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The primary aim of this research is to examine the effects of the Renovation, Conversion, and Extension (ROT) tax deduction for renovations on the scope and quality of renovations and its subsequent impact on house prices across various Swedish municipalities.

This study utilises a two-way fixed effect instrument variable (IV) spatial Manski approach, analysing balanced panel data from 2004 to 2020 at the municipal level (290 municipalities) in Sweden. The methodology is designed to assess the impact of the ROT subsidy on the housing market.

The study reveals that the ROT subsidy has significantly influenced house prices, with noticeable variations between municipalities. These differences are attributed to the varying amounts of tax reductions for renovations and the extent to which property owners utilise these subsidies.

The research is limited to the context of Sweden and may not be generalisable to other countries with different housing and subsidy policies. The findings are crucial for understanding the specific impacts of government subsidies on the housing market within this context.

For policymakers and stakeholders in the housing market, this study highlights the tangible effects of renovation subsidies on property values. It provides insights into how such financial incentives can shape the housing market dynamics.

The research underscores the role of government policies in potentially influencing equitable access to housing. It suggests that subsidies like ROT can have broader social implications, including the distribution of housing benefits among different income groups and regions.

This study contributes original insights into the field of applied real estate economics by quantitatively analysing the impact of a specific government subsidy on the housing market. It offers a unique perspective on how fiscal policies can affect property values and renovation activities at the municipal level in Sweden.

Due to the increase in energy demand and the effects of global warming, energy-efficient buildings have gained significant importance in the modern construction industry. To create a suitable framework with the aim of reducing energy consumption in the building sector, the external walls of a residential building were considered with two criteria of global warming potential and energy consumption.

In the first stage, to achieve a nearly zero-energy building, energy analysis was performed for 37 different states of thermal insulation. Then, the insulation materials’ life cycle assessment was performed. These results were used to find a set of optimal modes in the Pareto front by using non-dominated sorting genetic algorithm II multi-objective genetic algorithm. Thus, based on the data obtained from this method, it was possible to compare and choose different thermal insulation materials based on the distance from the Pareto front, reducing the environmental effects.

The results showed that replacing the windows was possible to save 3.24% in energy consumption. Also, selecting the proper insulation reduced energy consumption value by 63.13%. Finally, this building can save 69.31% of energy consumption compared to the base building by following the zero-energy building standard. As a result, the Pareto curve was introduced as a guide for the optimal design of the building’s wall insulation.

The proposed method provides designers with a framework for latent carbon analysis to access quickly and select optimal scenarios. It can also be used without restrictions for other decisions with different goals and criteria.

The study aims to tackle Egypt's rising electricity consumption due to climate change and population growth, focusing on the building sector, which accounts for up to 60% of the issue, by developing new energy-efficient design guidelines for Egyptian buildings.

This study comprises six key steps. A literature review focuses on energy consumption and efficiency in buildings, monitoring a single-family building in Cairo, using Energy Plus for simulation and verification, performing multi-objective optimization, comparing energy performance between base and controlled cases, and developing a localized version of the Passive House (PH) called Energy Efficiency Design Criteria (EEDC).

The research shows that applying the (EEDC) suggested by this study can decrease energy consumption by up to 58% and decrease cooling consumption by up to 63% in residential buildings in Egypt while providing thermal comfort and reducing greenhouse gas emissions. This can benefit users, alleviate local power grid strain, contribute to Egypt's economy, and serve as a model for other countries with similar climates.

To date, no studies have focused on developing energy-efficient design standards tailored to the Egyptian climate and context using the Passive House Criteria concept. This study contributes to the field by identifying key principles, design details, and goal requirements needed to promote energy-efficient design standards for residential buildings in Egypt.

The residential buildings sector has a high priority in the climate change adaptation process due to significant CO₂ emissions, high energy consumption and negative environmental impacts. The article investigates how, conversely speaking, the residential buildings will be affected by climate change, and how to improve existing structures and support long-term decisions.

The climate dataset was created using the scenarios determined by the Intergovernmental Panel on Climate Change (IPCC), and this was used in the study. Different building envelope and Heating, Ventilating and Air Conditioning (HVAC) systems scenarios have been developed and simulated. Then, the best scenario was determined with comparative results, and recommendations were developed.

The findings reveal that future temperature-increase will significantly impact buildings' cooling and heating energy use. As the outdoor air temperatures increase due to climate change, the heating loads of the buildings decrease, and the cooling loads increase significantly. While the heating energy consumption of the house was calculated at 170.85 kWh/m² in 2020, this value shall decrease significantly to 115.01 kWh/m² in 2080. On the other hand, the cooling energy doubled between 2020 and 2080 and reached 106.95 kWh/m² from 53.14 kWh/m² measured in 2020.

Single-family houses constitute a significant proportion of the building stock. An in-depth analysis of such a building type is necessary to cope with the devastating consequences of climate change. The study developed and scrutinised energy performance improvement scenarios to define the climate change adaptation process' impact and proper procedure. The study is trying to create a strategy to increase the climate resistance capabilities of buildings and fill the gaps in this regard.

In developing countries, including achieving Kingdom of Saudi Arabia’s (KSA) Vision 2030, housing loans for low-income employees are challenging and may thwart housing-related sustainable development goals (SDGs). Studies investigating housing finance inaccessibility for KSA Vision 2030 low-income earners and its impact on achieving housing-related SDGs are scarce. Hence, this study aims to investigate KSA housing financial inaccessibility and its effect on housing-related SDGs. Also, it offered suggestions for achieving housing provision in Vision 2030 and, by extension, improving housing-related SDGs.

The study adopted a virtual interview approach and covered Alqassim, Riyadh and Medina. The researcher engaged 24 participants who were knowledgeable about KSA’s housing finance and SDGs. They include selected low-income earners, academicians, financial operators and government ministries/departments/agencies. The study manually analysed the collated data through a thematic approach and presented the main themes.

Findings reveal that KSA’s low-income earners’ housing finance inaccessibility threatens Vision 2030 and housing-related SDGs. Inadequate funding of the Real Estate Development Fund, inability to make down payment, absence of collateral, insufficient household income and failure to recover the loan and associated charges from the auction were perceived major issues contributing to low-income earners’ house-loan rejection and recommended measures to improve achieving housing-related SDGs.

The study investigated the factors contributing to low-income earners’ housing loan rejection and its impact on achieving KSA’s Vision 2030 and housing-related SDGs from the participants’ perspective. The findings reveal that low-income earners’ housing finance accessibility has been compounded by the slow recovery from the post-COVID-19 pandemic.

This research explores the role of concrete 3D printing (C3DP) in the development of culturally appropriate housing in Indigenous Reserves in Canada through the design, building and evaluation of the Star Lodge project located in the Siksika Nation of Alberta, Canada. The project aims to assess the potential of C3DP in addressing the escalating housing demands in Indigenous communities in Canada.

The research involved a collaborative and multidisciplinary approach, engaging Blackfoot Elders, Knowledge Keepers from the Siksika Nation, Siksika Housing and Nidus3D. Central to this was the design, build and documentation of the Star Lodge project to analyse the advantages and challenges, guided by weekly meetings and site visits.

The project harnessed C3DP to streamline construction, enhance durability, reduce maintenance costs and enhance the energy performance of the homes. Notable time savings were achieved compared to conventional construction methods. Challenges included developing strategies to overcome extreme cold weather conditions, achieving a consistent concrete mix and integrating conventional construction elements such as drywall construction in interiors. The project served as a platform for collaboration and community participation, shaping the design and construction process while raising awareness of innovative construction techniques in the community.

This study provides an evidence-based framework for the evaluation of C3DP technology by analysing the Star Lodge Project, the first C3DP project in Alberta and the largest of its kind in Canada. By addressing housing challenges in Indigenous communities, the research holds broader implications for sustainable development and Indigenous empowerment across Canada.

This research examined the accountability measures put into practice during the housing reconstruction following the 2015 Nepal earthquakes. Additionally, it aimed to identify gaps in accountability practices and suggest approaches for improving their efficacy.

The research methodology encompassed a qualitative approach. Around 30 research participants were selected for in-depth interviews using a purposive sampling strategy to ensure data richness and relevance. The interviews were recorded, transcribed and then iteratively analysed using thematic framework analysis. This analytical technique involved identifying recurrent themes and patterns within the transcriptions of the participants' articulation.

The study showed the pivotal role of meetings and interactive forums in promoting transparency and disseminating vital information during housing reconstruction. Additionally, it underscored the contributions of nongovernmental organizations (NGOs) and community-based organizations (CBOs) in information dissemination within affected communities. Policy challenges centre on identifying vulnerable populations, local support mechanisms and contextualizing reconstruction policies, specifically focusing on urban heritage settlements. Strengthening local service delivery and complaint mechanisms, capacity building and defining the roles and responsibilities of actors and beneficiaries are suggestive measures for a participatory and inclusive reconstruction process.

Research holds distinctive value due to its recent inception and its focus on both the subject matter and the specific geographical context. It contributes novel insights into the principles and practices of accountability mechanisms during the housing reconstruction process following a major disaster.

This study aims to examine the effect of proximity and spatial dependence on the house price index for the nascent market Dar es Salaam, Tanzania. Despite the ongoing housing market transactions, there is no single house price index that takes into account proximity and spatial dependence. The proximity considerations in question are proximal to arterial roads, public hospitals, an airport and food markets. Previous studies on sub-Saharan Africa have focused on the ordinary least squares (OLS)-based hedonic model for the index and ignored spatial and proximity considerations.

Using the OLS and spatial econometric approach, the paper tests for the significance of the two effects – proximity and spatial dependence in the hedonic price model with year dummy variables from 2010 to 2019. The paper then compares the three indices in the following configurations: without the two effects, with proximity factors only, and with both effects, i.e. proximity and spatial dependence.

The inclusion of proximity factors and spatial dependence – spatial autocorrelation – seems to improve the hedonic price model but does not significantly improve the house price index. However, further research should be called for on account of the nascent nature of the market.

The paper brings new knowledge by demonstrating that it may not be necessary to take into account proximity factors and spatial dependence for the Dar es Salaam house price index.

Scholars, activists, and policymakers have paid increasing attention to housing instability, especially where eviction is a cause. Housing instability is a dynamic process rather than a discrete catastrophic event, and eviction imposes vulnerability on consumers. Even the threat of it can trigger the onset of a crisis. In this project, we deepen the understanding of eviction by exploring its use in property management practice. We begin by summarizing its definition and causes from a cross-disciplinary and still-evolving literature. We then provide an extended example of how eviction can be used to pursue strategic and financial goals using rental markets in Arkansas as an example. Arkansas is characterized by a quintessentially laissez-faire regulatory environment that imposes few restrictions on property owners. We conclude by posing questions that should be at the forefront of a vulnerability-focused, policy-oriented research agenda on eviction.

This study aims to develop a modelling framework of housing supply dynamics within the context of urban microsimulation systems. Housing markets have witnessed substantial investigation over recent decades, predominantly concerning residential demand. However, comparatively limited attention has been directed towards comprehending the housing supply dynamics. Housing policy disconnects with the developers’ market behaviours, which leads to significant mismatch between the housing construction and affordable housing needs of the population. Research attention should be made in comprehending the residential construction market activities. To address this gap, this study developed an autoregressive distributed lag (ARDL) model and analyzed the temporal evolution of housing construction.

An ARDL model was developed to address the issue of temporal modelling of the housing supply. An empirical study was conducted in the Greater Toronto and Hamilton Area (GTHA) based on a longitudinal housing starts data set from 1998 to 2020. The model integrates diverse variables, including macroeconomic conditions, property development costs, dwelling prices and opportunity costs. Notably, the model captures both the path-dependent effects stemming from supply market fluctuations and the temporal lag effect of influential factors.

The findings reveal that the supply-side’s responsiveness to market condition alterations may span up to 18 months. The model has reasonable and satisfying performance in fitting the observed starts. The methodological foundations laid will facilitate future modelling of housing supply dynamics.

This study innovatively separated the modelling of housing supply within the context of urban microsimulation, into two parts, the modelling of housing starts and completion. The housing starts are determined in a complex and regressive process influenced by both the micro-economic environment and the construction cost and housing market trends. Through the temporal modelling method, this study captures how long it would take for the housing supply to respond to multiple factors and provides insight for urban planners in regulating the housing market and leveraging various policies to influence the housing supply.