University of Tokyo
July 27, 2022, 11:00GC B1 10
The sample selection modeling approach has been applied to describe unobserved dependency between residential location choice and travel behavior due to residential self-selection. Sample selection models describe a missing data mechanism in which expected travel behavior outcomes in residential locations are incidentally truncated by actual residential location choice, referred to as endogenous switching. A limitation of existing sample selection models in the literature is to assume a simple binary endogenous switching that describes people�s residential choices by a binary choice, e.g., choosing between urban or suburban residential areas. This study proposes a general sample selection modeling framework with a multinomial endogenous switching. The proposed model has a large-scale open-form structure, and this study thus employs an efficient Markov chain Monte Carlo algorithm according to the model structure for the parameter estimation. The proposed model can be a useful tool for providing insights into coordination between land use and transportation planning.
Hajime Watanabe received a Ph.D. in engineering from Kumamoto University, Japan, in March 2022, with a thesis on �Bayesian approaches for handling and identifying endogeneity in discrete choice modeling.� He is currently a Japan Society for the Promotion of Science (JSPS) Research Fellow at the University of Tokyo and working with Prof. Eiji Hato. His research interests include activity-travel behavior analysis using discrete choice modeling, causal inference, and machine learning.