Spatial Voting Research Articles

When religion meets incumbency: The limits of Islamist electoral advantage

Why do religious-based parties in Muslim-majority contexts win when they run in elections as incumbents? Does Islamist advantage make them appealing to voters? The sources of Islamist advantage such as their organizations, services, images, and being a refuge are well-documented. However, the literature primarily focuses on contexts where religious-based parties compete under adverse conditions as opposition actors, rather than as incumbents facing more favorable conditions. Through an innovative conjoint experiment in Turkey using candidate videos, we explore the extent of Islamist advantage arguments. Our findings suggest that the universal Islamist advantage, by which Islamists appeal to broader segments, disappears under Islamist incumbency because Islamists can no longer appeal through those sources of Islamist advantage as incumbents. Instead, Islamists may still win due to two factors: incumbency advantage and a persisting particularistic Islamist advantage, driven by increasing spatial voting. Our findings provide evidence for a frequently proposed, yet unsubstantiated, claim about the extent of Islamist advantage.

A Novel Class of Unfolding Models for Binary Preference Data

Abstract We develop a new class of spatial voting models for binary preference data that can accommodate both monotonic and non-monotonic response functions, and are more flexible than alternative “unfolding” models previously introduced in the literature. We then use these models to estimate revealed preferences for legislators in the U.S. House of Representatives and justices on the U.S. Supreme Court. The results from these applications indicate that the new models provide superior complexity-adjusted performance to various alternatives and that the additional flexibility leads to preferences’ estimates that more closely match the perceived ideological positions of legislators and justices.

Ballot Box Representation: Spatial Voting and the Effects of Information in Direct Democracy Elections

AbstractIn states and localities with direct democracy, citizens can advance their policy interests without the aid of elected officials. Research documenting citizens’ lack of political knowledge raises questions about their ability to do so. We conduct three studies during real-world direct democracy elections to determine whether citizens choose alternatives (the ballot proposal or status quo) that are closest to their ideological positions and whether political information improves this outcome. Using original surveys, our first two studies estimate citizens’ ideological positions and show that citizens regularly choose alternatives that are closest to these positions. Using a survey experiment, our third study indicates that political information (party cues, policy information, and spatial maps) further improves such spatial voting. These results demonstrate citizens’ capacity to advance their policy interests in direct democracy elections and identify conditions under which political information strengthens the relationship between citizens’ policy interests and choices about ballot propositions.

Spatial Voting with Incomplete Voter Information

We consider spatial voting where candidates are located in the Euclidean d-dimensional space, and each voter ranks candidates based on their distance from the voter's ideal point. We explore the case where information about the location of voters' ideal points is incomplete: for each dimension, we are given an interval of possible values. We study the computational complexity of finding the possible and necessary winners for positional scoring rules. Our results show that we retain tractable cases of the classic model where voters have partial-order preferences. Moreover, we show that there are positional scoring rules under which the possible-winner problem is intractable for partial orders, but tractable in the one-dimensional spatial setting. We also consider approval voting in this setting. We show that for up to two dimensions, the necessary-winner problem is tractable, while the possible-winner problem is hard for any number of dimensions.

Rural Decline and Spatial Voting Patterns

Abstract How does rural decline affect electoral politics? A well-known argument is that the growing geographical polarisation of populations between prospering major cities and declining hinterlands is emerging as a cleavage of electoral politics in developed countries. But prior work has focussed on specific outcomes of rural decline rather than examining whether the geographical distribution of political attitudes and behaviours within countries has become more uneven in the last decades. Using a measure of party nationalisation capturing spatial differences in electoral support across districts in OECD countries over the last 60 years, we find that a declining rural population increases differences in the geographical distribution of partisan support within countries. Nationalisation determines a party’s orientation toward distribution of public resources and support for region-specific interests.

Vote Choices and Valence: Intercepts and Alternate Specifications

Abstract Valence is a crucial concept in studying spatial voting and party competition. The widely adopted approach is to rely on intercepts of vote choice models and to infer, based on their size and direction, how valence affects party strategies in empirical settings. The approach suffers from fundamental statistical flaws. This contribution provides the statistical fundamentals to advance the empirical modeling of valence. It proposes an appropriate modeling approach to interpret intercepts as valences and alternate specifications to parameterize the effects of valence.

Crossing the Line: Evidence for the Categorization Theory of Spatial Voting

Abstract Bølstad and Dinas (2017) propose a model of spatial voting, based on social identity theory, that suggests supporting a candidate/policy on the other side of the ideological spectrum has a disutility that is not accounted for by common spatial models. Unfortunately, the data they use cannot speak directly to whether the disutility arises because individuals perceive their ideology as a social identity. We present the results of an experimental study that measures the norm against crossing the ideological spectrum; tests the cost of doing so, controlling for spatial effects; and demonstrates that this cost increases with the salience and strength of identity norms. By demonstrating the norm mechanism for the disutility of crossing the ideological spectrum, we provide strong support for B&D's model.

The finagle point is close to the yolk

The yolk and the finagle point are two well-known solution concepts in spatial voting games without a core. No relationship between them has been rigorously established in the literature. We prove that every finagle point must be within 2.32472 yolk radii of every yolk center, in all dimensions. This result tightens and generalizes a claimed bound of 2.5 for two dimensions. The bound applies to all points with finagle radius less than the yolk radius. If the finagle radius is half the yolk radius, the bound decreases to 1.7607.

Spatial voting in non-partisan cities: A case study

In spatial voting theory, voters choose the candidate whose policy preferences are most like their own. This requires that (a) voters and candidates have policy preferences that can be meaningfully summarized in terms of low-dimensional “ideal points” on a left-right scale; (b) voters are able to discern, either directly or through relevant cues, the ideal points of the candidates who are running for office; and (c) voters incorporate this information into the choices they make at the ballot box. Perhaps more than in any other elections, it is not clear that any of these requirements are met in non-partisan municipal elections: policy preferences may not be ideologically structured, information may be inadequate, and voters may choose candidates for reasons other than ideology. This makes non-partisan municipal elections an especially hard test for spatial voting theory. Using novel data from both municipal candidates and eligible voters in a major non-partisan municipal election in Canada, we show that municipal policy attitudes are ideologically structured and that these municipal policy ideal points are strongly related to mayoral and council vote choice. Thus, despite the institutional and informational obstacles, spatial voting can play an important role in non-partisan municipal elections.

Students' Attitude towards Political Participation and Democratic Values in Nigeria: Critical Democracy Education Implications

This study investigated the attitudes of university students toward political participation, as well as four other selected democratic values – freedom and liberty, human rights/human rights protest, corruption resistance, and separation of powers in Nigeria. A descriptive survey design, with a tool entitled ‘Attitude towards Democratic Values Questionnaire (ADVQ)’, was used to collect data from randomly selected 250 undergraduate students (male = 120; female = 130) from a university in Nigeria. Six research questions were answered using descriptive statistics in guiding the study. The results showed that university students reported an unwillingness to protest human rights violations as well as the tendency to accept bribes and campaign for a wrong political candidate for financial gains, despite general findings that indicated positive attitudes towards all selected democratic values among university students. The result of the variance analysis conducted to ascertain the influence of gender on attitudes towards democratic values showed that female students scored significantly higher than their male counterparts in all measured democratic principles, excepting human rights and separation of powers. Implications of findings for a critical democratic education that emphasises critical consciousness, spatial voting, and socio-political resilience are discussed.

The geography of discontent and resentment: A spatiotemporal analysis of populist radical right voting in Czechia between 1992 and 2021

This article analyses the populist radical right in Czechia since the fall of the Communist regime and the democratisation of elections. We categorise given political movements on the basis of relevant theoretical concepts (nativism, populism, authoritarianism) and then analyse spatial patterns of their electoral support to examine the geographical aspects of party replacement. We found substantial differences in the electoral outcomes of the old and the new populist radical right. Nevertheless, we have also observed a considerable convergence of spatial voting patterns between SPR-RSČ and SPD in the latest elections, which suggests a tendency that might prove to be more significant in the future. The main result of this study is the identification of specific places, which, along the contemporary literature nexus, we refer to as “places that are left behind or do not matter”. Such initial recognition might prove vital if we wish to understand places theoretically filled with discontent and resentment that potentially use voting as an act of revolt against the malleably perceived ‘Other’.

A spatial interaction model of vote dispersion

How do votes disperse through a territory? Studies of spatial voting patterns have largely focused on the influence of local factors on voting. The “Friends and Neighbors” model (Key (1949)) explains the advantage of candidates running for office in the locality with which they are associated (Arzheimer and Evans (2012, 2014): Collignon and Sajuria (2018); Horiuchi et al. (2018); Jankowski (2016); Hunt (2020); Munis (2021)), and the “neighbor” effect helps to explain why votes spread. More recent studies have found that the dispersion of votes decreases with distance (Put et al. (2020); Arzheimer and Evans (2012)). However, we know little about how spatial patterns of voting emerge or the mechanism behind the neighbor effect. We argue that this effect depends on the neighbors’ access to information about a candidate, which is constrained by the way information flows. Although scholars have argued that information is a relevant driver explaining the dispersion of votes (Bowler et al. (1993); Arzheimer and Evans (2012); Evans et al. (2017); Campbell, Cowley, Vivyan, and Wagner (2019)), no research has examined the relevance of the network through which information flows. We propose that a spatial interaction model (Wilson (1971)) allows us to predict where this information flows or the voting pattern that will form. Taking advantage of a quasi-natural experiment in Brazilian legislative elections in 1974 and 1978, we show that votes spread through areas of influence created by a hierarchy of cities based on the flows of exchanges among them, including information. We then use our spatial interaction model to predict voting patterns in the elections of 1978 using data from the 1974 elections. Our findings show that the spatial interaction model results fit the data quite well and can help predict spatial patterns of voting.

A Bayesian spatial voting model to characterize the legislative behavior of the Colombian Senate 2010–2014

This paper characterizes the legislators voting behavior in the Colombian Senate 2010–2014, by implementing a one-dimensional standard Bayesian ideal point estimator via Markov chain Monte Carlo algorithms. Our main goal is to retrieve the political preferences of legislators from their roll-call voting records, which individualizes the electoral behavior of the legislative chamber. Furthermore, we conclude about the nature of the latent trait underlying the deputies voting decisions and the legislators locations in political space. Finally, we also offer several methodological and theoretical tools to guide the analysis of nominal voting data in the context of unbalanced parliaments (multi-party systems), taking as reference the particular case of the Colombian Senate.

Continuity in Discontinuity? Spatial Patterns of Electoral Behaviour in the 2021 Czech Parliamentary Elections

This article examines the spatial factors that shaped the 2021 parliamentary elections. Building on a great deal of research in electoral geography and spatial analysis, it focused on specific spatial elements of voting behaviour that have not been previously studied, and on the key time-specific factors that shaped the electoral map and party system in the 2021 elections. Employing a quantitative approach to aggregate electoral and socio-demographic data, the study maps the electoral dynamic by exploiting the unique political situations that were characterized by a competition between two blocs – the two centre-right coalitions, SPOLU and the Pirates and STAN, and the populist ANO and SPD parties. Despite profound changes in the party system, the spatial stratification of Czech politics remained unchanged. Quite the contrary, the societal cleavages shaped the spatial voting patterns even more intensively. Additionally, the study shows that regional context factors modified the overall nationwide trend. Varying from region to region, factors included religiosity, local patriotism, the role of local entrepreneurs, and the effect of a popular local leader.

Региональные тенденции электоральной поддержки латвийских партий: фактор соседства

The article analyses the neighbourhood effect in the voting behaviour of the Latvians at the four recent parliamentary elections, the ethnic and national leaning of parties considered. The study expands a set of electoral geography tools by adding modern techniques of spatial analysis as well as by increasing the knowledge on the position of the Russian speakers within Latvia’s political party landscape. The research aims to evaluate the role of the neighbourhood effect at Latvian elections and identify stable spatial voting clusters. The degree of spatial autocorrelation and changes in it were analysed for each parliamentary party and the non-parliamentary but still influential Latvian Russian Union (LRU). Statistically significant spatial clusters of high and low support were identified and compared; their steadiness over the study period was examined. The structure of these clusters is generally the same for the ‘Russian’ parties (Harmony and the LRU), whilst the ‘Latvian’ parties are characterized by greater spatial diversity. The analysis shows that regions bordering on Russia have clear spatial clusters where election results correspond to the parties’ attitudes towards Russian speakers and the Russian Federation. The ‘Russian’ parties and those more or less favourably disposed to Russian speakers (For a Good Latvia, For Latvia from the Heart) have clusters of high support in the area and the ‘Latvian’ parties of low. This pattern, however, may be due to the high proportion of the non-Latvian population in Latgale (a region with strong historical connections with Russia) and the character of the development of the border area, rather than to the proximity to the Russian border.

Shapley Value and Income Taxation

Income taxation is modeled as a spatial voting game where Shapley value leads to a simple linear tax function on gross income with a single marginal tax rate and a universal basic income subsidy. Shapley net income is not generally in the game core; therefore, it is inherently unstable and subject to relentless pressure from higher gross income individuals to reduce their taxes and increase their net incomes.

Kernel density smoothing of composite spatial data on administrative area level

Composite spatial data on administrative area level are often presented by maps. The aim is to detect regional differences in the concentration of subpopulations, like elderly persons, ethnic minorities, low-educated persons, voters of a political party or persons with a certain disease. Thematic collections of such maps are presented in different atlases. The standard presentation is by Choropleth maps where each administrative unit is represented by a single value. These maps can be criticized under three aspects: the implicit assumption of a uniform distribution within the area, the instability of the resulting map with respect to a change of the reference area and the discontinuities of the maps at the borderlines of the reference areas which inhibit the detection of regional clusters.In order to address these problems we use a density approach in the construction of maps. This approach does not enforce a local uniform distribution. It does not depend on a specific choice of area reference system and there are no discontinuities in the displayed maps. A standard estimation procedure of densities are Kernel density estimates. However, these estimates need the geo-coordinates of the single units which are not at disposal as we have only access to the aggregates of some area system. To overcome this hurdle, we use a statistical simulation concept. This can be interpreted as a Simulated Expectation Maximisation (SEM) algorithm of Celeux et al (1996). We simulate observations from the current density estimates which are consistent with the aggregation information (S-step). Then we apply the Kernel density estimator to the simulated sample which gives the next density estimate (E-Step).This concept has been first applied for grid data with rectangular areas, see Groß et al (2017), for the display of ethnic minorities. In a second application we demonstrated the use of this approach for the so-called “change of support” (Bradley et al 2016) problem. Here Groß et al (2020) used the SEM algorithm to recalculate case numbers between non-hierarchical administrative area systems. Recently Rendtel et al (2021) applied the SEM algorithm to display spatial-temporal clusters of Corona infections in Germany.Here we present three modifications of the basic SEM algorithm: 1) We introduce a boundary correction which removes the underestimation of kernel density estimates at the borders of the population area. 2) We recognize unsettled areas, like lakes, parks and industrial areas, in the computation of the kernel density. 3) We adapt the SEM algorithm for the computation of local percentages which are important especially in voting analysis.We evaluate our approach against several standard maps by means of the local voting register with known addresses. In the empirical part we apply our approach for the display of voting results for the 2016 election of the Berlin parliament. We contrast our results against Choropleth maps and show new possibilities for reporting spatial voting results.

Spatial voting models in circular spaces: A case study of the U.S. House of Representatives

The use of spatial models for inferring members’ preferences from voting data has become widespread in the study of deliberative bodies, such as legislatures. Most established spatial voting models assume that ideal points belong to a Euclidean policy space. However, the geometry of Euclidean spaces (even multidimensional ones) cannot fully accommodate situations in which members at the opposite ends of the ideological spectrum reveal similar preferences by voting together against the rest of the legislature. This kind of voting behavior can arise, for example, when extreme conservatives oppose a measure because they see it as being too costly, while extreme liberals oppose it for not going far enough for them. This paper introduces a new class of spatial voting models in which preferences live in a circular policy space. Such geometry for the latent space is motivated by both theoretical (the so-called “horseshoe theory” of political thinking) and empirical (goodness of fit) considerations. Furthermore, the circular model is flexible and can approximate the one-dimensional version of the Euclidean voting model when the data supports it. We apply our circular model to roll-call voting data from the U.S. Congress between 1988 and 2019 and demonstrate that, starting with the 112th House of Representatives, circular policy spaces consistently provide a better explanation of legislators’s behavior than Euclidean ones and that legislators’s rankings, generated through the use of the circular geometry, tend to be more consistent with those implied by their stated policy positions.

Ideological proximity, issue importance, and vote choice

This paper investigates what proportion of voters select their candidate based on policy proximity in a spatial voting framework and evaluates policy proximity's importance for vote choices. We develop a novel procedure to identify proximity voting and directly estimate the weights of policies from vote choices. Using the American National Election Studies (ANES) for 1996–2008 and nationally representative replication data from Leeper and Robison’s (2020) survey experiments, we find that more than 80% of voters choose the most policy proximate candidate. Among these voters, we find that a one standard deviation change in relative proximity for an extremely important issue has a similar substantive effect on vote choice as partisan identification (moving from Independent to a Not Very Strong Democrat or Republican). Together, these findings suggest that policy positions and issue importance influence citizens' vote choices even after controlling for party identification and demographic characteristics.

Condorcet Relaxation In Spatial Voting

Consider a set of voters V, represented by a multiset in a metric space (X,d). The voters have to reach a decision - a point in X. A choice p∈ X is called a β-plurality point for V, if for any other choice q∈ X it holds that |{v∈ V ∣ β⋅ d(p,v)≤ d(q,v)}| ≥|V|/2 . In other words, at least half of the voters ``prefer'' over q, when an extra factor of β is taken in favor of p. For β=1, this is equivalent to Condorcet winner, which rarely exists. The concept of β-plurality was suggested by Aronov, de Berg, Gudmundsson, and Horton [SoCG 2020] as a relaxation of the Condorcet criterion. Denote by β*(X,d) the value sup{ β ∣ every finite multiset V in X admits a β-plurality point}}. The parameter β* determines the amount of relaxation required in order to reach a stable decision. Aronov et al. showed that for the Euclidean plane β*(ℝ2,\|⋅\|2)=√3/2 , and more generally, for d-dimensional Euclidean space, 1/√d ≤ β*(ℝd,\|⋅\|2)≤√3/2 . In this paper, we show that 0.557≤ β*(ℝd,\|⋅\|2) for any dimension d (notice that 1/√d