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.

中文翻译：

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随着价格上涨，住宅和位置选择集形成的演变：大多伦多地区的十年面板分析

家庭位置的选择基于住宅的特征（例如，大小、风格、卧室数量）和位置（例如，靠近工作地点、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如何影响家庭考虑的住宅类型和位置。使用大多伦多地区 2006 年和 2016 年的大量房地产清单样本来开发经验模型。研究中使用了两个最近开发的离散选择模型：具有潜在类反馈 (LCF) 的嵌套 logit 模型和半补偿性独立可用性 logit (SCIAL) 模型。提出了一种替代聚合方法来克服经常阻碍选择集模型估计的计算障碍。我们发现，在 2006 年至 2016 年期间，较大家庭考虑联排别墅和公寓的概率显着高于独立的单户住宅。