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Linear Probability Models of the Demand for Attributes with an Empirical Application to Estimating the Preferences of Legislators

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Heckman, James, Snyder, James·1996·National Bureau of Economic Research

Abstract

This paper formulates and estimates a rigorously-justified linear probability model of binary choices over alternatives characterized by unobserved attributes. The model is applied to estimate preferences of congressmen as expressed in their votes on bills. The effective dimension of the attribute space characterizing votes is larger than what has been estimated in recent influential studies of congressional voting by Poole and Rosenthal. Congressmen vote on more than ideology. Issue-specific attributes are an important determinant of congressional" voting patterns. The estimated dimension is too large for the median voter model to describe congressional voting

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Metadata

Authors
Heckman, J., & Snyder, J.
Venue
National Bureau of Economic Research
Published
1996-10
OpenAlex
W3025136986
Cited by
351
References
0
Type
report
Language
en
Open access
green

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CoChat. (2026). Citation check: Linear Probability Models of the Demand for Attributes with an Empirical Application to Estimating the Preferences of Legislators. https://app.cochat.ai/papers/10.3386/w5785
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Heckman, J., & Snyder, J. (1996). Linear Probability Models of the Demand for Attributes with an Empirical Application to Estimating the Preferences of Legislators. National Bureau of Economic Research. https://doi.org/10.3386/w5785

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