Driving forces for the US residential housing price: a predictive analysis

2019 ◽  
Vol 9 (4) ◽  
pp. 515-529
Author(s):  
Amirhosein Jafari ◽  
Reza Akhavian
Keyword(s):  
Real Estate ◽  
Predictive Models ◽  
Driving Forces ◽  
Housing Prices ◽  
Housing Price ◽  
Data Set ◽  
Content Type ◽  
The Usa ◽  
Decision Making Processes ◽  
The Impact

Purpose The purpose of this paper is to determine the key characteristics that determine housing prices in the USA. Data analytical models capable of predicting the driving forces of housing prices can be extremely useful in the built environment and real estate decision-making processes. Design/methodology/approach A data set of 13,771 houses is extracted from the 2013 American Housing Survey (AHS) data and used to develop a Hedonic Pricing Method (HPM). Besides, a data set of 22 houses in the city of San Francisco, CA is extracted from Redfin real estate brokerage database and used to test and validate the model. A correlation analysis is performed and a stepwise regression model is developed. Also, the best subsets regression model is selected to be used in HPM and a semi-log HPM is proposed to reduce the problem of heteroscedasticity. Findings Results show that the main driving force for housing transaction price in the USA is the square footage of the unit, followed by its location, and its number of bathrooms and bedrooms. The results also show that the impact of neighborhood characteristics (such as distance to open spaces and business centers) on the housing prices is not as strong as the impact of housing unit characteristics and location characteristics. Research limitations/implications An important limitation of this study is the lack of detailed housing attribute variables in the AHS data set. The accuracy of the prediction model could be increased by having a greater number of information regarding neighborhood and regional characteristics. Also, considering the macro business environment such as the inflation rate, the interest rates, the supply and demand for housing, and the unemployment rates, among others could increase the accuracy of the model. The authors hope that the presented study spurs additional research into this topic for further investigation. Practical implications The developed framework which is capable of predicting the driving forces of housing prices and predict the market values based on those factors could be useful in the built environment and real estate decision-making processes. Researchers can also build upon the developed framework to develop more sophisticated predictive models that benefit from a more diverse set of factors. Social implications Finally, predictive models of housing price can help develop user-friendly interfaces and mobile applications for home buyers to better evaluate their purchase choices. Originality/value Identification of the key driving forces that determine housing prices on real-world data from the 2013 AHS, and development of a prediction model for housing prices based on the studied data have made the presented research original and unique.

Real estate agent dynamism and licensing entry barriers

2019 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Samuel J. Ingram ◽  
Aaron Yelowitz
Keyword(s):  
Labor Market ◽  
Real Estate ◽  
Housing Prices ◽  
Occupational Licensing ◽  
Content Type ◽  
Percent Increase ◽  
The Usa ◽  
Real Estate Agents ◽  
The Cost ◽  
The Impact

Purpose The purpose of this paper is to examine the labor market entry of real estate agents in the USA and the potential effect of occupational licensing on entry. Design/methodology/approach Data from the 2012 to 2017 American Community Survey are linked to local housing price fluctuations from the Federal Housing Finance Agency for 100 large metro areas. The cost of entry associated with occupational licensing for new real estate agents is carefully measured for each market and interacted with housing fluctuations to investigate the role for barriers to entry. Findings A 10 percent increase in housing prices is associated with a 4 percent increase in the number of agents. However, increased license stringency reduces the labor market response by 30 percent. The impact of licensing is stronger for women and younger workers. Originality/value This work contributes to the growing literature investigating the impact of occupational licensing on labor supply and entry in the USA, as well as potential impacts of regulation on dynamism and entrepreneurship. To the authors’ knowledge, this study is also the first to quantify the cost of occupational licensing in the real estate industry.

The impact of external factors on housing prices in Lithuania

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Alina Stundziene ◽  
Vaida Pilinkienė ◽  
Andrius Grybauskas
Keyword(s):  
Real Estate ◽  
Housing Prices ◽  
Housing Price ◽  
Real Estate Market ◽  
External Factors ◽  
Content Type ◽  
The Real ◽  
The Real Estate ◽  
The Real Estate Market ◽  
The Impact

Purpose This paper aims to identify the external factors that have the greatest impact on housing prices in Lithuania. Design/methodology/approach The econometric analysis includes stationarity test, Granger causality test, correlation analysis, linear and non-linear regression modes, threshold regression and autoregressive distributed lag models. The analysis is performed based on 137 external factors that can be grouped into macroeconomic, business, financial, real estate market, labour market indicators and expectations. Findings The research reveals that housing price largely depends on macroeconomic indicators such as gross domestic product growth and consumer spending. Cash and deposits of households are the most important indicators from the group of financial indicators. The impact of financial, business and labour market indicators on housing price varies depending on the stage of the economic cycle. Practical implications Real estate market experts and policymakers can monitor the changes in external factors that have been identified as key indicators of housing prices. Based on that, they can prepare for the changes in the real estate market better and take the necessary decisions in a timely manner, if necessary. Originality/value This study considerably adds to the existing literature by providing a better understanding of external factors that affect the housing price in Lithuania and let predict the changes in the real estate market. It is beneficial for policymakers as it lets them choose reasonable decisions aiming to stabilize the real estate market.

House price index (HPI) and Covid-19 pandemic shocks: evidence from Turkey and Kazakhstan

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yeşim Aliefendioğlu ◽  
Harun Tanrivermis ◽  
Monsurat Ayojimi Salami
Keyword(s):  
Real Estate ◽  
Price Index ◽  
Housing Prices ◽  
House Price ◽  
Monthly Basis ◽  
Data Set ◽  
House Price Index ◽  
Content Type ◽  
Asymmetric Pricing ◽  
Long Run

Purpose This paper aims to investigate asymmetric pricing behaviour and impact of coronavirus (Covid-19) pandemic shocks on house price index (HPI) of Turkey and Kazakhstan. Design/methodology/approach Monthly HPIs and consumer price index (CPI) data ranges from 2010M1 to 2020M5 are used. This study uses a nonlinear autoregressive distributed lag model for empirical analysis. Findings The findings of this study reveal that the Covid-19 pandemic exerted both long-run and short-run asymmetric relationship on HPI of Turkey while in Kazakhstan, the long-run impact of Covid-19 pandemic shock is symmetrical long-run positive effect is similar in both HPI markets. Research limitations/implications The main limitations of this study are the study scope and data set due to data constraint. Several other macroeconomic variables may affect housing prices; however, variables used in this study satisfy the focus of this study in the presence of data constraint. HPI and CPI variables were made available on monthly basis for a considerably longer period which guaranteed the ranges of data set used in this study. Practical implications Despite the limitation, this study provides necessary information for authorities and prospective investors in HPI to make a sound investment decision. Originality/value This is the first study that rigorously and simultaneously examines the pricing behaviour of Turkey and Kazakhstan HPIs in relation to the Covid-19 pandemic shocks at the regional level. HPI of Kazakhstan is recognized in the global real estate transparency index but the study is rare. The study contributes to regional studies on housing price by bridging this gap in the real estate literature.

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.

Selling a house and the decision to use a real estate broker in Norway

2015 ◽  
Vol 33 (2) ◽  
pp. 173-186
Author(s):  
Mary Ann Stamsø
Keyword(s):  
Real Estate ◽  
Web Sites ◽  
Property Management ◽  
Real Estate Broker ◽  
Sales Price ◽  
Content Type ◽  
Sales Process ◽  
The Usa ◽  
The Impact ◽  
Estate Broker

Purpose – The purpose of this paper is to examine the widespread of property sellers choosing to sell by themselves or through an estate agent, what characterises them and the reason for their choice. In addition the paper contains comparisons of the gap between sales price and asking price between the sales methods and satisfaction with the sales process. This study is the first study of these phenomena carried out in Norway. Design/methodology/approach – The data used for this study was obtained from a national survey including 1,649 house sellers. A logistic regression analysis is used to analyse the impact of household’s characteristics on the sales method. Findings – The main findings of this study are that 83 per cent of the house sellers used an estate agent through the whole sales process and differences in the choices are related to urbanisation, age and education. The most important reason for preferring a real estate broker is that doing the sale on your own is considered too much work. Conversely, the most important reason for doing the sale on your own is that estate agents are too expensive. Those selling without an estate agent were more satisfied and the gap between sales price and asking price was smaller than for those selling through a real estate broker. Originality/value – Issues concerning competition within the market for estate agents should be central topics for property management. Property sellers selling their property by themselves are an important contribution to increase the competition in the market for estate agents. This issue has not been on the agenda in Norway, or in Europe, in the same way as in the USA. This is probably due to the complexity in the legislation and strict laws within property sales in Central and Southern Europe. However, in Norway, UK and in the Nordic countries, the legal system is not complicated. It is rather the lockout of private individuals from the housing web sites and the fact that the property sellers are not familiar with this kind of transaction that has prevented property sellers to sell their house by themselves. Today Norway is one of few countries with a booming housing market, which also has increased the commission for estate agents. From 2010 private individuals got access to advertise their house on the housing web sites in Norway. These have influenced the focus on alternative sales methods.

“When I get older, I wanna be an entrepreneur”: the impact of disability and dyslexia on entrepreneurial self-efficacy perception

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Benjamin Powers ◽  
Séverine Le Loarne-Lemaire ◽  
Adnane Maalaoui ◽  
Sascha Kraus
Keyword(s):  
Self Efficacy ◽  
Negative Impact ◽  
Research Question ◽  
Entrepreneurial Intention ◽  
Economic Life ◽  
Entrepreneurial Intentions ◽  
Data Set ◽  
Content Type ◽  
The Usa ◽  
The Impact

PurposeThis article contributes to the literature on entrepreneurship for people with disabilities through a better understanding of the impact of entrepreneurial self-efficacy perceptions on entrepreneurial intentions in populations with lower levels of self-esteem. It investigates the entrepreneurial intention and self-efficacy of a population of students suffering from dyslexia, which is a learning disability.Design/methodology/approachThe paper is based on the study of a data set of 796 male and female adolescents in the USA, aged 13–19 years, both with and without dyslexia. The sample is a convenient one. The whole sample replied to the questionnaire on their self-efficacy perception and their intention to create, one day, their own venture. They also self-declare their dyslexia. Regressions have been conducted to answer the research question.FindingsResults show that having dyslexia has a negative impact on entrepreneurial self-efficacy perceptions. They also reveal that self-efficacy perceptions mediate the relationship between dyslexia and entrepreneurial intentions and their three antecedents (social norms, control behavior and perceived ability).Research limitations/implicationsThe sample is composed of students from private schools and might socially be biased.Practical implicationsOur findings relaunch the debate on the necessity to develop education programs that consider the personal-level variables of students, specifically the development of entrepreneurial self-efficacy among adolescents with disabilitiesSocial implicationsSuch findings should help to better understand students who are suffering from dyslexia and help them find a place in society and economic life.Originality/valueThis is so far the first study that has been conducted on dyslexic adolescents.

scholarly journals Liquidity in global real estate securities markets

2016 ◽  
Vol 34 (4) ◽  
pp. 321-346 ◽  
Author(s):  
Nicole Lux ◽  
Alex Moss
Keyword(s):  
Real Estate ◽  
Stock Market ◽  
Market Liquidity ◽  
Company Size ◽  
Small Companies ◽  
Stock Performance ◽  
Content Type ◽  
The Usa ◽  
Market Capitalisation ◽  
The Impact

Purpose – The purpose of this paper is to test the relationship between liquidity in listed real estate markets, company size and geography during different market cycles, specifically pre-crisis (2002-2006) and post-crisis (2010-2014). Further, the study analyses the impact of stock liquidity on stock performance. In a previous study the authors examined the impact of liquidity on the valuation of European real estate shares. The result showed that there is a strong relationship between liquidity, valuation and market capitalisation post the Global Financial Crisis. Design/methodology/approach – The paper studies the linkages between regional market liquidity and company size for 60 listed real estate companies globally and determines the key drivers of company stock market liquidity pre- and post-crisis as well as the impact on stock performance. Analysis of variance is used to test cross-sectional independence in market liquidity combined with the Tukey’s post hoc test. The selected test indicators of liquidity to capture market depth and market tightness are daily stock turnover as percentage of market capitalisation and daily bid-ask spreads. Findings – Findings confirm previous studies that market liquidity factors are correlated globally over time indicating markets interdependence. However, sample groups by company size and geography form independent samples with different sample means, thus specific liquidity levels in each market may be different. First, stock turnover levels have not recovered post-crisis to pre-crisis levels in the majority of markets while spreads have continued moving downward to nearly insignificant levels in line with the rest of the equity market. Second, with regards to stock performance, the European bias previously detected is not apparent in the USA, and there is no evidence of the small cap vs large cap effect of small companies achieving superior returns, although smaller companies have outperformed in Europe and Asia in each of the last three years (2012-2014). Practical implications – The key implication is that although spread levels for smaller companies are higher, implying a slight risk premium when investing in small companies, this did not manifest into consistent superior stock market returns in the periods studied. In a mature market such as the USA or UK, liquidity levels in terms of stock turnover are higher and spreads are lower thus reducing trading costs, making them more attractive for investors. Originality/value – This research brings together previous analysis on stock market liquidity and stock performance on a global market level. It further tests the dependence of market liquidity on two key indicators, namely, geography and company size and analyses market changes with respect to liquidity pre- and post-crisis.

scholarly journals The effects of tourism on housing prices: applying a difference-in-differences methodology to the Portuguese market

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
António Manuel Cunha ◽  
Júlio Lobão
Keyword(s):  
Real Estate ◽  
Housing Prices ◽  
Housing Price ◽  
Generalized Least Squares ◽  
Equation Model ◽  
Seemingly Unrelated Regression ◽  
Housing Supply ◽  
Difference In Differences ◽  
Content Type ◽  
Price Increases

Purpose This paper aims to explore the effects of a surge in tourism short-term rentals (STR) on housing prices in municipalities within Portugal’s two largest Metropolitan Statistical Areas. Design/methodology/approach This study applies the difference-in-differences (DiD) methodology by using a feasible generalized least squares (FGLS) estimator in a seemingly unrelated regression (SUR) equation model. Findings The results show that the liberalization of STR had a significant impact on housing prices in municipalities where a higher percentage of housing was transferred to tourism. This transfer led to a leftward shift in the housing supply and a consequent increase in housing prices. These price increases are much higher than those found in previous studies on the same subject. The authors also found that municipalities with more STR had low housing elasticities, which indicates that adjustments to the transfer of real estate from housing to tourism were made by increasing house prices, and not by increasing supply quantities. Practical implications The study suggests that an unforeseen consequence of allowing property owners to transfer the use of real estate from housing to other services (namely, tourism) was extreme housing price increases due to inelastic housing supply. Originality/value This is the first time that the DiD methodology has been applied in real estate markets using FGLS in a SUR equation model and the authors show that it produces more precise estimates than the baseline OLS FE. The authors also find evidence of a supply shock provoked by STR.

Diversity and group performance in a real estate project

2019 ◽  
Vol 12 (1) ◽  
pp. 62-78 ◽  
Author(s):  
Liesa Schrand ◽  
Tobias Just
Keyword(s):  
Real Estate ◽  
Work Experience ◽  
Group Performance ◽  
Work Group ◽  
Group Formation ◽  
Data Set ◽  
Content Type ◽  
Real Estate Project ◽  
Group Diversity ◽  
The Impact

Purpose Successful developers need to manage a large number of cooperation partners and find innovative solutions for specific tasks, as each real estate project is somehow unique. Thus, the question arises as to whether intelligent group formation for real estate development calls for more or rather less diverse project groups. Design/methodology/approach This paper aims to test the impact of group diversity on overall group performance with a unique data set. The authors collected the results of 150 project assignments from real estate executive education students at the IREBS Real Estate Academy from 2010 until 2016. Findings The authors find that group results were impacted positively for groups with disparity in work experience and ability. Differences in sex and age did not yield any measurable impact, neither positive nor negative. Originality/value To the best of the authors’ knowledge, this is the first time that the relationship between work group diversity and group performance was tested for real estate educational projects. The authors believe that the results are highly relevant for all university work, for which teams have to cooperate on complex rather than basic assignments and problems. Moreover, they are the first to develop a framework that combines diversity theories with a clear distinction between three diversity concepts.

Application of ARMA Regression Model of Housing Prices Influence Factors of Xi'an

2013 ◽  
Vol 405-408 ◽  
pp. 3340-3342
Author(s):  
Hui Zhi ◽  
Yue Fan Wang
Keyword(s):  
Real Estate ◽  
Regression Model ◽  
Housing Prices ◽  
Influence Factors ◽  
Housing Price ◽  
The Real Estate ◽  
Housing Price Index ◽  
Long Run ◽  
The Government ◽  
The Impact

By selecting the relevant factors affect the real estate price, with the qualitative analysis method to analyze the housing prices changes of Xi'an, and then establish ARMA regression model of the housing price index, found that the factors exist long-run co-integration. In order to better reflect the actual, the government policy as a dummy variable is introduced into the model to make regression results more significantly, showing that government policies play an important role in the control of the impact on real estate prices.

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