scholarly journals Cultural Superstitions and Residential Real Estate Prices: Transaction-Level Evidence from the US Housing Market

2016 ◽  
Author(s):  
Brad R. Humphreys ◽  
Adam Nowak ◽  
Yang Zhou
Keyword(s):  
Real Estate ◽  
Housing Market ◽  
Residential Real Estate ◽  
The Us ◽  
Transaction Level ◽  
Real Estate Prices

Superstition and real estate prices: transaction-level evidence from the US housing market

2019 ◽  
Vol 51 (26) ◽  
pp. 2818-2841 ◽  
Author(s):  
Brad R. Humphreys ◽  
Adam Nowak ◽  
Yang Zhou
Keyword(s):  
Real Estate ◽  
Housing Market ◽  
The Us ◽  
Transaction Level ◽  
Real Estate Prices

Short Sales and Residential Real Estate Prices

2013 ◽  
Author(s):  
Andrew Narwold ◽  
Stephen J. Conroy ◽  
Dirk Yandell
Keyword(s):  
Real Estate ◽  
Short Sales ◽  
Residential Real Estate ◽  
Real Estate Prices

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.

scholarly journals 3D Modeling of Discontinuity in the Spatial Distribution of Apartment Prices Using Voronoi Diagrams

2020 ◽  
Vol 12 (2) ◽  
pp. 229 ◽  
Author(s):  
Mirosław Bełej ◽  
Marta Figurska
Keyword(s):  
Spatial Distribution ◽  
Real Estate ◽  
Housing Market ◽  
3D Modeling ◽  
3D Visualization ◽  
Voronoi Diagrams ◽  
Capital City ◽  
Data Sets ◽  
Spatial Continuity ◽  
Real Estate Prices

An immanent feature of the housing market is a large spatial dispersion of real estate prices along with their simultaneous high stratification. Application of classic methods of data interpolation results in an excessive simplification of the outcome because of a conversion of the dispersed data sets into areas of spatial continuity by reducing the above-average real estate prices. The main aim of the article was to search for spatial discontinuities of real estate prices’ distribution with 3D modeling using Voronoi diagrams as a method of irregular division of this space. Used methods of geospatial analyses with GIS tools enabled to identify clusters of high housing market activity and to avoid an excessive generalization of data resulting from the reduction of the above-average real estate prices. The research was conducted for over 7000 real estate transactions in years 2010–2017 in Olsztyn, the capital city of Warmia and Mazury in Poland, resulting in a 3D visualization of real estate prices for the chosen market, including the discontinuity in their spatial distribution.

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.

Asset concentration in the US agricultural balance sheet: a relative information approach

2018 ◽  
Vol 78 (4) ◽  
pp. 497-512
Author(s):  
Gulcan Onel ◽  
Jaclyn Kropp ◽  
Charles B. Moss
Keyword(s):  
Real Estate ◽  
Balance Sheet ◽  
State Level ◽  
United States Department ◽  
Factor Productivity ◽  
Content Type ◽  
Inequality Measures ◽  
The Us ◽  
The Usa ◽  
Real Estate Prices

Purpose Over the past four decades, real values of farm real estate and the share of assets on farmers’ balance sheets attributed to farm real estate have increased. The purpose of this paper is to examine the factors that explain the concentration of the US agricultural balance sheet around a particular asset, farm real estate, and the extent to which the degree of asset concentration varies across United States Department of Agriculture production regions. Design/methodology/approach State-level data from 48 states and entropy-based inequality measures are used to examine changes in asset distributions (real estate vs non-real estate assets) both within and between regions over time. Findings The agricultural balance sheet is found to concentrate into real estate in the USA over the period 1960-2003 with the rate of concentration varying across production regions. In some regions, the concentration is mainly due to changes in real estate prices, while in other regions concentration is also driven by changes in real estate holdings or changes in total factor productivity. Originality/value This study formally estimates the degree to which the concentration of balance sheet items can be explained by the observed changes in farm real estate prices relative to observed changes in agricultural factor productivity or changes in farm real estate holdings. The computed regional differences in asset concentration and its main drivers have implications for changes in equity and solvency positions of farmers as well as agricultural lenders’ risk exposure.

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.

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