In democracies, voter turnout fluctuates tremendously, ranging from less than 50 per cent of the population in countries such as Switzerland or Mali to over 90 per cent in countries such as Australia or Uruguay. What explains this variation? Since the pioneering studies of Powell (Reference Powell1982, Reference Powell1986) and Jackman (Reference Jackman1987), hundreds of analyses have tried to identify the constituents of macro-level electoral participation. These studies have focused on institutional factors such as the electoral system type or compulsory voting (Franklin 2004), socioeconomic factors such as the country’s level of development (Norris Reference Norris2002), as well as circumstantial and election-specific variables such as the competitiveness of the election (Anduiza Reference Anduiza2002). Ten years ago, the major findings of these studies were summarized in Geys’ (Reference Geys2006) meta-analysis and Blais’ (Reference Blais2006) review article. While admitting that there was little agreement on the effects of most factors on voter turnout, both studies nevertheless suggested a preliminary core model of macro-level electoral turnout. According to Geys (Reference Geys2006) and Blais (Reference Blais2006), turnout is higher under permissive institutions (e.g. proportional representation in large district and compulsory voting), in small highly developed countries and when the election outcome is close.

Ten years later, it is time for another review article. Turnout studies are ever expanding. From January 2004 to December 2013 more than 130 studies on macro-level turnout were published in peer-reviewed English-language journals alone.Footnote 1 Do these studies, which have been conducted in all regions of the world, across various geographical units, and which have brought to the fore more factors (e.g. corruption), confirm Geys (Reference Geys2006) and Blais (Reference Blais2006)? Or do more recent studies suggest a different core turnout model? What gaps remain in existing turnout studies? Interested in these questions, I conducted a new meta-analysis. This analysis complements the one that was published in March 2016 by Cancela and Geys, but also provides a different focus in various ways. In short, Cancela and Geys (2016) replicate Geys’ (Reference Geys2006) article. They use the same variables and research strategy. The only novelty is that they add a comparison of turnout studies at the national and at the sub-national level. For the national level, Cancela and Geys (2016) find that population size and stability, electoral closeness, campaign expenditures and electoral institutions are viable predictors of turnout. For their comparison between the national and the sub-national level, the two authors report some nuanced findings; they show that campaign expenditures, election closeness and voter registration requirements are better predictors at the national level, whereas population composition and size, concurrent election and the electoral system type are more salient sub-nationally.

I adopt a somewhat different research strategy. First, focusing more on institutions, I ask the question: are institutions still the most important predictors of turnout? Second, while it is unclear how Cancela and Geys (2016) retrieved their studies (they include books, book chapters and articles), I engage in a systematic search of English-language articles that use macro-level turnout as the dependent variable. This search strategy yielded 135 articles published between 2004 and 2013 – about one-third more articles than Cancela and Geys (2016). Third, I identify the most frequently used institutional, socioeconomic as well as circumstantial and election-specific variables from these studies. This allows me to cover the most important predictors of turnout, including those which have been more recently added to turnout models, such as income inequalities and corruption, factors that Cancela and Geys (2016) do not include in their meta-analysis. Fourth, I discuss the influence of the most widely used determinants of turnout more systematically than Cancela and Geys (2016). Fifth, I discuss the effect of several operationalizations of the same concept on turnout, something that Cancela and Geys (2016) do not do.

Given that I use a large sample and include more studies from the developing world, my results are somewhat more conservative than Cancela and Geys’ (2016) findings. I find that three variables: compulsory voting, important elections and a small population size consistently trigger higher turnout. In contrast, the empirical record for other predictors of electoral participation such as the electoral system type, the number of parties or electoral closeness does not provide any clear relationship.

This meta-analysis proceeds as follows. First, I situate this study within the larger turnout literature. Second, I systematically identify the effect the most widely used institutional, socioeconomic and circumstantial factors have on turnout. Third, I summarize the status of turnout studies and provide some avenues for future research.

THE TURNOUT LITERATURE: A SNAPSHOT Explaining and predicting electoral turnout has been a pillar of behavioural research over the past 30 years. The two seminal works, by Powell (Reference Powell1986) and Jackman (Reference Jackman1987), largely defined the research agenda in the comparative voting literature. Focusing on Western democracies, these two scholars found that two institutions – proportional representation (PR) and compulsory voting – increase electoral turnout (see also Franklin Reference Franklin1999; Jackman and Miller Reference Jackman and Miller1995). Building on these studies, the turnout literature has branched out in several directions. First, starting with Blais and Dobrzynska (Reference Blais and Dobrzynska1998), subsequent studies gradually extended the scope of analysis by increasing the number of countries included in turnout models. Second, research has tested the influence of more and more concepts and variables, such as income inequalities or corruption, on macro-level electoral participation (Kostadinova Reference Kostadinova2003; Mahler Reference Mahler2002). Third, studies have looked at turnout across more and more levels of government, including the supra-national level such as European elections or the sub-national level such as regional- or municipal-level elections (Jeffrey and Hough Reference Jeffrey and Hough2003). The first efforts to summarize and synthesize this growing literature were the meta-analysis by Geys (Reference Geys2006) and Blais’ (Reference Blais2006) review article. Both studies confirmed that turnout increases under compulsory voting. For PR, the other core variable in Powell (1996) and Jackman (1997), the two review articles offered a slightly more nuanced picture. Geys (Reference Geys2006) found solid positive influence for the effect of PR on turnout. In contrast, Blais (Reference Blais2006) was rather more prudent. He confirmed that PR pushes more citizens to turn out but also warned that the size of PR’s impact on electoral participation might be overestimated. In addition, Geys (Reference Geys2006) and Blais (Reference Blais2006) established the existence of two more relationships: that is, turnout increases when the election is decisive and when the population size is small. Ten years after their first reviews it is time to provide an update of the scholarship in this area. Given Blais’ (Reference Blais2006) doubts about the influence of PR on turnout, it is also worth asking whether institutions still shape electoral behaviour, or whether other non-institutional or circumstantial factors have become more important. A new meta-analysis is also justified, considering that over the last 10 years turnout studies have continued to become more diverse in their scope, methods and variables employed. There have been at least four developments in turnout research over the past 10 years. First, recent research has become very diverse with regard to the number of countries treated. For example, some studies are international in scope and use a global perspective (e.g. Endersby and Krieckhaus Reference Endersby and Krieckhaus2008), whereas others employ a regional or even country-specific focus (e.g. Boulding and Brown Reference Boulding and Brown2015). A second feature of recent turnout studies is their increasing methodological sophistication. The methods employed range from simple OLS regression analysis, to various types of pooled time-series analysis, to multilevel or structural equation modelling. Third, the recent wave of turnout studies has brought new variables to the fore, such as religion, thus increasing the list of possible predictors for macro-level turnout. A fourth and final characteristic is that there is no consensus on how to measure certain concepts (for example, the operationalization of development ranges, from GDP per capita, to literacy rates, to the Human Development Index). In this study, I aim to provide a much-needed update of Geys’ (Reference Geys2006) and Blais’ (Reference Blais2006) review articles, and a study that complements Cancela and Geys’ (2016) recent article. In addition to determining the key factors of electoral turnout, I have three goals that go beyond Cancela and Geys (2016). First, I intend to determine whether institutions are still the key predictors of turnout. Second, I want to find out whether ‘new’ predictors of turnout have come to the fore over the past 10 years. Third, I aim to discover whether the measurement of concepts matters. I answer these questions below.

DATA AND METHODS This meta-analysis covers 135 articles, published in English-language peer-reviewed journals between January 2004 and December 2013 where voter turnout at the municipal, regional or country level is the dependent variable. To identify these articles, I collaborated with a political science librarian. Firstly, we identified four databases that can be expected to cover all turnout studies published in peer-reviewed journals in English. These databases are ProQuest Political Science, PAIS International, EBSCO International Political Science Abstracts and International Bibliography of the Social Sciences (IBSS). Second, I used an encompassing search strategy to retrieve all turnout articles. I searched in the subject lines, titles and abstracts for the following key words: elections, turnout, voting, voter participation, electoral participation, voting participation and citizens’ participation. This search yielded more than 600 studies. Third, I manually checked all these articles for two criteria: (1) electoral turnout at the national, state regional or local level had to be the dependent variable; and (2) the research design had to be quantitative. This manual search limited the overall number of articles to 135 and returned slightly over 600 regression models, which make up the corpus of this meta-analysis. To manage this number of studies with their different foci, I cluster the variables into three types, namely institutional variables, socioeconomic variables and circumstantial and election-specific variables. Due to the sheer number of concepts covered by this meta-analysis (this review covers more than 50 concepts and more than 100 different variables), I do not aim to explain the particular result obtained in any individual study. Rather, it is my goal to provide summary patterns of the influence of the most important variables on electoral turnout. For each category, I try to cluster all relevant indicators according to their encompassing concepts (e.g. electoral system type or development), present the most used concepts and identify the variables that represent any of these concepts. For each individual indicator, I then present the following information: the absolute number of times the variable in question is used in the 135 turnout studies in my sample, the number of times it is statistically significant according to theoretical expectations, the number of times it shows the reverse rather than the expected relationship, and the number of times the variable is non-significant. I also calculate the success rate for each variable (computed as the percentage of times that the variable in question met the theoretical expectations and showed a significant relationship in the ‘right’ direction).

QUO VADIS TURNOUT STUDIES? Five results, which in many ways complement Cancela and Geys (2016), emerge from this meta-analysis. First, and in line with Cancela and Geys (2016), I find that the majority of the findings of Geys (Reference Geys2006) and Blais (Reference Blais2006) still hold; that is, I confirm that electoral turnout increases under three scenarios: (1) voting is compulsory; (2) the election is decisive; and (3) the population size is small. However, by merely confirming the consistent influence of three predictors on turnout, the findings of this meta-analysis are more conservative than the results of Cancela and Geys (2016). Contrary to their meta-analysis, which adds many more factors – such as voter registration requirements and electoral closeness to the list of viable predictors for turnout – I suggest a much more restricted core turnout model. Second, and again similarly to Cancela and Geys, I confirm that institutions (in particular, compulsory voting) are important to boosting turnout. However, I also highlight that institutions are no panacea or guarantee of high turnout. In particular, it seems that the positive effect of proportional representation in earlier studies was an artefact of case selection. Contrary to Geys (Reference Geys2006) and to a lesser degree Blais (Reference Blais2006), but also Cancela and Geys (2016), my study highlights that PR only has a positive effect on turnout in a minority of cases between 2004 and 2013. This more nuanced finding might stem from the fact that my analysis includes more studies and models, in particular more cases from non-Western countries. Third, by looking at several operationalizations of the same concept, I highlight that any concept’s influence on turnout might be partially dependent on its operationalization. For example, even if it rests below a 50 per cent success rate, district magnitude has a much higher likelihood of positively affecting turnout than dummy variables for various types of electoral system. Fourth, my study highlights that the influence of many of the predictors of turnout that have been recently added to turnout studies such as corruption or income inequalities vary from study to study; thus my study suggests more context-specific analyses. Fifth, and probably most importantly, more so than Cancela and Gey’s (2016), my study highlights that there is still no established core model of electoral turnout. No variable is omnipresent or appears in most studies. Rather, different variables are used in various contexts (e.g. different levels of analysis such as the municipal or national level use different variables). What does this mean for the turnout literature? Does it signify that the literature has not evolved over the past decade? The answer is a clear no. The literature has brought to the fore many new and possibly important predictors of turnout (e.g. religious doctrine, ethnic fractionalization, corruption or globalization); it has become more methodologically sophisticated by using more advanced modelling techniques; it has systematically evaluated turnout outside the Western world; and it has measured turnout at different levels of analysis (e.g. the local, regional, national and sub-national level). However, what is necessary now is to streamline the diverse findings. I suggest three directions for future research: (1) studies should be more context specific; (2) they should engage in systematic comparisons; and (3) they should focus on measurement. First, the fact that the influence of many factors (e.g. income inequalities, the number of parties) on turnout is inconclusive demands more contextual analysis. The question should no longer be: do PR, the number of parties or development increase turnout? But rather: under what conditions or in which socioeconomic and cultural contexts do PR, the number of parties or development increase turnout? For example, it is possible that various regional or, more specifically, country-specific contexts interact with many of the constituents of turnout, rendering their influence context-specific. Second, studies should engage in systematic comparisons. Cancela and Geys (2016) highlight that there is variation in the predictors of turnout between different levels (e.g. concurrent elections and the electoral system type may play a larger role on the sub-national level), but they do not establish the reasons for these differences. Hence, future studies could systematically compare various levels of analyses such as the local, regional and national levels, first in the same context and then, more broadly, to determine whether institutional or non-institutional factors have the same influence on macro-level electoral participation at any of these levels of analyses. This could allow us to establish domain restrictions of various predictors’ influence on macro-level electoral participation. Third, and possibly most important, future work should focus on measurement. This is significant for the operationalization of independent variables, but, even more so, the dependent variable. With regards to the independent variables, various concepts, including development, important elections or the electoral system, are operationalized in various ways. These types of operationalization might matter; for example, if development is operationalized by education level or per capita GDP. For instance, some countries might have a high per capita income (e.g. many of the Middle Eastern countries), but their education levels, and, in particular, their political education, might be rather low. Citizens in other countries (e.g. Cuba) are materially very poor, but still quite educated. Hence, the context might play a large role depending on one or the other operationalization. Even more importantly, future work should discuss the operationalization of the dependent variable. In the empirical literature, turnout is mainly operationalized in two ways: (1) turnout as the percentage of registered voters that cast their ballot at a given election (RV turnout); or (2) turnout as the percentage of the voting-age population that turned out at an election (VAP turnout) (e.g. Boulding Reference Boulding2010; Indridason Reference Indridason2008). However, RV turnout and VAP turnout are different measures of electoral participation. The former calculates turnout based on the number of individuals that have the right to vote, because their name features on electoral lists. The latter calculates turnout based on the voting-age population – that is, all adult residents that live in a given country (see Endersby and Krieckhaus Reference Endersby and Krieckhaus2008; Highton Reference Highton2004). In the empirical literature about two-thirds of existing studies use RV turnout and one-third of the studies use VAP turnout (see Table 9). While some authors justify the use of one measure over the other,Footnote 6 most studies make it seem a minor choice.Footnote 7 Yet the choice of indicator is not trivial. In fact, both operationalizations are suboptimal as neither measures what it is supposed to measure: the percentage of eligible voters who cast their ballot. For one, RV turnout is likely to overestimate turnout, because it does not include in the calculation of macro-level electoral participation those individuals who are eligible to vote, but who choose not to register. The degree of this overestimation depends on the voter registration requirements.Footnote 8 VAP turnout can either underestimate or overestimate turnout. It might underestimate turnout if the number of non-eligible residents (e.g. foreigners) is higher than the number of nationals living abroad. Vice versa, if the number of nationals living abroad exceeds the number of foreigners in a country, then VAP turnout should overestimate electoral participation.Footnote 9 The turnout literature on the US (e.g. Holbrook and Heidbreder Reference Holbrook and Heidbreder2010) has started to calculate turnout as the percentage of eligible voters using the following formula: VEP turnout = the number of citizens that voted / (the voting age population – foreign citizens at voting age – all adult citizens that are legally not permitted to vote + adult citizens at voting age who live in a foreign country and who have the right to vote) (see also McDonald and Popkin Reference McDonald and Popkin2001; Trounstine Reference Trounstine2013; Wattenberg Reference Wattenberg2005). Comparing turnout across all 49 US federal states, Holbrook and Heidbreder (Reference Holbrook and Heidbreder2010) not only find that the two measures are often more than 5 per cent apart from each other, but also that the influence of some of the determinants of turnout (e.g. log GDP and the percentage of Hispanics) changes, based on which operationalization of macro-level electoral participation is used. The comparative turnout literature should engage in a similar debate about measurement. This applies even more so, considering what can be approximated for the US: namely, the calculation or approximation of VEP turnout should also work comparatively.Footnote 10