Efficiency Gains in Rank‐ordered Multinomial Logit Models
| Published date | 01 February 2018 |
| Date | 01 February 2018 |
| DOI | http://doi.org/10.1111/obes.12190 |
122
©2017 The Department of Economics, University of Oxford and JohnWiley & Sons Ltd.
OXFORD BULLETIN OF ECONOMICSAND STATISTICS, 80, 1 (2018) 0305–9049
doi: 10.1111/obes.12190
Efficiency Gains in Rank-ordered Multinomial Logit
Models*
Arie Beresteanu and Federico Zincenko
Department of Economics, University of Pittsburgh (e-mail: arie@pitt.edu, zincenko@pitt.
edu)
Abstract
This paper considers estimation of discrete choice models when agents report their ranking
of the alternatives (or some of them) rather than just the utility maximizing alternative. We
investigate the parametric conditional rank-ordered Logit model. We show that conditions
for identification do not change even if we observe ranking. Moreover, we fill a gap in the
literature and show analytically and by Monte Carlo simulations that efficiency increases
as we use additional information on the ranking.
I. Introduction
The conditional Logit model (McFadden, 1974) is a widely used estimator for demand
estimation in discrete choice models. Typical data sets include the final choice made by
decision makers as well as the observed characteristics of the alternatives they faced. The
unobserved characteristic of each alternative is assumed to have a type one extreme value
distribution independent across alternatives and individuals. In some situations, however,
decision makers report their ranking of whole or part of the alternative set. This paper
explores the implications of observing more than just the maximal choice on estimation
of preferences parameters in the conditional Logit model.
Cases where decision makers report a ranking of several alternatives exist mostly in
survey data. For example,in optimal assignment problems it is common to ask respondents
to rank their top choices among the set of alternatives from which they can choose. A case
that received a lot of attention in the past is assigning medical school graduates to hospitals
for internship. This two-sided market and the mechanism design approach taken to make
it optimal is described in Roth and Peranson (1999). Another example that received much
attention is the literature on school choices by students and parents. The most famous
examples are the Boston and NYC public school systems where individuals are asked to
report their top two or three choices among the alternatives that they are facing.
Beggs, Cardell and Hausman (1981) analyse surveys on consumers demand for electric
cars. They note that while survey data is usually inferior to real life transactions, surveys
JEL Classification numbers: C25.
*Weare grateful to JF Richards for useful comments and detailed discussions. We thanks the seminar participants
at Vanderbilt, 10th GNYMA Econometrics Colloquium (Princeton), and 2015 Pittsburgh Economics Medley.
To continue reading
Request your trial