Dr. Hajime Watanabe

University of Tokyo

July 27, 2022, 11:00GC B1 10

Describing unobserved residential location choice and travel behavior dependency as a missing data mechanism: A Bayesian sample selection model with multinomial endogenous switching

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.