Back to Vocabulary

Affordability

Area: Design, planning and building

Affordability is defined as the state of being cheap enough for people to be able to buy (Combley, 2011). Applied to housing, affordability, housing unaffordability and the mounting housing affordability crisis, are concepts that have come to the fore, especially in the contexts of free-market economies and housing systems led by private initiatives, due to the spiralling house prices that residents of major urban agglomerations across the world have experienced in recent years (Galster & Ok Lee, 2021). Notwithstanding, the seeming simplicity of the concept, the definition of housing affordability can vary depending on the context and approach to the issue, rendering its applicability in practice difficult. Likewise, its measurement implies a multidimensional and multi-disciplinary lens (Haffner & Hulse, 2021).

One definition widely referred to of housing affordability is the one provided by Maclennan and Williams (1990, p.9): “‘Affordability’ is concerned with securing some given standard of housing (or different standards) at a price or a rent which does not impose, in the eyes of some third party (usually government) an unreasonable burden on household incomes”. Hence, the maximum expenditure a household should pay for housing is no more than 30% of its income (Paris, 2006). Otherwise, housing is deemed unaffordable. This measure of affordability reduces a complex issue to a simple calculation of the rent-to-income ratio or house-price-to-income ratio. In reality, a plethora of variables can affect affordability and should be considered when assessing it holistically, especially when judging what is acceptable or not in the context of specific individual and societal norms (see Haffner & Hulse, 2021; Hancock, 1993). Other approaches to measure housing affordability consider how much ‘non-housing’ expenditures are unattended after paying for housing. Whether this residual income is not sufficient to adequately cover other household’s needs, then there is an affordability problem (Stone, 2006). These approaches also distinguish between “purchase affordability” (the ability to borrow funds to purchase a house) and “repayment affordability” (the ability to afford housing finance repayments) (Bieri, 2014).

Furthermore, housing production and, ultimately affordability, rely upon demand and supply factors that affect both the developers and home buyers. On the supply side, aspects such as the cost of land, high construction costs, stiff land-use regulations, and zoning codes have a crucial role in determining the ultimate price of housing (Paris, 2006). Likewise, on the policy side, insufficient government subsidies and lengthy approval processes may deter smaller developers from embarking on new projects. On the other hand, the demand for affordable housing keeps increasing alongside the prices, which remain high, as a consequence of the, sometimes deliberate incapacity of the construction sector to meet the consumers' needs (Halligan, 2021). Similarly, the difficulty of decreasing household expenditures while increasing incomes exacerbates the unaffordability of housing (Anacker, 2019). In the end, as more recent scholarship has pointed out (see Haffner & Hulse, 2021; Mulliner & Maliene, 2014), the issue of housing affordability has complex implications that go beyond the purely economic or financial ones. The authors argue that it has a direct impact on the quality of life and well-being of the affected and their relationship with the city, and thus, it requires a multidimensional assessment. Urban and spatial inequalities in the access to city services and resources, gentrification, segregation, fuel and commuting poverty, and suburbanisation are amongst its most notorious consequences.

Brysch and Czischke, for example, found through a comparative analysis of 16 collaborative housing projects in Europe that affordability was increased by “strategic design decisions and self-organised activities aiming to reduce building costs” (2021, p.18). This demonstrates that there is a great potential for design and urban planning tools and mechanisms to contribute to the generation of innovative solutions to enable housing affordability considering all the dimensions involved, i.e., spatial, urban, social and economic. Examples range from public-private partnerships, new materials and building techniques, alternative housing schemes and tenure models (e.g., cohousing, housing cooperatives, Community Land Trusts, ‘Baugruppen’), to efficient interior design, (e.g., flexible design, design by layers[1]). Considering affordability from a design point of view can activate different levers to catalyse and bring forward housing solutions for cities; and stakeholders such as socially engaged real estate developers, policymakers, and municipal authorities have a decisive stake in creating an adequate environment for fostering, producing and delivering sustainable and affordable housing.

 

[1] (see Brand, 1995; Schneider & Till, 2007)

References

Anacker, K. B. (2019). Introduction: housing affordability and affordable housing. International Journal of Housing Policy, 19(1), 1–16. https://doi.org/10.1080/19491247.2018.1560544

Bieri, D.S. (2014). Housing Affordability. Encyclopedia of Quality of Life and Well-Being Research, pp.2971–2975.

Brand, S. (1995). How buildings learn: What happens after they’re built. Penguin.

Brysch, S. L., & Czischke, D. (2021). Affordability through design: the role of building costs in collaborative housing. Housing Studies. https://doi.org/10.1080/02673037.2021.2009778

Galster, G., & Ok Lee, K. (2021). Introduction to the special issue of the Global crisis in housing affordability. International Journal of Urban Sciences, 25(S1), 1–6. https://doi.org/10.1080/12265934.2020.1847433

Habitat for Humanity. (2019). What is housing affordability? [online] Available at: https://www.habitat.org/costofhome/what-is-housing-affordability [Accessed 14 Jul. 2021].

Haffner, M. E. A., & Hulse, K. (2021). A fresh look at contemporary perspectives on urban housing affordability. International Journal of Urban Sciences, 25(S1), 59–79. https://doi.org/10.1080/12265934.2019.1687320

Halligan, L. (2021). Home Truths: The UK’s chronic housing shortage – how it happened, why it matters and the way to solve it. Biteback Publishing.

Hancock, K. E. (1993). “Can Pay? Won’t Pay?” or Economic Principles of “Affordability.” Urban Studies, 30(1), 127–145. http://www.jstor.org/stable/43195877

Maclennan, D., & Williams, R. (1990). Affordable housing in Britain and the United States. York: Joseph Rowntree Foundation.

Mulliner, E., & Maliene, V. (2015). An Analysis of Professional Perceptions of Criteria  Contributing to Sustainable Housing Affordability. Sustainability, 7(1), 248–270. https://doi.org/10.3390/SU7010248

Paris, C. (2006). International Perspectives on Planning and Affordable Housing. Housing Studies, 22(1), 1–9. https://doi.org/10.1080/02673030601024531

Schneider, T., & Till, J. (2007). Flexible housing. Architectural press.

Sidewalk Labs, 2019. 6: Affordability by Design. [podcast] City of the Future. Available at: https://cityofthefuture.libsyn.com/6-affordability-by-design [Accessed 14 July 2021].

Stone, M. E. (2006). A Housing Affordability Standard for the UK. Housing Studies, 21(4), 453–476. https://doi.org/10.1080/02673030600708886

Created on 03-06-2022 | Update on 19-07-2023

Related definitions

Mass Customisation

Author: C.Martín (ESR14)

Area: Design, planning and building

Mass customisation (MC) is a process by which a company approaches its production in a customer-centric manner, developing products and services according to the needs and requirements of each individual customer, while keeping costs near to mass production (Piller, 2004). MC establishes a new relationship between producers and customers which becomes crucial in product development  (Khalili-Araghi & Kolarevic, 2016). Alvin Toffler (1970, 1980) was the first to refer to the MC concept in his books “Future shock”  and “The third wave”. Stanley Davis (1987) later cemented the term in his book “Future Perfect”. But it was not until 1993, when Joseph Pine  developed its practical application to business, that the concept started gaining greater importance in research and practice (Pine, 1993; Brandão et al., 2017; Piller et al., 2005). Nowadays, MC is understood as a multidimensional process embracing a combination of mass production, user-driven technologies, big data, e-commerce and e-business, digital design, and manufacturing technologies (Brandão et al., 2017). In the last twenty years, almost every sector of the economy, from industrial production to consumer products and services, has been influenced by mass customisation. The difference between mass customisation and massive customisation is the ability to relate the contextual features to the product features. This means that a random generation of design alternatives would not be sufficient; these alternatives should be derived from the cultural, technological, environmental and social context, as well as from the individual context of the user (Kolarevic & Duarte, 2019). As a business paradigm,  MC provides an attractive added value by addressing customer needs while using resources efficiently and avoiding an increase in operational costs (Piller & Tseng, 2009). It seeks to incorporate customer co-design processes into the innovation and strategic planning of the business, approaching economies of integration (Piller et al., 2005). As a result, the profitability of MC is achieved through product variety in volume-related economies (Baranauskas et al., 2020; Duray et al., 2000). The space in which it is possible to meet a variety of needs through a mass customisation offering is finite (Piller, 2004). This solution space represents the variety of different customisation units and encompasses the rules to combine them, limiting the set of possibilities in the search of a balance between productivity and flexibility (Salvador et al., 2009). The designer’s responsibility would be to meet the heterogeneities of the users in an efficient way, by setting a solution space and defining the degrees of freedom for the customer within a manufacturer’s production system (Hippel, 2001). Therefore, an important challenge for a company that aims at becoming a mass customizer is to find the right balance between what is determined by the designer and what is left for the user to decide (Kolarevic & Duarte, 2019). Value creation within a stable solution space is one of the major differences between traditional customisation. While a traditional customizer produces unique products and processes, a mass customizer uses stable processes to provide a high range of variety among their products and services (Pine, 1993). This would enable a mass customizer to achieve “near mass production efficiency” but would also mean that the customisation alternatives are limited to certain product features (Pine, 1995). As opposed to the industrial output of mass production, in which the customer selects from options produced by the industry, MC facilitates cultural production, the personalisation of mass products in accordance with individual beliefs. This means that the customer contributes to defining the processes, components, and features that will be involved in the flow of the design and manufacturing process (Kieran & Timberlake, 2004). Products or services that are co-designed by the customer may provide social benefits, resulting in tailor-made, fitting, and resilient outcomes (Piller et al., 2005). Thanks to parametric design and digital fabrication it is now viable to mass-produce non-standard, custom-made products, from tableware and shoes to furniture and building components. These are often customizable through interactive websites (Kolarevic & Duarte, 2019). The incorporation of MC into the housebuilding industry, through supporting, guiding, and informing the user via interactive interfaces (Madrazo et al., 2010), can contribute to a democratisation of housing design, allowing for an empowering, social, and cultural enrichment of our built environment. Our current housing stock is largely homogeneous, while customer demands are increasingly heterogeneous. Implementing MC in the housing industry could address the diverse consumer needs in an affordable and effective way, by creating stable solution spaces that could make good quality housing accessible to more dwellers. Stability and responsiveness are key in the production of highly customised housing. Stability can be achieved through product modularity, defining and producing a set of components that can be combined in the maximum possible ways, attaining responsiveness to different requests while reducing the complexity of product variation. This creates customisation alternatives within the solution space which require a smooth flow of information and effective collaboration between customers, designers, and manufacturers (Khalili-Araghi & Kolarevic, 2018). ICT technologies can help to effectively materialise this multidimensional and interdisciplinary challenge in the Architecture, Engineering and Construction (AEC) industry, as showcased in the Sato PlusHome multifamily block in Finland[1]. Nowadays, there are companies that have integrated a systematic methodology to produce mass customised single-family homes using prefabrication methods, such as Modern Modular[2]. On the other hand, platforms such as BIM that act as collaborative environments for all stakeholders have demonstrated that building performance can be increased and precision improved while reducing construction time. These digital twins offer a basis for fabricated components and enable early cooperation between different disciplines. Parametric tools have the potential to help customisation comply with the manufacturing rules and regulations, and increase the ability to sustainably meet customer requirements, using fewer resources and shorter lead times (Piroozfar et al., 2019). In summary, a mass customisable housing industry could be achieved if the products and services are parametrically defined (i.e., specifying the dimensions, constraints, and relationships between the various components), interactively designed (via a website or an app), digitally fabricated, visualised and evaluated to automatically generate production and assembly data (Kolarevic, 2015). However, for MC to be integrated effectively in the AEC industry, several challenges remain that range from cultural, behavioural and management changes, to technological such as the use of ICTs or those directly applied to the manufacturing process, as for example automating the production and assembly methods, the use of product configurators or managing the variety through the product supply chain (Piroozfar et al., 2019).   [1] Sato PlusHome. ArkOpen / Esko Kahri, Petri Viita and Juhani Väisänen (http://www.open-building.org/conference2011/Project_PlusHome.pdf) [2] The Modern Modular. Resolution: 4 Architecture (https://www.re4a.com/the-modern-modular)

Created on 06-07-2022 | Update on 06-07-2022

Read more ->
Life Cycle Costing

Author: A.Elghandour (ESR4)

Area: Design, planning and building

Life Cycle Costing (LCC) is a method used to estimate the overall cost of a building during its different life cycle stages, whether from cradle to grave or within a predetermined timeframe (Nucci et al., 2016; Wouterszoon Jansen et al., 2020). The Standardised Method of Life Cycle Costing (SMLCC) identifies LCC in line with the International Standard ISO 15686-5:2008 as "Methodology for the systematic economic evaluation of life cycle costs over a period of analysis, as defined in the agreed scope." (RICS, 2016). This evaluation can provide a useful breakdown of all costs associated with designing, constructing, operating, maintaining and disposing of this building (Dwaikat & Ali, 2018). Life cycle costs of an asset can be divided into two categories: (1) Initial costs, which are all the costs incurred before the occupation of the house, such as capital investment costs, purchase costs, and construction and installation costs (Goh & Sun, 2016; Kubba, 2010); (2) Future costs, which are those that occur after the occupancy phase of the dwelling. The future costs may involve operational costs, maintenance, occupancy and capital replacement (RICS, 2016). They may also include financing, resale, salvage, and end-of-life costs (Karatas & El-Rayes, 2014; Kubba, 2010; Rad et al., 2021). The costs to be included in a LCC analysis vary depending on its objective, scope and time period. Both the LCC objective and scope also determine whether the assessment will be conducted for the whole building, or for a certain building component or equipment (Liu & Qian, 2019; RICS, 2016). When LCC combines initial and future costs, it needs to consider the time value of money (Islam et al., 2015; Korpi & Ala-Risku, 2008). To do so, future costs need to be discounted to present value using what is known as "Discount Rate" (Islam et al., 2015; Korpi & Ala-Risku, 2008). LCC responds to the needs of the Architectural Engineering Construction (AEC) industry to recognise that value on the long term, as opposed to initial price, should be the focus of project financial assessments (Higham et al., 2015). LCC can be seen as a suitable management method to assess costs and available resources for housing projects, regardless of whether they are new or already exist. LCC looks beyond initial capital investment as it takes future operating and maintenance costs into account (Goh & Sun, 2016). Operating an asset over a 30-year lifespan could cost up to four times as much as the initial design and construction costs (Zanni et al., 2019). The costs associated with energy consumption often represent a large proportion of a building’s life cycle costs. For instance, the cumulative value of utility bills is almost half of the cost of a total building life cycle over a 50-year period in some countries (Ahmad & Thaheem, 2018; Inchauste et al., 2018). Prioritising initial cost reduction when selecting a design alternative, regardless of future costs, may not lead to an economically efficient building in the long run (Rad et al., 2021). LCC is a valuable appraising technique for an existing building to predict and assess "whether a project meets the client's performance requirements" (ISO, 2008). Similarly, during the design stages, LCC analysis can be applied to predict the long-term cost performance of a new building or a refurbishing project (Islam et al., 2015; RICS, 2016). Conducting LCC supports the decision-making in the design development stages has a number of benefits (Kubba, 2010). Decisions on building programme requirements, specifications, and systems can affect up to 80% of its environmental performance and operating costs (Bogenstätter, 2000; Goh & Sun, 2016). The absence of comprehensive information about the building's operational performance may result in uninformed decision-making that impacts its life cycle costs and future performance (Alsaadani & Bleil De Souza, 2018; Zanni et al., 2019). LCC can improve the selection of materials in order to reduce negative environmental impact and positively contribute to resourcing efficiency (Rad et al., 2021; Wouterszoon Jansen et al., 2020), in particular when combined with Life Cycle Assessment (LCA). LCA is concerned with the environmental aspects and impacts and the use of resources throughout a product's life cycle (ISO, 2006). Together, LCC and LCA contribute to adopt more comprehensive decisions to promote the sustainability of buildings (Kim, 2014). Therefore, both are part of the requirements of some green building certificates, such as LEED (Hajare & Elwakil, 2020).     LCC can be used to compare design, material, and/or equipment alternatives to find economically compelling solutions that respond to building performance goals, such as maximising human comfort and enhancing energy efficiency (Karatas & El-Rayes, 2014; Rad et al., 2021). Such solutions may have high initial costs but would decrease recurring future cost obligations by selecting the alternative that maximises net savings (Atmaca, 2016; Kubba, 2010; Zanni et al., 2019). LCC is particularly relevant for decisions on energy efficiency measures investments for both new buildings and building retrofitting. Such investments have been argued to be a dominant factor in lowering a building's life cycle cost (Fantozzi et al., 2019; Kazem et al., 2021). The financial effectiveness of such measures on decreasing energy-related operating costs, can be investigated using LCC analysis to compare air-condition systems, glazing options, etc. (Aktacir et al., 2006; Rad et al., 2021). Thus, LCC can be seen as a risk mitigation strategy for owners and occupants to overcome challenges associated with increasing energy prices (Kubba, 2010). The price of investing in energy-efficient measures increase over time. Therefore, LCC has the potential to significantly contribute to tackling housing affordability issues by not only making design decisions based on the building's initial costs but also its impact on future costs – for example energy bills - that will be paid by occupants (Cambier et al., 2021). The input data for a LCC analysis are useful for stakeholders involved in procurement and tendering processes as well as the long-term management of built assets (Korpi & Ala-Risku, 2008). Depending on the LCC scope, these data are extracted from information on installation, operating and maintenance costs and schedules as well as the life cycle performance and the quantity of materials, components and systems, (Goh & Sun, 2016) These information is then translated into cost data along with each element life expectancy in a typical life cycle cost plan (ISO, 2008). Such a process assists the procurement decisions whether for buildings, materials, or systems and/or hiring contractors and labour, in addition to supporting future decisions when needed (RICS, 2016). All this information can be organised using Building Information Modelling (BIM) technology (Kim, 2014; RICS, 2016). BIM is used to organise and structure building information in a digital model. In some countries, it has become mandatory that any procured project by a public sector be delivered in a BIM model to make informed decisions about that project (Government, 2012). Thus, conducting LCC aligns with the adoption purposes of BIM to facilitate the communication and  transfer of building information and data among various stakeholders (Juan & Hsing, 2017; Marzouk et al., 2018). However, conducting LCC is still challenging and not widely adopted in practice. The reliability and various formats of building related-data are some of the main barriers hindering the adoption of LCCs (Goh & Sun, 2016; Islam et al., 2015; Kehily & Underwood, 2017; Zanni et al., 2019).

Created on 05-12-2022 | Update on 20-05-2023

Read more ->
Measuring Housing Affordability

Author: A.Elghandour (ESR4), K.Hadjri (Supervisor)

Area: Design, planning and building

Measuring housing affordability refers to assessing the extent to which households can secure suitable housing in relation to their financial resources and other relevant factors. To date there is no global agreement on measuring housing affordability, nor is there a single metric which comprehensively encompasses all the considerations regarding households' ability to access suitable housing in a convenient location at an affordable cost (Ezennia & Hoskara, 2019; OECD, 2021b). Several approaches exist to measure housing affordability, with two popular approaches, namely the Income Ratio Method (IRM), and the Residual Income Method (RIM) (Ezennia & Hoskara, 2019; Stone et al., 2011). Both are recommended to be accompanied by housing quality standards to evaluate what a household is paying for and a measure of housing satisfaction (Haffner & Heylen, 2011; OECD, 2021b). However, the perception of what constitutes satisfactory, quality, or affordable housing is subjective. This perception can be influenced by economic and social circumstances that policymakers may not perceive as directly relevant to housing policy (OECD, 2021b). The Income Ratio Method (IRM) is the most commonly used in policy and housing market-relevant statistics, as it is easy to measure and compare among different countries. It is based on the housing costs to income ratio defined by national authorities not to exceed a certain proportion (Haidar & Bahammam, 2021; Smith, 2007; Stone, 2006). The official EU indicator for IRM is the "Housing Cost Overburden" index. It considers households suffering from affordability issues if more than 40% of their net income is spent on housing costs (AHC, 2019; Hick et al., 2022; OECD, 2020). However, IRM has been widely criticised as it does not reflect if the household could afford non-housing costs and for how long. The focus on housing costs neglects non-housing costs of utility bills, schools, health, transportation, and so on (AHC, 2019). In this sense, Ezennia & Hoskara, (2019) investigation of the weaknesses of measuring housing affordability emphasised the need to reflect a household's capability to balance current and future costs to attain a house – "access to a house at a certain period" while maintaining other basic expenses without experiencing any financial hardship. The Residual Income Method (RIM) is the second dominant approach. It recognises that after paying the housing costs, a household might be unable to satisfy its non-housing requirements. Thus, the RIM is the remaining income after subtracting housing costs, based on the idea that Housing Affordability is the households' ability to cover their housing costs while still being able to pay their non-housing expenditures (Stone et al., 2011; Stone, 2006). The residual income method took a step closer to resonating with non-housing costs. However, both Haffner & Heylen (2011) and Bramley (2012) advised that the IRM and RIM approaches "are not interchangeable" and need to be combined to provide a comprehensive perception of housing affordability. This combination becomes apparent when comparing both for different household compositions, health, or work conditions. For instance, a house might be affordable when measured using the IRM from the housing costs standpoint, but it might not be affordable utilising the RIM, which is connected with non-housing costs. This combination is referred to as the Composite Method from which several advanced economic modelling approaches to measure housing affordability were developed (Ezennia & Hoskara, 2019). However, relying solely on economic criteria to assess affordability and thus overlooking quality and sustainability may not prove sufficient. A poor-quality house can impose hardships on its residents, and an unsustainable dwelling can strain the environment. Mitigating this issue may involve complementing affordability measurements with indicators reflecting housing quality and sustainability to expand the purely economic view (Ezennia & Hoskara, 2019; Haffner & Heylen, 2011; Mulliner et al., 2013; Salama, 2011). Various indicators can be used to assess housing quality beyond just its cost. These indicators could be seen as serving three primary purposes: (1) to measure the quality of a housing scheme and compare it to others within a country (Homes and Communities Agency, 2011), (2) to measure the quality of housing in one country and compare it to other countries (OECD, 2021b), and (3) to measure housing satisfaction across groups (OECD, 2021a; Riazi & Emami, 2018). An example of the first purpose is England's Housing Quality Indicators (HQIs) system (Homes and Communities Agency, 2011), which is currently withdrawn. HQIs served  as “ measurement and assessment tool to evaluate housing schemes on the basis of quality rather than just cost” design standards mandated for affordable housing providers funded through the National Affordable Housing Programme from 2008 to 2011 and the Affordable Homes Programme from 2011 to 2015. The system comprised ten indicators, which can be categorized into four groups. The first category focused on the location and proximity to amenities and services. The second dealt with site-related aspects such as landscaping, open spaces, and pathways. The third pertained to the housing unit itself, encompassing factors like noise, lighting, accessibility, and sustainability. Lastly, the fourth category addressed the external environment (Homes and Communities Agency, 2011). To enable meaningful cross-country comparisons, it is crucial that the data used for measuring and assessing these indicators are both available and up-to-date. However, it is important to acknowledge that this may not be the case in all countries, as pointed out by the OECD in 2021 (OECD, 2021b). Consequently, to accurately determine what residents are paying for in terms of quality and to facilitate meaningful comparisons, the OECD 2021 Policy Brief on Affordable Housing has emphasized the necessity of two additional housing quality indicators to complement affordability measurements. The first proposed indicator is the "Overcrowding Rate," which evaluates whether a dwelling provides sufficient space for household members based on their composition. This metric assesses whether residents have adequate living space according to the size and structure of their household. The second indicator is the "Housing Deprivation Rates," which gauge inadequate housing conditions. This encompasses issues related to maintenance, such as roofs, walls, floors, foundations, and deteriorating window frames. Moreover, these rates consider the absence of essential amenities, including sanitary facilities. By taking all these factors into account, this indicator offers a comprehensive perspective on the overall quality and habitability of housing in a specific area. Considering subjective measures of housing affordability can be advantageous when assessing housing affordability and quality based on household perceptions. These measures aim to capture housing satisfaction, reflecting the quality of the dwelling as accommodation (OECD, 2021a). In a broader context, housing satisfaction might be termed residential satisfaction, encompassing not just the dwelling but also its surroundings, including places and people. Residential satisfaction assesses how well the current residence and surrounding environment align with the household's desired living conditions (Riazi & Emami, 2018). Therefore, incorporating subjective measures is valuable in assessing housing affordability, helping to identify the determinants of housing satisfaction. Indicators such as satisfaction with the availability of good and affordable housing are crucial aspects to consider in this context (OECD, 2021a). When it comes to sustainability indicators, incorporating them into the measurement of housing affordability remains a wicked  problem. Finding a single comprehensive measure that encompasses the multifaceted aspects of sustainability related to housing affordability is challenging. The technical complexity stems from the necessity to integrate assessments of household characteristics, environmental impacts, financing, and financial aspects, along with housing stress factors. This challenge is exacerbated by the persistent fluctuations in housing prices and recurring expenses like water and energy bills (AHC, 2019). Hence, easily calculable methods such as the Income-to-Rent Ratio (IRM) and Residual Income Model (RIM) continue to be widely used for assessing housing affordability from a top-down perspective at a macro level. Although imperfect, these methods still provide valuable support for policy decision-making to a certain extent (AHC, 2019; Haffner & Heylen, 2011; OECD, 2021a).   

Created on 17-10-2023 | Update on 18-10-2023

Read more ->

Related case studies

Related publications

Elghandour, A. (2023, June). Affordability-led decisions impacting households' health and economic wellbeing - A transdisciplinary perspective. In Schweiker, M. et al. (Eds.), Proceedings of Healthy Buildings 2023 Europe (pp. 482-484). Aachen, Germany.

Posted on 11-06-2023

Conference

Read more ->

Elghandour, A., & Hadjri, K. (2023, August). Rethinking housing affordability to advocate the design for health and wellbeing. In 21st ISQOLS Annual Conference, Rotterdam, the Netherlands.

Posted on 24-05-2024

Conference

Read more ->

Relational graph

icon case study Case Study
icon case study Concept
icon case study Publication
icon case study Blogposts