Search results

As the green economic bottom line is a strong motivating force when deciding to build, manage and/or operate green, this study aims to examine the financial impacts of green certifications on multifamily rental communities.

Using a multiple regression methodology, operating financial variables are examined.

Multifamily rental green buildings garner not only higher rental collections but also higher total expenses. When applying these higher rates to properties, the overall increase in rents outweighs the increases in total expenses.

While multiple studies have focused on the office sector, this study begins to fill the literature gap within the multifamily rental sector regarding the economic impacts of green-certified buildings. The outcomes of this study have positive implications for the multifamily real estate industry by providing developers, owners, managers and related parties with a better understanding of the financial impacts of multifamily rental green buildings; however, more research is needed.

The green building phenomenon has only recently extended to the residential sector. The purpose of this paper is to provide context on the prevalence of green building within the multifamily residential sector. The decisions on where green apartment buildings are sited are also examined.

A series of comparative analyses are performed on green criteria scorecards provided by the US Green Building Council (USGBC) across property types. Comparisons are made to determine whether the climate and rents differ substantially between green multifamily locations and the area means.

Green multifamily properties underperform other property types in each of the six categories that the USGBC uses in its green scoring criteria. While the siting of green multifamily properties was inordinately located in areas with high heating degree days during the early years of USGBC certification, green apartment buildings have since diffused to communities with more normal temperature patterns, suggesting an appeal of green buildings beyond simply energy savings. Finally, the median rents for areas where green apartments are located far outpace those of the surrounding areas, raising affordability concerns.

The nascence of the green movement within the multifamily residential sector limits the amount of available data for use within this research project.

This research represents one of the first attempts outside of the housing trade industry at examining green multifamily residential properties. This research helps policy makers understand how the multifamily sector differs from other property sectors seeking green certification.

The purpose of this paper is to establish measurable factors that can be used as early indicators of which neighborhoods are most likely to undergo a process of gentrification in a reasonably near future.

Using 1990 data on key demographic variables for 128 neighborhoods in Stockholm, Sweden a model that allows both for testing of spatial clustering and for spatial spillovers between neighborhoods is estimated. It is hypothesized not only that gentrification depends on inter-neighborhood characteristics but also that gentrified neighborhoods will cluster and preferably be located in proximity to existing high income neighborhoods.

The findings confirm the stated hypotheses. Among the results, it is shown that neighborhoods that gentrified between 1990 and 2012 were more likely to have been poor in 1990 and located closer to the CBD, they were also more likely to be close to neighborhoods with lower proportions of low income residents. It is also found that gentrified neighborhoods tend to cluster over space.

Much of the previous literature on gentrification has concerned the actual driving forces behind gentrifying neighborhoods. This paper is more concerned with indicators that can be used to spot neighborhoods that are likely to undergo a gentrification process in the future. Such information can be valuable for real estate developers in the private sector, as it may lead to more successful investments. It may also be useful for city developers at the municipal organization.

The purpose of this paper is to determine the effect that ownership and management structures have on ability to control operating expenses. For individual investors, intensity of management experience is also explored as a possible explanatory variable for operating expenses. For property management services that are contracted out, the level of the fee is investigated as a possible cause for movements in operating expenses as well. Finally, operating expenses are used as a possible explanatory variable for a property’s lease-up performance during the year.

The analysis consists of a series of regression models performed on data provided by the 2012 Rental Housing Finance Survey (RHFS) in the USA. The RHFS is a unique data set that covers a wide degree of information on multifamily properties. The RHFS represents 2,260 properties in total, and covers various aspects of the apartment industry, including financing and operational cost measures. Control variables used as independent variables include number of units, year of property acquisition, and age of building.

Individual ownership and self-management proved to be statistically significant drivers in driving down log operating expenses. Hours spent by individuals performing property management roles on their own properties had a slightly positive association with operating expenses. For professional managers, the fees devoted solely to the manager or management company had a highly significant and positive effect on other operating costs. Finally, when separating out the individual components of operating expenses, only two variables had significant effects on tenant lease-ups: management expenses (positive) and security expenses (negative).

The data set is potentially biased toward those properties with less than 100 units, and thus it would be problematic to assume that these findings are generalizable to the population at large. There are also no geographic coding indicators within the RHFS data set, which eliminates the potential to control for various market factors and rural/urban differences.

The research provides an understanding of some of the basic factors behind increases in operating expenses, which ultimately has implications for performance benchmarks such as net operating income and property market value.

The reasonable controlling of operating expenses ultimately has potentially positive implications for low- to moderate-income populations, who would ultimately experience lower rents as a result.

This research represents one of the first known uses of the RHFS database.

Establishing the strength of a novel variable–mortgage debt as a fraction of US gross domestic product (GDP)–on forecasting capitalisation rates in both the US office and multifamily sectors.

The authors specify a vector error correction model (VECM) to the data. VECM are used to address the nonstationarity issues of financial variables while maintaining the information embedded in the levels of the data, as opposed to their differences. The cap rate series used are from Green Street Advisors and represent transaction cap rates which avoids the problem of artificial smoothness found in appraisal-based cap rates.

Using a VECM specified with the novel variable, unemployment and past cap rates contains enough information to produce more robust forecasts than the traditional variables (return expectations and risk premiums). The method is robust both in and out of sample.

This has direct implications for governmental policy, offering a path to real estate price stability and growth through mortgage access–functions largely influenced by the Fed and the quasi-federal agencies Fannie Mae and Freddie Mac. It also offers a timely alternative to interest rate-based forecasting models, which are likely to be less useful as interest rates are to be held low for the foreseeable future.

This study offers a new and highly explanatory variable to the literature while being among the only to model either (1) transactional cap rates (versus appraisal) (2) out-of-sample data (versus in-sample) (3) without the use of the traditional variables thought to be integral to cap rate modelling (return expectations and risk premiums).

This study focuses on identifying key principles for implementing strategic changes in design and construction companies interested in successfully using offsite construction (OSC) in multifamily housing projects, considering the need for more affordable and sustainable multifamily housing in the United States of America (USA).

Using mixed methods, the study involved three phases of data collection and data analysis: (1) delphi survey, (2) online survey, (3) proposition of principles and validation interviews.

The key principles identified by the present research are (1) develop product-oriented business model, (2) promote leadership and mindset engagement with OSC principles, (3) engage in partnerships and more innovative contractual models, (4) shift toward digital transformation, (5) develop training and knowledge management strategies, (6) adopt lean construction (LC) practices, (7) develop training and knowledge management strategies and (8) integrate logistics and supply chain management with AEC (architecture, engineering and construction) processes.

The implementation of the principles and strategic changes identified in this study aims to prepare design and construction companies, especially small and medium-sized enterprises (SMEs), to embrace the increasing use of OSC in multifamily projects in the USA, which will make them more efficient and resilient and, ultimately, will contribute to the construction of more affordable and sustainable multifamily housing projects in the USA.

This is the first research to address holistic strategies to support design and construction companies in adopting OSC.

This paper aims to examine whether property managers who live on-site within a residential apartment building provide a value-added benefit to the management in the form of cost control and revenue maximization.

This research uses two large US data sets that cover operational and financial data of apartment owners/operators and the financial and individual housing situations of renters themselves. The regression models developed were general linear models with operating expenses, rent collection and monthly rent paid as dependent variables, with on-site resident manager status as the experimental variable.

This research finds that the value of on-site property managers does not definitively maximize rent revenue, as expected. On-site property managers also don’t show significant reductions in operating expenses, although they are not cost centers either. Individual renter households do, however, pay a significant rent premium for units in communities with on-site personnel living there.

The limitations of this research include the inability to merge the two data sets and the inability to measure the intangible attributes of the on-site residential manager’s experience.

As roughly 30 per cent of US rental apartment buildings have some form of on-site manager, this research has some practical implications for multifamily housing investors/owners, a highly visible US building sector.

The action of hiring an on-site residential property manager also addresses issues related to the optimization and efficient allocation of human resources for property management companies.

This appears to be the first research addressing property managers who live at the site where they also work.

The purpose of this paper is to explore the extent that interest subsidies have impacted on the total production of Swedish single‐ and multifamily houses. It also intends to examine whether tenure neutrality provision of interest subsidy that subsidy policy advocates was maintained.

Using a multiple regression of two models, a balanced panel data from 1975 to 2006 that consist of various related construction cost variables of all regions of Sweden will be analyzed. Instrumental variable (IV) and seemingly unrelated regressions (SUR) will be utilized to examine the role of subsidy on housing production and tenure neutrality, respectively.

The results seem to indicate that a general subsidy is expected to be ineffective since it may increase the existing stocks of a low demand region but not the housing stocks of big regions where the demand is high. Moreover, a targeted subsidy may change the balance between different types of housings since lower construction costs due to the subsidy could favor the development of certain profitable housing types.

The paper tries to substantiate (empirically) the assertion that subsidy policies contributed both to the production of housing units in low demand regions and distortion of the preference of different tenures.

The primary purpose of this study is to identify whether there is a price premium and consumers’ preferences for higher housing density, and whether there is a relationship between housing densities and sales prices. The second purpose was to identify if there is a non-linear relationship between housing density and prices even though housing density is directly associated with housing prices.

This paper applies hedonic modeling techniques to measure the value of development density of apartments in the metropolitan area of Seoul, South Korea. The regression of the sale price is a function of different types of variables such as density, market, location and other control variables.

For the first question, this paper concludes that the higher densities cause housing prices to decrease in Seoul. The summary of the results presents that housing density, floor area ratio (FAR), building coverage ratio and floor level are all important components affecting housing prices. Generally, consumers tend to buy housing with central heating systems, more parking spaces, smaller portion of rental housing within an apartment and buildings that have more of a mixed-use function. Consumers are also found to pay higher premiums for housing in areas with high population growth and less housing supply. It is conclusive that people are inclined to live in populated areas but do not want more density. For the second question, the results show that generally FAR has quadratic effects, but most housing density variables tend to have a non-linear relationship depending on the different quantile groups.

There is a knowledge gap in the area of estimating development density of apartments. Generally, studies investigating property value impacts of multifamily housing focus on external effects of the multifamily housing on home values to examine whether high density development could result in a decrease in nearby property values. These studies found that there are some positive effects. A study found that high-density housing increases property values of existing single-family homes (Joint Center for Housing Studies, 2011). More specifically, developments that are of a high design quality and superior landscaping increase values of single-family homes as well. Also, those residents who live in these high-density apartments can be good potential buyers for the existing single-family homes. The greater the number of buyers, the greater the housing market becomes. Similarly, according to a report by the Joint Center for Housing Studies (2011) at Harvard University, the presence of multifamily residents correlates with higher home values in “working communities”. Indeed, density can be an important factor determining value of apartments because of its unique characteristics. However, no empirical evidence has been provided in the literature with regard to the value of the development density. This study contributes toward improving this knowledge gap.

This study aims to examine the impact of housing construction on single-family housing values and the implications for urban development.

To achieve this objective, the author used the difference-in-difference methodology to examine the effect of multifamily and single-family housing construction on surrounding single-family homes in Stockholm, Sweden. The author analysed data from approximately 480 housing construction projects between 2009 and 2014 and 17,000 single-family detached house transactions between 2005 and 2018.

The research found that multifamily construction projects did not affect the value of surrounding single-family homes, while single-family home construction had a negative impact. The author attributes this result to single-family housing projects typically located in areas with initially positive externalities, while multifamily housing projects are often located on the edge of areas with negative externalities before construction.

The research is limited by its focus on a specific geographic area and time frame, and future research could expand the scope to include other cities and regions and different periods. Additionally, further research could examine the impact of housing construction on other economic factors beyond housing values.

The research has practical implications for urban planners and policymakers. They should consider the potential negative impact of new single-family home construction on existing single-family housing areas while balancing the need for new housing in urban areas. By carefully evaluating construction locations, policymakers can create more sustainable, livable and equitable urban environments that benefit all members of society.

This research paper contributes to the field of housing economics by examining the impact of housing construction on single-family housing values in the context of urban development and climate change mitigation. Using a difference-in-difference methodology, the study provides evidence of the price effect of multifamily and single-family housing construction on surrounding single-family homes, which has important policy implications for urban planners and policymakers. By identifying the negative impact of single-family home construction on surrounding areas and highlighting the need for careful evaluation of construction locations, the research provides valuable insights for creating sustainable, livable and equitable urban environments that benefit all members of society.