Housing Affordability in Metropolitan Areas. The Application of a Combination of the Ratio Income and Residual Income Approaches to Two Case Studies in Sicily, Italy

Napoli, Grazia

doi:10.3390/buildings7040095

Cited by 26 publications

(15 citation statements)

References 31 publications

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“…Prominent among the factors, according to PCA based on respondent's opinion, include: House price in relation to income (ESF01), and Rental cost in relation to income (ESF04) taking the 1st and 2nd position as the most severe factors. This finding is not surprising, given that studies have demonstrated that housing cost and its relation to income has been typically used to measure and define housing affordability situations [49,[83][84][85]; and that this ratio technique appeal to peoples' common sense experience [10]. This finding is congruent with Ghazali, et al [51] study, which noted that as many households are confronted with financial difficulties in making residential choices, housing cost remains a key factor that influences housing location decisions.…”

Section: Discussionmentioning

confidence: 93%

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Exploring the Severity of Factors Influencing Sustainable Affordable Housing Choice: Evidence from Abuja, Nigeria

Ezennia

Hoskara

2019

Sustainability

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It is a shared global experience that a house which is already expensive will become even more costly. This experience is partly because housing supply has always failed to satisfy demand. In many developing countries, the issues of affordable housing supply center on shortage and poor distribution. Recent studies on this subject reveal that distribution-related problems can be addressed through choice reconciliations. Therefore, understanding how housing affordability problems affect housing choice enables a broader interpretation of the issue. Thus, critical in housing policy making and implementation, as well as towards sustainable development/delivery of affordable housing programs. In Nigeria, housing choice has never been investigated, neither has it been studied within the framework of sustainability. It is not a common strategy to incorporate sustainability into the concept of affordable housing choice. However, integrating sustainability into the concept of affordable housing choice allows for the introduction of wide-ranging and broader criteria such as environmental and social factors, which are routinely neglected in housing choice literature. Therefore, this study aims at filling this literature gap by identifying the determinants of sustainable affordable housing choice (SAHC) in the study area. The purpose is to establish the severity of the identified factors based on respondents’ perception and discuss the agreement levels amongst the three respondent groups. Regarding this, a comprehensive list of 43 different factors contributing to SAHC were determined through a systematic literature review. Based on which a survey of 83 affordable housing applicants, 102 and 69 residents of affordable housing estate and shantytown respectively, was performed. Through statistical analysis, results reveal that the factors affecting SAHC cuts across economic, social and environmental dimensions. Also, there is an agreement (correlation) by each group and the overall ranking of all participants. The tests confidence level for all inferential statistics was 95%, which implies 0.05 level of significance. These figures indicate that the data were obtained from the same population and points to the relatedness of factors identified. Using principal component analysis (PCA), the 43 different factors were narrowed down to seven. The study findings show that “Housing price in relation to income” and “rental price in relation to income” are the most severe factors with relatively high overall scoring, which is consistent with similar studies in this domain. However, it was uncovered that respondents placed high priorities on other non-economic factors like security (safety), housing location and building type. The study presents an interesting topic, usually unexplored in the field of decisions and public policy. It argues that at present, the housing affordability concerns and affordable housing choice determinants in the study area cannot be restrictedly defined in economic terms. Our findings build on previous studies and reiterate the need to consider a broader view towards affordable housing problem. It offers salient information to stakeholders and real estate companies, which could aid sustainable development/delivery of housing projects that are affordable.

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Section: Discussionmentioning

confidence: 93%

“…The law of demand states that as the price of the goods/services increases, the consumption rate falls [49]. Thus, choice determines price rather than preference [46,47,50].…”

Section: Distinction Between the Housing Choice And Housing Preferencementioning

confidence: 99%

Exploring the Severity of Factors Influencing Sustainable Affordable Housing Choice: Evidence from Abuja, Nigeria

Ezennia

Hoskara

2019

Sustainability

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“…The LAI is not the only attempt to calculate multiple affordability measures, the socalled composite measures that, given the increasing urban nature of unaffordability problems, have mainly been developed in the twenty-first century (Bogdon & Can, 1997;Bramley, 2012;Gan & Hill, 2009;Li, 2014;Napoli, 2017;Tang, 2012). Multiple measures highlight different dimensions of affordability recognizing that the multiple dimensions of affordability need multiple measurements; i.e.…”

Section: Measurement Of Multiple Dimensions Of Urban Housing Affordabmentioning

confidence: 99%

A fresh look at contemporary perspectives on urban housing affordability

Haffner

Hulse

2019

International Journal of Urban Sciences

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The literature on housing affordability has grown rapidly since Hulchanski [1995, p. 489. The concept of housing affordability: six contemporary uses of the housing expenditure-to-income ratio. Housing Studies, 10(4), 471-491] declared that housing researchers should avoid using the term since it is not a robust concept and measurement often lacks validity. In the ensuing 24 years, however, scholars have continued to debate the definition and measurement of housing affordability as well as the prevalence and type of 'housing affordability problems' in various countries. This paper is a think piece which takes a fresh look at housing affordability as a concept which has persisted despite considerable contestation and scepticism about its use. It provides a critical and multidisciplinary assessment of housing affordability starting with early conceptualization of the nexus between economic principles and social norms about housing and living standards to a reworking of housing affordability in the twenty-first century as an urban issue affecting lower and middle-income households in cities, as a consequence of the financialization of housing and urban restructuring. It argues that the housing affordability concept has been repurposed such that the focus is less on understanding housing expenditures in contributing to poverty and disadvantage within the domain of social policy and more on the urban policy challenges of growing inequities in access to urban resources. The paper highlights the challenges for urban policy in adopting and adapting rather than rejecting a multidimensional concept of housing affordability and consequently the importance of new ways of measuring urban housing affordability.

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“…As detailed above, also considering the opacity of Italian real estate markets conditions [68,69], the small real estate sample used in this work should not prejudice the operational usability of statistical techniques.…”

Section: Data Descriptionmentioning

confidence: 99%

Real Estate Appraisals with Bayesian Approach and Markov Chain Hybrid Monte Carlo Method: An Application to a Central Urban Area of Naples

et al. 2017

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Abstract:This paper experiments an artificial neural networks model with Bayesian approach on a small real estate sample. The output distribution has been calculated operating a numerical integration on the weights space with the Markov Chain Hybrid Monte Carlo Method (MCHMCM). On the same real estate sample, MCHMCM has been compared with a neural networks model (NNs), traditional multiple regression analysis (MRA) and the Penalized Spline Semiparametric Method (PSSM). All four methods have been developed for testing the forecasting capacity and reliability of MCHMCM in the real estate field. The Markov Chain Hybrid Monte Carlo Method has proved to be the best model with an absolute average percentage error of 6.61%.

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Housing Affordability in Metropolitan Areas. The Application of a Combination of the Ratio Income and Residual Income Approaches to Two Case Studies in Sicily, Italy

Cited by 26 publications

References 31 publications

Exploring the Severity of Factors Influencing Sustainable Affordable Housing Choice: Evidence from Abuja, Nigeria

Exploring the Severity of Factors Influencing Sustainable Affordable Housing Choice: Evidence from Abuja, Nigeria

A fresh look at contemporary perspectives on urban housing affordability

Real Estate Appraisals with Bayesian Approach and Markov Chain Hybrid Monte Carlo Method: An Application to a Central Urban Area of Naples

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