Linear Probability Models of the Demand for Attributes with an Empirical Application to Estimating the Preferences of Legislators
James Heckman and
No 5785, NBER Working Papers from National Bureau of Economic Research, Inc
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
JEL-codes: C25 D72 (search for similar items in EconPapers)
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Published as James J. Heckman & James M. Snyder Jr., 1997. "Linear Probability Models of the Demand for Attributes with an Empirical Application to Estimating the Preferences of Legislators," The RAND Journal of Economics, vol 28.
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Persistent link: https://EconPapers.repec.org/RePEc:nbr:nberwo:5785
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