Does E-Voting Matter for Turnout, and to Whom?

Does E-Voting Matter for Turnout, and to Whom?

Adrien Petitpas, Julien M. Jaquet, Pascal Sciarini

Abstract

Empirical evidence suggests that e-voting has no measurable effects on turnout. However, existing studies did not look at e-voting effects on the individual level. We innovate by analyzing whether and to what extent the availability of e-voting fosters turnout among specific groups of citizens, and how this influences the equality of participation. To that end, we estimate Bayesian multi-level models on a unique set of official data on citizens’ participation covering 30 ballots between 2008 and 2016 in Geneva, Switzerland, which has the most far-reaching experience with e-voting worldwide. Despite the fact that e-voting was added to an easy-to-use form of postal voting, we find that offering e- voting has increased turnout among abstainers and occasional voters. By contrast, the effects of e-voting availability on the equality of participation are mixed with respect to the age cohorts and gender.

Keywords: turnout, participation, internet voting, e-voting, direct democracy

Acknowledgments: This paper is part of a project sponsored by the Swiss National Science Foundation (grant Nr. 10DL17_183139). A previous version of the paper was presented at the Annual Conference of the Swiss Political Science Association in St. Gallen in January 2017 and at the 2018 CUSO masterclass on advance quantitative methods. We are grateful to Fabio Cappelletti, Simon Hug, Moulay Lablih, Pierre-Louis Schmitt, Marco Steenbergen, Amal Tawfik and Reto Wüest for their helpful comments. We further thank the Statistical Cantonal Office (OCSTAT) and the Elections and Votes Service of the Geneva State for providing us with the registered data on participation.

Declaration of interest: none.

Color: none

Contact: Adrien Petitpas (corresponding author): adrien.petitpas@unige.ch, University of Geneva, Department of political science and international relations, Boulevard du Pont-d'Arve 40, 1205 Geneva, Switzerland.

Julien M. Jaquet: julien.jaquet@unige.ch, University of Geneva, Department of political science and international relations, Boulevard du Pont-d'Arve 40, 1205 Geneva, Switzerland.

Pascal Sciarini: pascal.sciarini@unige.ch University of Geneva, Department of political science and international relations, Boulevard du Pont-d'Arve 40, 1205 Geneva, Switzerland.

1. Introduction

Faced with the steady decline in electoral turnout, politicians and political scientists alike have pointed to new communication technologies as possible remedies. Simplifying the voting process and offering new, easy-to-use voting modes, such as internet voting, was expected to foster political participation or at least to put a halt to further turnout decline (Alvarez et al.

2009; Krueger 2002; Norris 2005; Trechsel 2007).¹ However, empirical records from studies in various countries (Canada, Estonia, UK, Switzerland) and on different levels of government are inconclusive. E-voting does not seem to have measurable effects on turnout. Rather than attracting new voters, it mainly substitutes to existing voting means, such as postal voting (Germann and Serdült 2017; Oostveen and Van den Besselaar 2004).

A caveat, however, applies. Existing studies do not tell the whole story, since they did not (or could not) assess the effects of the availability of e-voting on political participation on the individual level. On the one hand, studies relying on aggregate data are by definition ill-suited to detect fine-grained effects among citizens or groups of citizens. On the other hand, individual data taken from surveys do not provide valid measures of e-voting effects.

Therefore, we still know little about whether offering e-voting matters for citizens' decision to participate and, if yes, to whom.

This question bears strong implications for democracy. From the perspective of normative democratic theory, political participation is desirable to the extent that it helps to ensure equal consideration of the preferences and needs of each citizen (Teorell 2006; Teorell et al. 2007).

To our present purpose, the key question is whether the participatory effects of e-voting, if any, contribute to the equality of participation? Scholars hold contradictory views on this.

Some argue that e-voting may reduce inequalities by increasing turnout among groups that participate less, such as young voters (e.g., Krueger 2002; Serdült et al. 2015). Others disagree and fear that e-voting will reinforce the inequality of turnout by favoring those who already vote more, such as well-educated and wealthier citizens (e.g. Berinsky 2005, Gerlach and Gasser 2009; Norris 2001; Oostveen and Van den Besselaar 2004).

1 Internet voting is a specific form of e-voting that grants citizens the possibility to cast their vote through the internet. In this paper, we use ‘internet voting’ and ‘e-voting’ interchangeably, bearing in mind that we mean remote e-voting and not on-site electronic voting (at the polling station).

In this paper, we innovate by shedding light on the effects of offering e-voting as an additional voting channel on participation of specific segments of the electorate. Empirically, we take advantage of a unique collection of individual, registered data on citizens’ participation (or abstention) in 30 direct democratic votes held in the canton of Geneva, Switzerland, from June 2008 to September 2016. This dataset offers fertile ground for the analysis of e-voting effects. First, together with Estonia, Switzerland is a pioneering country with respect to internet voting (Alvarez et al. 2009; Mendez and Serdült 2014). Within Switzerland, Geneva is the canton with the most far-reaching experience with e-voting. One can arguably learn more from a case in which e-voting has been repeatedly offered, than from a case in which it has been a rare event (Trechsel 2007). Second, in Switzerland one does not need to register to vote. All Swiss citizens aged 18 or more are entitled to vote. This also means that our dataset offers full coverage of the electorate. Third, in the canton Geneva e-voting has been offered discontinuously across ballots and communes, which allows for a quasi-experiment.

Last but not least, Geneva – as Switzerland more generally – can be seen as a hard case with respect to e-voting effects (Germann and Serdült 2017). E-voting was introduced in addition to an easy-to-use form of postal voting and to voting at the polling station. This obviously limits the virtuous effects on turnout that e-voting can have. If such effects are at work in our Swiss case, we can be confident that they also hold in contexts where a convenient voting mode such as postal voting is not available.

2. E-voting and turnout

E-voting facilitates the voting act, by reducing the time and effort required to participate (Kenski 2005; Gainous and Wagner 2007; Powell et al. 2012). Such electoral reforms decrease the direct and objective costs of voting (Berinsky 2005) and also attempt to decrease the perceived costs of voting (see, e.g. Blais et al. 2019). Internet voting is especially attractive for citizens unable to cast a vote at the polling station, namely: For persons with limited mobility such as the elderly or disabled individuals; for those living in remote areas;

and for citizens residing abroad (expatriates), for whom it saves the return time associated with postal service (Germann and Serdült 2014). A related asset of internet voting is convenience and flexibility (Henry 2003; Sciarini et al. 2013). It can be used at any time and from anywhere – at home, at work, during holidays or business trips – and hence allows

citizens to “vote in [their] underwear” (Arent 1999). Finally, e-voting is supposed to appeal to the young generation, for whom internet and social networks have become the main mode of communication (Oostveen and Van den Besselaar 2004, Gerlach and Gasser 2009, but see Unt, Solvak and Vassil 2016; see also Germann 2020 for advantages relating to voters’

mistakes).

By offering an easy way to vote, internet voting is expected to increase turnout. As Norris (2004: 193) puts it: “If citizens will not come to the polls (...) why not bring the polls closer to citizens.” Yet whether and to what extent offering e-voting will indeed foster turnout is conditional on the institutional ‘starting conditions’, i.e. on the voting channels available at the time e-voting is introduced. In a context where only the classic on-site participation (i.e.

voting at the poll station) is in place, introducing e-voting will greatly simplify the voting act and may thus foster participation by mobilizing new voters. By contrast, in a context where another convenient voting mode, such as an easy-to-use postal voting, is already available, the added value of e-voting is small (Germann and Serdült 2017; Goodman and Stokes 2018;

Henry 2003). In such a context, e-voting mainly serves as substitutes to other voting modes (Bochsler 2010; Goodman 2014). That is, it is mainly used by those who usually vote, and who would have used another mode, had e-voting not been available. As e-voting does not 'diffuse' political participation to other groups beyond frequent voters (Vassil et al. 2016), it cannot increase turnout (Mendez and Serdült 2017).

In Switzerland, all-postal voting was introduced in all cantons in the 1990s, and it is extensively used. According to a comparative analysis across time and cantons, postal voting had a significant effect on participation (Luechinger et al. 2007): It increased turnout by 3 to 4 percentage points, on average. In some cantons, such as in Geneva, one must even talk of free postal voting, since sending back the ballot paper is free of stamp. Therefore, in Geneva – as in Switzerland more generally – the gains associated with the simplification of the voting act were already achieved with postal voting; introducing e-voting as a third voting channel did not represent a new qualitative leap (Sciarini et al. 2013).

Moreover, the potential positive effects of e-voting on turnout may also be hampered by citizens’ security concerns (Mendez and Serdült 2017; Sciarini et al. 2013; Trechsel and Vassil 2010). Fears of vote manipulation and fraud may discourage voters from using e- voting. In the extreme case, assuming e-voting is offered to citizens as the only voting mode,

concerns about the integrity of elections might even decrease turnout. Finally, while e-voting decreases the direct and objective costs of voting, it does not necessarily break down the most important barriers of political participation, such as political involvement and the cognitive efforts to form an opinion (Berinsky 2005).

Empirically, most studies relying on aggregate data have found no or nearly no effects of e- voting on turnout (Henry 2003). This also holds for Estonia and Switzerland, the two countries with the longest experience with e-voting. Analyzing election data from the 234 Estonian municipalities, Bochsler (2010) concludes that e-voting has no discernible influence on turnout. However, a more recent study based on descriptive statistics provides a more positive view of e-voting effects in Estonia (Vassil 2016: 11). According to that study, e- voting has helped to stop turnout decline. In the Swiss context, applying difference-in- difference estimation to participation data on the municipality level in two cantons (Geneva and Zurich), Germann and Serdült (2017) do not find any e-voting effects on aggregate turnout (see also Sciarini et al. 2013). Therefore, they conclude that “the convenience added by i-voting is too limited to raise turnout”, and argue that voters who cast their vote through the internet “would most likely have voted anyway had online voting not been on offer, be it by post or at the polling station” (Germann and Serdült 2017: 9).

Results from other contexts also tend to show that e-voting has no or only small effects on aggregate turnout. In Ontario, Goodman and Stokes (2018: 3) acknowledge that e-voting is not a “panacea”. They identify a small positive effect on turnout mostly only in contexts where the postal voting is not available. In their study of an election in Arizona in 2000, Alvarez and Nagler (2001) and Gibson (2002) even found that e-voting can distort the representativeness of the electorate, by disadvantaging the already disadvantaged groups.

However, studies based on aggregate data have important limitations. They cannot, by definition, detect e-voting effects on the individual level. Moreover, most studies cover short time periods (Gainous and Wagner 2007; Henry 2003; Kenski 2005; Segaard et al. 2013;

Solop 2001; Spada et al. 2016). Yet the effects of institutional innovations that change the 'rules of the game', such as the introduction of a new voting mode, are 'slow' to develop (Solvak and Vassil 2018). Accordingly, those effects must be evaluated in a medium or long- term perspective (Franklin 2004). In the present case, this means studying e-voting effects in a context with a durable experience in e-voting (Trechsel 2007).

Among studies using individual survey data, results are mixed. Some studies report a positive impact of e-voting on turnout (Gerlach and Gasser 2009; Solop 2001; Trechsel and Vassil 2010), but others find no effects (Breuer and Trechsel 2006). A third set of studies show that e-voting matters only for specific segments of the population (Kenski 2005), such as young voters (Alvarez et al. 2009, Solvak 2016) or ‘peripheral’ voters (Vassil and Weber 2011). Yet studies based on survey data are not well-fitted to assess the effects of e-voting on turnout.

Political participation taken from surveys is notoriously biased for reasons of voter overrepresentation and – even more relevant in the present context – of vote overreporting (Goldberg and Sciarini 2019; Sciarini and Goldberg 2016, 2017; Selb and Munzert 2013).

Therefore, studies reporting that voters would not have participated had internet voting not been available or that voters would participate more if e-voting were available (Alvarez et al.

2009; Christin and Trechsel 2005; Trechsel and Vassil 2010) must be taken with a grain of salt. Respondents’ self-assessments are plagued by social desirability pressure or wishful thinking, or both.

In sum, existing evidence about the effects of e-voting on turnout is mixed. While some studies – mainly those based on survey data – find positive effects, several studies from various countries and at different levels of government tend to show that these effects are small or even inexistent. The lack of effects holds especially in contexts where e-voting was added to another convenient voting mode, such as postal voting. In those contexts, rather than bringing new voters to the polls, e-voting mainly seems to substitute to other voting channels.

Yet very few studies have looked at the effects of e-voting on specific segments of the population. Even if e-voting has no measurable effects on aggregate turnout, it may still affect the composition of the voting population. In that sense, the question whether offering e-voting influences citizens' decision to participate and, if yes, which citizens and with which consequences for the quality of participation, remains open.

At this point, it should be added that offering e-voting may increase turnout both directly and indirectly. In addition to stimulating participation by providing citizens with an additional, convenient voting mode, making e-voting available voting may also have broader mobilization effects. E-voting is still in its infancy, and the opportunity to e-vote still remains a rare event. Offering internet voting is thus prone to give rise to advertising efforts by the government, and to attract media attention. This, in turn, acts as a signal to voters, and

reminds them about the upcoming vote and/or draws their attention to the specific ballot measure(s) at stake. Therefore, communication activities surrounding the opportunity to e- vote are likely to stimulate participation, regardless of whether citizens eventually vote through the internet or through another voting channel (at the ballot box or by postal mail).

In the next section, we elaborate on the specific segments of citizens that are likely to be sensitive to the availability of e-voting, and we reflect on the related consequences for the equality of participation.

3. E-voting effects among specific groups of citizens

From the perspective of democratic theory, citizens’ participation in elections and – wherever available – in direct votes is central to a well-functioning democracy. By electing parties and candidates and by voting on policy measures citizens can express their political preferences and, thereby, influence political decision-making. According to the participatory model of democracy (see, e.g., Pateman 1970), it is desirable to achieve maximal participation of citizens in political decisions affecting their lives. Departing from that view, some authors argue that the level of turnout is not the main issue. What matters more is the equality of participation (Teorell 2006; Teorell et al. 2007). That is, low turnout is not necessarily a problem, as long as abstention is evenly distributed among the population (Schäfer 2013). A legitimacy problem arises if political participation is unequal, that is, if specific social groups are systematically underrepresented. In light of this argument, the central question is not whether e-voting increases turnout overall, but whether it increases participation among citizens who usually abstain or participate less.

Some scholars trust that e-voting will decrease barriers to civic engagements and reduce inequalities in participation by attracting groups that participate less, such as young citizens or occasional voters (Christin and Trechsel 2005; Gerlach and Gasser 2009; Krueger 2002;

Kenski 2005; Vassil and Weber 2011; Vassil et al. 2016). Other scholars are more pessimistic.

They claim that e-voting does not change the motivational basis for political activism, and they even fear that e-voting will have the opposite effect, i.e. that it will reinforce the social stratification of the vote (Berinsky 2005, Gerlach and Gasser 2009; Henry 2003; Goodman 2014). By activating the digital divide, so the argument, e-voting will favor citizens who are

familiar with the internet and already vote regularly, namely the well-educated and the wealthier, and leave behind the less educated, the elderly, and women (Gainous and Wagner 2007; Norris 2001, 2002; Oostveen and Van den Besselaar 2004).

3.1 Cohort effects

According to a meta-analysis of 22 empirical studies, age is the most consistent sociodemographic determinant of e-voting use (Serdült et al. 2015). Young voters are typical e-voting users, whereas oldest voters resort to it the least (see also Alvarez et al. 2009;

Goodman 2010; Henry 2003; Kenski 2005; Sciarini et al. 2013). Note, however, that it is not the youngest age group that is e-voter champion, but citizens aged 25 to 39 years (Serdült et al. 2015). Heiberg et al. (2015) and Unt, Solvak and Vassil (2016) even find that the share of very young e-voters is comparable to the 65-75 years old citizens. Yet the use of e-voting and its impact on turnout are two different things (Vassil and Weber 2011). For instance, Solvak (2016) identifies a mobilization effect of e-voting among young citizens, although they have a lower probability to use it that other age groups.

Whereas existing studies did not distinguish age from cohort effects, we argue that the mobilization effects of e-voting availability depend more on the context in which citizens grew up than on their biological age. That is, we argue that e-voting effects on turnout relate more to a cohort rather than to an age effect. The so-called ‘digital natives’ were socialized with the internet, and their exposure to and familiarity with that technology reaches a high.

They use the internet in many facets of their life and they trust that technology. The fact that citizens who grew up with the internet rely strongly on the internet in general, renders them especially susceptible to e-voting effects, either because they are keen on voting through the internet or because offering e-voting will have indirect mobilizing effects on them. According to our first hypothesis, then, offering e-voting leads to higher turnout among voters born after 1990 (H1).

Participation classically follows a curvilinear pattern, with young and very old age cohorts voting the least, and intermediate cohorts the more (e.g. Rosenstone and Hansen 1993; Verba and Nie 1972; for Switzerland see, e.g., Sciarini et al. 2016). Therefore, if hypothesis 1 is confirmed, that is, if e-voting fosters turnout among young voters, introducing that new voting mode will contribute to the equality of participation. Moreover, in light of the theory that

voting is a habit (Aldrich et al. 2011; Denny and Doyle 2009; Green and Shachar 2000;

Plutzer 2002), if e-voting increases turnout among young voters, then this might have a durable impact on their participation record.²

3.2 Gender

The meta-analysis mentioned above further points to a gender gap in the resort to e-voting (Serdült et al. 2015). Even though the difference does not reach statistical significance in all reviewed studies, the share of e-voters is systematically higher among men than among women (but see Unt, Solvak, and Vassil 2016). According to Bimber (2000), two factors may explain that gender gap. First, a compositional effect is at work. The difference in socio- economic resources (as measured by education, socio-economic status and income) between men and women results in lower internet access and use among the latter. Second, psychological factors also play a role. Stereotypes still tend to signal that computer technology is more appropriately male than female. Moreover, internet related technologies were created by men and are thus “gendered by design” (Bimber 2000: 870), which may hinder their use among women. Accordingly, our second hypothesis states that offering e- voting leads to higher participation among men, but not so among women, and thus results in gender difference in turnout (H2).

This hypothesis echoes the fear that the digital divide may deepen the gender gap in turnout (e.g. Norris 2001). While that gap has in fact closed in most Western democracies,³ if offering e-voting increases participation among men but not among women, this may contribute to reopen the turnout gap between gender.

3.3 Type of voters

While the habituation thesis divides the electorate into two groups, frequent voters and abstainers, Swiss studies point to the existence of a third category of occasional voters (also

2 Suggestive evidence from survey data gathered in Estonia confirms that e-voting is habit forming, meaning that a first-time e-voter is likely to stay e-voting in subsequent years (Solvak and Vassil 2018). A study on the fidelity to internet voting in Switzerland further shows that it is the older voters (and not the younger) that are most likely to remain faithful to internet voting once they have experimented it (Mendez and Serdült 2017).

3 Switzerland appears as an exception in that regard, since there is still a residual difference in the level of participation between men and women in elections (Engeli et al. 2006; Tawfik et al. 2012), but no longer so with respect to direct democratic votes (Kriesi 2005; Sciarini 2017, 2018; Sciarini and Tresch 2014).

named “selective” or “irregular” voters), who alternate between participation and abstention (Goldberg et al. 2019; Serdült 2013; Sciarini et al. 2016). A study of contextual effects shows that occasional voters are more sensitive to campaign and ballot-related factors, than frequent voters and abstainers (Goldberg et al. 2019). In particular, the mobilization of occasional voters strongly depends on the intensity of the referendum campaign: The higher the campaign intensity, the higher the likelihood that occasional voters participate.

Given their sensitivity to context-related factors, occasional voters are also likely to be especially reactive to the availability of e-voting. On the one hand, the convenience and newness of e-voting may be especially appealing to occasional voters, and may thus contribute to their decision to participate – and to vote through the internet. On the other hand, as people weakly involved in politics, occasional voters are also prone to benefit most from the communication activities associated with offering e-voting. They will be reminded that a vote is about to take place and they will learn more about what is at stake. This may encourage them to participate – be it through the internet or through another voting channel.

Frequent voters, by contrast, can hardly be influenced by e-voting availability. As they do vote frequently – either by postal mail or at the polling station – providing them with the opportunity to vote through the internet cannot make a big difference for their likelihood to participate. If they use e-voting, they will do it mainly as a substitute to their usual voting mode. Similarly, as frequent voters, they are usually attentive to campaign activities and will thus not be much affected by the additional communication efforts surrounding e-voting availability.

We also expect positive e-voting effects on turnout among citizens who usually abstain.

Abstention is commonly due to entrenched factors such as a lack of interest in politics, political alienation or lack of internal efficacy. Offering them e-voting as an additional voting mode may thus not be enough to overcome their propensity to abstain. However, the study on campaign effects mentioned above shows that even abstainers end up voting, if the political campaign is highly intense (Goldberg et al. 2019). In the context of e-voting studies, some scholars argue that abstainers might be even more reactive to the availability of e-voting that occasional voters (Goodman 2014: 19): "internet voting can encourage some non-voters and (fewer) occasional voters to participate" (see also Christin and Trechsel 2005). Therefore, we

hypothesize that offering e-voting leads to higher turnout among occasional voters and abstainers (H3).

According to Sciarini et al. (2016)’s study, the group of occasional voters is highly heterogeneous in terms of socio-demographic profile, but leans towards abstainers in terms of political attitudes. Occasional voters display low levels of political interest, ideology, partisanship and competence. These characteristics prompt them to abstain, unless they are counterbalanced by contextual, mobilizing factors (Goldberg et al. 2019). Moreover, the group of occasional voters is by far the largest one in size (more than 60%). Therefore, if e- voting increases their propensity to vote, this will have positive side-effects on the equality of participation.

4. Data and Methods 4.1 Data

To get a more accurate view of e-voting effects, we must be able to break down the analysis to the level of citizens or sub-groups of citizens and to look at those effects on a long time-span, based on official participation data on the individual level. The data at our disposal meets all these requirements and is, therefore, fairly unique.⁴ The Geneva’s vote registry database provides official information on individual citizens’ participation (or abstention) across all 30 direct democratic votes held between 2008 and 2016 (see appendix A and B for details), together with a handful of socio-demographic characteristic (sex, age, marital status, electoral district, and the number of years of residence). Moreover, each individual is identified in the dataset through an anonymized numeric code. This enables us to track his/her participation record across ballots. That is, we have repeated measures of participation/abstention over time for each individual.

In Geneva, e-voting pilot projects started in 2004 but were limited to four municipalities. E- voting trials were then put on hold from 2005 to 2008, owing to the lack of legal basis. From November 2008 onwards, the federal legislation limited the share of citizens who could vote through the internet to 30% of the electorate. Accordingly, for federal-level ballots the Geneva

4 Unt, Solvak and Vassil (2016) and Heiberg et al. (2015) relied on similar data (official log-files) to assess the socio-demographic profile of e-voters.

state offered e-voting to citizens living in communes that taken together represented about 30% of the cantonal electorate, with the set of municipalities varying over time. In three cases, only cantonal ballot measures (and no federal ballot measure) were submitted to voters. In those cases, all municipalities offered the possibility to vote through the internet.⁵

Figure 1 shows the availability of e-voting (as indicated by crosses) together with the aggregate level of turnout on the commune level. Across communes, the availability of e- voting varies from 3 to 28 votes (out of 30).⁶ A first set of municipalities offered the opportunity to vote through the internet only in the three above mentioned cases, i.e. in the three cases where only cantonal ballot measures were submitted to voters and where e-voting was thus offered to all citizens of Geneva. In a second group of municipalities, by contrast, e- voting has been routinely offered. The third category of municipalities lies somewhere in- between these two extreme cases, meaning that these municipalities offered the possibility to e-vote to their citizens occasionally. More importantly, the fact that internet voting has been available discontinuously across communes and time draws near to a quasi-experiment.

Figure 1 also provides visual information about the turnout rate. We see that the turnout rate varies considerably across ballots, and much less so across communes. In line with existing studies, we also see that offering e-voting does not seem to increase turnout on the aggregate level. Additional information about the turnout rate on the municipality level and about the level (federal or cantonal) and type (referendum or initiative) of ballot measures submitted to voters on a given voting day appears in Appendix A.⁷

In September 2016 the Geneva state changed the rules of the game. From October 2016 on, all Geneva citizens must register to be able to vote through the internet — and are allowed to do so up to the 30% limit, according to the "first in-first served" principle. As a result of that

5 In 2008, about 77 % of households had an internet access in Switzerland. This proportion increased to 93 % in 2017 (FSO 2019).

6 In a few cases, e-voting was also offered for elections – the first time in November 2012, and again in Spring 2015 in the context of communal elections, and in Fall 2015 in the context of national parliamentary elections.

Yet e-voting is more complex and thus more demanding in elections with an open list PR, than in direct democratic votes with Yes or No choice. For the sake of comparability, we thus focus on direct democratic votes.

7 As Appendix A shows, in most cases a combination of federal and cantonal ballot measures were submitted to voters on the same voting day.

institutional change, the availability of e-voting does no longer depend on the commune in which one lives, but on individual registration. This prevents us from extending the analysis beyond 2016.⁸

Figure 1: Overview of aggregate turnout and e-voting opportunity by municipality and ballot

Note: Crosses indicate e-voting availability.

8 We do not have information on who registered, which also prevents us from studying the registration process.

Finally, note that our dataset focuses on residents and does not include expatriates. While the canton Geneva has offered e-voting to Swiss living abroad from September 2009 onwards, information on participation (or abstention) of that population was included in the official dataset at our disposal only as of June 2015. Given the very limited resulting time span (June 2015 to September 2016), we refrain from studying e-voting effects on expatriates. In that sense, our study has a conservative character, since e-voting is highly popular among expatriates (Germann and Serdült 2014).

4.2 Measures

Citizens’ participation (‘1’) or abstention (‘0’) in a given ballot, as recorded in the official voting registry, is the dependent variable in our analysis⁹. Among independent variables, the main variable of interest is the availability of e-voting. It is coded ‘1’ if a person was living in a commune in which e-voting was available for a given ballot and ‘0’ otherwise. With such variables, our models estimate the impact of e-voting availability on the probability to vote, regardless of the actual voting mode. That is, we can test whether e-voting availability increases the likelihood to participate, but we cannot demonstrate whether this increase, if any, is due to people voting through the internet or through another voting mode (postal vote or vote at the ballot box). The descriptive statistics appearing in appendix C nevertheless suggest that offering e-voting does have mobilization effects, i.e. that it contributes to bring abstainers to the polls.¹⁰

9 Our measure of citizens' participation in a given vote identifies whether a person voted or abstained, but does not distinguish between ballot measures (i.e. if several ballot measures were submitted to voters on the same voting day, it does not tell whether for a specific ballot proposal a voter casted a blank vote). This is only a minor drawback, however, since blank votes are very rare, so that aggregate turnout on one voting day rarely vary more than one percentage point across ballot measures.

10 That table presents information on the voting mode used by citizens who could vote through the internet in a given vote. More specifically, it shows the transition paths from the previous vote to the vote in question (e.g.

from abstention to e-voting, from postal vote to e-voting, etc.). The share of voters who voted through the internet amounts to 15%, on average. More importantly, table in appendix C also shows that 2% of citizens who did not participate in the previous vote voted through the internet in the vote in question. In addition, about 9%

of citizens who abstained in the previous vote through another voting mode in the vote in question. As we argued above, it is plausible that offering e-voting also contributed to bring these voters to the poll, even though they eventually voted through postal vote or in-site.

We measure cohorts through a set of dummies indicating the decade of birth: born ‘1990- 1998’ for the youngest cohort, ‘1980-1989’ for the second, ... , and born ‘before 1930’ for the oldest cohort. As mentioned above, the existing literature did not distinguish age from cohort effects, which is arguably due to their cross-section nature. Unfortunately, our own study does not avoid that problem: given the short time-span covered by our data (8 years), it is almost impossible to disentangle the age and cohort effects.¹¹ As we argued in the theory section, however, e-voting effects relate mainly to cohort rather than to age effects. Accordingly, we will refer to cohort effects in the remainder of this paper.

The dummy for sex has men as reference category. To identify citizens’ participation profile, we look at their frequency of participation in the five previous votes.¹² The resulting variable takes six values: a person either never voted out of five votes (‘abstainer’), or voted one, two, three or four times (‘occasional voter’), or always voted (‘frequent voter’). Note that this measure is re-calculated for each successive ballot. This dynamic measure allows individuals to move from one group of voters to another across ballots. This means that the two extreme categories do not capture ‘true’ abstainers or ‘true’ frequent voters. For example, a citizen may have participated in five ballots in a row, but abstained in the sixth. In this case, she/he will be considered as frequent voter at vote number six, but as an occasional voter at vote number seven.

Further, we include some additional socio-demographic variables as controls: marital status, which distinguishes singles from married, divorced, and widowed people, and residence duration expressed in years. Unfortunately, the data does not provide information on other common determinants of participation, such as socio-economic status, education, political interest or political trust). However, the past participation record variable to some extent captures the effect of these classic drivers of voting. In any case, the usual frequency of participation is among the strongest determinants of participation in current vote (Smets and van Ham 2013).

11 For example, in our data citizens aged 20-30 necessarily pertain to the 1990 cohort.

12 For this variable, we also rely on data prior to the period under study. For example, to compute the past participation record of an individual at the first vote in June 2008, we use information from the five previous votes taking place in 2007 and early 2008.

4.3 Model

To analyze the impact of e-voting availability on political participation at the individual level, we estimate a cross-classified multilevel logit model. The unit of analysis is the citizen-ballot- municipality combination. Due to the hierarchical structure, we introduce varying intercepts for the citizen, the ballot, and the municipality levels. This helps to take into consideration that each citizen has repeated measures and that e-voting was offered discontinuously across ballots and electoral districts (communes)¹³. The diagram in appendix D summarizes the data structure.

As we are interested in the effect of offering internet voting among specific segments of citizens, we interact the e-voting availability variable with the other socio-demographic variables of interest. This results in the following model specification, where the parentheses account for the cross-classification:

ηi(jkl) = α0 + β1Interneti(jkl) + β2Cohorti(jkl) + β3Genderi(jkl) + β4Typei(jkl) + β5Interneti(jkl) × Cohorti(jkl) + β6Interneti(jkl) × Genderi(jkl) + β7Interneti(jkl) × Typei(jkl) + β8XiT(jkl) + υj + µk + ωl

Where ηi(jkl) is the probability for a citizen l, living in a municipality k, to participate in a given ballot j. The Internet variable is the e-voting opportunity; Cohort is the cohort of each individual; and Type stands for individuals’ frequency of participation in the last five votes. In light of the panel structure of the data, Type acts as a lag for the dependent variable. The X represents a matrix of control variables while the υ, µ, and ω terms denote the varying intercepts. The estimation takes place in a Bayesian framework (see appendix D for more information).

Our original data includes all citizens of the canton of Geneva (i.e. about 200,000 citizens times 30 ballots, or 6 million observations). The large number of observations dramatically increases the computation time. Therefore, we drew a random sample of about 10% (or 22,469 individuals, for a total of 617,380 observations). To be able to track citizens' participation over time, once an observation (i.e, the information about a citizen's

13 While we do not have any measures of ballot and campaign-related characteristics, such as issue importance or campaign intensity, the varying intercepts capture the differences in turnout across ballots, and thus indirectly controls for unobserved ballot or campaign characteristics.

participation or abstention in a given vote) is selected, all other available observations for this citizen are also included.

5. Results

Table 1 shows the point-estimates for each variable. The point-estimate is the median of the posterior distribution and represents the most probable value of the parameter. It is comparable to the coefficients in a frequentist framework. The High Density Intervals (HDIs) presents the uncertainty around the parameters (see Makowski et al. 2019). For example, the effect of e-voting has a 95% chance of falling between 0.10 and 0.22. This means that voting in a municipality offering the opportunity to vote electronically increases the probability of participation among the reference category.

Commenting first on the group-level effects, we can see interesting differences. The individual level is the most important group-level effect. As we study turnout at the individual level, it is not surprising that there is a high level of heterogeneity between individuals in our data. In addition, our model includes a limited number of predictors, which results in a rather important unobserved heterogeneity. The second most important level is the ballot. The differences in turnout across direct democratic votes make sense, as these votes may vary strongly from each other, e.g. in terms of the number of ballot proposals submitted to voters, the importance of those proposals or the intensity of the related campaigns. Finally, differences in turnout are smaller across municipalities. Thus, turnout depends more on individuals' and ballots' characteristics, than on the municipalities.

Turning to the main effects of the variables included in our model, the age cohort variables show a clear curvilinear pattern. The participation is low among the youngest cohort, it then increases for older cohorts, peaks among peopled born between 1940 and 1949, and sharply decreases among the oldest cohort. Second, women are less likely to vote than men. Third, married people are more likely to participate than singles, whereas divorced and widowed people are less likely to participate than singles. Finally, the frequency of participation in the five last votes unsurprisingly has a very strong positive effect on participation in the vote at stake: The higher the number of previous votes citizens participated in, the higher their propensity to participate in current vote.

More importantly, and as already mentioned, the parameter measuring the effect of e-voting availability is positive and credible. For a person belonging to the reference category (i.e. a man, single, born between 1960 and 1969, residing in Geneva for a median number of years and who participated in none of the last five votes), the opportunity to vote through the internet has a positive effect on the likelihood to participate in current vote. The effects of e- voting availability on other age cohorts and on citizens with other participation profiles (i.e.

on occasional and frequent voters) are more difficult to assess in a logit model including multiple interaction terms. In such a situation, it is more appropriate to rely on predicted probabilities (Brambor et al. 2006; Kam and Franzese 2007).

Table 1: E-voting effects on turnout

Population-level effects Median Interval

E-voting 0.16 [0.10;0.22]

Birth cohort (ref. = 1960-1969)

Birth cohort: < 1930 -0.38 [-0.50;-0.25]

Birth cohort: 1930-1939 0.53 [0.43;0.62]

Birth cohort: 1940-1949 0.64 [0.55;0.72]

Birth cohort: 1950-1959 0.33 [0.25;0.41]

Birth cohort: 1970-1979 -0.34 [-0.42;-0.26]

Birth cohort: 1980-1989 -0.55 [-0.64;-0.46]

Birth cohort: 1990-1998 -0.64 [-0.75;-0.53]

Woman -0.06 [-0.10;-0.01]

Past participation 2.67 [2.63;2.72]

E-voting * Birth cohort (ref. = 1960-1969)

E-voting * Birth cohort: < 1930 0.08 [-0.02;0.18]

E-voting * Birth cohort: 1930-1939 0.09 [0.01;0.17]

E-voting * Birth cohort: 1940-1949 0.10 [0.03;0.17]

E-voting * Birth cohort: 1950-1959 -0.03 [-0.10;0.03]

E-voting * Birth cohort: 1970-1979 0.03 [-0.03;0.10]

E-voting * Birth cohort: 1980-1989 -0.01 [-0.08;0.06]

E-voting * Birth cohort: 1990-1998 0.00 [-0.11;0.11]

E-voting * Woman -0.08 [-0.12;-0.04]

E-voting * Past participation -0.26 [-0.31;-0.20]

Marital status (ref. = single)

Married 0.23 [0.18;0.27]

Divorced -0.19 [-0.25;-0.13]

Widower -0.36 [-0.45;-0.28]

Years of residence 0.88 [0.72;1.03]

Intercept -1.55 [-1.80;-1.29]

Group-level effects (sd)

Individual 1.48 [1.46;1.51]

Municipality 0.11 [0.07;0.15]

Ballot 0.67 [0.52;0.89]

Observations 617,380

N Individuals 22,469

N Municipalities 45

N Ballots 30

Estimates from a cross-classified multilevel Bayesian logit model. 95 % HDIs in brackets for population-level effects.

Figure 2 shows the differences in the predicted probability to vote for citizens who could vote through the internet, in comparison to citizens for whom e-voting was not available, across age cohorts, while setting the other variables at the median or reference category. This enables us to compare the probability of participation of a given cohort to other cohorts and, more importantly, to compare the probability of participation of a given cohort if e-voting is available and if it is not available (e.g. to compare the predicted probability to vote of the 1990 cohort with and without e-voting availability). Given the strong influence of the past participation record variable, we show the results for three different values of that variable, namely for participation in none of the five last votes (figure on the left-hand side), in two out of five votes (middle) and in four out of five votes (right-hand side).

Our first hypothesis states that e-voting leads to higher turnout among voters born after 1990.

It is not supported by the data. Starting with abstainers (figure 2, left panel), i.e. with citizens who participated in none of the five last votes, offering e-voting increases the probability of participation among all cohorts, but this especially so among people born between 1930 and 1949 (+0.06). The corresponding figures are far smaller for the youngest cohort, and they are in fact smaller than for all other cohorts: Among people born after 1990, the predicted probability to vote if internet voting is offered increases by only 0.02; the same holds for the second youngest cohort. A 0.02 or a 0.06 increase may seem small. Remember, however, that we are considering citizens who abstained in the five previous votes. Among them, the average turnout rate in current vote is smaller than 10%. In light of this, the mobilizing effects associated with the opportunity to e-vote are strong.

The effects of the availability of e-voting also run against our first hypothesis among occasional voters who participated in two votes out of five (figure 2, panel in the middle).

Those effects peak among the three oldest cohorts (+0.032 to + 0.037), whereas offering e- voting has a very small and not credible effect on participation among the youngest cohort.

Finally, the effects of offering e-voting completely vanish among people with a high past

participation record, i.e. among people who participated in four out of the five previous votes (figure 2, right panel). For one specific cohort (people born between 1950 and 1959), the influence on e-voting availability even gets negative.

Figure 2: Difference in predicted probabilities of voting as a function of cohort and e-voting availability

In sum, the effect of e-voting availability on turnout does vary across cohorts, but the way e- voting condition the relationship between cohorts and turnout does not fit our theoretical expectations. First, regardless of age cohort, e-voting effects hold only for people who usually abstain or vote occasionally. Second, we hypothesized that the opportunity to e-vote would foster participation among young citizens, but the results go in the opposite direction: Among abstainers and occasional voters, e-voting increases participation more for old than for young cohorts. In that sense, e-voting does not narrow the gap in turnout between young and old voters. As mentioned in the theory section, the convenience of internet voting especially

appeals to people suffering from illness or mobility problems. This presumably accounts for the positive effects of e-voting availability on (very) old abstainers and occasional voters.¹⁴ Figure 3 helps to test hypothesis 2 that offering e-voting has varying effects among men and women. It shows the difference in the probability to vote for women in comparison to men, when e-voting is not available and when it is available.

Figure 3: Difference in the predicted probabilities of voting between women and men, with and without e-voting availability

If e-voting is not available (figures on the top), for each level of past participation the predicted probability to participate in current vote is smaller among women than among men, yet the difference is small (about 0.01). For all three types of voters, the corresponding differences are more than twice greater when e-voting is available (about 0.03). As the average turnout rate in a given vote is far lower among abstainers (8% for both men and women) than among occasional voters (48%) and – even more so – than among frequent voters (about 80%), the 0.03 increase in the difference in probability to vote between men and women brought about by e-voting availability will be (far) more strongly felt among abstainers than among occasional or frequent voters. Therefore, the results support our

14 Note that our results regarding cohorts do not back recent empirical evidence from Estonia. Solvak (2016:

101) found a strong mobilization effect among the youngest voters (aged 20 to 35), a smaller effect for the 35-50 years old voters, and nearly no effect for the 60-95 years old voters. Differences between contexts, together with difference in research design, presumably account for these contrasted results.

second hypothesis that e-voting leads to differences in participation between men and women, but this especially so among people who do usually not vote.

With regard to the third hypothesis, the considerable influence of citizens’ participation profile clearly transpires from figure 4. For citizens belonging to the reference category, e- voting availability increases the likelihood of turnout for people who participated in zero or in two out of the five last votes (this also holds for people who participated in one vote – results not shown). For those persons, offering e-voting increases the probability of participation by 0.014 (for occasional voters) any by 0.029 (for abstainers). Bearing again in mind that the average turnout rate in current vote is far smaller among abstainers (8%) than among occasional voters (48%), these results confirm that the opportunity to vote through the internet has the strongest positive effects on turnout for voters who abstained in the last five votes.

Finally, and as already noted above, offering e-voting as an additional voting channel does not make any difference for people who participated in four of the last five votes (the result is the same for people who participated in three or in five votes – results not shown).

Figure 4: Difference in predicted probabilities of voting as a function of past participation and e-voting availability

From the perspective of the equality of participation, our results yield ambivalent messages.

On the one hand, they question previous studies arguing that e-voting merely substitute to

other forms of voting mode. While this may hold true for frequent voters, the opportunity to vote through the internet helps to bring abstainers and – to a lesser extent – occasional voters – to the poll. Given our research design, we cannot be sure whether abstainers and occasional voters end up voting through the internet or through another voting channel, yet we can be sure that offering e-voting as an additional voting channel has mobilizing effects on them.

This is an important result, which highlights the virtuous effects of e-voting. As mentioned in the theory section occasional voters, as abstainers, display political attitudes that are conducive to abstention (i.e., low levels of interest in politics, ideology, political competence and partisanship). Yet offering e-voting as an additional voting mode seems to work at cross- purpose and, by mobilizing abstainers and – to some extent also – occasional voters, contributes to the equality of participation. On the other hand, offering e-voting does not seem to reduce the inequality of participation between young and old occasional voters, or between male and female occasional voters. Quite to the contrary, among this specific group of voters, offering e-voting seems to increase the age and gender gaps in turnout.

6. Robustness tests

We submit our results to two robustness tests (see appendix E). As already mentioned, institutional changes such as the introduction of new voting modes are not likely to exert their effects overnight (Trechsel 2007). In the present context, one must first learn how e-voting works before being able to use it regularly (Solvak and Vassil 2018). In other words, voting through the internet comes with some ‘entry costs’, as citizens have to go through a succession of identification and traceability checks. Therefore, we may assume that the effects of e-voting on turnout varies depending on the degree of familiarity with that new voting mode. The effects are presumably stronger among citizens who repeatedly had the opportunity to vote through the internet, than among those rarely exposed to it. Yet another effect is also plausible. The novelty of e-voting is also an asset. Voters may be eager to vote through the internet because they are interested in technological innovation or simply because they are sensitive to the newness of e-voting. In such a scenario, a ‘fashion effect’ would be at work, with voters resorting more to e-voting the first time it is offered to them.

To assess whether the exposure to or novel character of e-voting plays a role, we run an additional model including a count variable and a dummy variable: At each ballot, the count

variable calculates the number of votes (out of the five last votes) in which e-voting was offered to a given citizen; the dummy variable takes the value of 1 the first time (ballot) e- voting was offered to him/her, and 0 otherwise. Table in the appendix 2 show that there is no novelty effect: The parameter for the first e-voting opportunity is not different from zero. By contrast, the past experience with e-voting has a credible positive effect on the probability to vote. Nevertheless, and more importantly, the effects of the three main variables of interest (age, gender and past participation record) remain the same.

7. Conclusion

Thanks to a rich set of registered participation data covering 30 direct democratic votes and a period of eight years, our article contributes to the convenience voting literature, by highlighting whether offering e-voting as an additional voting channel fosters citizens' political participation. While according to existing studies e-voting does not have any measurable effect on aggregate turnout, our study breaks new ground by analyzing whether and to what extent e-voting influences participation among specific groups of citizens, and with which consequences for the equality of participation. Moreover, we test our hypotheses in a Swiss canton that has the most far-reaching experience with e-voting worldwide, and that allows for a conservative test of e-voting effects in a setting coming close to a quasi- experiment.

The main takeaway is that the availability of e-voting does have an influence on turnout, but that this influence holds for specific groups of citizens only. More specifically, our results highlight the crucial conditional role played by citizens’ participation profile. Offering e- voting in addition to postal and on-site vote increases participation among abstainers and – to a lesser extent – among occasional voters. The result that e-voting availability has mobilizing effects on peripheral voters is important. It is in line with Solvak and Vassil's (2016: 100-101) finding on the Estonian case, and it underlines the positive contribution of e-voting to the equality of participation. By the same token, it contradicts Berinsky's (2015) pessimistic view that e-voting produces a retention of habitual voters rather than a stimulation of unengaged citizens.

By contrast, according to our Swiss data offering e-voting as an additional voting channel does not have any effect on turnout among frequent voters. Given that they do already vote regularly, it is not surprising that they are insensitive to e-voting availability. This does not mean that those voters do not resort to e-voting, but if they do so they substitute it to other voting channels. From a normative viewpoint, this is in fact again reassuring, since this limits the risk that offering e-voting increases the inequality of participation, by fostering participation among those who already vote frequently.

Going one step further, our results help to specify the effects of the availability of e-voting on participation among usual abstainers and occasional voters. Here, the findings are more mixed from a normative perspective. First, e-voting does not contribute to lower the age gap in turnout between young and old cohorts. Among abstainers and – to a lesser extent – among occasional voters, the increase of participation associated with e-voting is smaller among young age cohorts than among old ones. The only category of seldom voters benefiting from the opportunity to vote through the internet is the oldest cohort of people born before 1930.

For this specific cohort – but for this specific cohort only – the convenience of e-voting has virtuous effects on the equality of participation.

A similar result holds for the difference in turnout between gender. Among abstainers and – again to a lesser extent – among occasional voters, offering e-voting increases participation significantly more among men than among women. For this specific category of occasional voters, offering e-voting thus tends to contribute to the inequality of participation between men and women.

The finding that the effects of the availability of e-voting are conditional on citizens' participation profile, i.e that these effects hold mainly for abstainers and seldom voters, breaks new ground. It may account for the fact that e-voting effects remained unnoticed in extant research. Yet our study is not without limitations. The first and main limitation is that we cannot demonstrate that the impact of e-voting availability on participation operates through the usage of internet voting, or through another voting channel. Further work, based on more sophisticated modelling strategy, is needed to assess the direct impact of e-voting on individual participation through internet voting. While transition models taking into account the voting mode would be helpful in that respect, they may raise severe computational issues

and model convergence problems, owing to the complexity of the related multinomial, multilevel models that such an analysis would require.

Another limitation of our study is that it does not take into consideration the effects of other ballot-related or campaign-related factors. While earlier studies showed that the mobilization of usual abstainers and occasional voters is highly dependent on campaign contacts and campaign intensity (Goldberg et al. 2019; Niven 2004; Parry et al. 2008), we find that it is also influenced by the availability of e-voting. This raises the question whether e-voting availability interacts with other campaign-related factors, e.g. whether e-voting effects on turnout are stronger when campaign is highly intense.

Finally, due to data limitations, i.e. due to the limited time period under consideration (8 years). we were unable not disentangle the age and cohort effects. Assuming e-voting will again be offered in the future, it will then be possible to study e-voting effects on a longer time-span. Relying on an age-period-cohort (APC) approach (e.g. Bell and Jones 2014 and 2015) would then help to disentangle the three age effects and to test, as we argued in this article, that these effects mainly relate to cohort effects.

While our study focuses on the Geneva canton, we believe that is has broader implications beyond Switzerland. Finding, as we do, e-voting effects in a context with such unfavorable starting conditions increases our confidence that such effects would also be at work – and would be even stronger – in contexts where e-voting would greatly simplify the voting process. With more countries introducing e-voting, the potential for comparative studies would also increase. Yet such a prospect is obviously conditional on the willingness of governments to offer e-voting. For the time being, security concerns and the fear that e-voting can be manipulated hinders its development. In Switzerland, security concerns have recently led the Federal government to put the e-voting experience on hold. This should nevertheless not discourage us from studying the effects of e-voting, which will certainly reappear sooner or later, possibly as a side-effect of the Covid-19 crisis.

References

Aldrich, J. H., Montgomery, J. M., and Wood, W. (2011). Turnout as habit. Political Behavior, 33(4):535– 563.

Alvarez, R. M., Hall, T. E., and Trechsel, A. H. (2009). Internet voting in comparative perspective: the case of Estonia. PS: Political Science & Politics, 42(3):497–505.

Alvarez, R. M. and Nagler, J. (2001). The likely consequences of Internet voting for political representation. Loyola Law Review, 34, 1115-1153.

Arent, L. (1999).Vote in your underwear. Wired News. Retrieved from http://archive.wired.com/politics/law/news/1999/11/32266?currentPage=all.

Bell, A., and Jones, K. (2014). Current practice in the modelling of age, period and cohort effects with panel data: a commentary on Tawfik et al. (2012), Clarke et al. (2009), and McCulloch (2012). Quality and Quantity, 48(4), 2089-2095.

Bell, A., and Jones, K. (2015). Age, period and cohort processes in longitudinal and life course analysis: A multilevel perspective. In A life course perspective on health trajectories and transitions, pages 197-213. Springer, Cham.

Berinsky, A. J. (2005). The perverse consequences of electoral reform in the United States.

American Politics Research, 33(4), 471-491.

Bimber, B. (2000). Measuring the gender gap on the internet. Social Science Quarterly, 81(3):868–876.

Blais, A., Daoust, J. F., Dassonneville, R., & Péloquin-Skulski, G. (2019). What is the cost of voting?. Electoral Studies, 59, 145-157.

Bochsler, D. (2010). Can internet voting increase political participation? remote electronic voting and turnout in the Estonian 2007 parliamentary elections. In Paper presented at the Conference ’Internet and Voting’, Florence. European University Institute.

Brambor, T., Clark, W. R., and Golder, M. (2006). Understanding interaction models:

Improving empirical analyses. Political Analysis, 14:63–82.

Breuer, F. and Trechsel, A. H. (2006). E-voting in the 2005 local elections in estonia. Report for the Council of Europe.

Bürkner PC (2018). Advanced Bayesian Multilevel Modeling with the R Package brms. The R Journal, 10(1), 395–411.

Bürkner, P. C. (2017). Brms: An r package for bayesian multilevel models using stan.Journal of Statistical Software, 80.

Carpenter, B., Gelman, A., Hoffman, M. D., Lee, D., Goodrich, B., Betancourt, M., Brubaker, M., Guo, J., Li, P., and Riddell, A. (2017). Stan: A probabilistic programming language.

Journal of statistical software, 76(1).

Christin, T. and Trechsel, A. H. (2005). Analyse du scrutin du 26 septembre 2004 dans quatre communes genevoises (Anières, Carouge, Cologny et Meyrin). Technical report, E-

democracy center, Geneva.

Denny, K. and Doyle, O. (2009). Does voting history matter? analyzing persistence in turnout. American Journal of Political Science, 53(1):17–35.

Engeli, I., Ballmer-Cao, T.-H., and Giugni, M. (2006). Gender gap and turnout in the 2003 federal elections. Swiss Political Science Review, 12(4):217–242.

Franklin, M. N. (2004). Voter Turnout and the dynamics of electoral competition in established democracies since 1945. Cambridge University Press, Cambridge.

FSO (2019). Federal Statistical Office: Accès des ménages à internet. Retrieved from:

https://www.bfs.admin.ch/bfs/fr/home/statistiques/culture-medias-societe-information- sport/societeinformation.assetdetail.11068667.html (last consultation february 21, 2020).

Gainous, J. and Wagner, K. (2007). The electronic ballot box: A rational voting model for class, age, and racial bias. American Review of Politics, 28:19–35.

Gelman, A. and Rubin, D. B. (1992). Inference from iterative simulation using multiple sequences. Statistical Science, 457–472.

Gelman A., Carlin J.B., Stern H.S., Rubin D.B. (2014). Bayesian Data Analysis, volume 2.

Taylor& Francis.

Gerlach, J. and Gasser, U. (2009). Three case studies from Switzerland: E-voting. Berkman Center Research Publication, 3(1).

Germann, M. (2020). Making votes count with internet voting. Political Behavior. In press.

Germann, M. and Serdült (2014). Internet voting for expatriates: The Swiss case. e-Journal of eDemocracy & Open Government, 6(2):197–215.

Germann, M. and Serdült, U. (2017). Internet voting and turnout: Evidence from switzerland.

Electoral Studies, 47:1–12.

Gibson, R. (2002). Elections online: Assessing internet voting in light of the Arizona democratic primary. Political Science Quarterly, 116: 561-583.

Goldberg, A. and Sciarini, P. (2019). Who gets lost, and what difference does it make? Mixed modes, nonresponse follow-up surveys and the estimation of turnout. Journal of Survey Statistics and Methodology, 7:520-544.