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

RAND JOURNAL OF ECONOMICS, Vol. 27, No. 0, Special Issue

Posted: 25 Feb 1997

See all articles by James J. Heckman

James J. Heckman

University of Chicago - Department of Economics; National Bureau of Economic Research (NBER); American Bar Foundation; Institute for the Study of Labor (IZA); CESifo (Center for Economic Studies and Ifo Institute)

James M. Snyder

Massachusetts Institute of Technology (MIT) - Department of Political Science & Department of Economics

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Abstract

We formulate and estimate a rigorously justified linear probability model of binary choices over alternatives characterized by unobserved attributes. We apply the model 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 Classification: H50, D72, H73

Suggested Citation

Heckman, James J. and Snyder, James M., Linear Probability Models of the Demand for Attributes with an Empirical Application to Estimating the Preferences of Legislators. RAND JOURNAL OF ECONOMICS, Vol. 27, No. 0, Special Issue. Available at SSRN: https://ssrn.com/abstract=4681

James J. Heckman (Contact Author)

University of Chicago - Department of Economics ( email )

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James M. Snyder

Massachusetts Institute of Technology (MIT) - Department of Political Science & Department of Economics ( email )

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