Polity IV, days since election (for time-contingent effects of media coverage), district magnitude (as a proxy for electoral systems and consequent differences in constituent-representative linkage), party ID (which has a moderate positive effect) age (which has a positive effect), gender (being male has a strong positive effect, which is covered extensively in literature elsewhere on measurement error in knowledge studies), and household income (weak positive effect). Intercepts are modelled as random effects, controlling for clustered standard errors by election and interview mode of administration

Interactions: age * CV

Conclusion and implications Strongly enforced CV has an overall positive effect on political knowledge But effects are disparate: - education is less important for knowledge - has no effect on knowledge by gender - increases the concentration of knowledge with age Why? - effects of habitual voting? - heterogenous effects of no GOTV? Compelled engagement may not be so direct… Strong effect of the strongest levels of enforcement undermined somewhat by apparent negative effects of moderate enforcement Weak enforcement also throws argument – turnout is relatively low in the two weakly enforced countries (Mexico and Greece), but they’ve got other things going on. Possible to control for this, without introducing correlations among the independent variables? Next step is to look more closely at the countries by level of enforcement