Housing Investment Research Articles

Tenure security and housing investment: Owner-occupants and renters in Bangladesh's poor settlements

This paper explores the relationship between land tenure security and housing investment among households in Bangladeshi poor settlements. The level of housing investment is measured through the type of physical structure of the house, or more specifically, floor materials. Cluster-robust standard error logistic regression method is utilized to explore this relationship in order to fix the issue of households located in the same settlement being correlated with each other. The results show that houses with greater tenure security, whether owner-occupied or rented out, are more likely than houses with insecure tenure to have cement floors, which are more permanent and expensive than other types of floors like bamboo, wood, or dirt/mud. Importantly, renters are more likely than owner-occupants to have cement floors. In sum, although greater tenure security may positively impact housing investment, the market force in which housing is seen as a business opportunity may be an equally strong factor in encouraging investment even in poor communities.

Dreaming of a Remittance House: Understanding Transnational Housing Aspirations

Migrant housing investments in the countries of origin are a demonstration of their transnational engagement and their potential contribution to local development. Yet, these investments remain relatively understudied on a large scale. In this paper, we explore three related questions on the drivers, prevalence, and development of transnational housing, drawing on an original survey of Ecuadorian and Indian migrants in different European cities. First, what factors account for the likelihood of migrants owning a remittance house? Second, for those migrants without houses abroad, what factors account for the likelihood of aspiring to have a remittance house in the first place, as opposed to “not being interested”? Third, how do factors affecting the likelihood of owning a remittance house compare to those affecting the likelihood of being a remittance house dreamer? Our findings suggest that, among those without a remittance house, the likelihood of being a transnational house dreamer decreases with the length of residence abroad, while the length of stay has no statistically significant impact on the likelihood of transnational house ownership. We also find that migrants with greater economic capacity are less likely to be dreamers and more likely to be transnational house-owners, suggesting that the difference between being a transnational house-dreamer and a transnational house-owner is often financial. Finally, greater attachment to the country of origin increases the likelihood of being both a transnational house owner and a transnational dreamer. We also discuss how the results change across migrant groups and across genders.

Beyond luck: The key to profitable residential real estate investments for individual investors in Türkiye

Individual residential investors are influenced by the media and their environment in their investment preferences, as they lack the experience of property investors and professional residential investors. Concerns about regret, fears of further property price rises and social circumstances put pressure on investors. Under these conditions, are individual housing investors seeing all the opportunities in the housing market? What types of buyers are taking advantage of these opportunities? This study aims to create tools to help individual residential investors identify opportunity periods in the market, analyse such opportunities retrospectively and test consumer behaviours in response to these opportunities. We analysed the opportunity for access to housing, the opportunity of lower loan interest rates and the opportunity of lower housing prices in Türkiye in the 120 months between 2013 and 2022 using the income-housing price scale. We analysed residential sales (total, credit and cash) in the opportunity periods resulting from the equations set up for the opportunity periods. We tested the criteria for selecting opportunity periods using the analysis of variation (ANOVA) method. We analysed changes in consumer preferences for credit and cash home purchases during periods of opportunity. We found that residential investors did not use the opportunity of accessing residential properties, and that cash home buyers used the opportunities of residential loan interest rates and residential price declines. We analysed changes in consumer preferences for credit and cash home purchases during periods of opportunity. We found that residential investors did not use the opportunity of accessing residential properties, and that cash home buyers used the opportunities of residential loan interest rates and residential price declines.

Public private partnerships and water and sanitation infrastructure development in Zimbabwe: what determines financing?

BackgroundZimbabwe envisions being an upper-middle-income economy by the year 2030. The vision 2030 has infrastructure development as a stand-out pillar upon which it is founded. The vision envisages well-developed, modern, efficient and resilient infrastructure as paramount to Zimbabwe’s economic recovery. The policy plan seeks to increase infrastructure investments in energy, transport, information technology, tourism, housing, and water and sanitation. However, a still hesitant private sector exists with regard to investment in water and sanitation infrastructure even in developed countries. Thus, the study seeks to analyse determinants of financing water and sanitation public private partnerships in Zimbabwe given that there is no consensus between reseachers on how determinant factors impact PPP investments.MethodsThe study applied Tobit regression methodology on data collected for the 25 years ending 2021 to investigate determinants of financing water sanitation PPPs in Zimbabwe. Tobit regression method is preferred given the censored nature of the investment values of water and sanitation public private partnerships that reached financial closure in Zimbabwe.ResultsIn Zimbabwe, financial market development is a key financing determinant of water and sanitation public private partnerships. Both the capital and bank market development influences infrastructure financing in Zimbabwe`s water and sanitation sector. Moreover, foreign direct investment negatively and significantly relates with water and sanitation public private partnership investments.ConclusionAttracting private investment into Zimbabwe`s water and sanitation sector requires that policy design targets capital and bank market development. Reforms can be achieved through putting in place sound frameworks that facilitate effective financial intermediation systems, enhance market liquidity and lower cost of capital.

Discrete-event simulation modeling for housing of homeless populations.

The San Francisco Bay Area has experienced a rapid rise in homelessness over the past decade. There is a critical need for quantitative analysis to help determine how to increase the amount of housing to meet the needs of people experiencing homelessness. Noting that the shortage of housing available through the homelessness response system can be modeled as a queue, we propose a discrete-event simulation to model the long-term flow of people through the homelessness response system. The model takes as input the rate of additional housing and shelter available each year and delivers as output the predicted number of people housed, sheltered, or unsheltered in the system. We worked with a team of stakeholders to analyze the data and processes for Alameda County in California and use this information to build and calibrate two simulation models. One model looks at aggregate need for housing, while the other differentiates the housing needs of the population into eight different types. The model suggests that a large investment in permanent housing and an initial ramp up of shelter is needed to solve unsheltered homelessness and accommodate future inflow to the system.

주택시장과 거시경제의 관계에 관한 실증분석

The purpose of this paper is to analyze the relationship between the housing market and the macroeconomy using macroeconomic variables, and housing price variables of South Korea from the first quarter of 1991 to the fourth quarter of 2021. In consideration of the macroeconomic transmission mechanism of housing price fluctuations, I built a VAR model with variables such as real GDP, private consumption, housing investment, private credit, policy interest rate, and housing transaction price. In respect of the impulse response, the result of the analysis showed that housing prices rose when real GDP, private consumption, housing investment, and private credit had risen. When housing prices rose, real GDP, prices, private consumption, private credit, and policy interest rates rose. As a result of forecast error variation decomposition, I found that the contribution of changes in housing prices to changes in each variable was not significant, but changes in real GDP and interest rates had a major impact on changes in housing prices. In the historical decomposition I performed, the contribution of policy interest rates to fluctuations in housing prices was also high. In particular, private credit was considerably affected by the rapid increase in housing prices in 2020. Based on the above results, I found that the increase in housing prices had a relatively long-term impact on the credit market but a poor impact on the real economy through increased consumption and housing investment, while I confirmed that the GDP and interest rates had a major effect on changes in housing prices.

전국 주택구매력지수(HAI)의 변화가 지방 주택매매시장에 미치는 영향에 관한 연구

This study analyzed the effect of changes in the national housing purchasing power index on the local housing sales market, which is recognized as a heterogeneous market with the metropolitan area. The analysis method used the Vector Error Correction Model in consideration of the time-series observation characteristics of the main variables of this study. The summary and implications of this study are as follows.
 First, if housing prices in the metropolitan area soar and housing investors' investment capacity in the metropolitan area decreases, it is estimated that they are interested in the local housing market with relatively high price benefits. In particular, the effect of the change in housing purchasing power is expected to occur mainly in the housing market in local hub cities. Second, it can be seen that the local housing market is most affected by income increase through economic growth in the long run. Third, the total population of Jeollabuk-do is expected to gradually flow out due to the concentration of the economy in the metropolitan area, and the trend of aging is expected to increase rapidly. However, Jeonju, a hub city, is expected to show a significant difference in the housing sales market depending on regional characteristics, such as the continuous influx of population. Finally, unlike the results of a study conducted on the housing market in the Seoul metropolitan area, changes in major macroeconomic variables such as interest rates excluding economic growth did not have a significant effect. This result is judged to be because local housing prices have a very low price level compared to the metropolitan area, so the merit as investment goods or inflation hedging is not high.

“We know what's going on in our community”: A qualitative analysis identifying community assets that deter gun violence

Communities of color are disproportionately impacted by gun violence. Unlocking potential community-led solutions could be the key to quelling the gun violence epidemic and its impact on these communities. In this qualitative study, we explored community perspectives on local assets that may prevent and mitigate gun violence. We conducted semi-structured, in-depth interviews (n ​= ​45) among individuals not directly involved in gun violence (i.e., shooting victim or perpetrator) despite having a high probability of being involved in gun violence in New Haven, CT. Participants were asked to describe social structures that may deter local gun violence. Here, we report emergent themes to preventing gun violence across multiple levels, including role models (interpersonal), social cohesion and home ownership (neighborhood), and community-based organizations (organizational). Our findings suggest that investments in stable housing, efforts to build social cohesion, access to community-based mental health services, and youth activities are needed to curb the drivers of community gun violence.

Macroprudential policy and household wealth inequality: Evidence from China

The influence of LTV ceiling on household wealth inequality is not constant. This paper finds that when the return on housing investment is higher than the return on liquid assets, the LTV ceiling generally has a negative impact on household wealth inequality; otherwise, it is more likely to be positive. Increasing the LTV ceiling can significantly alleviate household wealth inequality in China. Housing price and the number of houses purchased are important channels, and the house purchase preference (savings rate and house purchase intention) plays a key role in regulating wealth distribution through the LTV ceiling.

Forecasting housing investment

AbstractThis study applies a model averaging approach to conditionally forecast housing investment in the largest Euro area countries and the Euro area. To account for substantial modeling uncertainty, it estimates a large and diverse number of vector error correction models using a wide set of long‐ and short‐run determinants and applies subset selection based on in‐sample and out‐of‐sample criteria. First, a pseudo out‐of‐sample forecast exercise shows that our model averaging approach consistently beats a battery of distinguished benchmark models, including BVARs, FAVARs, LASSO, and Ridge regressions. This evidences that model averaging provides more accurate forecasts also in the case of housing investment. Second, we find remarkable cross‐country heterogeneity in the drivers of housing investment. Overall, these findings guide forecasters and modelers on improving housing investment models and policymakers on implementing country‐specific housing market policies.

Speeding up risk capital allocation to deliver net-zero ambitions

Chris Greig is the Theodora D. ('78) and William H. Walton III ('74) Senior Research Scientist at the Andlinger Center for Energy and the Environment at Princeton University. His academic career follows 28 years as a senior executive in the energy and industrial sectors, developing large energy and industrial projects throughout the Asia-Pacific. His research focuses on the feasibility and implementation of large-scale energy transitions taking a systems perspective across energy systems analysis, business, social sciences, and policy. He was a principal investigator on Princeton's recent Net-Zero America study and co-leads similar efforts in Australia and Asia. David Keto is managing principal of SRI Group, a responsible investment consulting firm. Prior roles include chief operating officer for New Tower Trust, the bank trustee for the Multi-Employer Property Trust, a multi-billion-dollar socially responsible real estate fund. Prior to that, he served as chief operating officer for the AFL-CIO Investment Trust Corporation and as general counsel and chief of staff for the AFL-CIO Housing Investment Trust. He also served as undersecretary for the Massachusetts Executive Officer of Economic Affairs and as special counsel to the Boston Redevelopment Authority. He holds degrees from Princeton University and Yale Law School. Scott Hobart is chief investment officer at Mercator Partners, a sustainability-focused asset manager based in Princeton, New Jersey. Mercator invests across public equity markets globally with a focus on identifying sectors and business models that support the urgent need to decarbonize asset-heavy industries. The investment process at Mercator draws heavily on insights from academia and national laboratories. Benjamin Finch is an undergraduate senior in the Department of Electrical and Computer Engineering at Princeton University. Ryan Winkler is an undergraduate junior in the Department of Economics at Princeton University.

How ‘bad’ is renter protection for institutional investment in multifamily housing?

We assess the role of state-level renter protection regulations on the pricing, performance and risk of multifamily housing. We construct a renter protection score (RPS) to measure the extent of renter protection in each state. Using a proprietary property-level dataset from loans backed by commercial mortgage backed securities (CMBS) and census tract socioeconomic variables, we study the role of RPS on initial capitalization (cap) rates, annual net operating income (NOI) and annual loan delinquency rates of multifamily housing. We find that, contrary to conventional wisdom that renter protection is ‘bad’ for investors, multifamily housing in high RPS states is associated higher annual NOI and NOI growth and lower delinquency rates. We also show that better tenant protection is associated with lower initial cap rates. The results point to investors perceiving properties in more regulated states as lower risk due to reduced income volatility. For institutional investors, higher levels of renter protection are, therefore, not ‘bad’ but are instead associated with lower cash flow volatility and better income growth prospects.

Housing Price and Interest Rate Hike: A Tale of Five Cities in Australia

Australian housing prices are reported to be overvalued and unaffordable for the past two decades. Many researchers and practitioners have attributed the persistent growth in housing prices to the prolonged period of low borrowing costs. However, due to inflationary pressure, the Central Bank has raised its cash rate consecutively in recent months. This paper aims to examine whether interest rate rises affect housing price in different parts of Australia. Evidence generated from the analysis reported bipolar results between the large and smaller cities, whereby housing prices in Sydney and Melbourne show a significant negative relationship with interest rate changes while Brisbane and the Gold Coast and Perth and Adelaide, respectively, are showing negative but insignificant results during the study period. Short-run trend projections on housing prices indicate that Sydney, Melbourne, Brisbane and the Gold Coast are on a downward trend while Adelaide and Perth will maintain its current momentum before plateauing out later next year. Likewise, control variables, such as oil prices, inflation rate and stock market performance, are found to be related to housing prices in larger cities only. These findings have implications on housing policy, house purchase decisions and investment portfolio management strategy.

“Home away from home” in pandemic times: how has COVID-19 changed the Airbnb market in Melbourne?

PurposeThis study aims to investigate how the COVID-19 pandemic has impacted and changed Airbnb market in the Greater Melbourne area in terms of its temporal and spatial patterns and identify possible shifts in underlying trends in travel activities.Design/methodology/approachA panel data set of Airbnb listings in Melbourne is analysed to compare temporal patterns, spatial distribution and lengths of stay of Airbnb users before and after the COVID outbreak.FindingsThis study found that the COVID disruption did not fundamentally change the temporal cycle of the Airbnb market. Month-to-month fluctuations peaked at different levels from pre-pandemic times mainly because of lockdowns and other restrictive measures. The impact of COVID-19 disruptions on neighbourhood-level Airbnb revenues is associated with distance to CBD rather than number of COVID cases. Inner city suburbs suffered major loss during the pandemic, whereas outer suburbs gained popularity due to increased domestic travel and long stays. Long stays (28 days or more, as defined by Airbnb) were the fastest growing segment during the pandemic, which indicates the Airbnb market was adapting to increasing demand for purposes like remote working or lifestyle change. After easing of COVID-related restrictions, demand for short-term accommodation quickly recovered, but supply has not shown signs of strong recovery. Spatial distribution of post-pandemic supply recovery shows a similar spatial variation. Neighbourhoods in the inner city have not shown signs of significant recovery, whereas those in the middle and outer rings are either slowly recovering or approaching their pre-COVID levels.Practical implicationsThe COVID-19 pandemic has significantly impacted short-term rental markets and in particular the Airbnb sector during the phase of its rapid development. This paper helps inform in- and post-pandemic housing policy, market opportunity and investment decision.Originality/valueTo the best of the authors’ knowledge, this is one of the first attempts to empirically examine both temporal and spatial patterns of the COVID-19 impact on Airbnb market in one of the most severely impacted major cities. It is one of the first attempts to identify shifts in underlying trends in travel based on Airbnb data.

Access to Decent Housing in Congolese Urban Areas: Evolution of Associated Factors between 2005 and 2016

The proportion of decent housing found from the data of the 1-2-3/2012 DR Congo survey in urban areas is 7.8%. This situation prompted us to conduct a study on the evolution of factors associated with access to decent housing in urban areas of the DR Congo, based on data from the 1-2-3/2005, 1-2-3/2012 and E-QUIBB/2016 surveys, in order to identify the factors that are determining over time over these three periods. Our specific objectives are to indicate the proportion of decent housing in urban areas of the DR Congo from 2005 to 2016, to find the factors associated with access to decent housing in urban areas of the DR Congo over the three periods, and to study the evolution of these associated factors. In 2005, 2012 and 2016, the proportions of decent housing in urban areas of the country were respectively 4.1%, 9% and 12.3% respectively. The associated factors (in relation to the head of the household) acting over the three periods are: province of residence, socio-professional category, age, housing occupation status, education and gender. These six determinants all evolved over time, resulting in an overall increase in decent housing of about 8%. These results showed that in DR Congo there is not enough investment in housing. Thus, investment by the State and other partners in the construction of low-cost housing, and the facilitation of land and property loans and investment loans, will enable vulnerable social groups, such as young people of both sexes throughout the country, to have easier access to decent housing.

Airbnb as a Novel Housing Investment Option

Airbnb as a Novel Housing Investment Option

Forecasting Housing Investment

Forecasting Housing Investment

Are remittances a solution to housing issues? A case study from Sri Lanka

The objective of this paper is to analyze the impact of remittances on four different aspects of housing investment – expenditure, affordability, quality and household assets in Sri Lanka. Housing expenditure is calculated based on the household expenditure on housing rent, house building or repair cost, and utility bills, while housing affordability is measured by shelter poverty index. The housing quality index is developed based on the structure of the dwelling unit, housing services, and the location. An overall assets index was developed using 45 household assets. The house's location is crucial to enhance the quality of housing, location-based characteristics were considered in constructing the housing quality index. Receiving remittances has a self-selection issue since it is not a random process. The propensity matching score method was employed in the current study, overcoming the issue of self-selection. The study finds that though there are differences between sectors and income groups, remittances positively and significantly affect housing expenditure, affordability, and assets, but the impact on housing quality is minimal. The findings give insight into the areas, in which policymakers can focus to improve the impact of remittances on different aspects of housing and thereby reach SDG targets of “leaving no one behind”.

Short-Term Forecasting Housing Investment: An Averaging Approach from a CEE Country

Short-Term Forecasting Housing Investment: An Averaging Approach from a CEE Country

ANALISIS INVESTASI PERUMAHAN PURI MAHKOTA MUKTIWARI DI KABUPATEN BEKASI

As the population grows rapidly and the standard of living increases, the demand for housing will increase. One way to meet housing needs is to build housing. Housing development must be in accordance with careful planning in determining the investment model to be made in housing development. The initial stages of housing development start from surveying the location, number and type of houses to be built, marketing, to selling to consumers. The housing development process must also be calculated economically with the investment method, to find out whether this housing can be economically profitable or not. Based on the calculation of investment analysis with an investment period of 6 years, the Net Present Value (NPV) is Rp. 33,716,228,908 (NPV0), the Internal Rate of Return (IRR) is 23,18% (IRRMARR), Payback Period (PP) in the 3rd year to 11th months is smaller than the 6 year investment period, Benefit Cost Ratio (BCR) is 1.42 (BCR 1), and Break Event Point (BEP) gets a percentage for type 30/60 of 90% with 132 units, type 36/60 by 69% with 207 units, type 36/72 by 56% with 172 units, and type 48/84 by 48% with 32 units. And from the sensitivity analysis results it is known that housing investment Puri Mahkota Muktiwari will still be feasible if the increase in investment costs is less than 20.15%, the decrease in the occupancy rate is not more than 16.74%, the decrease in the selling price level is not more than 16.7% and the increase in loan interest rates is less of 122.22%.Keywords: Investment Feasibility,Housing, industrial estate, Investment analysis, Sensitivity Analys