Back to results

Massachusetts Institute of Technology

Endogeneity and Sampling of Alternatives in Spatial Choice Models

Abstract

dc:description.abstract

Addressing the problem of omitted attributes and employing a sampling of alternatives strategy, are two key requirements of practical spatial choice models. The omission of attributes causes endogeneity when the unobserved variables are correlated with the measured variables, precluding the consistent estimation of the model parameters. The consistent estimation while sampling alternatives in non-Logit models has been an open problem for three decades. This dissertation is concerned with both the endogeneity and the sampling of alternatives in non-Logit models, two problems that have hindered the development of suitable modeling tools for urban policy analysis, but have been neglected in spatial choice modeling. For the problem of endogeneity, this research applies, enhances, adapts, and develops efficient and tractable methods to correct and test for it in models of residential location choice, and also develops novel methods to validate the success of the correction. For the problem of sampling of alternatives in non-Logit models, this study develops and demonstrates a novel method to achieve consistency, relative efficiency, and asymptotic normality when the underlying model belongs to the Multivariate Extreme Value class. This development allows for the estimation of spatial choice models with more realistic error structures. Monte Carlo experiments and real data from Lisbon, Portugal, are employed to illustrate the significant benefits of these novel methods in correcting for endogeneity and addressing sampling of alternatives in non-Logit models, with specific reference to urban policy analysis.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Dept. of Civil and Environmental Engineering.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2010

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Guevara-Cue, Cristián Angelo
Advisor dc:contributor.advisor
  • Moshe E. Ben-Akiva.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/62098
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/62098

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Guevara-Cue, Cristián Angelo. Endogeneity and Sampling of Alternatives in Spatial Choice Models. Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/62098