Nonlinear Income Effects in Random Utility Models

Abstract

Random utility models (RUMs) are used in the literature to model consumer choices from among a discrete set of alternatives, and they typically impose a constant marginal utility of income on individual preferences. This assumption is driven partially by the difficulty of constructing welfare estimates in models with nonlinear income effects. Recently, McFadden (1995) developed an algorithm for computing these welfare impacts using a Monte Carlo Markov chain simulator for generalized extreme-value variates. This paper investigates the empirical consequences of nonlinear RUMs in the case of sportfishing modal choice, while refining and contrasting the available methods for welfare estimation. NONLINEAR INCOME EFFECTS IN RANDOM UTILITY MODELSJoseph A. Herriges and Catherine L. Kling* Abstract -Random utility models (RUMs) are used in the literature to model consumer choices from among a discrete set of alternatives, and they typically impose a constant marginal utility of income on individual preferences. This assumption is driven partially by the difficulty of constructing welfare estimates in models with nonlinear income effects. Recently, McFadden (1995) developed an algorithm for computing these welfare impacts using a Monte Carlo Markov chain simulator for generalized extreme-value variates. This paper investigates the empirical consequences of nonlinear RUMs in the case of sportfishing modal choice, while refining and contrasting the available methods for welfare estimation.

Income effects and the welfare consequences of tax in differentiated product oligopoly

“…We present results adopting the latter perspective, based on realized utilities. Like Herriges and Kling (1999) we find in our application that both views yield similar estimates.…”

“…It is well understood that these assumptions are restrictive. They place strong restrictions on income e↵ects, on the curvature of demand, and hence on predictions of pass-through (see, inter alia, McFadden (1999), Herriges and Kling (1999), Weyl and Fabinger (2013) and Fabinger and Weyl (2014)). Nevertheless, it is commonly believed that for small budget share product categories, the assumption of a constant marginal utility of income is a reasonable approximation.…”

“…McFadden (1999) and Herriges and Kling (1999) develop Monte Carlo Markov chain simulation methods that allow for computation of CV in the case of a nested logit model with income e↵ects. More recently Dagsvik and Karlström (2005) have exploited duality results applied to random utility models to characterize the distribution of cv for general random utility models.…”

School Quality, School Cost, and the Public/Private School Choices of Low-Income Households in Pakistan

“…McFadden (1996) has shown that the Small and Rosen derivation only applies for linear-in-income utility, and that nonlinear income requires a laborious bootstrapping methodology. However, Herriges and Kling (1999) have shown that the bias from using the Small and Rosen approximation is small.…”

On the path independence conditions for discrete-continuous demand

“…Recognising this limitation, a number of contributors (e.g. Dagsvik & Karlström, 2005;Hau, 1985;Herriges & Kling, 1999;Jara-Díaz & Videla, 1989, 1990Karlström, 1999;Karlström & Morey, 2001;McFadden, 1995) have explored methods for estimating the Hicksian compensating variation. The attraction of the compensating variation -relative to S&R's measure -is that it elicits a path independent measure of consumer surplus, even when non-linear income effects are present.…”