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The purpose of this paper is to empirically test for submarket existence based on an understanding of the residential rental housing market in Ghana.

Based on extant literature and market observations, the authors provide key concepts and an overview of the residential rental market dynamics in Ghana. Reseachers appreciate that submarkets may exist in the Ghanaian rental market but have ignored the empirical testing for submarket existence due to data asymmetries. Based on real estate experts and stakeholder consultations, a priori delineation of submarkets are constructed based on spatial, structural and a nested approach. Submarket existence is tested using the Kruskal–Wallis H test and Hedonic modelling techniques.

By using fieldwork data from Accra rental market, the analysis provides credence to the conceptualisation of submarkets and how to empirically test for same. It is argued that researchers should use alternative methods to compare results to make far-reaching conclusions.

Examining the hypothesis that differential rental values exists for submarkets has implications for policy decisions to target submarket constructs differently to improve market maturity.

The research provides stakeholder investors in the rental space an understanding of market dynamics for profit maximisation, and end-users to maximise utility in deciding where to live – and as such households could benefit from making informed investment decisions on housing.

This research is one of the first attempts to empirically identify and test for submarkets existence in Ghana’s residential rental housing market.

This paper aims to construct rental housing indices and identify market segmentation for more effective property-management strategies.

The hedonic model was employed to construct the rental indices. Using the k-means++ and REDCAP (Regionalisation with Dynamically Constrained Agglomerative Clustering and Partitioning) approaches, the authors conducted clustering analysis and identified different market segmentation. The empirical study relied on the database of 80,212 actual rental transactions in Beijing, China, spanning 2016–2018.

Rental housing market segmentation may distribute across administrative boundaries. Properly segmented indices could provide a better account for the heterogeneity and spatial continuity of rental housing and as well be crucial for effective property management.

Residential rent might not only vary over space but also interplays with housing price. It would be worth studying how the rental market functions together with the owner-occupied sector in the future.

Residential rental indices are of great importance for policymakers to be able to evaluate housing policies and for property managers to implement competitive strategies in the rental market. Their constructions largely depend on the analysis of market segmentation, a trade-off between housing spatial heterogeneity and continuity.

This paper fills the gap in knowledge concerning segmented rental indices construction, particularly in China. The spatial constrained clustering approach (REDCAP) was also initially introduced to identify regionalised market segmentation due to its superior performance.

This paper aims to explain the main difficulties in the Spanish residential rental market becoming a true alternative to home ownership.

Currently, the Spanish rental market only meets temporary housing needs; it is very atomized and lacks professionalism. It does not provide an adequate legal framework to fulfil the parties’ aspirations (i.e. stability, affordability and flexibility for tenants; profitability, security and guarantees to landlords). The analysis of this proposition and the resulting proposal are based on six years of research, which started with the TENLAW European project.

Overcoming these constrains is essential to double the rate of residential leases in Spain and get closer to the European average, thus achieving a true diversification of housing tenures and avoiding future housing bubbles.

The paper makes a series of recommendations to legislators and policymakers to draft an adequate legal framework aimed at increasing the housing rental market share. This is based on the experience of mature tenancy markets in Europe, such as the German, Swiss and Austrian ones.

The new proposed legal framework will help to transform the tenancy model in Spain into a functional one, making it more stable, affordable and flexible, while increasing safety and profitability for landlords. The model is also applicable, on a more general level, to all Mediterranean European countries.

Rethinking the regulation of tenancies, in a context of housing crisis and unaffordability (still a reality in many European and worldwide countries) has valuable potential for making this type of tenure more popular and for avoiding future housing bubbles.

This is the first article to apply a machine learning approach to the analysis of time on market on real estate markets.

The random survival forest approach is introduced to the real estate market. The most important predictors of time on market are revealed and it is analyzed how the survival probability of residential rental apartments responds to these major characteristics.

Results show that price, living area, construction year, year of listing and the distances to the next hairdresser, bakery and city center have the greatest impact on the marketing time of residential apartments. The time on market for an apartment in Munich is lowest at a price of 750 € per month, an area of 60 m2, built in 1985 and is in a range of 200–400 meters from the important amenities.

The findings might be interesting for private and institutional investors to derive real estate investment decisions and implications for portfolio management strategies and ultimately to minimize cash-flow failure.

Although machine learning algorithms have been applied frequently on the real estate market for the analysis of prices, its application for examining time on market is completely novel. This is the first paper to apply a machine learning approach to survival analysis on the real estate market.

Private sector residential property investors aiming to achieve optimal total returns need to be able to identify the best performing suburbs in a city. The purpose of this paper is to analyse the risk‐adjusted investment performance of 19 suburbs within Auckland City and provide some insight into the likely future performance of some of these suburbs.

The annual pre‐tax and unleveraged investment performance of a residential property is a function of the changes in the value of the property plus the net yield. House price data for the suburbs were taken from the Real Estate Institute of New Zealand. Rental information was obtained from the Department of Building and Housing.

Surprisingly, the suburb showing the highest average yields was also the suburb recording the greatest increase in house prices. This result appears to be a consequence of government intervention in the form of increased rental subsidies for renters, tax concessions for landlords and low‐deposit home loans aimed for first home buyers.

It is all very well analysing the past performance of suburbs but investors are likely to be more interested in future performance, rather than past performance, when they make buying and selling decisions. In some cases, the characteristics of suburbs that have done well in the past can be useful in identifying suburbs likely to do well in the future.

The hypothesis advanced in this paper is that suburbs with lower than average household income to house price ratios and house income to rent ratios, combined with a trend for household incomes and rents to be increasing above the city‐wide average, are likely to be the best prospects for future residential investment.

The main social implication appears to be the unintended consequences of rental subsidies increasing rents and house prices more than the average in the lower priced suburbs.

There has been very little published work comparing total returns on investor housing within a city, by suburb. This has been made possible by the combination of real estate sales information and a comprehensive rental database. In addition, census information on households' incomes at suburban level is also integrated into the study.The study also makes a novel contribution by suggesting variables likely to influence future total returns by suburb.

The purpose of this paper is to investigate the role of distinct types of heating technology and their price impact in German residential real estate markets, considering a wide range of other housing market determinants. The authors aim to test and to verify specifically, whether the obsolescence of heating technology leads to a significant price discount and whether higher technological standards (and environmental friendliness) come with a price premium on the market.

The authors create housing market models for rental and sales segments by constructing generalized additive models with explicit multi-layered spatial components. To elaborate a profound and contemporary answer using these models, the authors perform large-sample regression analyses based on more than 400,000 observations covering German residential properties in 2015.

First and foremost, the heating system indeed shows significant explanatory importance for measuring housing rents and purchasing price. Second, the authors find that it makes a difference whether clean “green” technologies are implemented or whether “brown” systems with obsolete technology or fossil energy sources is on hand. Ultimately, the authors conclude that while low energy consumption indeed comes with a price premium, this needs to be interpreted together with the property’s heating type, as housing markets seem to outweigh the “green premium” by “brown discounts” if low energy consumption figures are powered by a certain type of heating technology system.

Aside of a possible omitted variable bias, the main research limitation is constituted by the integration of asking prices in the analysis, as actual transaction prices are not systematically transparent on national level in Germany. Limitations are discussed at the end of the paper.

This work supports investors who face the challenge of making environmental- and energy-related decisions as well as appraisers who deliver financial fundamentals for such. Third, the paper supports both asset managers as well as investment strategists in argumentation pro-environmental investments beyond all ecological necessity.

This paper contributes to the current discussion on climate change and the eclectic role of real estate in this context. The authors deliver evidence on pricing effects as a measure of socioeconomic acceptance of progressive heating technology and environmental friendliness as an imperative of twenty-first century societies.

This is the first study on “green premiums” or “brown discounts” that includes heating technology as a potential and distinct driver of value and rents. It is a contemporary contribution and delivers original information on the quantitative impact of contemporary and anachronistic technology in heating to researchers as well as investors and appraisers.

Foreclosure risk is a key concern to lenders of real estate mortgages. Using auction data, this study provides the first analysis of mortgage foreclosure in Singapore by examining how macro‐economic variables affect the probability of foreclosure. The foreclosure rate for properties is found to be increasing in the first five years of purchase and decreases as the holding period lengthens. The likelihood of foreclosure increases with unemployment rate, mortgage rate and expenditure and decreases with equity, dividend yield and lending volume at fourth and twentieth quarters lag. Further analysis shows considerable differences between residential and non‐residential properties. However, when the analysis on non‐residential properties is further separated into office, retail and industrial sub‐sectors, the results are relatively similar among the three sub‐sectors. This implies that banks and financial institutions should apply different underwriting standards for residential properties, mainly for owner‐occupation and non‐residential properties for the purpose of businesses and rental income.

The purpose of this paper is to examine the market liquidity (time-on-market (TOM)) and its determinants, for rental dwellings in the largest seven German cities, with big data.

The determinants of TOM are estimated with the Cox proportional hazards model. Hedonic characteristics, as well as socioeconomic and spatial variables, are combined with different fixed effects and controls for non-linearity, so as to maximise the explanatory power of the model.

Higher asking rent and larger living space decrease the liquidity in all seven markets, while the age of a dwelling, the number of rooms and proximity to the city centre accelerate the letting process. For the other hedonic characteristics heterogeneous implications emerge.

The findings are of interest for institutional and private landlords, as well as governmental organisations in charge of housing and urban development.

This is the first paper to deal with the liquidity of rental dwellings in the seven most populated cities of Europe’s second largest rental market, by applying the Cox proportional hazards model with spatial gravity variables. Furthermore, the German rental market is of particular interest, as approximately 60 per cent of all rental dwellings are owned by private landlords and the German market is organised polycentrically.

The purpose of this paper is to investigate the nature and dimension of non-compliance (defiance) with lease agreement obligations in private rental housing market between managers (agents/private rental housing providers or landlords) and end-users (tenants – rental housing consumers), with a view to identifying challenges in rental housing lease administration in Nigeria emerging rental market.

The quantitative data collected from practicing estate surveyor and valuers (statutorily registered agents), who manage private rental housing in their portfolios on behalf of owners and tenants, who occupy rental housing within Lagos state (the largest property market in Nigeria and West Africa). Using a theoretical model in the context of five lease agreement obligations, data collected were analyzed using descriptive and inferential statistics (one sample t-test, independent t-test and correlation).

While economic circumstances (economic factors) are considered the major vulnerable factor that cause acts of non-compliance, defiance against “covenant not- to- sublet (subletting covenant (SC))” and “prompt rental payment covenant” are the two most non-compliance attitudes (precipitation events) observed from both actors. There is correlation among all vulnerability elements and precipitating events. While a significant relationship was only observed between “SC” and all vulnerability elements on the part of agents, there is significant relationship among all the vulnerability elements and precipitating events on the part of tenants. Also, while tenants attached higher significance to all the vulnerability factors than managers, both actors attached different level of priority to precipitating events. Lastly, equitable remedies and peaceful entry are the two most adopted intervention tools.

This paper is limited to seeking both the professional opinion of licensed/registered agents and the rental housing consumers-tenants.

The research points to an increasing need for the stakeholders – Estate Surveyors and Valuers Registration Board of Nigeria (a Government parastatal) and the Nigerian Institutions of Estate Surveyors and Valuers (the constituted professional body), to establish and reform the code of practice in this direction with due consideration to the factors identified in this study. Effort also should be upgraded in the intervention techniques adopted in order to improve on emerging rental market.

The paper explores an important aspect of lease administration in private rental housing market. It also provides platform on which the acts of defiance can be wiped out in the emerging rental market.

The purpose of this paper is to explore the significance impact of air quality as a contributing factor on residential property rents by applying geo-informatics to economic issues. Since air pollution poses a severe health threat, city residents should have a right to know about the (invisible) hazards they are exposed to.

Within spatial-temporal modeling of air pollutants in Berlin, Germany, three interpolation techniques are tested. The most suitable one is selected to create seasonal maps for 2018 and 2021 with pollution concentrations for particulate matter values and nitrogen dioxide for each 1,000 m² cell within the administrative boundaries. Based on the evaluated pollution particulate matter values, which are used as additional variables for semi-parametric regressions the impact of the air quality on rents is estimated.

The findings reveal a compelling association between air quality and the economic aspect of the residential real estate market, with noteworthy implications for both tenants and property investors. The relationship between air pollution variables and rents is statistically significant. However, there is only a “willingness-to- pay” for low particulate matter values, but not for nitrogen dioxide concentrations. With good air quality, residents in Berlin are willing to pay a higher rent (3%).

These results suggest that a “marginal willingness-to-pay” occurs in a German city. The research underscores the multifaceted impact of air quality on the residential rental market in Berlin. The evidence supports the notion that a cleaner environment not only benefits human health and the planet but also contributes significantly to the economic bottom line of property investors.

The paper has a unique data engineering approach. It collects spatiotemporal data from network of state-certified measuring sites to create an index of air pollution. This spatial information is merged with residential listings. Afterward non-linear regression models are estimated.