Segmented Housing Market Structure in Istanbul Metropolitan Area and Observed Housing Price Differences Related to These Segments

2002 ◽  
Keyword(s):  
Market Structure ◽  
Housing Market ◽  
Metropolitan Area ◽  
Housing Price ◽  
Price Differences

scholarly journals Micro-Analysis of Price Spillover Effect among Regional Housing Submarkets in Korea: Evidence from the Seoul Metropolitan Area

Land ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 879
Author(s):  
Leeyoung Kim ◽  
Wonseok Seo
Keyword(s):  
Housing Market ◽  
Metropolitan Area ◽  
Mutual Influence ◽  
Housing Prices ◽  
Spillover Effect ◽  
Housing Price ◽  
Sales Price ◽  
Seoul Metropolitan Area ◽  
Housing Submarkets ◽  
The City

This study examined the price spillover effect of housing submarkets in cities in the Seoul metropolitan area in South Korea by using the Granger causality test and vector autoregressive model (VAR). We found that housing prices showed a higher spillover effect within regions with similar housing market characteristics. Additionally, the spatial spillover of housing prices revealed a difference between sales price and jeonse price. The spillover of jeonse price was characterized by mutual influence among neighboring cities, while that of sales price was characterized by the influence being transferred in one direction hierarchically. Furthermore, the effects of housing price indicated a slight difference between sales price and jeonse price. Although jeonse price was mainly affected by a neighboring area (geographic boundary), sales price was more influenced by the city with the highest housing prices. Lastly, the housing price spillover tended to be expansive around the city with the highest price. These results suggest that housing price policies targeting specific regions or areas in Korea must be differentiated according to the type of occupancy (jeonse or sales), and it is essential to consider the externalities when promoting policies in the housing market wherein externalities may be significant.

scholarly journals The Impacts of Housing Affordability on Social and Economic Sustainability in Beijing

2013 ◽  
Vol 1 (1) ◽  
pp. 47
Author(s):  
Zhimin Wang ◽  
Jung Hoon ◽  
Benson Lim
Keyword(s):  
Housing Market ◽  
Economic Performance ◽  
Census Data ◽  
Housing Price ◽  
Housing Affordability ◽  
Economic Sustainability ◽  
National Bureau ◽  
Demographic Trends ◽  
Sustainable Housing ◽  
Price Growth

China has undergone significant housing price growth since its 1998’s policy reformation – triggering housing affordability issues in large cities such as Beijing and Shanghai. Although studies have been done to investigate Chinese cities’ housing market policies, it appears that hitherto little is known about the effect of housing affordability on the cities’ social and economic sustainability. The aim of this paper is to investigate the relationships among housing affordability, macro-economic performance and socio-demographic trends in Beijing. Under this aim, the specific objectives are to: examine Beijing’s housing market performance, housing affordability, economic development and socio-demographic trends; and model the relationships among housing affordability, economic performance and socio-demographic trends in Beijing. Twelve years of retrospective census data from National Bureau of Statistics of China were collated and analysed. The results show that economic growth is positively influenced by housing affordability. However, it is shown that low level of housing affordability could lead to economic and social un-sustainability. This research informs urban planners and researchers about the effect of housing affordability on a nation’s urban economic and social development, offering a new plausible insight towards developing a sustainable housing market.

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.

Three essays on China's housing market, monetary policy and macroeconomy

2019 ◽  
Author(s):  
◽  
Yifeng Jia
Keyword(s):  
Monetary Policy ◽  
Housing Market ◽  
Negative Impact ◽  
House Price ◽  
Housing Price ◽  
Policy Instruments ◽  
Heterogeneous Effects ◽  
Price Appreciation ◽  
Economic Stimulus ◽  
Monetary Policy Shock

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] This dissertation studies China's housing market and macroeconomic activity with a strong focus on the role of monetary policy behind the markets. The first two chapters concentrate on the house price dynamics in China. Chapter 1 examines the in influence of monetary policy on China's housing price fluctuation by estimating a VAR model with China's aggregated house price data from 1998Q1 to 2015Q4. The monetary policy shock is identify ed by the sign restriction approach following Uhlig (2005), with the identification assumptions extended to three common policy instruments utilized by the central bank of China: interest rate, required reserve ratio and M2. The results suggest a negative impact of a contractionary monetary policy shock on the house price, and M2 tends to be the most effective monetary instruments in terms of policy transmission. The framework is also extended to examine the link between China's 2008 government economic stimulus plan and the subsequent house price appreciation. The obtained evidence suggests that the economic stimulus props up the house price, but its contribution to the post-2008 house price appreciation is not as prominent as indicated by other relevant studies. However, this discrepancy may be explained by the heterogeneous effects of the stimulus policy on local housing markets across China

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.

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