Abstract
Spatial models of political competition over multiple issues typically assume that agents’ preferences are represented by utility functions that are decreasing in the Euclidean distance to the agent’s ideal point in a multidimensional policy space. I describe theoretical and empirical results that challenge the assumption that quasiconcave, differentiable or separable utility functions, and in particular linear, quadratic or exponential Euclidean functions, adequately represent multidimensional preferences, and I propose solutions to address each of these challenges.
This working paper is meant to be published as a chapter in the volume “Advances in Political Economy”, edited by G. Caballero, D. Kselman and N. Schofield. I thank Scott Tyson for suggestions. Comments to ammend errors or to provide updates to the working paper are welcome even after the publication of the volume.
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Notes
- 1.
- 2.
In support of their assumption of exponential utility functions, Poole and Rosenthal (1997) argue that (standard) concave utility functions do not fit the data well.
- 3.
Calvo et al. (2012) analyze an additional complication: agents may not agree on which alternative is to the right or left of another on a given issue. If so, we cannot use a unique spatial representation; rather, we must have subjective maps of the set of the set of alternatives, one for each agent.
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Eguia, J.X. (2013). Challenges to the Standard Euclidean Spatial Model. In: Schofield, N., Caballero, G., Kselman, D. (eds) Advances in Political Economy. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35239-3_8
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