Residential Assets Research Articles

Estimating Direct and Indirect Damage to Industrial Facilities from Coastal Flooding: Case of Ulsan, Korea

As climate change accelerates, the damage caused by natural disasters to logistics and industrial facilities near coastal areas is expected to increase. This study estimates the economic damage caused by coastal inundation in Ulsan Metropolitan City in detail, based on the frequency of inundation and building types. An object-based analysis is conducted to calculate the damage by building type, and the results show that the ripple effect of the disaster accounted for the majority of the total damage. Ulsan's major industrial clusters are concentrated along the coastline, with factories accounting for 92% of the total direct damage. The results of an input-output analysis based on industry linkage tables showed that the indirect damages were 22.1, 8.6, and 3.8 times greater than the direct damages for petrochemicals, automobiles, and shipbuilding, respectively, which represent the main industries in Ulsan. The automobile industry has a large impact on employment, with ripple effects on both directly related industries and other industries. Unlike residential assets, industrial assets exhibit different damage characteristics, depending on whether coastal inundation affects a specific industry or the entire sector. Coastal areas are densely populated with multiple industries. Hence, the ripple effects on assets and employment are significant. Therefore, it is important to accurately identify industries that are highly interdependent with others in the development of effective disaster preparedness and recovery policies. The results of this study can be used as a basis for cost–benefit analyses of climate change disaster measures and policies in coastal cities.

Development of mechanics-based fragility curves for the Italian masonry school asset

This article presents the derivation of a fragility model for the Italian masonry school building asset, comprising 265 sets of fragility curves for as many building types, classified on the basis of few parameters: construction age, number of stories, plan area, and type of masonry (i.e. with regular or irregular pattern). The fragility assessment was carried out by means of parametric analyses, generating more than 7500 samples which were then analyzed through the mechanics-based procedure Vulnus. Sample fragilities were then linearly combined to obtain fragility curves consistent with the adopted taxonomy based on few parameters. A macroseismic–heuristic model from the literature was used to extend the fragility model to five damage states, according to the European Macroseismic Scale (EMS98). The proposed model was compared to empirical information in terms of observed damage on three existing schools and fragility curves recently derived by processing data of school damaged by the 2009 L’Aquila earthquake, showing a satisfactory agreement. In addition, a comparison with fragility sets for residential buildings was carried out. Both fragility models were developed with the same procedure, so as to point out differences between schools and ordinary buildings. Similar fragilities were observed for schools and residential buildings built before 1945, whereas for later periods, schools showed a higher fragility than the residential asset. Finally, seismic damage maps were developed at national scale showing the distribution of expected damage as a possible application of the derived model.

Is religion an inferior good? Evidence from fluctuations in housing wealth

An increase in local house prices in the US is associated with a decrease in the time homeowners spend on religious activities compared to renters. Notably, this effect is not observed in volunteering and civic activities. The decline in religious activities is more pronounced for credit-constrained households. The main result is attributed to a wealth effect, whereby activities that have an inferior-good component decline with housing wealth, and to a substitution effect whereby the attractiveness of activities linked to the residential asset increases during housing booms.

Assessing the Suitability of the Flood Defense Policy of Republic of Korea for Risk Reduction in Local Rivers

This study examines whether the fluvial flood defense system of Korea is appropriate for risk reduction. Using spatial socioeconomic data and remote sensing, we estimated the potential economic damage that can be caused by the flooding of local streams and rivers along the Nakdong River (the longest river in Korea). For the analysis, a river risk map including return periods (50, 80, 100, and 200 years) and spatial inventories (residential, agricultural, industrial assets, and human lives) was employed to determine flood-prone areas and assess the damage within the inundation areas. A quantitative flood analysis was conducted using an object-based method to estimate the expected annual damage. We then compared the estimated damage for each tributary within the designed return periods and found no correlation. Numerous tributaries with low-defense targets were considered high-risk, while those with high-defense targets were assessed as low-risk. The dataset used in this study covered four damage categories. Among them, flood damage to residential assets appeared to have the highest value, whereas flood damage to industrial assets had the lowest value. The results demonstrate that the Korean government needs to tailor its flood defense policy based on quantitative risk assessments to effectively manage flood risks, especially given the increasing risk of climate change.

Housing in the greater Paris area as an inflation hedge?

PurposeOver a long period, even low inflation has an impact on portfolio value and households’ purchasing power. In such a context, inflation hedging should remain an important issue for investors. In particular, long-term investors, who are concerned with the protection of their wealth, seek to hold effective hedging assets. This study aims to demonstrate that residential assets in “Grand Paris” are a hedge against inflation and particularly against its unexpected component.Design/methodology/approachIn this study, the physical residential markets in 127 communes in Paris and the Parisian first-ring suburbs are considered as potential asset classes. We simplified the analysis by clustering the 127 communes into five homogenous groups using ascending hierarchical classification (AHC). Then, we test the hedging ability of these groups within a mixed asset portfolios using both correlation and regression analysis.FindingsThis paper presents an analysis of the “Grand Paris” housing market and its inflation hedging ability with comparison to other financial asset classes. Results show that the five housing groups act as a highly positive hedge against unexpected inflation. Furthermore, cash and bonds seem to provide, respectively, a partial and an over hedge against unexpected inflation. Stocks act as a perverse hedge against unexpected inflation and provide no significant hedge against expected inflation. Also, indirect listed real estate demonstrates little correlation with inflation, which makes us reject its hedging ability contrary to physical residential real estate.Research limitations/implicationsThe inflation topic: although several researches exist that question the hedging property of real estate, very few concentrate on physical residential assets and to the best of the authors’ knowledge, this study is the only one that targets the “Grand Paris” area. Residential assets of the “Grand Paris” communes are confirmed to be a hedge against inflation and particularly against its unexpected component thanks to its capital appreciation rather than income one. Also, we show that the listed real estate in France (Sociétés d’Investissement Immobilier Cotée) does not provide the same hedging properties contrary to the US real estate investment trusts (REITs) who demonstrate this ability. Listed real estate could thus not be used interchangeably with housing to protect from inflation in the French market.Practical implicationsProtection of investors against inflation and in particular in the face of its return to France in 2022. Reassuring promoters and investors of the interest of residential investment projects in “Greater Paris” and of the potential that this holds.Social implicationsInflation takes a chunk out of the purchasing power of money and thereby erodes the real value of people’s finance. Investors and households who seek protection from inflation erosion should invest in direct housing, and in particular within areas that are experiencing an effective metropolization process.Originality/valueThe originality of the study is precisely relative to the geographical area studied. The latter has experienced favorable economic conditions for several years and offers interesting fundamentals to explore and exploit in investment strategies that prove capable of protecting against imminent inflation. The database is specific to this project and has been built through the compilation of several sources and with the support of BNP Paribas Real Estate.

Optimal Structure of Real Estate Portfolio Using EVA: A Stochastic Markowitz Model Using Data from Greek Real Estate Market

The purpose of this paper is to examine the issue of portfolio optimization. Optimization consists of minimizing the risk for a given rate of return or achieving a bigger return for a given level of risk. We use historical data from the Bank of Greece to calculate the net return and the standard deviation (std) for each type of property that is available. The objective is to maximize the economic value added (EVA) of a property’s assets portfolio under a specific rate of standard deviation, following the classic Markowitz model (M-V). The stochastic procedure entry in the model uses the Monte Carlo Simulation method with debt to equity (DTE) following PERT distribution for the portfolio’s invested budget, and the net return for the normal distribution with the mean of the expected return and std are taken from historical data, correspondingly. The returns verify that they follow the base assumption of normality through the Lilliefors test in the Greek real estate market. We observe the maximization of EVA and the expected return maximizing concurrently, but the minimizing risk of EVA is diversified with the minimization of portfolio risk. We observe that the max weight that a residential asset takes is 22.7% because a bigger percent reduces both mean and std. The study provides an explicit portfolio optimization procedure under uncertainty in the real estate market and enriches the academic debate about EVA and revenue.

Optimal home energy management including batteries and heterogenous uncertainties

Energy storage will play a vital role in the decarbonization of the electricity sector, especially in domestic installations. In such kind of systems, home energy management applications are becoming essential. These kinds of tools enable active control of domestic appliances and storage systems to pursue a more efficient use of energy in household installations. However, the emergence of renewable generators and electric vehicles makes the operation of residential assets more difficult, as multiple uncertainties should be managed on a whole. These unknowns have a different character, in fact, some of them can be easily predicted while others are subject to a high level of randomness. This paper addresses this issue by developing a novel home energy management tool that accounts for the different levels of the randomness of the uncertainties involved in home operation. To this end, a novel Lexicographic-Interval formulation of the home energy management problem is presented, by which the uncertainties can be easily modelled using interval notation. Unlike conventional tools, the new proposal sorts the uncertainties according to their level of randomness. Then, the energy management mechanism performs the scheduling plan according to the predefined classification so that the more random parameters rule the impact of others, thus giving more importance to those uncertainties that are hardly predictable. A benchmark case study is performed to validate the new proposal and illustrate its capabilities. Different tariffs are compared, showing that the Time-of-Use mechanism is normally more expensive than Real-Time-Pricing tariffs, increasing the electricity bill by 12 % in some cases. However, the level of robustness achieved with Time-of-Use tariffs seems higher, allowing to assume an abruptly unexpected reduction of photovoltaic generation.

Housing and Setting Constraints: The Portuguese Evidence

In the last few decades, Portugal has witnessed an extraordinary quantitative and qualitative transformation in housing provision. The pace of housing construction was so extensive that the contemporary real estate market is currently characterized by an excessive supply, vis-à-vis the resident population. In this study, we discuss the impact of the financial process on the housing sector in comparison with tenancy. We consider transaction prices of the housing assignments, either through acquisition or through tenancy. The recent shock resulting from the pandemic situation did not slow down house prices but caused a slight drop in rents. The model used proposes to analyze the fluctuations in prices and rents in the face of external shocks. In the residential market, the estimation is complex due to the many heterogeneous attributes of residential assets. Non-fluctuating variables, such as size, location, and external demand for homes, explain a large part of the variation in price levels included in the model.

Data-driven decision support system for building stocks energy retrofit policy

In most European countries, residential assets account for as much as 85% of the building stock floor area and are, on average, very outdated and energy inefficient. Moreover, the European Commission published the EU Green Deal invigorating higher retrofit of private and public buildings. Nowadays, public authorities collect extensive datasets to analyze the existing building stock; however, the complex and diverse scenario makes the definition of retrofit policies cumbersome. The biggest hurdle is often linked to the high cost of acquiring information. The presented research tries to overcome these issues by introducing a decision support system for retrofit policymaking from low-cost data-driven approaches. The method is based on: i) clustering techniques to divide building assets into groups with similar characteristics and energy consumption, and ii) Montecarlo simulation to compute each cluster's energy savings based on different retrofit scenarios. The proposed method has been successfully applied to an extensive portfolio of residential assets in Lombardy Region in Italy, called the CENED database, with over one million assets. As a result, the introduced method defines the optimum retrofit scenario with a low cost of information (e.g., without expensive surveys to gather data on existing assets' characteristics and performance indicators) and determines the number of assets to be retrofitted along with the expected energy savings. This data-driven approach can be easily updated given new renovations and status changes in the built environment, making it useable for the long term or in different regions. To summarize, data-driven solutions are now required to accomplish the European Union's decarbonization ambitions, and the proposed method helps decision-makers choose better energy retrofit policies for the built environment.

Real Estate Insights Safe as houses? Thinking on the rise of investment into UK residential markets

PurposeIn recent decades, institutional investment has become increasingly focussed on residential property in the United Kingdom, reflecting interest in what was previously considered an “alternative” asset class, but is now an evolving and ever more complex sector. This short thought piece considers how such processes may be understood through investment-related research.Design/methodology/approachThe UK residential market has experienced substantial capital inflows in the wake of the global financial crisis. This reflective piece suggests there is a need for more research into residential real estate as an institutional asset class to further unpack and understand shifting market dynamics within the United Kingdom. It offers insight into evolving market trends across a diverse range of investors and market sub-sectors.FindingsThis paper considers the diverse research opportunities within the residential investment markets, including, but not limited to, the private rented sector, build-to-rent and purpose-built student accommodation, presenting opportunities for burgeoning research.Practical implicationsThe viewpoint suggests how this research lacuna may be bridged through additional research in not just the UK residential market, but also how investors may further integrate and operationalise UK residential assets in diversified or specialised investments, from domestic to international propositions. The suggested research agenda promotes enhanced understandings of residential markets and processes driving investment decision-making.Originality/valueAs the integration of residential property into vehicles such as Real Estate Investment Trusts, private equity funds and managed multi-asset portfolios continues to increase, there is an amplified need to understand the market context in which such investment flows occur, including the potential impact of COVID-19, Brexit and the cyclical evolution of real estate markets more broadly.

An Automatic Tool for the Determination of Housing Rental Prices: An Analysis of the Italian Context

In the last decades, some global events such as the economic crisis of 2008 and the COVID-19 emergency of 2020, have generated more attention towards the housing rental market and its capacity to meet several social needs. In order to study the existent demand for houses, then define the interventions on the residential assets to make them more affordable for the most fragile population groups, adequate evaluation tools are required. With reference to the residential property segment of five metropolitan cities located in the Italian territory, the present research is aimed at analyzing the contribution of the most influencing factors on rental prices. In particular, this research refers to the rented properties of the second half of 2019, with a set of variables that represent the intrinsic and extrinsic factors of the local market. The implementation of an automated valuation model allows the determination of the most significant factors and the functional relationships that they have with housing rental fees. The outputs obtained could support the improvement of equitable public housing policies or could guide private investment decisions, such as refurbishment interventions of certain significant factors that could increase the market rental value. This study is the first step in wider research that is currently in progress, which aims to investigate the effects of the existing COVID-19 pandemic on the residential rental market.

All grown up? Market maturity and investment in London's purpose-built student accommodation sector

PurposeThe UK's purpose-built student accommodation (PBSA) sector has seen significant institutional investment in recent decades. This paper unpacks contemporary trends and perspectives on the sector. It questions whether PBSA has moved from being an “alternative” to “mainstream” residential asset class, framing the analysis through the lens of market maturity.Design/methodology/approachThe methods triangulate perspectives drawn from literature on the evolution of PBSA as an asset class with illustrations of investment trends across the UK between 2005 and 2020 using data from Real Capital Analytics (RCA), combined with findings from 40 semi-structured interviews with investors and stakeholders in PBSA in the UK London is the focus of the work, whilst other regional cities are integrated for comparison.FindingsThe results demonstrate that London's PBSA market is ahead of trends currently being replicated in regional cities. However, the regions currently offer greater return potential and opportunities for risk taking compared to London, where yields are compressed, and the market is considered lower risk. The concept of maturity remains useful as a framework for evaluating markets, however a more granular analysis of sectors is necessary to further understand asset classes within sectors. PBSA continues to trade at a premium across the UK; it is considered the most mature residential asset class.Practical implicationsThe emergence of PBSA as an asset class continues to play a developing role within the residential sector and UK investment market. Risk, value and local context remain key when integrating PBSA into institutional portfolios, and as the first to consider the UK market from a qualitative research approach, this research provides a snapshot of these influences in 2021.Originality/valueOur approach offers original insight into investment trends across the UK and is the first to focus reflections on the London market specifically. The research highlights the role of PBSA as a vanguard asset class for investors into residential, situating its growth within the framework of market maturity and drawing out market nuances from interviews.

Corporate focus, residential assets, and the performance of French REITs

AbstractThis paper raises the question of the specific impact of the share of residential assets on the performance of real estate investment trusts (REITs). In the literature, many articles questioning the importance of the nature of assets held in general (and residential assets in particular) do not take the level of diversification of REITs into account. We incorporate this factor into our analysis and integrate our measure of the effects of residential assets in a framework controlling for the impact of the diversification of the type of real estate assets held. Based on French data, we question whether REITs holding residential assets perform better than REITs holding little or no residential assets for a given level of diversification. We do not detect any significant diversification effect on the performances of French REITs. We also test the impact of asset diversification on REITs market volatility. We provide some evidence that firms with strongly concentrated balance sheets are more volatile than diversified firms, but this effect is weaker for REITs holding mostly residential rather than other types of assets.

ANALYSIS OF REAL ESTATE VALUATION METHODS (ON THE EXAMPLE OF RESIDENTIAL BUILDINGS)

One of the most important conditions for the viability, existence in this sector of the market, as well as a necessary condition for the functioning of the real estate market is the availability of information infrastructure. It, in turn, provides market participants with up-to-date, complete and reliable information, and also performs an effective analysis of real estate valuation methods, which will allow for a deeper, objective and complete assessment of land and residential assets

Stay or Return? A Study of Migrants’ Savings and Labor Supply Decisions

The large-scale migrant is a significant feature of China’s economy. In 2018, the migrant was 241 million, accounting for 17.28% of the total population, which means that one in every six people is the migrant. However, these migrants have been in a very “hard” state for a long time, characterized by “high saving rate” and “high labor supply”. This paper attempts to explain the above phenomena based on the hypotheses of labor inter-temporal substitution and settlement costs. The inter-temporal substitution hypothesis is also one of the basic theories in macroeconomics. It can also be applied and tested at a micro level, which is helpful to understand the laws of China’s overall macro savings and labor supply. In addition, the analysis of savings and labor supply decisions contributes to extrapolating the determinants of social welfare among the migrating population and giving some suggestions on supportive policies. Based on the theoretical model and the dynamic monitoring data of China’s migrants, this paper analyzes the impact of settlement intention and residential assets on savings and labor supply. The study finds that migrants intending to stay have a lower saving rate and less labor supply than migrants intending to return based on the consideration that their incomes tend to decline in the future, which supports the inter-temporal substitution hypothesis. Migrants with no house located in the place of immigration have a higher savings rate and more labor supply, which supports the settlement cost hypothesis. The reason for the high savings rate and more labor supply of migrants varies in different groups: Migrants who move alone and have lower skills work harder and consume less based on the inter-temporal substitution hypothesis, while those who move with the whole family and have higher skills tend to supply more labor and save more so as to afford settlement costs to integrate into the local society. For the former, the government can reduce the impact of inter-temporal substitution by narrowing the income gap between regions, actively promoting the employment of returnees nearby and helping them to start their own business. For the latter, the government should increase the effective supply of indemnificatory housing, improve the accessibility of public services for migrants, and reduce the restrictions on the settlement of certain groups, especially for those who have worked and lived in cities for more than five years, those who have moved with the whole family, and those with high skills. The contributions of this paper are as follows: First, on the basis of discussing the problem of high savings of migrants, it further explores the causes of high labor supply and analyzes the welfare conditions of migrants more comprehensively. Second, for the particularity of migrants, the income difference between the immigration and emigration places, as well as settlement costs, are included in the utility function. Third, it divides the migrants into two groups: those who intend to stay and those who intend to return, and further analyzes the heterogeneity of their behavioral motivation of saving and labor supply.

Private assets for public benefit: the challenge of long-term management of domestic rainwater tanks

Abstract This study explored the relationship private landowners have with their domestic rainwater tank and how that relationship influences the reliability of privately operated rainwater tanks for long-term performance and delivery of service. It found that tank owners generally placed a high value on their tank, desired to have them fully operational and made a reasonable effort to keep them functioning. However, the frequency and extent of maintenance action and effort was variable, and in the context of a private residence, rainwater tanks were typically afforded a low relative priority for repair when compared with other residential assets. This low relative priority could be a primary driver for the reported delay between when a fault occurs with the tank and when it is repaired. This ‘repair lag’ means that a portion of domestic rainwater tanks are likely to be non-operational at any one time. When planning a decentralised system for the management of stormwater, redundancies should be included to cover these gaps in service delivery. It is also recommended that programmes that support private landowners to maintain their rainwater tanks are implemented to minimise repair lag.

A probabilistic approach to estimating residential losses from different flood types

Residential assets, comprising buildings and household contents, are a major source of direct flood losses. Existing damage models are mostly deterministic and limited to particular countries or flood types. Here, we compile building-level losses from Germany, Italy and the Netherlands covering a wide range of fluvial and pluvial flood events. Utilizing a Bayesian network (BN) for continuous variables, we find that relative losses (i.e. loss relative to exposure) to building structure and its contents could be estimated with five variables: water depth, flow velocity, event return period, building usable floor space area and regional disposable income per capita. The model’s ability to predict flood losses is validated for the 11 flood events contained in the sample. Predictions for the German and Italian fluvial floods were better than for pluvial floods or the 1993 Meuse river flood. Further, a case study of a 2010 coastal flood in France is used to test the BN model’s performance for a type of flood not included in the survey dataset. Overall, the BN model achieved better results than any of 10 alternative damage models for reproducing average losses for the 2010 flood. An additional case study of a 2013 fluvial flood has also shown good performance of the model. The study shows that data from many flood events can be combined to derive most important factors driving flood losses across regions and time, and that resulting damage models could be applied in an open data framework.

Estimating exposure of residential assets to natural hazards in Europe using open data

Abstract. Natural hazards affect many types of tangible assets, the most valuable of which are often residential assets, comprising buildings and household contents. Yet, information necessary to derive exposure in terms of monetary value at the level of individual houses is often not available. This includes building type, size, quality, or age. In this study, we provide a universal method for estimating exposure of residential assets using only publicly available or open data. Using building footprints (polygons) from OpenStreetMap as a starting point, we utilized high-resolution elevation models of 30 European capitals and pan-European raster datasets to construct a Bayesian-network-based model that is able to predict building height. The model was then validated with a dataset of (1) buildings in Poland endangered by sea level rise, for which the number of floors is known, and (2) a sample of Dutch and German houses affected in the past by fluvial and pluvial floods, for which usable floor space area is known. Floor space of buildings is an important basis for approximating their economic value, including household contents. Here, we provide average national-level gross replacement costs of the stock of residential assets in 30 European countries, in nominal and real prices, covering the years 2000–2017. We either relied on existing estimates of the total stock of assets or made new calculations using the perpetual inventory method, which were then translated into exposure per square metre of floor space using data on countries' dwelling stocks. The study shows that the resulting standardized residential exposure values provide much better coverage and consistency compared to previous studies.

Understanding real estate investments through big data goggles

PurposeThis paper aims to develop a conceptual understanding and a methodological approach for calculating residential net initial yields for both a buy-to-hold and rental investment strategy from hedonic models.Design/methodology/approachThe markets modelled comprehend of dwellings for rent and sell in Germany. For each of them, two regression models are estimated to extract implicit prices and rents for an artificial identical dwelling and estimate the willingness to pay for the same asset from both a buy-to-hold and rental investment strategy.FindingsThe 3,381 estimated net initial yields in the 161 German markets showed a spatial pattern with the biggest and most attractive cities showing the lowest yields and a self-adjusting process in the markets surrounding the top cities. The net initial yields over time show that prices have increased stronger than rents, leading to rock bottom yields for residential assets and a significant premium in comparison to government bond yields. The approach responds to the spatial hierarchy of markets in Germany, meaning that the level of the estimated yields is accurate and achievable from an investment perspective.Practical implicationsThe investment case in residential markets is certainly unique as net initial yields are scarce, especially due to the relatively low number of investment comparables. The paper sheds light on this problem from a conceptual and methodological perspective and confirms that investment yields are deducible by making usage of hedonic models and big data.Originality/valueIn the era of digitalization and big data, residential assets are mostly brought to the market via digital multiple listing systems. Transparency is an essential barrier when assessing the pricing conditions of markets and deriving investment decisions. Although international brokers do provide detailed investment comparables on – mostly commercial – real estate markets, the residential sector remains a puzzle when it comes to investment yields. The paper sheds light on this problem.

Building back bigger in hurricane strike zones

Despite decades of regulatory efforts in the United States to decrease vulnerability in developed coastal zones, exposure of residential assets to hurricane damage is increasing — even in places where hurricanes have struck before. Comparing plan-view footprints of individual residential buildings before and long after major hurricane strikes, we find a systematic pattern of ‘building back bigger’ among renovated and new properties. US coastlines that are exposed to hurricanes are subject to a myriad of regulations regarding building and rebuilding of structures, yet satellite imagery shows that the footprint of residential buildings increases after hurricane events for both new and renovated structures. Such an effect poses a challenge for vulnerable coastlines to build resilience in the face of growing hazards and houses.