TY - JOUR
T1 - Accommodating spatial correlation across choice alternatives in discrete choice models
T2 - An application to modeling residential location choice behavior
AU - Sener, Ipek N.
AU - Pendyala, Ram
AU - Bhat, Chandra R.
N1 - Funding Information:
This research was funded in part by Environmental Protection Agency Grant R831837 . The authors are grateful to Lisa Macias for her help in formatting this document. The authors would like to thank two anonymous reviewers for their suggestions that helped improve the paper.
PY - 2011/3
Y1 - 2011/3
N2 - This paper presents a modeling methodology capable of accounting for spatial correlation across choice alternatives in discrete choice modeling applications. Many location choice (e.g., residential location, workplace location, destination location) modeling contexts involve choice sets where alternatives are spatially correlated with one another due to unobserved factors. In the presence of such spatial correlation, traditional discrete choice modeling methods that are often based on the assumption of independence among choice alternatives are not appropriate. In this paper, a Generalized Spatially Correlated Logit (GSCL) model that allows one to represent the degree of spatial correlation as a function of a multi-dimensional vector of attributes characterizing each pair of location choice alternatives is formulated and presented. The formulation of the GSCL model allows one to accommodate alternative correlation mechanisms rather than pre-imposing restrictive correlation assumptions on the location choice alternatives. The model is applied to the analysis of residential location choice behavior using a sample of households drawn from the 2000 San Francisco Bay Area Travel Survey (BATS) data set. Model estimation results obtained from the GSCL are compared against those obtained using the standard multinomial logit (MNL) model and the spatially correlated logit (SCL) model where only correlations across neighboring (or adjacent) alternatives are accommodated. Model findings suggest that there is significant spatial correlation across alternatives that do not share a common boundary, and that the GSCL offers the ability to more accurately capture spatial location choice behavior.
AB - This paper presents a modeling methodology capable of accounting for spatial correlation across choice alternatives in discrete choice modeling applications. Many location choice (e.g., residential location, workplace location, destination location) modeling contexts involve choice sets where alternatives are spatially correlated with one another due to unobserved factors. In the presence of such spatial correlation, traditional discrete choice modeling methods that are often based on the assumption of independence among choice alternatives are not appropriate. In this paper, a Generalized Spatially Correlated Logit (GSCL) model that allows one to represent the degree of spatial correlation as a function of a multi-dimensional vector of attributes characterizing each pair of location choice alternatives is formulated and presented. The formulation of the GSCL model allows one to accommodate alternative correlation mechanisms rather than pre-imposing restrictive correlation assumptions on the location choice alternatives. The model is applied to the analysis of residential location choice behavior using a sample of households drawn from the 2000 San Francisco Bay Area Travel Survey (BATS) data set. Model estimation results obtained from the GSCL are compared against those obtained using the standard multinomial logit (MNL) model and the spatially correlated logit (SCL) model where only correlations across neighboring (or adjacent) alternatives are accommodated. Model findings suggest that there is significant spatial correlation across alternatives that do not share a common boundary, and that the GSCL offers the ability to more accurately capture spatial location choice behavior.
KW - Activity-travel behavior modeling
KW - Discrete choice modeling
KW - Distance-decay function
KW - Residential location choice
KW - Spatial correlation
KW - Spatially correlated logit model
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U2 - 10.1016/j.jtrangeo.2010.03.013
DO - 10.1016/j.jtrangeo.2010.03.013
M3 - Article
AN - SCOPUS:79953812453
SN - 0966-6923
VL - 19
SP - 294
EP - 303
JO - Journal of Transport Geography
JF - Journal of Transport Geography
IS - 2
ER -