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Orvin, Muntahith Mehadil

University of British Columbia

This thesis microsimulates residential relocation decisions within an integrated urban model – i.e., STELARS. STELARS is an agent-based (i.e., individuals and households) model, which simulates land use, transportation, and energy-related decisions of each agent for a region. This thesis focuses on the residential relocation module, conceptualizing it as a four-stage decision-making process of: i) decision to move (mobility), ii) location search, iii) housing price, and iv) location choice. Advanced econometric and machine learning-based models are developed to represent the behavioural dynamics of residential relocation decisions. For example, a joint model is developed to capture the inter-dependency of mobility and location choice decisions. In the case of mobility, a competing hazard-based model is formulated to capture continuous time dynamics of stay duration at a location. For location choice, a latent segmentation-based logit model is developed that accommodates unobserved heterogeneity and correlated sequence of repeated choices occurring over the life-time of households. To examine the effects of location choice on mobility, logsum parameters are estimated from the location choice model and fed as an exogenous input into the mobility model. Location search and price components are developed using Gaussian Mixture and latent segmentation-based autoregressive models, respectively. These behavioural models are methodologically consistent with the simulation technique of STELARS. For example, STELARS adopts an event-based hybrid of continuous and discrete time microsimulation technique. In the case of event-based approach, for example, mobility decisions are conceptualized to be triggered by events such as childbirth, which is established through empirical evidence. In the case of hybrid simulation, mobility is simulated as a continuous time decision using a hazard-based model. Subsequent decisions involving location search, housing price, and location choice are simulated at discrete time-steps. STELARS is implemented for the entire population of Okanagan region from 2011-2021. This research also tests the housing market for COVID-19 pandemic. To incorporate the behavioural change of housing market during pandemic, separate price models for pre-pandemic and pandemic periods are estimated and implemented. This thesis performs a multi-year validation exercise, and presents a spatio-temporal analysis of predicted housing prices and location choices for different socio-demographic groups before and during pandemic.

Text

2023-12-14

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/86947

Civil Engineering

University of British Columbia

UBCO

http://creativecommons.org/licenses/by-nc-nd/4.0/