Special Issue "Discrete Choice Modeling"

A special issue of Econometrics (ISSN 2225-1146).

Deadline for manuscript submissions: closed (31 May 2016).

Special Issue Editor

William Greene
E-Mail Website
Guest Editor
NYU Stern School of Business, Department of Economics, Henry Kaufman Management Center, 44 West 4 St., New York, NY 10012, USA
Interests: Applied Econometrics, Health Economics, Transport, Production/Efficiency/Productivity, Choice Modeling, Entertainment and Media, Numerical Analysis and Computation

Special Issue Information

Dear Colleagues,

The focus of the Special Issue will be on theory and applications for models of discrete outcome variables, such as choice among unordered alternatives (e.g., brand choice), ordered alternatives (such as survey data), binary choice, and combinations of any or all of these. We are interested in both theoretical development of estimation and analysis platforms, hypothesis testing, inference methods, etc., and applications of the techniques of discrete choice modeling in observed settings, such as health and retirement, labor markets, travel choice, environmental economics, and market equilibrium.

The aim of the Special Issue is to contribute to the very large and still emerging literature on models and methods for analyzing individual choices. The availability of many rich public data sets, such as NLS, GSOEP, HILDA and BHPS has provided researchers with excellent opportunities for the pursuits suggested for this Special Issue.

Prof. Dr. William Greene
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Econometrics is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Discrete Choice
  • Econometrics
  • Choice Experiment
  • Panel Data
  • Ordered Choice
  • Binary Choice
  • Dynamic Models
  • Multinomial Choice

Published Papers (3 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Article
Social Networks and Choice Set Formation in Discrete Choice Models
Econometrics 2016, 4(4), 42; https://doi.org/10.3390/econometrics4040042 - 27 Oct 2016
Cited by 9 | Viewed by 4790
Abstract
The discrete choice literature has evolved from the analysis of a choice of a single item from a fixed choice set to the incorporation of a vast array of more complex representations of preferences and choice set formation processes into choice models. Modern [...] Read more.
The discrete choice literature has evolved from the analysis of a choice of a single item from a fixed choice set to the incorporation of a vast array of more complex representations of preferences and choice set formation processes into choice models. Modern discrete choice models include rich specifications of heterogeneity, multi-stage processing for choice set determination, dynamics, and other elements. However, discrete choice models still largely represent socially isolated choice processes —individuals are not affected by the preferences of choices of other individuals. There is a developing literature on the impact of social networks on preferences or the utility function in a random utility model but little examination of such processes for choice set formation. There is also emerging evidence in the marketplace of the influence of friends on choice sets and choices. In this paper we develop discrete choice models that incorporate formal social network structures into the choice set formation process in a two-stage random utility framework. We assess models where peers may affect not only the alternatives that individuals consider or include in their choice sets, but also consumption choices. We explore the properties of our models and evaluate the extent of “errors” in assessment of preferences, economic welfare measures and market shares if network effects are present, but are not accounted for in the econometric model. Our results shed light on the importance of the evaluation of peer or network effects on inclusion/exclusion of alternatives in a random utility choice framework. Full article
(This article belongs to the Special Issue Discrete Choice Modeling)
Show Figures

Figure 1

Article
Removing Specification Errors from the Usual Formulation of Binary Choice Models
Econometrics 2016, 4(2), 26; https://doi.org/10.3390/econometrics4020026 - 03 Jun 2016
Cited by 2 | Viewed by 3890
Abstract
We develop a procedure for removing four major specification errors from the usual formulation of binary choice models. The model that results from this procedure is different from the conventional probit and logit models. This difference arises as a direct consequence of our [...] Read more.
We develop a procedure for removing four major specification errors from the usual formulation of binary choice models. The model that results from this procedure is different from the conventional probit and logit models. This difference arises as a direct consequence of our relaxation of the usual assumption that omitted regressors constituting the error term of a latent linear regression model do not introduce omitted regressor biases into the coefficients of the included regressors. Full article
(This article belongs to the Special Issue Discrete Choice Modeling)
Show Figures

Figure 1

Article
Multiple Discrete Endogenous Variables in Weakly-Separable Triangular Models
Econometrics 2016, 4(1), 7; https://doi.org/10.3390/econometrics4010007 - 04 Feb 2016
Cited by 3 | Viewed by 3560
Abstract
We consider a model in which an outcome depends on two discrete treatment variables, where one treatment is given before the other. We formulate a three-equation triangular system with weak separability conditions. Without assuming assignment is random, we establish the identification of an [...] Read more.
We consider a model in which an outcome depends on two discrete treatment variables, where one treatment is given before the other. We formulate a three-equation triangular system with weak separability conditions. Without assuming assignment is random, we establish the identification of an average structural function using two-step matching. We also consider decomposing the effect of the first treatment into direct and indirect effects, which are shown to be identified by the proposed methodology. We allow for both of the treatment variables to be non-binary and do not appeal to an identification-at-infinity argument. Full article
(This article belongs to the Special Issue Discrete Choice Modeling)
Show Figures

Figure 1

Back to TopTop