房价上涨对居住和区位选择集形成的影响:大多伦多地区的十年面板分析

IF 1.6 4区 工程技术 Q4 TRANSPORTATION Journal of Transport and Land Use Pub Date : 2021-11-21 DOI:10.5198/jtlu.2021.1854
Jason Hawkins, Khandker Nurul Habib
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引用次数: 0

摘要

住宅位置的选择是基于住宅的特征(例如,大小,风格,卧室数量)和位置(例如,靠近工作,学校质量,可达性)。近年来,许多大城市的房价急剧上涨。在这项研究中,我们研究了这些价格上涨是如何影响家庭考虑的住宅类型和地点的。本文以2006年和2016年大多伦多地区的房地产上市为样本,建立了实证模型。本研究采用了两种新近发展的离散选择模型:具有潜在类反馈(LCF)的嵌套logit模型和半补偿独立可用性logit模型。为了克服选择集模型估计的计算障碍,提出了一种替代聚合方法。我们发现,在2006年至2016年期间,考虑到联排别墅和公寓,大型家庭的可能性比独立的单户住宅显著增加。
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The evolution of choice set formation in dwelling and location with rising prices: A decadal panel analysis in the Greater Toronto Area
Home location choice is based on both the characteristics of the dwelling (e.g., size, style, number of bedrooms) and the location (e.g., proximity to work, quality of schools, accessibility). Recent years have seen a steep increase in the price of housing in many major cities. In this research, we examine how these price increases are affecting the types of dwelling and locations considered by households. A large sample of real estate listings from 2006 and 2016 from the Greater Toronto Area is used to develop the empirical models. Two recently developed discrete choice models are used in the study: a nested logit model with latent class feedback (LCF) and a semi-compensatory independent availability logit (SCIAL) model. A method of alternative aggregation is proposed to overcome the computational hurdle that often impedes the estimation of choice set models. We find a significant increase in the probability of larger households considering townhouses and apartments over detached single-family dwellings between 2006 and 2016.
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来源期刊
CiteScore
3.40
自引率
5.30%
发文量
34
审稿时长
30 weeks
期刊介绍: The Journal of Transport and Land Usepublishes original interdisciplinary papers on the interaction of transport and land use. Domains include: engineering, planning, modeling, behavior, economics, geography, regional science, sociology, architecture and design, network science, and complex systems. Papers reporting innovative methodologies, original data, and new empirical findings are especially encouraged.
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