Evaluating returns in the residential rental sector

Rossini, Peter; Kershaw, Paul; Marano, Wayne; Kupke, Valerie

doi:10.1108/02637470510618424

Cited by 4 publications

(4 citation statements)

References 6 publications

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“…The metropolitan area which contains over 300 suburbs of variable sizes and around 100 postal (zip) codes constitutes 10 geographical sub-divisions (Figure 1). Established in a previous study (Rossini et al, 2005), these have been used for indexing the Adelaide housing market with the spatial groupings formed from contiguous postcodes and based on a combination of socio-economic and physical criteria.…”

Section: Datamentioning

confidence: 99%

“…The TOM distribution is less peaked than price (kurtosis is 5.11, compared to 42.87 for sale price) and less skewed (2.04 compared to 4.34 for sale price). Using the 10 sub-divisions identified for the Adelaide housing market (Rossini et al, 2005), median TOM suggests appreciable spatial variation across the metropolitan area and also by time over the period 2002 to 2011. This pattern of variation in TOM forms the basis of the analysis in the subsequent sections of this paper.…”

Section: Datamentioning

confidence: 99%

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Measuring the influence of space and time effects on time on the market

et al. 2016

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This paper is concerned with spatial effects of time on the market for residential property and time varying relationships using a dataset of properties from the Adelaide metropolitan area, Australia, during the period 2002-2011. The analysis firstly considers the spatial dependence in time on the market and secondly extends the analysis to a space-time model using 2SLS regression. The findings demonstrate the complexity in spatial analysis with results indicating a random distribution of time on the market in 86% of observations a pattern that is consistent over time. Spatial autocorrelation is shown to increase time on the market in the subject property while spatial error decreases time on the market in the subject property suggesting a high level of market transparency and improved liquidity. The compensating or nullifying effects of both types of spatial association is shown to contribute to the random distribution observed in time on the market. A strong explanatory capacity of the business cycle suggests that economic drivers are leading time on the market rather than prices.

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Section: Datamentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

Measuring the influence of space and time effects on time on the market

et al. 2016

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“…As important as the owner-occupied housing sector, the rental housing market plays a vital role in promoting urban development, mitigating housing market dynamics and providing affordable housing for migrants (Saiz, 2003;Miller and Peng, 2006;Reed and Wu, 2010;Peppercorn and Taffin, 2013;Yang and Chen, 2014;Laamanen, 2017). Thus, the availability of rental information produced increases transparently and, considered especially across different housing segments within the residential rental market, is of paramount importance for effective property management (Yun Joe Wong et al, 2003;Rossini et al, 2005;Salvo et al, 2014;Huston et al, 2015;Wadu Mesthrige, 2021;Wong and Lai, 2021).…”

Section: Introductionmentioning

confidence: 99%

Constructing segmented rental housing indices: evidence from Beijing, China

Song

Wilhelmsson

Yang

2022

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PurposeThis paper aims to construct rental housing indices and identify market segmentation for more effective property-management strategies.Design/methodology/approachThe hedonic model was employed to construct the rental indices. Using the k-means++ and REDCAP (Regionalisation with Dynamically Constrained Agglomerative Clustering and Partitioning) approaches, the authors conducted clustering analysis and identified different market segmentation. The empirical study relied on the database of 80,212 actual rental transactions in Beijing, China, spanning 2016–2018.FindingsRental housing market segmentation may distribute across administrative boundaries. Properly segmented indices could provide a better account for the heterogeneity and spatial continuity of rental housing and as well be crucial for effective property management.Research limitations/implicationsResidential rent might not only vary over space but also interplays with housing price. It would be worth studying how the rental market functions together with the owner-occupied sector in the future.Practical implicationsResidential rental indices are of great importance for policymakers to be able to evaluate housing policies and for property managers to implement competitive strategies in the rental market. Their constructions largely depend on the analysis of market segmentation, a trade-off between housing spatial heterogeneity and continuity.Originality/valueThis paper fills the gap in knowledge concerning segmented rental indices construction, particularly in China. The spatial constrained clustering approach (REDCAP) was also initially introduced to identify regionalised market segmentation due to its superior performance.

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“…The relationship between the first advertised price and the sale price has also been analysed spatially across ten regions of Adelaide. These represent regions across Adelaide established by the Centre for Land Economics and Real Estate Research in a previous study (Rossini et al, 2005) which can be used for indexing and other purposes. The ten regions are made up of contiguous postcodes and based on a combination of socio-economic and physical criteria.…”

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Bait pricing: evaluating the success of regulatory reform in advertising

Kupke

Rossini

Kershaw

2014

International Journal of Housing Markets and Analysis

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Purpose – The purpose of this paper is to evaluate the effectiveness of this legislative reform in the state of South Australia (SA) through an examination of the relationship between listed or advertised price and transaction prices before and after the changes in regulation. Between 2000 and 2008, legislative changes took place throughout Australia to make real-estate transactions more transparent and to deal with misleading conduct by real-estate agents. The practice of “charm” or “bait” pricing was targeted. This denotes the under-quoting of estimated selling prices in real-estate sale advertisements which can be considered deceptive or even fraudulent. Design/methodology/approach – The study area is Adelaide, the state capital of SA and includes analysis of first and last advertised prices and eventual selling price for > 120,000 residential sales transactions over a nine-year period between 2003 and 2011. The analysis to test these hypotheses included, first, a descriptive evaluation of the percentage price difference over time and a spatial breakdown of mean percentage price difference before and after legislation. Second, for each hypothesis, the change was tested by measuring the variance of the percentage change, with significance established through the Levene and Brown–Forsythe tests, rather than by the mean percentage change. Findings – The results, both descriptive and statistical, support the effectiveness of the reform in legislation. Research limitations/implications – The study has application in terms of agents as social gatekeepers and confirms the role of regulation to ensure market values are achieved and consumers not disadvantaged. With friction in the market, imperfect information and the possible behavioural responses of land agents, there may be incomplete market correction of underpricing strategies. This paper confirms the effectiveness of one such market intervention. Social implications – Some half a million dwellings are purchased in Australia every year. Annually, in the state of SA, some 53,000 dwellings are financed to be purchased or built. These levels of purchase reflect national home ownership rates of about 69 per cent, with some 33 per cent of Australians owning their houses outright and a growing number, some 36 per cent, owners with a mortgage. Australian households also move house relatively frequently. In 2008, 43 per cent of Australians reported moving in the previous 5 years, 15 per cent had moved 3 or more times. The most common reasons for moving were twofold, either to buy a house or to buy a bigger house. These levels of purchase, home ownership and mobility underpin the importance and viability of some 10,000 real-estate services businesses in Australia; a sector which, up to 2,000, was largely self-regulated. Originality/value – This paper is one of the first in Australia to effectively quantify the success of legislative reform on residential agency behaviour.

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Evaluating returns in the residential rental sector

Cited by 4 publications

References 6 publications

Measuring the influence of space and time effects on time on the market

Measuring the influence of space and time effects on time on the market

Constructing segmented rental housing indices: evidence from Beijing, China

Bait pricing: evaluating the success of regulatory reform in advertising

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