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	Spatial Voting Model	Ideal Point Estimation
Field	Political Science	Political Science
Family	MCDM	Latent structure
Year of origin	1957	2004
Originator	Harold Hotelling, Duncan Black & Anthony Downs	Clinton, Jackman & Rivers (Bayesian formulation); Poole & Rosenthal (spatial tradition)
Type	Formal model of electoral and legislative choice	Latent-variable spatial model of binary choice data
Seminal source	Downs, A. (1957). An Economic Theory of Democracy. Harper & Row. ISBN: 9780060417505	Clinton, J., Jackman, S., & Rivers, D. (2004). The Statistical Analysis of Roll Call Data. American Political Science Review, 98(2), 355–370.
Aliases	Spatial Theory of Voting, Downsian Model, Proximity Voting Model, Median Voter Model	Ideal point model, Item response theory for roll calls, Spatial voting model, Bayesian ideal points
Related	4	4
Summary	The spatial voting model represents voters and political alternatives as points in a common geometric policy space and assumes that each voter supports the alternative nearest to their own ideal point. Rooted in Hotelling's location theory, Duncan Black's 1948 single-peakedness result, and Anthony Downs's 1957 economic theory of democracy, the model yields two foundational results: the median voter theorem, which identifies the equilibrium policy in one dimension, and the Downsian prediction that two vote-seeking parties converge toward the center. It is the workhorse formalism behind modern empirical estimation of political positions.	Ideal point estimation recovers the latent policy positions — ideal points — of political actors from their observed binary choices, most often legislators' yea/nay votes on roll calls. Building on the spatial theory of voting and formalized as a Bayesian item-response model by Clinton, Jackman, and Rivers in 2004, it places each legislator and each bill in a low-dimensional policy space and estimates positions so that the probability a legislator votes yea increases as the bill's 'yea' outcome moves closer to that legislator's ideal point.