scholarly journals Sustainable Policy Dynamics—A Study on the Recent “Bust” of Foreign Residential Real Estate Investment in Sydney

2019 ◽  
Vol 11 (20) ◽  
pp. 5856
Author(s):  
Xiao Ma ◽  
Zhe Zhang ◽  
Yan Han ◽  
Xiao-Guang Yue
Keyword(s):  
Real Estate ◽  
Material Culture ◽  
Foreign Capital ◽  
Real Estate Market ◽  
Future Research ◽  
Residential Real Estate ◽  
Structured Interviews ◽  
Real Estate Investment ◽  
Boom And Bust ◽  
Boom And Bust Cycle

We undertook an autopsy of the drivers of individual foreign real estate investment ‘bust’ in Australia through a new theoretical lens of ‘habitus’. Our autopsy data drew contours around the individual foreign real estate capital ‘boom and bust’ cycle, as well as the long-term commitment of professionals in the real estate sector to Australia’s real estate market. More specifically, we showed that the foreign capital ‘boom and bust’ cycle began in earnest in about 2010 (starting at A$8.7 billion), grew to A$72.4 billion in 2016–2017, and then declined to A$12.5 billion in 2017–2018. This decline in foreign capital into Australian real estate occurred within a domestic real estate market in Sydney that also started to slow in 2017. Based on 20 semi-structured interviews with real estate professionals in Sydney and public material culture data, we found out that the off-the-plan apartment sales and global policy landscape changes contributed to the decline of foreign real estate investment in Australia. The three possible implications for Sydney’s future residential real estate development: (1) The loss of investors, (2) the evolution of the labor force, and (3) the diversification of housing products, have been raised as part of a future research road map.

scholarly journals International Real Estate Review

2017 ◽  
Vol 20 (1) ◽  
pp. 51-73
Author(s):  
Steven Stelk ◽  
◽  
Leonard V. Zumpano ◽  
Keyword(s):  
Real Estate ◽  
Selection Bias ◽  
Real Estate Market ◽  
Residential Real Estate ◽  
Market Conditions ◽  
Home Prices ◽  
Boom And Bust ◽  
The Impact

This study investigates the impact of the brokerage market on home prices in both a seller's market (2006) and a buyer's market (2009). In both years, homes sold with brokerage assistance realized higher prices when compared with homes sold without the aid of a broker, even after controlling for selection bias in the seller¡¦s choice to use a broker. This is the first study that uses a national dataset from extreme boom and bust markets that has documented evidence of price segmentation in the residential real estate market. The findings may be the result of the market conditions in 2006 and 2009.

scholarly journals VARIÁVEIS QUE EXPLICAM O RETORNO DOS FUNDOS IMOBILIÁRIOS BRASILEIROS

2020 ◽  
Vol 9 (1) ◽  
pp. 17-33
Author(s):  
Janaína Morais de Oliveira ◽  
Bruno Milani
Keyword(s):  
Real Estate ◽  
Stepwise Regression ◽  
Structural Break ◽  
Real Estate Market ◽  
Commercial Real Estate ◽  
Residential Real Estate ◽  
Real Estate Investment ◽  
Investment Funds ◽  
Risk And Return ◽  
Explanatory Variables

Este artigo tem o objetivo de analisar o risco e o retorno do Fundos Imobiliários Brasileiros no período de janeiro de 2012 até dezembro de 2017. Para isso, foi adotada a metodologia da regressão stepwise, com a finalidade de compreender a influência de cada uma das variáveis explanatórias sobre a variável dependente IFIX, que serve como proxy para os Fundos Imobiliários. Como variáveis explicativas, foram utilizados diversos índices macroeconômicos e de mercado. Os resultados apontaram que o Índice Ibovespa é a única variável que explica o retorno dos Fundos Imobiliários quando a amostra é analisada em toda sua extensão. Porém, foi verificado também que há uma quebra estrutural, a partir da qual a locação de imóveis comercias e a venda de imóveis residenciais passa a explica-los.Palavras-Chave: Fundos de Investimento Imobiliário. Mercado Imobiliário. Bolsa de Valores. VARIABLES THAT EXPLAIN THE RETURN OF BRAZILIAN REAL ESTATE FUNDSAbstract: This article aims to analyze the risk and return of Brazilian Real Estate Funds from January 2012 to December 2017. For this purpose, the stepwise regression methodology was adopted, in order to understand the influence of each on the variable IFIX, which serves as a proxy for Real Estate Funds. As explanatory variables, several macroeconomic and market indices were used. The results showed that the Ibovespa Index is the only variable that explains the return of Real Estate Funds when the sample is analyzed to its full extent. However, it was also found that there is a structural break, from which the rental of commercial real estate and the sale of residential real estate explains them.Keywords: Real Estate Investment Funds. Real Estate Market. Stock Market.

scholarly journals The Impact of Single-Family Rental REITs on Regional Housing Markets: A Case Study of Nashville, TN

Societies ◽  
2018 ◽  
Vol 8 (4) ◽  
pp. 93 ◽  
Author(s):  
Ken Chilton ◽  
Robert Silverman ◽  
Rabia Chaudhrey ◽  
Chihaungji Wang
Keyword(s):  
Real Estate ◽  
Census Data ◽  
Housing Markets ◽  
Future Research ◽  
Individual Investors ◽  
Single Family ◽  
Real Estate Investment ◽  
Wealth Concentration ◽  
The Impact ◽  
The U.S

The U.S. Congress authorized the creation of real estate investment trusts (REITs) in 1960 so companies could develop publically traded real estate investment portfolios. REITs focus on commercial property, retail property, and rental property. During the last decade, REITs became more active in regional housing markets across the U.S. Single-family rental (SFR) REITs have grown tremendously, buying up residential properties across the country. In some regional housing markets, SFR REITs own noticeable shares of single-family homes. In those settings, SFR REITs take large numbers of housing units off of real estate markets where homeownership transactions occur and manage these properties as part of commercial rental inventories. This has resulted in a new category of multiple property owners, composed of institutional investors as opposed to individual investors, which further exacerbates property wealth concentration and polarization. This study examines the socio–spatial distribution of properties in SFR REIT portfolios to determine if SFR REIT properties tend to cluster in distinct areas. This study will focus on the regional housing market in Nashville, TN. Nashville has one of the most active SFR REIT sectors in the country. County tax assessor records were used to identify SFR REIT properties. These data were joined with U.S. Census data to create a profile of communities. The data were analyzed using SPSS statistical software and GIS software. Our analysis suggests that neighborhoods with clusters of SFR REITs fit the SFR REIT business model. Clusters occur in communities with newer homes, residents with higher levels of educational attainment, and middle to upper-middle incomes. The paper concludes with several recommendations for future research on SFR REITs.

scholarly journals International Real Estate Review

2021 ◽  
Vol 24 (2) ◽  
pp. 139-183
Author(s):  
Kristoffer B. Birkeland ◽  
◽  
Allan D. D’Silva ◽  
Roland Füss ◽  
Are Oust ◽  
...  
Keyword(s):  
Real Estate ◽  
Real Estate Market ◽  
Percentage Error ◽  
Residential Real Estate ◽  
Valuation Model ◽  
Stacked Generalization ◽  
Novel Approach ◽  
Out Of Sample ◽  
Selection For ◽  
Automated Valuation

We develop an automated valuation model (AVM) for the residential real estate market by leveraging stacked generalization and a comparable market analysis. Specifically, we combine four novel ensemble learning methods with a repeat sales method and tailor the data selection for each value estimate. We calibrate and evaluate the model for the residential real estate market in Oslo by producing out-of-sample estimates for the value of 1,979 dwellings sold in the first quarter of 2018. Our novel approach of using stacked generalization achieves a median absolute percentage error of 5.4%, and more than 96% of the dwellings are estimated within 20% of their actual sales price. A comparison of the valuation accuracy of our AVM to that of the local estate agents in Oslo generally demonstrates its viability as a valuation tool. However, in stable market phases, the machine falls short of human capability.

scholarly journals Assessment of Average Market Investment Returns in Development of the Residential Real Estate in the Moscow Region

2019 ◽  
Vol 12 (3) ◽  
pp. 140-152
Author(s):  
S. G. Sternik ◽  
Ya. S. Mironchuk ◽  
E. M. Filatova
Keyword(s):  
Real Estate ◽  
Initial Data ◽  
Housing Market ◽  
Return On Investment ◽  
High Reliability ◽  
Real Estate Market ◽  
Moscow Region ◽  
Residential Real Estate ◽  
Market Return ◽  
Total Investment

In the previous work, G.M. Sternik and S.G. Sternik justified the options for the method of assessing the average current annual return on investment in residential real estate development, depending on the nature and content of the initial data on the costs contained in the sources of information (construction costs or total investment costs). Based on the analysis of the composition of the elements of development costs used in various data sources, we corrected the coefficients that allowed us to move from the assessment of the current annual return on investment in development in relation to the cost (full estimated cost) of construction to the assessment of the current annual return on investment in relation to the total investment costs. This calculation method was tested on the example of the housing market inMoscow. As a result, we concluded it is possible its use for investment management in the housing market. In this article, based on G.M. Sternik and S.G. Sternik’s methodology for assessing the return on investment into the development, and taking also into account the increase of information openness of the real estate market, we improved the calculation formulas, using new sources of the initial data, and recalculated the average market return on investment into the development of residential real estate in the Moscow region according to the data available for 2014–2017. We concluded that, since 2015, the average market return on investment takes negative values, i.e. the volume of investment in construction exceeds the revenue from sales in the primary market. However, in the second half of 2017, the indicator has increased to positive values, which was due to a greater extent of the decrease in the volume of residential construction in the region. The data obtained by us, together with the improved method of calculations, allow predicting with high reliability the potential of the development of the regional markets of primary housing for the purpose of investment and state planning of housing construction programs.

scholarly journals What Drives Consumer’s Intention to use Online Property Websites: A Conceptual Model

2018 ◽  
pp. 630-633
Keyword(s):  
Real Estate ◽  
Conceptual Model ◽  
Construction Industry ◽  
Real Estate Market ◽  
Future Research ◽  
Intention To Use ◽  
The Real Estate ◽  
Proposed Model ◽  
The Real Estate Market ◽  
Conceptual Paper

The real estate market in Malaysia is growing as the nation grows more prosperous. There were 376,583 transactions recorded in Malaysia in 2010 with an aggregate worth RM107.44 billion (Construction Industry Development ,2016). This study intends to inspect the factors that drive consumer’s intention to use online property website. Previous literature does not include in-depth analyses such as consumer behavior. Hence, this conceptual paper proposes a model the key constructs that determine consumers’ intention to use online property website based on the Stimulus-Organism-Response (S-O-R) model. The proposed model integrates the S-O-R model with atmospheric cues from websites such as informativeness, effectiveness and entertainment. The results of the study provide significant insights the phenomenon of using online property ads and factors that influence consumers’ intention regarding online property websites. Recommendations for future research are also presented.

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