Richard Spady

We propose dual regression as an alternative to the quantile regression process for the global estimation of conditional distribution functions under minimal assumptions.

We propose simultaneous mean-variance regression for the linear estimation and approximation of conditional mean functions.

We propose an alternative ('dual regression') to the quantile regression process for the global estimation of conditional distribution functions under minimal assumptions.

We propose an alternative (“dual regression”) to the quantile regression process for the global estimation of conditional distribution functions under minimal assumptions.

This paper formalizes conditions under which a population distribution ofcategorical responses to attitudinal questions (items) has a scale representation; developstests for whether a particular sample of item responses is consistent with a scale representation; develops methods for nonparametrically estimating the relation between an outcome and a scale value; and generalizes the foregoing to the multi-scale case.

new methodology that estimates attitudes semiparametrically and estimates actions nonparametrically, as a function of the resulting attitudinal measures, is used to examine the behavioral effects of cultural and economic preferences in the Presidential elections of 1984 and 1992.