In political science and social choice theory, the spatial (sometimes ideological or ideal-point) model of voting, also known as the Hotelling–Downs model, is a mathematical model of voting behavior. It describes voters and candidates as varying along one or more axes (or dimensions), where each axis represents an attribute of the candidate that voters care about.[1]: 14 Voters are modeled as having an ideal point in this space and preferring candidates closer to this point over those who are further away; these kinds of preferences are called single-peaked.
The most common example of a spatial model is a political spectrum or compass, such as the traditional left-right axis,[2] but issue spaces can be more complex. For example, a study of German voters found at least four dimensions were required to adequately represent all political parties.[2]
Besides ideology, a dimension can represent any attribute of the candidates, such as their views on one particular issue.[3][4][5] It can also represent non-ideological properties of the candidates, such as their age, experience, or health.[3]
the underlying political landscapes ... are inherently multidimensional and cannot be reduced to a single left-right dimension, or even to a two-dimensional space. ... From this representation, lower-dimensional projections can be considered which help with the visualization of the political space as resulting from an aggregation of voters' preferences. ... Even though the method aims to obtain a representation with as few dimensions as possible, we still obtain representations with four dimensions or more.
Since our model is multi-dimensional, we can incorporate all criteria which we normally associate with a citizen's voting decision process — issues, style, partisan identification, and the like.
The spatial model of voting is the work horse for theories and empirical models in many fields of political science research, such as the equilibrium analysis in mass elections ... the estimation of legislators' ideal points ... and the study of voting behavior. ... Its generalization to the multidimensional policy space, the Weighted Euclidean Distance (WED) model ... forms the stable theoretical foundation upon which nearly all present variations, extensions, and applications of multidimensional spatial voting rest.