Real Estate Market Segmentation: Hotels as Exemplar

Beracha, Eli; Hardin, William G.; Skiba, Hilla

doi:10.1007/s11146-017-9598-z

Cited by 15 publications

(23 citation statements)

References 33 publications

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“…That would mean that an increase in capital flows into a sector or market could act as a signal that investors are revising upwards their expectations regarding future income streams which may lead to higher asset prices. Beracha et al (2018) find that hotel properties are segmented by hotel class arguing that the notion of aggregate pricing models bunching properties by their type would bias estimators. Sagi (2017) and Badarinza et al (2018) use search models to explain returns on the real estate markets.…”

Section: Literature Reviewmentioning

confidence: 96%

Preferences of Institutional Investors in Commercial Real Estate

Cvijanović

Milcheva

Minne

2021

J Real Estate Finan Econ

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In this paper we analyze market segmentation by firm size in the commercial real estate transaction process. Using novel micro-level data, we look at the probability distribution of investors acquiring a specific bundle of real estate characteristics, distinguishing between investors based on the size of their real estate portfolio. We find evidence of market segmentation by investor size: institutional investors segment across property characteristics based on the size of their real estate portfolio. The probability that a large (small) seller will sell a property to a similar-sized buyer is higher, keeping all else equal. We explore potential drivers of this market segmentation and find that it is mainly driven by investor preferences. During the Global Financial Crisis (GFC), large investors were less likely to buy the ‘average’ property, as compared to the period before or after the crisis, indicating time-varying investor preferences.

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Section: Literature Reviewmentioning

confidence: 96%

Preferences of Institutional Investors in Commercial Real Estate

Cvijanović

Milcheva

Minne

2021

J Real Estate Finan Econ

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show abstract

Section: Literature Reviewmentioning

confidence: 96%

Preferences of Institutional Investors in Commercial Real Estate

2019

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In this paper we analyze market segmentation by firm size in the commercial real estate transaction process. Using novel micro-level data, we look at the probability distribution of investors acquiring a specific bundle of real estate characteristics, distinguishing between investors based on the size of their real estate portfolio. We find evidence of market segmentation by investor size: institutional investors segment across property characteristics based on the size of their real estate portfolio. The probability that a large (small) seller will sell a property to a similar-sized buyer is higher, keeping all else equal. We explore potential drivers of this market segmentation and find that it is mainly driven by investor preferences. During the Global Financial Crisis (GFC), large investors were less likely to buy the 'average' property, as compared to the period before or after the crisis, indicating time-varying investor preferences.

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“…Fewer studies considered commercial property segmentation, with the majority of them involving the office subsector (Costa & Cazassa, 2018;Costa et al, 2016;Dunse et al, 2001;Nappi-Choulet, 2009;Sivitanidou, 1995). Few exceptions are hotel properties (Beracha et al, 2018;Kim, 2020), retail properties (Hardin & Carr, 2006;Sevtsuk & Kalvo, 2018) and industrial properties (Grissom et al, 1987).…”

Section: Introductionmentioning

confidence: 99%

A Priori Spatial Segmentation of Commercial Property Market using Hedonic Price Modelling

Usman

Lizam

Burhan

2021

Real Estate Management and Valuation

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The improvement of property price modelling accuracy using property market segmentation approaches is well documented in the housing market. However, that cannot be said of the commercial property market which is adjudged to be volatile, heterogeneous and thinly traded. This study, therefore, determines if the commercial property market in Malaysia is spatially segmented into submarkets and whether accounting for the submarkets improves the accuracy of price modelling. Using a 11,460 shop-offices transaction dataset, the commercial property submarkets are delineated by using submarket binary dummies in the market-wide model and estimating a separate hedonic model for each submarket. The former method improves the model fit and reduces error by 5.6% and 6.5% respectively. The commercial property submarkets are better delineated by estimating a separate hedonic model for each submarket as it improves the model fit by about 7% and reduces models’ error by more than 10%. This study concludes that the Malaysian commercial property market is spatially segmented into submarkets. Modelling the submarkets improves the accuracy and correctness of price modelling.

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Real Estate Market Segmentation: Hotels as Exemplar

Cited by 15 publications

References 33 publications

Preferences of Institutional Investors in Commercial Real Estate

Preferences of Institutional Investors in Commercial Real Estate

Preferences of Institutional Investors in Commercial Real Estate

A Priori Spatial Segmentation of Commercial Property Market using Hedonic Price Modelling

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