利用享乐主义模型评估印度城市贫民的住房负担能力和住房需求

IF 1.5 Q3 URBAN STUDIES
P. Rao, Arindam Biswas
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引用次数: 0

摘要

目的 本研究旨在以印度勒克瑙市为背景,使用享乐回归模型评估住房负担能力并估算需求。本研究通过考虑各种住房和家庭相关变量来评估住房负担能力。本研究的重点是城市贫困人口,因为他们的住房短缺情况最为严重。本研究的主要目的是全面了解市场的需求动态。对住房需求的理解可以通过对其特征和构成要素的研究来实现。个人在决定购买或租住房屋时,会考虑与各组成部分相关的隐含价值。这些组成部分和特征是从与住房和家庭有关的变量中获得的。 设计/方法/途径 对勒克瑙市贫民窟的 450 个家庭进行了社会经济调查。为本研究论文建立了两阶段回归模型。第一个模型编制了一个享乐主义价格指数,以了解住房支出与各种住房特征之间的关系。享乐主义模型所考虑的住房特征包括住房单元面积、类型、条件、便利设施和基础设施。在第二阶段,建立家庭特征之间的回归模型。需求估算模型中考虑的家庭特征包括家庭规模、年龄、教育程度、社会类别、收入、非住房支出、迁移和拥挤程度。 研究结果 根据回归模型的结果,显而易见,享乐主义模型是估算城市贫民住房负担能力和住房需求的有效工具。各种与住房和家庭相关的变量都会对住房支出产生积极或消极的影响。两阶段享乐回归模型可以确定特定家庭对一套具有各种属性的住房的支付意愿。结果显示,居住单元的大小、质量和设施(R2 > 0.9,P < 0.05)对租金/估算租金具有重要影响。需求函数表明,收入具有直接影响,而其他变量则具有混合影响。 研究局限性/启示 本研究针对具体案例,使用的数据集来自一次初级调查。虽然针对大样本量的住户调查是一项资源密集型工作,但它为利用微观数据更好地了解贫民窟复杂的住房状况提供了机会。 实际意义 所有利益相关者都可以利用调查结果制定有效的住房政策。应考虑那些在统计上有意义且与住房成本有正相关关系的变量,以便为城市贫民提供基本的生活标准。在制定政策时,应适当考虑居住在贫民窟地区的经济弱势群体的住房偏好。 独创性/价值 本文使用原始调查数据(由作者收集)来评估勒克瑙市城市贫民的住房负担能力。这使研究结果具有可信度,并有助于进一步应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Housing affordability and housing demand assessment for urban poor in India using the hedonic model
Purpose This study aims to assess housing affordability and estimate demand using a hedonic regression model in the context of Lucknow city, India. This study assesses housing affordability by considering various housing and household-related variables. This study focuses on the impoverished urban population, as they experience the most severe housing scarcity. This study’s primary objective is to understand the demand dynamics within the market comprehensively. An understanding of housing demand can be achieved through an examination of its characteristics and components. Individuals consider the implicit values associated with various components when deciding to purchase or rent a home. The components and characteristics have been obtained from variables relating to housing and households. Design/methodology/approach A socioeconomic survey was conducted for 450 households from slums in Lucknow city. Two-stage regression models were developed for this research paper. A hedonic price index was prepared for the first model to understand the relationship between housing expenditure and various housing characteristics. The housing characteristics considered for the hedonic model are dwelling unit size, typology, condition, amenities and infrastructure. In the second stage, a regression model is created between household characteristics. The household characteristics considered for the demand estimation model are household size, age, education, social category, income, nonhousing expenditure, migration and overcrowding. Findings Based on the findings of regression model results, it is evident that the hedonic model is an effective tool for the estimation of housing affordability and housing demand for urban poor. Various housing and household-related variables affect housing expenditure positively or negatively. The two-stage hedonic regression model can define willingness to pay for a particular set of housing with various attributes of a particular household. The results show the significance of dwelling unit size, quality and amenities (R2 > 0.9, p < 0.05) for rent/imputed rent. The demand function shows that income has a direct effect, whereas other variables have mixed effects. Research limitations/implications This study is case-specific and uses a data set generated from a primary survey. Although household surveys for a large sample size are resource-intensive exercises, they provide an opportunity to exploit microdata for a better understanding of the complex housing situation in slums. Practical implications All the stakeholders can use the findings to create an effective housing policy. The variables that are statistically significant and have a positive relationship with housing costs should be deliberated upon to provide the basic standard of living for the urban poor. The formulation of policies should duly include the housing preferences of the economically disadvantaged population residing in slum areas. Originality/value This paper uses primary survey data (collected by the authors) to assess housing affordability for the urban poor of Lucknow city. It makes the results of the study credible and useful for further applications.
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CiteScore
2.80
自引率
29.40%
发文量
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