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      An empirical stochastic model of Argentina’s Impossible Game (1955–1966)

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      Journal of Theoretical Politics
      SAGE Publications

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          The Statistical Analysis of Roll Call Data

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            The Ideological Mapping of American Legislatures

            The development and elaboration of the spatial theory of voting has contributed greatly to the study of legislative decision making and elections. Statistical models that estimate the spatial locations of individual decision-makers have made a key contribution to this success. Spatial models have been estimated for the U.S. Congress, the Supreme Court, U.S. presidents, a large number of non-U.S. legislatures, and supranational organizations. Yet one potentially fruitful laboratory for testing spatial theories, the individual U.S. states, has remained relatively unexploited, for two reasons. First, state legislative roll call data have not yet been systematically collected for all states over time. Second, because ideal point models are based on latent scales, comparisons of ideal points across states or even between chambers within a state are difficult. This article reports substantial progress on both fronts. First, we have obtained the roll call voting data for all state legislatures from the mid-1990s onward. Second, we exploit a recurring survey of state legislative candidates to allow comparisons across time, chambers, and states as well as with the U.S. Congress. The resulting mapping of America's state legislatures has great potential to address numerous questions not only about state politics and policymaking, but also about legislative politics in general.
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              A Model of Political Competition with Citizen-Candidates

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                Author and article information

                Journal
                Journal of Theoretical Politics
                Journal of Theoretical Politics
                SAGE Publications
                0951-6298
                1460-3667
                May 23 2016
                June 03 2015
                : 28
                : 2
                : 266-287
                Article
                10.1177/0951629815586874
                47a9e1c7-b43d-4389-b2a9-9310024c54a7
                © 2015

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

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