scholarly journals International Real Estate Review

2018 ◽  
Vol 21 (2) ◽  
pp. 251-274
Author(s):  
Yuming Li ◽  
◽  
Jing Yang ◽  
Keyword(s):  
Real Estate ◽  
Housing Market ◽  
House Price ◽  
Excess Risk ◽  
Single Family ◽  
Price Changes ◽  
The Real Estate ◽  
Long Run ◽  
Short Run ◽  
The U.S

We examine the relation between risk and returns in the U.S. residential housing market. We find that the risk of house price changes and the magnitude relative to the risk of income changes vary with economic conditions. We measure the excess risk of house price changes by adjusting for the risk of income changes and economic variables associated with the real estate and financial sectors of the economy, and find a significant and positive relation between house price changes and excess risk. We also find that excess risk has significantly adverse effects on the short-run momentum and long-run reversal of house price changes across metro areas, thus implying that excess risk induces price rigidity and helps to explain for the serial correlations in price changes in the U.S. single-family housing market.

Resilient homeownership: how partnership-based finance would have prevented the 2008 US mortgage crisis

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mejda Bahlous-Boldi
Keyword(s):  
Housing Market ◽  
Home Ownership ◽  
House Price ◽  
Capital Gains ◽  
Wealth Accumulation ◽  
Causality Test ◽  
Content Type ◽  
Long Run ◽  
Default Rates ◽  
Short Run

Purpose The purpose of this study is to demonstrate that the conventional mortgage system is not appropriate for household finance because it encourages equity extraction and excessive leverage during housing boom and leads to negative equity during a housing bust, a situation that translates into mortgage defaults and foreclosures. Home financing could alternatively be structured as a diminishing partnership preventing the homeowner from ever having negative equity. Design/methodology/approach Using Johansen’s cointegration test, the authors provide evidence of a long-run relationship between the delinquency rates, volume of refinancing and the change in house price index (HPI) during the 1994–2019 period. To unravel the short run dynamics between these variables, the authors used a Granger causality test that concludes that the volume of refinancing and the change in the HPI Granger cause default rates. Findings The authors provide evidence that under the current conventional mortgage system, excessive refinancing opportunities and equity extraction that are the main factors determining delinquency rates leading to a non-sustainable homeownership. Practical implications If mortgages were such that they do not incentivize defaults and foreclosures during a housing downturn, the recovery of the housing market always leads to capital gains. Therefore, disincentivizing refinancing and equity extraction would lead to a more sustainable homeownership. Social implications Households would be encouraged to pursue sustainable homeownership through a partnership-based model with long-term wealth accumulation for themselves and their heirs rather than short-term home ownership through the conventional mortgage system, leading to negative equity and defaults when the housing market slumps. Originality/value Policymakers ought to rethink the mortgage design by promoting partnership-based finance to protect the equity a household accumulates over a lifetime and thereby enhancing stable and sustainable homeownership.

scholarly journals The Real Estate Market and Financial Stability

2020 ◽  
Vol 5 (6) ◽  
pp. 1270-1283
Author(s):  
My-Linh Thi Nguyen ◽  
Toan Ngoc Bui
Keyword(s):  
Real Estate ◽  
Financial Stability ◽  
Real Estate Market ◽  
Data Series ◽  
Stock Market Volatility ◽  
The Real ◽  
The Real Estate ◽  
Long Run ◽  
The Real Estate Market ◽  
Short Run

This paper investigates the relationship between the real estate market (REM) and financial stability in Vietnam. Financial stability is measured using stock market volatility. The research is performed in Vietnam, a developing country whose stock and real estate markets are considered to be nascent, so the data series is very short. To solve this problem, the autoregressive distributed lag (ARDL) approach, which generates more valid results than its counterparts, is adopted. Furthermore, the ARDL approach is appropriate for a model with non-stationary data series and especially allows the analysis of the impact between data series in the short run and the long run. The results reveal the positive relationship between the real estate market and stock market volatility. However, this correlation only exists in the short run, which is a difference between Vietnam and developed countries. The paper also obtains an unprecedented finding confirming that the global financial crisis exerted a negative impact on the REM in Vietnam in the short run and the long run.

scholarly journals The Real Estate and Credit Bubble in Spain; Implications for Poland

2019 ◽  
Vol 19(34) (2) ◽  
pp. 77-88
Author(s):  
Zbigniew Korzeb
Keyword(s):  
Real Estate ◽  
Housing Market ◽  
Growth Rates ◽  
Banking Sector ◽  
House Price ◽  
Current Situation ◽  
The Real ◽  
The Real Estate ◽  
Mortgage Crisis ◽  
Price Growth

The aim of this article is to establish whether the symptoms of an emerging housing bubble can be observed on the Polish market. The concept of this study is based on a comparison between economic, financial and demographic conditions at the time of the mortgage crisis in Spain and the current situation on the housing market and on the market of housing loans granted to households in Poland. An analysis of two economic indicators, (i) housing loans to households-to-GDP expressed in growth rates and (ii) rates of house price growth, does not indicate that a speculative bubble occurs in Poland now. This, however, does not mean that the conclusions drawn from the Spanish crisis cannot and should not have a bearing on the Polish market, especially in terms of potential consequences the crisis may have for the banking sector.

scholarly journals International Real Estate Review

2020 ◽  
Vol 23 (1) ◽  
pp. 65-106
Author(s):  
Mohsen Bahmani-Oskooee ◽  
◽  
Seyed Ghodsi ◽  
Keyword(s):  
House Prices ◽  
House Price ◽  
Oil Prices ◽  
Asymmetric Effects ◽  
Long Run ◽  
Short Run ◽  
Using Data ◽  
Almost All ◽  
The Impact ◽  
The U.S

Since oil is used as an input in the production and delivery process, any change in its price can affect almost all sectors of an economy. Researchers have tried to assess the impact of the rising price of oil on domestic production, inflation, investment, the stock market, etc. In order to determine if inflationary effects of rising oil prices have spread to house prices in the U.S., unlike previous research, we investigate the link between oil prices and house prices by using data from each state of the U.S. Furthermore, for the first time, we engage in asymmetry analysis and find short-run asymmetric effects in almost all of the states but short-run cumulative effects or asymmetric impact in 15 states. Although we also find significant long-run asymmetric effects in 26 states, the results reveal that an increase in oil prices has contributed to house price increase in only 11 states and a decrease in oil prices lowered house prices in only three states.

scholarly journals International Real Estate Review

2020 ◽  
Vol 23 (2) ◽  
pp. 267-308
Author(s):  
Are Oust ◽  
◽  
Ole Martin Eidjord ◽  
Keyword(s):  
Real Estate ◽  
Housing Market ◽  
House Prices ◽  
House Price ◽  
Search Term ◽  
Housing Bubble ◽  
Search Terms ◽  
Search Volume ◽  
Google Search ◽  
The U.S

The aim of this paper is to test whether Google search volume indices can be used to predict house prices and identify bubbles in the housing market. We analyze the data that pertain to the 2006?2007 U.S. housing bubble, taking advantage of the heterogeneous house price development in both bubble and non-bubble states in the U.S. Using 204 housing-related keywords, we test both single search terms and indices that comprise search term sets to see whether they can be used as housing bubble indicators. We find that several keywords perform very well as bubble indicators. Among all of the keywords and indices tested, the Google search volume for ¡§Housing Bubble¡¨ and ¡§Real Estate Agent¡¨, and a constructed index that contains the twelve best-performing search terms score the highest at both detecting bubbles and not erroneously detecting non-bubble states as bubbles. A new housing bubble indicator may help households, investors, and policy makers receive advanced warning about future housing bubbles. Moreover, we show that the Google search outperforms the well-established consumer confidence index in the U.S. as a leading indicator of the housing market.

Prescience evidence of the housing market and production sector performance nexus

2019 ◽  
Vol 12 (1) ◽  
pp. 131-147 ◽  
Author(s):  
Andrew Adewale Alola
Keyword(s):  
Real Estate ◽  
Housing Market ◽  
Housing Sector ◽  
Stable Model ◽  
Production Sector ◽  
Content Type ◽  
The Real ◽  
The Real Estate ◽  
Long Run ◽  
Sector Performance

PurposeObservation of misalignment of the house prices with fundamentals in Malta was recently investigated (Vakili-Zad and Hoekstra, 2011; Micallef, 2018). As such, this study aims to investigate nexus evidence of the housing market and production sector performance in Malta by using quarterly data spanning from 2005Q1 to 2016Q4.Design/methodology/approachIndustrial expansion and development indicator-producer price index (ppi) and unemployment (uem) are used along with volatility index (vix) and fertility rate (frate) as control variables in a multivariate autoregressive distributed lag approach.FindingsPrecisely, the investigation reveals that any disequilibrium in the long-run equilibrium among these variables is subsequently corrected by the movement in the housing market vis-à-vis real residential property price. As the system is observed to adjust with a speed of 39.7 per cent in a situation of economic disequilibrium, the long-run impacts on the housing market are positive for ppi and vix but negative for frate and eum. The observed direction of the impacts in the short-run are the same as in the long-run for all variables. A reported sensitivity test indicates a very minimal differential impact for each variable in the long-run but with a significantly different adjustment parameter of 81.9 per cent. Also, the estimated system posits a very stable model that is void of serial correlation and heteroskedasticity.Research limitations/implicationsIn view of the vibrant nature of the real estate and the housing sector of the country, consideration of the effective policy instruments provided by this study is strongly encouraged. On a wider note, these practicable tools could further be recommended to other regional countries.Originality/valueThe research presents a novel perspective of the real estate and housing sector of Malta, specifically in the light of economic diversification. The country’s housing sector is studied in relation with the performance of other sectors for the first time.

scholarly journals DO EUROPEAN REAL ESTATE STOCKS HEDGE INFLATION? EVIDENCE FROM DEVELOPED AND EMERGING MARKETS

2014 ◽  
Vol 18 (2) ◽  
pp. 178-197 ◽  
Author(s):  
Chyi Lin Lee ◽  
Ming-Long Lee
Keyword(s):  
Real Estate ◽  
Emerging Markets ◽  
Least Squares ◽  
Ordinary Least Squares ◽  
The Real Estate ◽  
Empirical Results ◽  
Expected Inflation ◽  
Long Run ◽  
Short Run ◽  
Inflation Hedging

This study examines the inflation-hedging properties of European real estate stocks in developed and emerging markets over 1990 to 2011. The Fama and Schwert model and a dynamic ordinary least squares (DOLS) regression were employed to study the inflation-hedging characteristics of European real estate stocks over the short run and long run. The empirical results show little inflationhedging ability of European real estate stocks over the short run. Over the long run, developed real estate stocks provide a positive inflation hedge against expected inflation, while no similar evidence is found in the emerging markets. The findings suggest that the inflation-hedging properties of real estate stocks are related to the institutional involvement in the real estate stock markets. The finding could have profound implications to institutional investors.

Integration between real estate and stock markets: new evidence from Pakistan

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Imran Yousaf ◽  
Shoaib Ali
Keyword(s):  
Real Estate ◽  
Stock Market ◽  
Stock Markets ◽  
Content Type ◽  
Real Estate Markets ◽  
The Real ◽  
The Real Estate ◽  
Long Run ◽  
Short Run ◽  
The Relationship

Purpose This study aims to empirically examine the relationship between real estate and stock market of Pakistan. Design/methodology/approach The data of two real estate indices (house price index and plot price index) are taken for the Pakistan and its four big cities, i.e. Lahore, Karachi, Rawalpindi and Islamabad. It estimates the integration between series by applying the Johansen cointegration test. Moreover, the vector error correction model is applied to examine the short and long-run causal relationships between series. Findings The findings show that the real estate markets are cointegrated with the stock market. They imply that the real estate and stock markets are good substitutes in investment allocation, but investors cannot get the benefit of diversification by making a portfolio of real estate and stock markets in Pakistan. Moreover, the long-run causality is observed from majority house markets to the stock market, whereas short-run causality is evident from majority plot markets to the stock market. Hence, the real estate market leads the stock market in the short run and long run, suggesting the credit-price effect in the majority of real estate markets in Pakistan. These causality results are helpful for investors in the forecasting of real estate and stock markets in Pakistan. Research limitations/implications The limitation of the study is the lower number of observations (107), because house and land prices are only available in monthly frequency from January 2011 in Pakistan. Originality/value To the best of the authors’ knowledge, no researcher has investigated the real estate and stock market nexus in Pakistan. Therefore, this study focuses on examining the relationship between the real estate and stock market of Pakistan. The link between real estate and stock markets will provide useful insights to the portfolio managers, real estate companies, property agents, stockbrokers and investors.

scholarly journals Information Spillover Effects of Real Estate Markets: Evidence from Ten Metropolitan Cities in China

2021 ◽  
Vol 14 (6) ◽  
pp. 244
Author(s):  
Junjie Li ◽  
Li Zheng ◽  
Chunlu Liu ◽  
Zhifeng Shen
Keyword(s):  
Real Estate ◽  
Rapid Development ◽  
House Price ◽  
Principal Component ◽  
Spillover Effects ◽  
Real Estate Markets ◽  
The Real ◽  
The Real Estate ◽  
Information Interaction ◽  
Information Spillover

With the rapid development of information communication technology and the Internet, information spillover between cities in real estate markets is becoming more frequent. The influence of information spillover in real estate markets is becoming more and more prominent. However, the current research of information spillover between cities is still relatively insufficient. In view of this research gap, this paper builds a research framework on the information conduction effect in the real estate markets of 10 Chinese cities by using Baidu search data, text mining and principal component analysis and analyzes the information interaction and dynamic influence of the real estate markets in each city by using the vector autoregressive model empirically. The results show that the information interaction among the real estate markets in each city has a network pattern and there is a significant two-way information spillover effect in most cities. When the “information distance” becomes closer, the information interaction between the markets of the cities becomes closer and it is easier for cities to influence each other. The results help to explain the information spillover mechanism behind the house price spillover and to improve the ability to predict and analyze the information spillover process in real estate markets.

Sign in / Sign up

Export Citation Format

Share Document