scholarly journals International Real Estate Review

2008 ◽  
Vol 11 (1) ◽  
pp. 113-127
Author(s):  
Elif Alkay ◽  
Keyword(s):  
Real Estate ◽  
Housing Market ◽  
Household Income ◽  
Housing Prices ◽  
Housing Price ◽  
Market Area ◽  
Empirical Results ◽  
Price Structure ◽  
Average Household Income ◽  
Significant Difference

This study tests the hypothesis that in a segmented housing market, housing price structure is different in each segment and whole market area price structure does not reflect a realistic housing price structure effectively. Submarket existence is tested in order to average household income in neighbourhoods in the Istanbul housing market. Whether the consequential variations in prices in each segment have large effects on the overall prices of housing is emphasized by the replication of the Schnare and Struyk (1976) process. The empirical results show that as a stratifier, average household income in neighbourhoods affects housing prices in each segment and, considering the submarkets based on average household income in neighbourhoods, is an effective for the Istanbul housing market. Implicit attribute prices vary and there is a statistically significant difference in the prices of each segment. These differences have a large effect on the overall price of housing.

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.

scholarly journals Capital Gain Expectations And Efficiency In The Real Estate Markets

2011 ◽  
Vol 6 (4) ◽  
Author(s):  
Shady Kholdy ◽  
Ahmad Sohrabian
Keyword(s):  
Real Estate ◽  
Housing Market ◽  
Housing Prices ◽  
Housing Price ◽  
Capital Gain ◽  
Real Estate Markets ◽  
The Real ◽  
The Real Estate ◽  
Real Estate Price ◽  
Economic Fundamentals

Capital gain expectation is known to be an important determinant of housing price hikes during the real estate booms. Empirically, however, specifying the way expectations about current and future economic variables are formed is a dilemma. Although it is reasonable to assume that economic fundamentals have a significant effect on the investors’ expectation about future gains, a number of housing market analysts claim that expectations of housing prices are extrapolative. This study attempts to investigate the mechanism by which investors’ capital gain expectations and psychology are shaped. The results suggest that housing prices are predictable with respect to capital gain expectations only when these expectations are formed by extrapolation of past price appreciations. Considering the large number of empirical evidence on housing market anomaly with respect to capital gain expectations, the results suggest that the extrapolative expectations can better explain the real estate price behavior than expectations that are formed by economic fundamentals.

International Real Estate Review

2011 ◽  
Vol 14 (3) ◽  
pp. 311-329
Author(s):  
Charles Ka Yui Leung ◽  
◽  
Jun Zhang ◽  
Keyword(s):  
Real Estate ◽  
Trading Volume ◽  
Price Dispersion ◽  
Housing Prices ◽  
Housing Price ◽  
Short Paper ◽  
Future Research ◽  
Positive Correlation ◽  
Time On The Market ◽  
Empirical Regularities

Three striking empirical regularities have been repeatedly reported: the positive correlation between housing prices and trading volume, and between housing price and time-on-the-market (TOM), and the existence of price dispersion. This short paper provides perhaps the first unifying framework which mimics these phenomena in a simple competitive search framework. In the equilibrium, sellers with heterogeneous waiting costs and buyers are endogenously segregated into different submarkets, each with distinct market tightness and prices. With endogenous search efforts, our model also reproduces the well-documented price- volume correlation. Directions for future research are also discussed.

scholarly journals Did the COVID-19 Pandemic Crisis Affect Housing Prices Evenly in the U.S.?

2021 ◽  
Vol 13 (21) ◽  
pp. 12277
Author(s):  
Xinba Li ◽  
Chuanrong Zhang
Keyword(s):  
Real Estate ◽  
Spatial Patterns ◽  
Price Change ◽  
Housing Prices ◽  
Housing Price ◽  
Real Estate Market ◽  
Moran’S I ◽  
Moran's I ◽  
Price Changes ◽  
The U.S

While it is well-known that housing prices generally increased in the United States (U.S.) during the COVID-19 pandemic crisis, to the best of our knowledge, there has been no research conducted to understand the spatial patterns and heterogeneity of housing price changes in the U.S. real estate market during the crisis. There has been less attention on the consequences of this pandemic, in terms of the spatial distribution of housing price changes in the U.S. The objective of this study was to explore the spatial patterns and heterogeneous distribution of housing price change rates across different areas of the U.S. real estate market during the COVID-19 pandemic. We calculated the global Moran’s I, Anselin’s local Moran’s I, and Getis-Ord’s statistics of the housing price change rates in 2856 U.S. counties. The following two major findings were obtained: (1) The influence of the COVID-19 pandemic crisis on housing price change varied across space in the U.S. The patterns not only differed from metropolitan areas to rural areas, but also varied from one metropolitan area to another. (2) It seems that COVID-19 made Americans more cautious about buying property in densely populated urban downtowns that had higher levels of virus infection; therefore, it was found that during the COVID-19 pandemic year of 2020–2021, the housing price hot spots were typically located in more affordable suburbs, smaller cities, and areas away from high-cost, high-density urban downtowns. This study may be helpful for understanding the relationship between the COVID-19 pandemic and the real estate market, as well as human behaviors in response to the pandemic.

scholarly journals Are There Any Housing Bubbles in Turkey?

2021 ◽  
Author(s):  
Özge Korkmaz ◽  
Ebru Çağlayan Akay ◽  
Hoşeng Bülbül
Keyword(s):  
Housing Market ◽  
House Prices ◽  
Housing Prices ◽  
Housing Price ◽  
Economic Fundamentals ◽  
The Past ◽  
Price Increases ◽  
Long Time ◽  
Housing Bubbles ◽  
Turkish Lira

It is very important that the housing market, which meets the most basic need of people is needed for shelter from the past to the present, has a stable structure. The instability structure of the housing market is generally associated with the presence of housing bubbles. The deviation of housing prices from their basic value and not being able to be explained by economic fundamentals leads to the formation of housing bubbles. Housing bubbles can lead to permanent losses, as it may take a long time to return to normal prices. For Turkey as a developing country, it is important to identify an unstable structure in house prices discuss the basic economic factors related to this. After the global increases in housing prices, inflation, and depreciation in the Turkish lira, Turkey has become the country with the highest housing price increases globally in 2020. In the study, the presence of bubbles in the housing market for Ankara, Izmir, Istanbul, and Turkey in general, was investigated by SADF and GSADF unit root tests for the period 2010:01-2021:02. In this context, the study examines the presence of bubbles in housing prices for Ankara, Izmir, Istanbul, and Turkey in general, which are the three cities with the highest price increases. As a result of the study, the presence of bubbles in the housing market has been determined for Ankara, Istanbul, Izmir, and Turkey in general.

scholarly journals Housing Prices in Unregulated Markets: Study on Verticalised Dwellings in Santiago de Chile

Buildings ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 6 ◽  
Author(s):  
José Francisco Vergara-Perucich ◽  
Carlos Aguirre-Nuñez
Keyword(s):  
Housing Market ◽  
Affordable Housing ◽  
Housing Prices ◽  
House Price ◽  
Housing Price ◽  
Housing Affordability ◽  
Price Formation ◽  
Land Values ◽  
Santiago De Chile ◽  
Data Transparency

Chile faces a housing affordability crisis, given that most of the population is unable to secure a house. While housing prices between 2008 and 2019 increased by 63.96%, wages only increased by 21.85%. This article presented an analysis of the housing price configuration for the main borough in the country—Santiago. The assessment focused on verticalised housing constructed between 2015 and 2019. The article developed an exploratory study on the price of housing in Santiago to generate a diagnosis to identify the role played by expectations of profitability when configuring price. Based on the information generated, we sought to contribute to the discussion on public policies that advance the development of affordable housing in central boroughs with high urban value, as is the case for Santiago’s borough of Greater Santiago. We hypothesised that profit expectation of real estate developers plays a key role in the housing prices, and an adjustment in the profit ratios might increase the affordability while keeping the housing market above profitable rates. This research addressed the lack of data transparency in the Chilean housing market with archival research, reconstructing costs and earnings from projects based on official registrations of transactions at the borough level. In Chile, the access to investment costs, land values, yields, and house price formation are not publicly available, even though these factors imply that many households are facing severe difficulties in paying for and accessing decent housing.

scholarly journals Urban Structure, Subway Systemand Housing Price: Evidence from Beijing and Hangzhou, China

2019 ◽  
Vol 11 (3) ◽  
pp. 669 ◽  
Author(s):  
Xiaoqi Zhang ◽  
Yanqiao Zheng ◽  
Lei Sun ◽  
Qiwen Dai
Keyword(s):  
Housing Market ◽  
Housing Prices ◽  
Housing Price ◽  
Structural Features ◽  
Urban Structure ◽  
Constrained Clustering ◽  
The Core ◽  
Urban Core ◽  
Subway System ◽  
The Relationship

Using housing market data of Beijing and Hangzhou, China, we conduct a case study to detect how the difference of urban structure can affect the relationship between the subway system and housing prices. To quantify the characteristics of urban structure, we propose a constrained clustering method, which can not only reveal the spatial heterogeneity of the housing market, but also provides a link between heterogeneity and the underlying urban structure. Applying constrained clustering to Beijing and Hangzhou, we find that the relationship between accessibility to metro stations and housing prices is weak and vulnerable, while the improvement of commuting efficiency, measured by a key variable, the metro index, does have a robust connection to metro premium on housing units. In particular, only a large metro index can be associated with a positive metro premium. Structural features, such as the size of urban core and the existence of multiple sub-centers, influence the metro premium by affecting the value and spatial distribution of the metro index. The evidence from Beijing and Hangzhou supports that in a mono-centric city, the size of the urban core is positively associated with the metro index and the metro premium, while in a poly-centric city with a small urban core, the metro index tends to be lower in the core region and higher in the satellite regions, which enforces the metro premium to be negative in the core while positive outside of the core.

Housing price and enterprise financing: does mortgage effect exist?

2019 ◽  
Vol 9 (1) ◽  
pp. 137-152 ◽  
Author(s):  
Shujing Li ◽  
Nan Gao
Keyword(s):  
Financial Development ◽  
Design Methodology ◽  
Empirical Test ◽  
Housing Prices ◽  
Housing Price ◽  
Fixed Effect Model ◽  
Content Type ◽  
Empirical Results ◽  
Effect Model ◽  
High Level

Purpose The purpose of this paper is to explore the influence of the rise in housing prices on enterprise financing and also the sustainability and heterogeneity of this effect. Design/methodology/approach Empirical test, panel data, fixed-effect model, IV and 2SLS were used in this paper. Findings The empirical results indicate that the mortgage effect does exist, and the authors further analyze the heterogeneity of this effect by dividing the sample based on the degree of financial development and property rights; the empirical results reveal that the mortgage effect is significantly higher in places with the high level of financial development. Besides, compared to the SOE enterprise, the mortgage effect has more influence on non-SOE companies. Research limitations/implications The results indicate that the mortgage effect should be considered when regulating housing market, and in order to improve the financing capability of company, its profitability and financial market efficiency should be emphasized. Originality/value This paper not only confirms the existence of the mortgage effect, but also explores its sustainability and heterogeneity, which reveals the risk and bubble in the effect of house market on enterprise financing, and enlightens how to promote financing ability of company.

scholarly journals Evaluation of Residential Housing Prices on the Internet: Data Pitfalls

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-15
Author(s):  
Ming Li ◽  
Guojun Zhang ◽  
Yunliang Chen ◽  
Chunshan Zhou
Keyword(s):  
Real Estate ◽  
Central City ◽  
Housing Prices ◽  
Housing Price ◽  
Data Sources ◽  
City Centre ◽  
The Internet ◽  
Residential Housing ◽  
For Profit ◽  
Comparison Results

Many studies have used housing prices on the Internet real estate information platforms as data sources, but platforms differ in the nature and quality of the data they release. However, few studies have analysed these differences or their effect on research. In this study, second-hand neighbourhood housing prices and information on five online real estate information platforms in Guangzhou, China, were comparatively analysed and the performance of neighbourhoods’ raw information from four for-profit online real estate information platforms was evaluated by applying the same housing price model. The comparison results show that the official second-hand residential housing prices at city and district level are generally lower than those issued on four for-profit real estate websites. The same second-hand neighbourhood housing prices are similar across each of the four for-profit real estate websites due to cross-referencing among real estate websites. The differences of housing prices in the central city area are significantly fewer than those in the periphery. The variation of each neighbourhood’s housing prices on each website decreases gradually from the city centre to the periphery, but the relative variation stays stable. The results of the four hedonic models have some inconsistencies with other studies’ findings, demonstrating that errors exist in raw information on neighbourhoods taken from Internet platforms. These results remind researchers to choose housing price data sources cautiously and that raw information on neighbourhoods from Internet platforms should be appropriately cleaned.

Regional heterogeneity and the trans-regional interaction of housing prices and inflation: Evidence from China’s 35 major cities

Urban Studies ◽  
2016 ◽  
Vol 53 (16) ◽  
pp. 3472-3492 ◽  
Author(s):  
Huayi Yu ◽  
Yanfen Huang
Keyword(s):  
Housing Prices ◽  
Consumer Price Index ◽  
Housing Price ◽  
Positive Influence ◽  
Theoretical Explanation ◽  
Price Shocks ◽  
Monetary Aggregates ◽  
Empirical Results ◽  
Regional Interaction ◽  
Housing Price Dynamics

This paper proposes a theoretical framework to analyse the regionally heterogeneous responses of housing prices and inflation to the monetary aggregates shock and the trans-regional interaction of housing prices and inflation, which has seldom been discussed in previous literature. Using a GVAR (Globe Vector Autoregression) model, evidence based on China’s 35 major cities for this framework is provided. The results show that (1) the housing price shocks have weak positive influence on CPIs (consumer price index); (2) the housing price shocks, especially the shocks in first-tier cities and eastern cities, have strong positive influence on domestic housing price dynamics and housing prices of other cities; (3) monetary aggregates shock has strong influence on the housing prices of first-tier cities and eastern cities, while weak influence on that of central and western cities. CPIs are barely influenced by monetary aggregates shocks. The empirical results are in accordance with the theoretical explanation. Based on empirical results, this paper proposes policy recommendations for stabilising housing prices.

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