scholarly journals Booms and Busts in Housing Market and Health Outcomes for Older Americans

2021 ◽  
Author(s):  
Dahai Yue ◽  
Ninez A Ponce
Keyword(s):  
Older Adults ◽  
Housing Market ◽  
Fixed Effects ◽  
Price Index ◽  
Housing Prices ◽  
Housing Price ◽  
Health Impacts ◽  
Price Dynamics ◽  
Housing Price Index ◽  
Housing Price Dynamics

Abstract Background and Objectives The U.S. housing market has experienced considerable fluctuations over the last decades. This study aimed to investigate the impacts of housing price dynamics on physical health, mental health, and health-related behaviors for older American outright owners, mortgaged owners, and renters. Research Design and Methods We drew longitudinal data from the 1992-2016 Health and Retirement Study and merged it to the five-digit ZIP-code level Housing Price Index. The analytic sample comprised 34,182 persons and 174,759 person-year observations. We used a fixed-effects model to identify the health impacts of housing price dynamics separately for outright owners, mortgaged owners, and renters. Results A 100% increase in Housing Price Index was associated with a 2.81 and 3.50 percentage points (pp) increase in the probability of reporting excellent/very good/good health status for mortgage owners and renters, respectively. It was also related to a lower likelihood of obesity (1.82 pp) for outright owners, and a less chance of obesity (2.85 pp) and smoking (3.03 pp) for renters. All of these relationships were statistically significant (p<0.05). Renters also experienced significantly decreased depression scores (-0.24), measured by the Center for Epidemiologic Studies Depression Scale, associated with the same housing price changes. Discussion and Implications Housing price dynamics have significant health impacts, and renters are more sensitive to fluctuations in the housing market. Our study rules out the wealth effect as the mechanism through which changes in housing prices affect older adults’ health. Our findings may inform policies to promote older adults’ health by investing in local area amenities and improving socioeconomic conditions.

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 Dynamics of the US Housing Market: A Quantal Response Statistical Equilibrium Approach

Entropy ◽  
2018 ◽  
Vol 20 (11) ◽  
pp. 831 ◽  
Author(s):  
Özlem Ömer
Keyword(s):  
Housing Market ◽  
Maximum Entropy ◽  
Price Index ◽  
Housing Price ◽  
Statistical Equilibrium ◽  
Market Dynamics ◽  
Quantal Response ◽  
Housing Price Index ◽  
The Us ◽  
Equilibrium Approach

In this article, we demonstrate that a quantal response statistical equilibrium approach to the US housing market with the help of the maximum entropy method of modeling is a powerful way of revealing different characteristics of the housing market behavior before, during and after the recent housing market crash in the US. In this line, a maximum entropy approach to quantal response statistical equilibrium model (QRSE) is employed in order to model housing market dynamics in different phases of the most recent housing market cycle using the S&P Case Shiller housing price index for 20 largest- Metropolitan Regions, and Freddie Mac housing price index (FMHPI) for 367 Metropolitan Cities for the US between 2000 and 2015. Estimated model parameters provide an alternative way to understand and explain the behaviors of economic agents, and market dynamics by questioning the traditional economic theory, which takes assumption for the behavior of rational utility maximizing representative agent with self-fulfilled expectations as given.

The Impact of Tourism, Game of Thrones and Income on Croatian Housing Prices

2021 ◽  
Author(s):  
Billie Ann Brotman
Keyword(s):  
Price Index ◽  
Housing Prices ◽  
Housing Price ◽  
Least Squares Regression ◽  
Television Show ◽  
Tourism Impact ◽  
Housing Price Index ◽  
The Republic ◽  
The Impact ◽  
Game Of Thrones

The Game of Thrones television program was widely seen throughout the world. The show acted as an advertisement for travel and home purchases in the Republic of Croatia. A hedonic least squares regression model adjusted for autocorrelation is used to consider the impact of the television show, tourist visits to the country and domestic personal income on the housing price index. The descriptive statistics and regression results suggest that the television show and tourism impact existing housing prices. Visitors to the country purchased or rented enough housing to cause demand to increase for residential properties which results in a higher housing price index. Per capita domestic income is not a significant factor influencing the housing price index for existing dwellings.

CONSTRUCTING HOUSING PRICE INDEX FOR TERRACED PROPERTIES IN JOHOR BAHRU, MALAYSIA

2021 ◽  
Vol 19 (17) ◽  
Author(s):  
Wendy Wen Xin Lim ◽  
Burhaida Burhan ◽  
Mohd Lizam Mohd Diah
Keyword(s):  
Price Index ◽  
Housing Prices ◽  
Housing Price ◽  
Hedonic Price ◽  
Property Market ◽  
Price Variation ◽  
Vector Property ◽  
Hedonic Price Analysis ◽  
Housing Price Index ◽  
Housing Attributes

Housing is a country’s biggest asset. Hence, the pattern of the housing price index (HPI) is an important topic to gain insight into the housing market while identifying the prevailing housing issues. The determinants of housing price vary for each city and state based on the different characteristics in each location. Accordingly, HPI should consider the property’s quality differences. Besides, national HPI is insufficient and restricted to the housing price at the state level. Thus, the study focused on constructing a specified HPI model for different cities, districts, and states. Effective HPI can give parties a better idea of the current property market situation and act as an analytical tool in managing the sector. Specifically, the study aims to examine the relationship between the heterogeneity housing attributes and housing prices of the terraced properties in Johor Bahru, Malaysia. Additionally, the study provides detailed information on the key determinants of the housing price variation in Johor Bahru. Hedonic price analysis is useful in constructing HPI, expressing housing price as a function of vector property characteristics. Furthermore, HPI is constructed based on the yearly indices and by pooling the data into certain periods. The results show the percentage of variance explained by the factors of HPI for the terraced properties in Johor Bahru. Correspondingly, the underlying correlation between the tested housing attributes with the housing price is explained through the analysis results.

scholarly journals The Private Housing Market Cyclical Price Dynamics

2020 ◽  
Vol 6 (2) ◽  
pp. p173
Author(s):  
SUN, Jingbo ◽  
HO, Kim Hin / David
Keyword(s):  
Housing Market ◽  
Housing Price ◽  
Market Mechanism ◽  
Price Dynamics ◽  
Herd Behavior ◽  
Momentum Strategy ◽  
For Profit ◽  
Long Run ◽  
Private Housing ◽  
Housing Price Dynamics

Two types of heterogeneous investors (momentum and disposition) form a unique difference model to interpret housing price dynamics. Three parameters are crucial: auto-correlation, the rate of mean reversion and the contemporaneous adjustment towards long-term equilibrium price. For Singapore, we examine the dynamic structures that oscillate and/or diverge from equilibrium. Disposition investors predominate although the interaction between momentum and disposition investors acts as a key determinant of private housing price dynamics for a given time in a specific market. Key implication is that Singapore’s private housing market is low risk, offering stable returns owing to virtually no divergence even in the speculative 1990s. The best way to invest is to consider the momentum strategy and avoid the herd behavior for profit sustainability. For policy-makers, the Singapore private housing market is over-damped in the long run. Predominating disposition investors contribute to the market mechanism, which automatically adjusts private housing market prices. It is imperative to relax government intervention in Singapore’s private housing market to enhance its efficiency.

scholarly journals International Real Estate Review

2005 ◽  
Vol 8 (1) ◽  
pp. 110-127
Author(s):  
John Clithero ◽  
◽  
Nathan Pealer ◽  
Keyword(s):  
Real Estate ◽  
Housing Market ◽  
Price Index ◽  
Housing Price ◽  
Repeat Sales ◽  
Data Set ◽  
The Past ◽  
Housing Price Index ◽  
Recent Trends ◽  
Oriented Approach

Although there have been many recent studies of the housing market and the possible housing bubble, very few studies take a micro-oriented approach. We construct a repeat-sales housing price index from a new data set for Irvine, California to understand recent trends in its housing market. Our analysis for 1984 to 2003 suggests that Irvine’s housing market did demonstrate traits of a bubble during certain periods of time. In fact, the bubble of the late 1980s and early 1990s appears to have been even more pronounced in Irvine. Our analysis does not, however, demonstrate conclusively that Irvine’s housing market has been experiencing a bubble the past few years.

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.

Sign in / Sign up

Export Citation Format

Share Document