scholarly journals Are There Any Housing Bubbles in Turkey?

2021 ◽  
Author(s):  
Özge Korkmaz ◽  
Ebru Çağlayan Akay ◽  
Hoşeng Bülbül

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.

Author(s):  
Shady Kholdy ◽  
Ahmad Sohrabian

Capital gain expectation is known to be an important determinant of housing price hikes during the real estate booms. Empirically, however, specifying the way expectations about current and future economic variables are formed is a dilemma. Although it is reasonable to assume that economic fundamentals have a significant effect on the investors’ expectation about future gains, a number of housing market analysts claim that expectations of housing prices are extrapolative. This study attempts to investigate the mechanism by which investors’ capital gain expectations and psychology are shaped. The results suggest that housing prices are predictable with respect to capital gain expectations only when these expectations are formed by extrapolation of past price appreciations. Considering the large number of empirical evidence on housing market anomaly with respect to capital gain expectations, the results suggest that the extrapolative expectations can better explain the real estate price behavior than expectations that are formed by economic fundamentals.


2021 ◽  
Vol 13 (22) ◽  
pp. 12791
Author(s):  
Jie Wang ◽  
Biyu Peng ◽  
Xiaohua Xia ◽  
Zhu Ma

Focusing on the rapid rise of China’s housing prices in recent years, in this paper, we construct a model using the cheap talk game that centers on how information receivers in a market make inferences about the true state of the information based on the cost-free signals they receive and then make decisions based on these inferences, which in turn affect market equilibrium. By constructing a cheap talk game model of house prices, we examine the correlation between market expectations, economic fundamentals, and individual housing purchase decisions. Then, we conduct an empirical analysis using the dynamic GMM method based on the panel data of 35 large and medium-sized cities in China. The analysis reveals that: (1) when the whole of society expects housing prices to rise, housing prices will rise regardless of the true state of economic fundamentals; (2) when information on economic fundamentals is accurate and reliable, home buyers tend to make purchase decisions based on such information, thus maximizing the utility of society as a whole; but when information on economic fundamentals is unreliable, home buyers tend to make purchase decisions according to their own housing price expectations, which is not conducive to the optimization of the utility of society as a whole; (3) the empirical results also reveal that expectations are a non-negligible factor in the rise of housing prices, and the coefficient of expectations exceeds that of each economic fundamental; this demonstrates the investment-driven attribute of the housing market in China. At the same time, economic fundamentals have a definite effect on housing prices, which implies that the rise of housing prices in China is supported by objective conditions.


2015 ◽  
Vol 18 (2) ◽  
pp. 217-240
Author(s):  
Weida Kuang ◽  
◽  
Peng Liu ◽  

In recent years, housing prices and inflation have been growing constantly in China. Higher house prices and higher inflation affect both household consumption and economic growth. We have developed a four-sector general equilibrium model of consumers, developers, firms, and the central bank to illustrate the relationship of house prices with inflation. The theoretical model demonstrates that house prices and inflation are positively correlated and endogenously determined. By using panel databases of 35 major cities in China during the period of 1996-2010, we find that the association between house prices and inflation is asymmetric. The impact of inflation on housing prices is greater than that of housing prices on inflation, which implies that housing prices effectively hedge inflation. Secondly, household income positively affects housing prices, but interest rates negatively influence housing prices. Accordingly, to curb soaring housing prices, policymakers not only should balance supply and demand, but also control for inflation. Thirdly, economic growth has less of an impact on inflation than housing prices. Hence, abnormal housing price increases are more likely to exacerbate inflation than economic growth. In addition, housing prices have a greater impact on inflation than rental prices, albeit the latter is a component of the consumer price index (CPI). Finally, money supply has much greater effects on inflation than housing prices and economic growth.


2020 ◽  
Vol 24 (3) ◽  
pp. 165-181
Author(s):  
Fang-Ni Chu ◽  
I-Chun Tsai

This study investigates the housing market in Taiwan, an emerging market with relatively severe housing price inflation. Using data from the first quarter of 1991 to the second quarter of 2017 for four cities in Taiwan, this study compares the risk transmission and sources of their housing prices. The results reveal that Taipei−Taiwan’s main financial hub−has the highest house prices among the four cities but maintains the lowest risk. Thus, in terms of price volatility risk, Taipei has the safest housing market among the studied cities. Other studies have discussed the potential housing price bubbles in regions with high housing prices but have been unable to explain the continual overheating of the housing markets. The findings of this study reveal that despite having the highest housing prices and the greatest potential bubble, the Taipei housing market has the lowest fluctuation risk, making it the safest market in terms of housing investment. The results of this study imply that Taiwan’s economic development is excessively concentrated in Taipei, causing people to bear low returns and high risk when purchasing real estate in other areas, in turn increasing the continual imbalance between regional housing markets.


2021 ◽  
pp. 0308518X2198894
Author(s):  
Peter Phibbs ◽  
Nicole Gurran

On the world stage, Australian cities have been punching above their weight in global indexes of housing prices, sparking heated debates about the causes of and remedies for, sustained house price inflation. This paper examines the evidence base underpinning such debates, and the policy claims made by key commentators and stakeholders. With reference to the wider context of Australia’s housing market over a 20 year period, as well as an in depth analysis of a research paper by Australia’s central Reserve Bank, we show how economic theories commonly position land use planning as a primary driver of new supply constraints but overlook other explanations for housing market behavior. In doing so, we offer an alternative understanding of urban housing markets and land use planning interventions as a basis for more effective policy intervention in Australian and other world cities.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zhijiang Wu ◽  
Yongxiang Wang ◽  
Wei Liu

Purpose Economic fundamentals are recognized as determining factors for housing on the city level, but the relationship between housing price and land supply has been disputed. This study aims to examine what kind of impact housing prices have on land supply and whether there is heterogeneity in different regional spaces. Design/methodology/approach This study collects the relevant data of land supply and housing prices in Nanchang from 2010 to 2018, constructs a vector autoregression (VAR) model, including one external factor and four internal factors of land supply to explore the dynamic effects and spatial heterogeneity of land supply on housing prices through regression analysis. Also, the authors use the geographic detector to analyze the spatial heterogeneity of housing prices in Nanchang. Findings This study found that the interaction between land supply and housing price is extremely complex because of the significant differences in the study area; the variables of land supply have both positive and negative effects on housing price, and the actual effect varies with the region; and residential land and GDP are the two major factors leading to the spatial heterogeneity in housing price. Research limitations/implications The dynamic effects of land supply on housing price are mainly reflected in the center and edge of the city, the new development area, and the old town, which is consistent with the spatial pattern of the double core, three circles and five groups in Nanchang. Originality/value This is a novel work to analyze the dynamic effects of land supply on house prices, instead of a single amount of land supply or land prices. Furthermore, the authors also explore the spatial heterogeneity according to the regional characteristics, which is conducive to targeted policymaking.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Billie Ann Brotman

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.


2019 ◽  
Vol 12 (5) ◽  
pp. 849-864
Author(s):  
Arash Hadizadeh

Purpose In the Iranian economy, investing in the housing market has been very important and beneficial for investors and households, because of inflationary environment, low real interest rates, underdeveloped financial and tax systems and economic sanctions. Hence, prediction of house prices is the main concern of housing market agents in the economy. The purpose of this paper is to test the stationary properties of Iran's provinces to improve the prediction of future housing prices. Design/methodology/approach In this paper, the authors have tested the stationary properties of 20 Iran’s province centers over the period from 1993 to 2017 using a novel Fourier quantile unit root test and conventional ordinary/generalized least squares (O/GLS) linear unit root/stationary tests. Findings According to conventional O/GLS linear unit root/stationary tests, most of the house prices series exhibit random walk behavior, whereas by applying the Fourier quantile unit root test, the null hypothesis of unit root is rejected for 15 out of 20 series. Other results indicated that house prices of cities responded differently to positive and negative shocks. Originality/value Previous studies only addressed conventional OLS or GLS linear unit root or stationary tests, but novel Fourier quantile unit root test was not used. New results were obtained based on this unit root test, that, as a priori knowledge, will help benefiting from the positive effects, or avoiding being victimized by the negative effects.


Buildings ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 6 ◽  
Author(s):  
José Francisco Vergara-Perucich ◽  
Carlos Aguirre-Nuñez

Chile faces a housing affordability crisis, given that most of the population is unable to secure a house. While housing prices between 2008 and 2019 increased by 63.96%, wages only increased by 21.85%. This article presented an analysis of the housing price configuration for the main borough in the country—Santiago. The assessment focused on verticalised housing constructed between 2015 and 2019. The article developed an exploratory study on the price of housing in Santiago to generate a diagnosis to identify the role played by expectations of profitability when configuring price. Based on the information generated, we sought to contribute to the discussion on public policies that advance the development of affordable housing in central boroughs with high urban value, as is the case for Santiago’s borough of Greater Santiago. We hypothesised that profit expectation of real estate developers plays a key role in the housing prices, and an adjustment in the profit ratios might increase the affordability while keeping the housing market above profitable rates. This research addressed the lack of data transparency in the Chilean housing market with archival research, reconstructing costs and earnings from projects based on official registrations of transactions at the borough level. In Chile, the access to investment costs, land values, yields, and house price formation are not publicly available, even though these factors imply that many households are facing severe difficulties in paying for and accessing decent housing.


2019 ◽  
Vol 12 (1) ◽  
pp. 32-61 ◽  
Author(s):  
Maher Asal

Purpose This paper aims to investigate the presence of a housing bubble using Swedish data from 1986Q1-2016Q4 by using various methods. Design/methodology/approach First, the authors use affordability indicators and asset-pricing approaches, including the price-to-income ratio, price-to-rent ratio and user cost, supplemented by a qualitative discussion of other factors affecting house prices. Second, the authors use cointegration techniques to compute the fundamental (or long-run) price, which is then compared with the actual price to test the degree of Sweden’s housing price bubble during the studied period. Third, they apply the univariate right-tailed unit root test procedure to capture bursting bubbles and to date-stamp bubbles. Findings The authors find evidence for rational housing bubbles with explosive behavioral components beginning in 2004. These bubbles do not continuously diverge but instead periodically revert to their fundamental value. However, the deviation is persistent, and without any policy correction, it takes decades for real house prices to return to equilibrium. Originality/value The policy implication is that monetary policy designed to contain mortgage demand and thereby prevent burst episodes in the housing market must address external imbalances, as revealed in real exchange rate undervaluation. It is unlikely that current policies will stop the rise of house prices, as the growth of mortgage credit, improvement in Sweden’s international competitiveness and the path of interest rates are much more important factors.


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