Understanding real estate investments through big data goggles

2019 ◽  
Vol 12 (4) ◽  
pp. 661-686 ◽  
Author(s):  
Marcelo Cajias
Keyword(s):  
Big Data ◽  
Real Estate ◽  
Methodological Approach ◽  
Investment Strategy ◽  
Commercial Real Estate ◽  
Hedonic Models ◽  
Bond Yields ◽  
Content Type ◽  
Real Estate Investments ◽  
Implicit Prices

Purpose This 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/approach The 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. Findings The 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 implications The 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/value In 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.

Determinants of foreign direct real estate investment in selected MENA countries

2016 ◽  
Vol 34 (2) ◽  
pp. 116-142 ◽  
Author(s):  
Mohamed Salem ◽  
Andrew Baum
Keyword(s):  
Real Estate ◽  
Emerging Market ◽  
Empirical Work ◽  
Tobit Model ◽  
Commercial Real Estate ◽  
Econometric Analysis ◽  
Content Type ◽  
Mena Countries ◽  
Real Estate Sector ◽  
Real Estate Investments

Purpose – The purpose of this paper is to identify the main determinants of foreign direct real estate investments (foreign direct investment (FDI)) in selected Middle Eastern and North African (MENA) countries. Design/methodology/approach – The empirical work of this study is an econometric analysis of FDI in the commercial real estate sector for eight MENA markets, namely Algeria, Egypt, Morocco, Qatar, Saudi Arabia, Turkey, Tunisia and the UAE during the period 2003-2009. The econometric analysis is carried out using the pooled Tobit model technique for panel data. Findings – The paper finds that both country-specific factors and real estate sector-specific variables consistently support hypotheses explaining commercial real estate-related FDI, and find evidence that political stability explains why some selected MENA countries attract more real estate investments than other MENA countries. Practical implications – The findings should be seriously considered in any policy making effort on the part of governments in the region. Originality/value – The authors contribute to the existing literature in many ways. First, the study aims to develop econometric models, using both conventional and unique variables, to be generalised and applied to any developed or emerging market. The study applies relevant techniques in estimating the models, including the pooled Tobit model. Second, the research studies eight selected MENA real estate markets from 2003 to 2009, a timeframe and geography not examined in previous published empirical work on commercial real estate investments. Lastly, and for the first time in real estate literature, the study applies the location dimension of Dunning’s OLI paradigm as a theoretical explanation for the behaviour of foreign investors in commercial real estate towards the selected MENA markets.

A post-global financial crisis (GFC) framework for strategic planning, assessment and management decision making for US sustainable commercial real estate

2017 ◽  
Vol 35 (6) ◽  
pp. 589-618 ◽  
Author(s):  
Pernille Hoy Christensen
Keyword(s):  
Decision Making ◽  
Financial Crisis ◽  
Real Estate ◽  
Performance Indicators ◽  
Institutional Investors ◽  
Global Financial Crisis ◽  
Real Estate Market ◽  
Commercial Real Estate ◽  
Content Type ◽  
Sustainability Initiatives

Purpose The purpose of this paper is to understand both the facts and the values associated with the breadth of issues, and the principles related to sustainable real estate for institutional investors. Sustainable real estate is a growing sector within the commercial real estate industry, and yet, the decision-making practices of institutional investors related to sustainability are still not well understood. In an effort to fill that gap, this research investigates the post-global financial crisis (GFC) motivations driving the implementation of sustainability initiatives, the implementation strategies used, and the predominant eco-indicators and measures used by institutional investors. Design/methodology/approach This paper presents the results of a three-round modified Delphi study conducted in the USA in 2011-2012 investigating the nature of performance measurements and reporting requirements in sustainable commercial real estate and their impact on the real estate decision-making process used by institutional investors. Two rounds of in-depth interviews were conducted with 14 expert panelists. An e-questionnaire was used in the third round to verify qualitative findings. Findings The key industry drivers and performance indicators influencing institutional investor decision making were associated with risk management of assets and whether initiatives can improve competitive market advantage. Industry leaders advocate for simple key performance indicators, which is in contrast to the literature which argues for the need to adopt common criteria and metrics. Key barriers to the adoption of sustainability initiatives are discussed and a decision framework is presented. Practical implications This research aims to help industry partners understand the drivers motivating institutional investors to uptake sustainability initiatives with the aim of improving decision making, assessment, and management of sustainable commercial office buildings. Originality/value Building on the four generations of the sustainability framework presented by Simons et al. (2001), this research argues that the US real estate market has yet again adjusted its relationship with sustainability and revises their framework to include a new, post-GFC generation for decision making, assessment, and management of sustainable real estate.

scholarly journals What sells in a crisis? Determinants of sale probability over a cycle and through a crash

2017 ◽  
Vol 35 (6) ◽  
pp. 619-637 ◽  
Author(s):  
David Scofield ◽  
Steven Devaney
Keyword(s):  
Real Estate ◽  
Sample Selection ◽  
Sampling Technique ◽  
Real Estate Market ◽  
Commercial Real Estate ◽  
Content Type ◽  
Asset Selection ◽  
The Uk ◽  
Real Estate Cycle ◽  
Over Time

Purpose The purpose of this paper is to understand what affects the liquidity of individual commercial real estate assets over the course of the economic cycle by exploring a range of variables and a number of time periods to identify key determinants of sale probability. Design/methodology/approach Analyzing 12,000 UK commercial real estate transactions (2003 to 2013) the authors use an innovative sampling technique akin to a perpetual inventory approach to generate a sample of held assets for each 12 month interval. Next, the authors use probit models to test how market, owner and property factors affect sale probability in different market environments. Findings The types of properties that are most likely to sell changes between strong and weak markets. Office and retail assets were more likely to sell than industrial both overall and in better market conditions, but were less likely to sell than industrial properties during the downturn from mid-2007 to mid-2009. Assets located in the City of London more likely to sell in both strong and weak markets. The behavior of different groups of owners changed over time, and this indicates that the type of owner might have implications for the liquidity of individual assets over and above their physical and locational attributes. Practical implications Variation in sale probability over time and across assets has implications for real estate investment management both in terms of asset selection and the ability to rebalance portfolios over the course of the cycle. Results also suggest that sample selection may be an issue for commercial real estate price indices around the globe and imply that indices based on a limited group of owners/sellers might be susceptible to further biases when tracking market performance through time. Originality/value The study differs from the existing literature on sale probability as the authors analyzed samples of transactions drawn from all investor types, a significant advantage over studies based on data restricted to samples of domestic institutional investors. As well, information on country of origin for buyers and sellers allows us to explore the influence of foreign ownership on the probability of sale. Finally, the authors not only analyze all transactions together, but the authors also look at transactions in five distinct periods that correspond with different phases of the UK commercial real estate cycle. This paper considers the UK real estate market, but it is likely that many of the findings hold for other major commercial real estate markets.

scholarly journals Cap rates and risk: a spatial analysis of commercial real estate

2018 ◽  
Vol 35 (1) ◽  
pp. 25-43
Author(s):  
Florian Unbehaun ◽  
Franz Fuerst
Keyword(s):  
Real Estate ◽  
Risk Perceptions ◽  
Large Scale ◽  
Risk Premia ◽  
Real Estate Market ◽  
Commercial Real Estate ◽  
Data Series ◽  
Large Set ◽  
Content Type ◽  
The Impact

Purpose This study aims to assess the impact of location on capitalization rates and risk premia. Design/methodology/approach Using a transaction-based data series for the five largest office markets in Germany from 2005 to 2015, regression analysis is performed to account for a large set of asset-level drivers such as location, age and size and time-varying macro-level drivers. Findings Location is found to be a key determinant of cap rates and risk premia. CBD locations are found to attract lower cap rates and lower risk premia in three of the five largest markets in Germany. Interestingly, this effect is not found in the non-CBD locations of these markets, suggesting that the lower perceived risk associated with these large markets is restricted to a relatively small area within these markets that are reputed to be safe investments. Research limitations/implications The findings imply that investors view properties in peripheral urban locations as imperfect substitutes for CBD properties. Further analysis also shows that these risk premia are not uniformly applied across real estate asset types. The CBD risk effect is particularly pronounced for office and retail assets, apparently considered “prime” investments within the central locations. Originality/value This is one of the first empirical studies of the risk implications of peripheral commercial real estate locations. It is also one of the first large-scale cap rate analyses of the German commercial real estate market. The results demonstrate that risk perceptions of investors have a distinct spatial dimension.

scholarly journals Blockchain technology in commercial real estate transactions

2019 ◽  
Vol 37 (6) ◽  
pp. 570-579 ◽  
Author(s):  
Hugo Pieter Wouda ◽  
Raymond Opdenakker
Keyword(s):  
Real Estate ◽  
Design Science ◽  
Science Research ◽  
Commercial Real Estate ◽  
Office Building ◽  
Content Type ◽  
Blockchain Technology ◽  
Transaction Process ◽  
Current Transaction ◽  
Pain Points

Purpose The transaction process of an office building is known to be time consuming and inefficient, in part due to the lack of market transparency. The purpose of this paper is to focus on the development of a blockchain application that can improve the transaction process of office buildings in the Netherlands. Design/methodology/approach Conducting design science research, the current transaction process of an office building and status quo of blockchain technology in real estate is investigated. Subsequently, multiple parties are interviewed to define major pain points within the process. The interview findings are used to design a blockchain solution which overcomes the aforementioned pain points. After designing, the interviewees are asked again to pragmatically validate the proposed model. Findings One of the major pain points identified concerning the transaction process of an office building is that it is difficult to define the characteristics of a property, due to lack of data structure and quality. The proposed application improves the way specific assets are understood by structuring physical and contractual information in one place and guarantees the quality of the data by using the blockchain mechanisms. Practical implications A blockchain application is proposed, which can improve the transaction process of an office building. Originality/value Recent studies indicate that blockchain technology could lead to improvements in efficiency, transparency and therefore trust within the transaction process. Therefore, the proposed application is of value for the future of real estate data management and the transaction process.

Does the commercial real estate industry need “more pussy on the block?”

2019 ◽  
Vol 37 (5) ◽  
pp. 627-637 ◽  
Author(s):  
Dustin C. Read
Keyword(s):  
Real Estate ◽  
Gender Bias ◽  
Second Generation ◽  
Commercial Real Estate ◽  
Real Estate Industry ◽  
Structured Interviews ◽  
Content Type ◽  
Local Chapter ◽  
Professional Credibility ◽  
The Impact

Purpose In a controversial 2018 interview, commercial real estate mogul Sam Zell insinuated that companies should promote their employees based exclusively on merit and avoid purposefully taking steps to get “more pussy on the block” in the name of gender equality. The comment was criticized not only for its crassness, but also for its failure to recognize the challenges many women working in the commercial real estate industry face in their efforts to obtain the same opportunities, compensation and status as similarly-qualified men. In an effort to overcome these disparities, the purpose of this paper is to focus on the pervasiveness of second-generation gender bias and stereotyping in the field through a qualitative analysis. Design/methodology/approach Semi-structured interviews were conducted with 39 women serving as local chapter presidents of a prominent commercial real estate trade group to explore the impact of gender on their career advancement and their experiences with second-generation gender bias. Findings The findings suggest unintentional discrimination often influences women’s careers by drawing their communication skills, professional credibility and commitment to the organizations for whom they work into question. Originality/value The research contributes to the existing literature by offering additional evidence that unintentional discrimination is common in male-dominated industries, such as commercial real estate. It also provides clear examples of social cues women perceive to heighten tension along gender lines and impinge upon their ability to ascend to leadership positions.

Spatial effects and non-linearity in hedonic modeling

2018 ◽  
Vol 36 (1) ◽  
pp. 32-49 ◽  
Author(s):  
Marcelo Cajias ◽  
Sebastian Ertl
Keyword(s):  
Real Estate ◽  
Functional Form ◽  
Asymptotic Properties ◽  
Additive Model ◽  
Percentage Error ◽  
Spatial Effects ◽  
Hedonic Models ◽  
Data Set ◽  
Content Type ◽  
Out Of Sample

Purpose The purpose of this paper is to test the asymptotic properties and prediction accuracy of two innovative methods proposed along the hedonic debate: the geographically weighted regression (GWR) and the generalized additive model (GAM). Design/methodology/approach The authors assess the asymptotic properties of linear, spatial and non-linear hedonic models based on a very large data set in Germany. The employed functional form is based on the OLS, GWR and the GAM, while the estimation methodology was chosen to be iterative in forecasting, the fitted rents for each quarter based on their 1-quarter-prior functional form. The performance accuracy is measured by traditional indicators such as the error variance and the mean squared (percentage) error. Findings The results provide evidence for a clear disadvantage of the GWR model in out-of-sample forecasts. There exists a strong out-of-sample discrepancy between the GWR and the GAM models, whereas the simplicity of the OLS approach is not substantially outperformed by the GAM approach. Practical implications For policymakers, a more accurate knowledge on market dynamics via hedonic models leads to a more precise market control and to a better understanding of the local factors affecting current and future rents. For institutional researchers, instead, the findings are essential and might be used as a guide when valuing residential portfolios and forecasting cashflows. Even though this study analyses residential real estate, the results should be of interest to all forms of real estate investments. Originality/value Sample size is essential when deriving the asymptotic properties of hedonic models. Whit this study covering more than 570,000 observations, this study constitutes – to the authors’ knowledge – one of the largest data sets used for spatial real estate analysis.

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