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

Heckman, James J.; Snyder, James M.

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

NBER Working Paper No. w5785

73 Pages Posted: 4 Feb 1997 Last revised: 24 Apr 2022

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

There are 2 versions of this paper

Date Written: October 1996

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

Suggested Citation: 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 (October 1996). NBER Working Paper No. w5785, Available at SSRN: https://ssrn.com/abstract=4607