scholarly journals Information transparency and pricing strategy in the Scottish housing market

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Daniel Lo ◽  
Nan Liu ◽  
Michael James McCord ◽  
Martin Haran
Keyword(s):  
Real Estate ◽  
Spatial Autocorrelation ◽  
Housing Market ◽  
Government Policy ◽  
Price Determination ◽  
Residential Real Estate ◽  
Spatial Lag ◽  
Content Type ◽  
Information Transparency ◽  
Residential Market

Purpose Information transparency is crucially important in price setting in real estate, particularly when information asymmetry is concerned. This paper aims to examine how a change in government policy in relation to information disclosure and transparency impacts residential real estate price discovery. Specially, this paper investigates how real estate traders determined asking prices in the context of the Scottish housing market before and after the implementation of the Home Report, which aimed to prevent artificially low asking prices. Design/methodology/approach This paper uses spatial lag hedonic pricing models to empirically observe how residential asking prices are determined by property sellers in response to a change in government policy that is designed to enhance market transparency. It uses over 79,000 transaction data of the Aberdeen residential market for the period of Q2 1998 to Q2 2013 to test the models. Findings The empirical findings provide some novel insights in relation to the price determination within the residential market in Scotland. The spatial lag models suggest that spatial autocorrelation in property prices has increased since the Home Report came into effect, indicating that property sellers have become more prone to infer asking prices based on prior sales of dwellings in close vicinity. The once-common practice of setting artificially low asking prices seems to have dwindled to a certain extent statistically. Originality/value The importance of understanding the relationship between information transparency and property price determination has gathered momentum over the past decade. Although spatial hedonic techniques have been extensively used to study the impact of various property- and neighbourhood-specific attributes on residential real estate market in general, surprisingly little is known about the empirical relationship between spatial autocorrelation in real estate prices and information transparency.

Examining why developers encourage foreign investment in local residential real estate in India

2016 ◽  
Vol 9 (4) ◽  
pp. 580-600
Author(s):  
Alok Tiwari ◽  
Mohammed Aljoufie
Keyword(s):  
Real Estate ◽  
Housing Market ◽  
United Arab Emirates ◽  
Foreign Investment ◽  
Large Population ◽  
Political Stability ◽  
Primary Data ◽  
Residential Real Estate ◽  
Content Type ◽  
Property Developers

Purpose The study aims to explore the role of non-resident Indian (NRI) investors into staggering local housing market and the efforts of developers and regulators to lure such investors. Design/methodology/approach Primary data for this exploratory study were assembled through a Google form-based questionnaire circulated over internet among NRIs residing in Kingdom of Saudi Arabia, USA, Singapore and United Arab Emirates, whereas the secondary data sources include the Government of India policy documents, World Bank data, Reserve Bank of India archives and reports published in reputed financial and others print media sources. Findings Indian housing market is confronted with a demand and supply mismatch at present. While a massive demand lingers at affordable housing segment, on the contrary, millions of housing inventories are also piling up. Consequently, property developers are attempting to lure the large population of NRIs residing at global cities. Study observes that sentimental attachment to the homeland, higher rate of returns, anticipated rental incomes are the major decisive elements. Additionally, growth in infrastructure, world-class amenities offered by developers, conformity to sustainability and political stability is the other critical reasons. Research limitations/implications On first hand, the study outlines a novel kind of foreign investment in Indian local residential real estate that is via NRI channel. Second, non-resident investors might surprise to the property developers and government through a realistic strategic approach. Originality/value Probably, the study is first of its type gazing at NRI investors, as a foreign investor, in the local residential real estate.

scholarly journals The securitization of residential rental revenue streams in Europe

2017 ◽  
Vol 10 (4) ◽  
pp. 503-518 ◽  
Author(s):  
Jaume Roig Hernando
Keyword(s):  
Real Estate ◽  
Housing Market ◽  
Risk Sharing ◽  
Rental Housing ◽  
Cash Flows ◽  
Property Market ◽  
Investment Funds ◽  
Content Type ◽  
The Usa ◽  
Residential Market

Purpose The purpose of this paper is to analyze the securitization of rental streams, a new investment and finance product introduced in the USA in 2013 that enables fundraising from large residential portfolios owned by major investment funds and investment banking. The securities are made up of non-performance loans as well as real estate portfolios of financial entities. Design/methodology/approach An academic analysis of the European securitization market is performed, as well as a broad overview of the state of the art of the rental housing market and investment property market. Moreover, a market study of Real Estate Owned (hereinafter, REOs) and Real Estate Debts is carried out to determine both the present framework and future trends. Various financial entities and real estate management companies are examined through interviews and data collection to assess the reality of distressed assets and residential portfolios owned by major investors. It introduced the Broker’s Price Opinion concept, de loan-to-value concept and the London Interbank Offered Rate. Findings REO-to-rental securitization is a step forward toward the democratization of finance through the globalization of the residential market, improving risk sharing for major and retail investors. The securitization of rental streams in Europe has not taken off, despite several issuances in the USA since 2013 with significant success where first tranches obtained a credit qualification of triple-A from the majority of the main rating agencies. Originality/value At the end of 2013, a global investment firm launched an innovative finance and investment vehicle that securitized the cash flows originating from leased residential properties. That issue resulted in considerable success and in the development of a new alternative and innovative financing source for real estate activity. Taking into account that housing is a primary need of our society, there is a strong motivation for improving the residential market, and thus, REO-to-rental securitization could help take a step forward in making the housing market more efficient.

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.

Property investor decisions using income and rental ratio signals

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Billie Ann Brotman
Keyword(s):  
Real Estate ◽  
Housing Market ◽  
Discount Rate ◽  
Price Index ◽  
Housing Prices ◽  
Housing Price ◽  
Consumer Sentiment ◽  
Content Type ◽  
Income Ratio ◽  
Real Estate Prices

PurposeThis paper, a case study, aims to consider whether the income ratio and rental ratio tracks the formation of residential housing price spikes and their collapse. The ratios are measuring the risk associated with house price stability. They may signal whether a real estate investor should consider purchasing real property, continue holding it or consider selling it. The Federal Reserve Bank of Dallas (Dallas Fed) calculates and publishes income ratios for Organization for Economic Cooperation and Development countries to measure “irrational exuberance,” which is a measure of housing price risk for a given country's housing market. The USA is a member of the organization. The income ratio idea is being repurposed to act as a buy/sell signal for real estate investors.Design/methodology/approachThe income ratio calculated by the Dallas Fed and this case study's ratio were date-stamped and graphed to determine whether the 2006–2008 housing “bubble and burst” could be visually detected. An ordinary least squares regression with the data transformed into logs and a regression with structural data breaks for the years 1990 through 2019 were modeled using the independent variables income ratio, rent ratio and the University of Michigan Consumer Sentiment Index. The descriptive statistics show a gradual increase in the ratios prior to exposure to an unexpected, exogenous financial shock, which took several months to grow and collapse. The regression analysis with breaks indicates that the income ratio can predict changes in housing prices using a lead of 2 months.FindingsThe gradual increases in the ratios with predetermine limits set by the real estate investor may trigger a sell decision when a specified rate is reached for the ratios even when housing prices are still rising. The independent variables were significant, but the rent ratio had the correct sign only with the regression with time breaks model was used. The housing spike using the Dallas Fed's income ratio and this study's income ratio indicated that the housing boom and collapse occurred rapidly. The boom does not appear to be a continuous housing price increase followed by a sudden price drop when ratio analysis is used. The income ratio is significant through time, but the rental ratio and Consumer Sentiment Index are insignificant for multiple-time breaks.Research limitations/implicationsInvestors should consider the relative prices of residential housing in a neighborhood when purchasing a property coupled with income and rental ratio trends that are taking place in the local market. High relative income ratios may signal that when an unexpected adverse event occurs the housing market may enter a state of crisis. The relative housing prices to income ratio indicates there is rising housing price stability risk. Aggregate data for the country are used, whereas real estate prices are also significantly impacted by local conditions.Practical implicationsRatio trends might enable real estate investors and homeowners to determine when to sell real estate investments prior to a price collapse and preserve wealth, which would otherwise result in the loss of equity. Higher exuberance ratios should result in an increase in the discount rate, which results in lower valuations as measured by the formula net operating income dividend by the discount rate. It can also signal when to start reinvesting in real estate, because real estate prices are rising, and the ratios are relative low compared to income.Social implicationsThe graphical descriptive depictions seem to suggest that government intervention into the housing market while a spike is forming may not be possible due to the speed with which a spike forms and collapses. Expected income declines would cause the income ratios to change and signal that housing prices will start declining. Both the income and rental ratios in the US housing market have continued to increase since 2008.Originality/valueA consumer sentiment variable was added to the analysis. Prior researchers have suggested adding a consumer sentiment explanatory variable to the model. The results generated for this variable were counterintuitive. The Federal Housing Finance Agency (FHFA) price index results signaled a change during a different year than when the S&P/Case–Shiller Home Price Index is used. Many prior studies used the FHFA price index. They emphasized regulatory issues associated with changing exuberance ratio levels. This case study applies these ideas to measure relative increases in risk, which should impact the discount rate used to estimate the intrinsic value of a residential property.

Real effects of real estate: evidence from unemployment rates

2020 ◽  
Vol 37 (4) ◽  
pp. 605-623
Author(s):  
Can Dogan ◽  
John Can Topuz
Keyword(s):  
Real Estate ◽  
Housing Prices ◽  
Real Economy ◽  
Residential Real Estate ◽  
Content Type ◽  
Unemployment Rates ◽  
The Real ◽  
Real Estate Price ◽  
Real Effects ◽  
Real Estate Prices

Purpose This paper aims to investigate the relationship between residential real estate prices and unemployment rates at the Metropolitan Statistical Area (MSA) level. Design/methodology/approach This paper uses a long time-series of MSA-level quarterly data from 1990 to 2018. It uses an instrumental variable approach to estimate the effects of residential real estate prices on unemployment rates using the geography-based land constraints measure of Saiz (2010) as the instrument. Findings The results show that changes in residential real estate prices do not have a causal effect on unemployment rates in the same quarter. However, it takes 9-12 months for an increase (decrease) in real estate prices to decrease (increase) unemployment rates. This effect is significant during both pre- and post-financial crisis periods and robust to control for the economic characteristics of MSAs. Research limitations/implications This paper contributes to the emerging literature that studies the real effects of real estate. Particularly, the methodology and the findings can be used to investigate causal relationships between housing prices and small business development or economic growth. The findings are also of interest to policymakers and practitioners as they illustrate how and when real estate price shocks propagate to the real economy through unemployment rates. Practical implications This study’s findings have important implications for academics, policymakers and investors as they provide evidence of a snowball effect associated with shocks to real estate prices: increasing (decreasing) unemployment rates following a decrease (increase) in real estate prices exacerbates the real estate price movements and their economic consequences. Originality/value This paper analyzes a significantly longer period, from 1990 to 2018, than the existing literature. Additionally, it uses the MSA-level land unavailability measure of Saiz (2010) as an instrument to explore the effects of residential real estate prices on unemployment rates and when those effects are observed in the real economy.

Residential property market determinants: evidence from the 2018 Australian market downturn

2019 ◽  
Vol 38 (2) ◽  
pp. 157-175
Author(s):  
Peng Yew Wong ◽  
Woon-Weng Wong ◽  
Kwabena Mintah
Keyword(s):  
Housing Market ◽  
Economic Conditions ◽  
Residential Property ◽  
Investment Fund ◽  
Property Market ◽  
Data Set ◽  
Content Type ◽  
Econometric Methods ◽  
Residential Market ◽  
Australian Bureau Of Statistics

Purpose The purpose of this paper is to validate and uncover the key determinants revolving around the Australian residential market downturn towards the 2020s. Design/methodology/approach Applying well-established time series econometric methods over a decade of data set provided by Australian Bureau of Statistics, Reserve Bank of Australia and Real Capital Analytics, the significant and emerging drivers impacting the Australian residential property market performance are explored. Findings Besides changes in the significant levels of some key traditional market drivers, housing market capital liquidity and cross-border investment fund were found to significantly impact the Australian residential property market between 2017 and 2019. The presence of some major positive economic conditions such as low interest rate, sustainable employment and population growth was perceived inadequate to uplift the Australian residential property market. The Australian housing market has performed negatively during this period mainly due to diminishing capital liquidity, excess housing supplies and retreating foreign investors. Practical implications A better understanding of the leading and emerging determinants of the residential property market will assist the policy makers to make sound decisions and effective policy changes based on the latest development in the Australian housing market. The results also provide a meaningful path for future property investments and investigations that explore country-specific effects through a comparative analysis. Originality/value The housing market determinants examined in this study revolve around the wider economic conditions in Australia that are not new. However, the coalesce analysis on the statistical results and the current housing market trends revealed some distinguishing characteristics and developments towards the 2020s Australian residential property market downturn.

The housing demand analysis and prediction of the real estate based on the AWGM (1, N) model

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xin Xiong ◽  
Huan Guo ◽  
Xi Hu
Keyword(s):  
Real Estate ◽  
Housing Market ◽  
Housing Demand ◽  
Grey Model ◽  
Content Type ◽  
First Order ◽  
Model Based ◽  
Per Capita ◽  
Improved Model ◽  
Grey Relational

PurposeThe purpose of this paper is to seek to drive the modernization of the entire national economy and maintain in the long-term stability of the whole society; this paper proposes an improved model based on the first-order multivariable grey model [GM (1, N) model] for predicting the housing demand and solving the housing demand problem.Design/methodology/approachThis paper proposes an improved model based on the first-order multivariable grey model [GM (1, N) model] for predicting the housing demand and solving the housing demand problem. First, a novel variable SW evaluation algorithm is proposed based on the sensitivity analysis, and then the grey relational analysis (GRA) algorithm is utilized to select influencing factors of the commodity housing market. Finally, the AWGM (1, N) model is established to predict the housing demand.FindingsThis paper selects seven factors to predict the housing demand and find out the order of grey relational ranked from large to small: the completed area of the commodity housing> the per capita housing area> the one-year lending rate> the nonagricultural population > GDP > average price of the commodity housing > per capita disposable income.Practical implicationsThe model constructed in the paper can be effectively applied to the analysis and prediction of Chinese real estate market scientifically and reasonably.Originality/valueThe factors of the commodity housing market in Wuhan are considered as an example to analyze the sales area of the commodity housing from 2015 to 2017 and predict its trend from 2018 to 2019. The comparison between demand for the commodity housing actual value and one for model predicted value is capability to verify the effectiveness of the authors’ proposed algorithm.

Germany will face long-term housing problems

2018 ◽  
Keyword(s):  
Young People ◽  
Real Estate ◽  
Housing Market ◽  
Social Housing ◽  
Large Scale ◽  
Content Type ◽  
Housing Investment ◽  
Will Force ◽  
German Cities

Subject Germany's housing dilemma. Significance Demographic changes and the shift from publicly to corporately owned housing have led to accommodation shortages and rising rents in West German cities. Despite the government's plans for large-scale social housing investment, these trends will have long-term implications for Germany's housing market. Impacts Over-priced real estate will force developers to invest overseas. Accommodation shortfalls and rising prices will result in mass mobilisation and protests of young people across Germany. Lack of social housing will increase rates of homelessness in German cities.

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