Nonlinear Income Effects in Random Utility Models
Joseph Herriges and
Catherine Kling
The Review of Economics and Statistics, 1999, vol. 81, issue 1, 62-72
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. © 1999 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology
Date: 1999
References: Add references at CitEc
Citations: View citations in EconPapers (76)
Downloads: (external link)
http://www.mitpressjournals.org/doi/pdf/10.1162/003465399767923827 (application/pdf)
Access to full text is restricted to subscribers.
Related works:
Working Paper: Nonlinear Income Effects in Random Utility Models (1999)
Working Paper: Nonlinear Income Effects in Random Utility Models (1999) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:tpr:restat:v:81:y:1999:i:1:p:62-72
Ordering information: This journal article can be ordered from
https://mitpressjour ... rnal/?issn=0034-6535
Access Statistics for this article
The Review of Economics and Statistics is currently edited by Pierre Azoulay, Olivier Coibion, Will Dobbie, Raymond Fisman, Benjamin R. Handel, Brian A. Jacob, Kareen Rozen, Xiaoxia Shi, Tavneet Suri and Yi Xu
More articles in The Review of Economics and Statistics from MIT Press
Bibliographic data for series maintained by The MIT Press ().