Euclidean Revealed Preferences: Testing the Spatial Voting Model

In the spatial model of voting, voters choose the candidate closest to them in the ideological space. Recent work by (Degan and Merlo 2009) shows that it is falsifiable on the basis of individual voting data in multiple elections. We show how to tackle the fact that the model only partially identifies the distribution of voting profiles and we give a formal revealed preference test of the spatial voting model in 3 national elections in the US, and strongly reject the spatial model in all cases. We also construct confidence regions for partially identified voter characteristics in an augmented model with unobserved valence dimension, and identify the amount of voter heterogeneity necessary to reconcile the data with spatial preferences.

[1]  Ilya Molchanov,et al.  Sharp identification regions in models with convex predictions: games, individual choice, and incomplete data , 2009 .

[2]  R. Vickerman,et al.  DETERMINANTS OF TRAVEL CHOICE , 1978 .

[3]  Keith T. Poole,et al.  Spatial Models of Parliamentary Voting , 2005 .

[4]  Andrew Chesher,et al.  Testing for Neglected Heterogeneity , 1984 .

[5]  Stephen Ansolabehere,et al.  Valence Politics and Equilibrium in Spatial Election Models , 2000 .

[6]  Marc Henry,et al.  Set Identification in Models with Multiple Equilibria , 2011, 2102.12249.

[7]  Yaron Azrieli.  An Axiomatic Foundation for Multidimensional Spatial Models of Elections with a Valence Dimension , 2009 .

[8]  Yasutora Watanabe,et al.  Inferring Strategic Voting , 2012 .

[9]  Claude Berge,et al.  The theory of graphs and its applications , 1962 .

[10]  Antonio Merlo,et al.  Do voters vote ideologically? , 2009, J. Econ. Theory.

[11]  Norman Schofield,et al.  The Mean Voter Theorem: Necessary and Sufficient Conditions for Convergent Equilibrium , 2007 .

[12]  Tim Groseclose,et al.  A Model of Candidate Location When One Candidate Has a Valence Advantage , 2001 .

[13]  K. T. Poole,et al.  Congress: A Political-Economic History of Roll Call Voting , 1997 .

[14]  H. Hotelling.  Stability in Competition , 1929 .

[15]  Jeffrey S. Racine,et al.  Nonparametric Estimation of Conditional CDF and Quantile Functions With Mixed Categorical and Continuous Data , 2008 .

[16]  D. McFadden.  Econometric Models of Probabilistic Choice , 1981 .

[17]  A. Galichon,et al.  Matching with Trade-Offs: Revealed Preferences Over Competing Characteristics , 2009, 2102.12811.

[18]  Alain Monfort,et al.  Coherency Conditions in Simultaneous Linear Equation Models with Endogenous Switching Regimes , 1979 .

[19]  R. Michael Alvarez,et al.  When Politics and Models Collide: Estimating Models of Multiparty Elections , 1998 .

[20]  Tasos Kalandrakis,et al.  Rationalizable voting , 2007 .

[21]  Ruud H. Koning,et al.  On the compatibility of nested logit models with utility maximization , 1994 .

[22]  Uud,et al.  Discrete choice and stochastic utility maximization , 2005 .

[23]  Martin Browning,et al.  Best Nonparametric Bounds on Demand Responses , 2005 .

[24]  A. Downs.  An Economic Theory of Political Action in a Democracy , 1957, Journal of Political Economy.

[25]  Joel L. Horowitz.  Structural Analysis of Discrete Data with Econometric Applications: Charles F. Manski and Daniel McFadden, eds. , 1983 .

[26]  Gyung-Ho Jeong,et al.  Testing the Predictions of the Multidimensional Spatial Voting Model with Roll Call Data , 2007, Political Analysis.

[27]  J. Heckman,et al.  Linear Probability Models of the Demand for Attributes with an Empirical Application to Estimating the Preferences of Legislators , 1996 .

[28]  J. Heckman.  Dummy Endogenous Variables in a Simultaneous Equation System , 1977 .

[29]  Amit Gandhi,et al.  Identifying Preferences under Risk from Discrete Choices , 2009 .