scholarly journals Capital Gain Expectations And Efficiency In The Real Estate Markets

2011 ◽  
Vol 6 (4) ◽  
Author(s):  
Shady Kholdy ◽  
Ahmad Sohrabian
Keyword(s):  
Real Estate ◽  
Housing Market ◽  
Housing Prices ◽  
Housing Price ◽  
Capital Gain ◽  
Real Estate Markets ◽  
The Real ◽  
The Real Estate ◽  
Real Estate Price ◽  
Economic Fundamentals

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.

scholarly journals Prosperity or Real Estate Bubble? Exuberance Probability Index of Real Housing Prices in Chile

2021 ◽  
Vol 9 (3) ◽  
pp. 51
Author(s):  
Byron J. Idrovo-Aguirre ◽  
Francisco J. Lozano ◽  
Javier E. Contreras-Reyes
Keyword(s):  
Real Estate ◽  
Financial Market ◽  
Housing Prices ◽  
Housing Price ◽  
The Real ◽  
The Real Estate ◽  
Real Estate Price ◽  
Mortgage Interest ◽  
Real Estate Bubble ◽  
Probability Index

In this paper, we approached the concept of real estate bubble, analyzing the risk its bursting could generate for the Chilean financial market. Specifically, we analyzed the relationship between real housing prices, the economic activity index, and mortgage interest rates denominated in inflation-linked units from 1994 to 2020. The analysis was based on a second order Markov switching model with the predetermined variables mentioned later, whose parameters were obtained through the expectation–maximization algorithm. Then, we built a probability index as early warning indicator for potential imbalances in the real estate price that could put financial market stability at risk. The indicator is important to evaluate economic policy calibrations in time. A main finding was that the real housing price had a non-linear relationship with economic activity and the mortgage interest rate. Therefore, the evolution of the real estate price has been consistent with fundamental macroeconomic variables, even under a high growth regime, with increases above 12% per year. About 92% of housing price variability derived from changing macrofinancial conditions, suggesting a low margin of speculative behavior.

scholarly journals COVID-19 Infects Real Estate Markets: Short and Mid-Run Effects on Housing Prices in Campania Region (Italy)

2020 ◽  
Vol 9 (7) ◽  
pp. 114 ◽  
Author(s):  
Vincenzo Del Giudice ◽  
Pierfrancesco De Paola ◽  
Francesco Paolo Del Giudice
Keyword(s):  
Real Estate ◽  
Housing Prices ◽  
Real Estate Market ◽  
Campania Region ◽  
Real Estate Markets ◽  
The Real ◽  
The Real Estate ◽  
Short Run ◽  
Predator Model ◽  
Real Estate Prices

The COVID-19 (also called “SARS-CoV-2”) pandemic is causing a dramatic reduction in consumption, with a further drop in prices and a decrease in workers’ per capita income. To this will be added an increase in unemployment, which will further depress consumption. The real estate market, as for other productive and commercial sectors, in the short and mid-run, will not tend to move independently from the context of the aforementioned economic variables. The effect of pandemics or health emergencies on housing markets is an unexplored topic in international literature. For this reason, firstly, the few specific studies found are reported and, by analogy, studies on the effects of terrorism attacks and natural disasters on real estate prices are examined too. Subsequently, beginning from the real estate dynamics and economic indicators of the Campania region before the COVID-19 emergency, the current COVID-19 scenario is defined (focusing on unemployment, personal and household income, real estate judicial execution, real estate dynamics). Finally, a real estate pricing model is developed, evaluating the short and mid-run COVID-19 effects on housing prices. To predict possible changes in the mid-run of real estate judicial execution and real estate dynamics, the economic model of Lotka–Volterra (also known as the “prey–predator” model) was applied. Results of the model indicate a housing prices drop of 4.16% in the short-run and 6.49% in the mid-run (late 2020–early 2021).

scholarly journals Analysis of Urban Residents' Sports Consumption Demand Based on Intercepted Regression Model

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Qing Liu
Keyword(s):  
Real Estate ◽  
Housing Prices ◽  
Real Estate Market ◽  
Survey Method ◽  
Real Estate Industry ◽  
The Real ◽  
The Real Estate ◽  
Real Estate Price ◽  
Real Estate Prices ◽  
The Impact

At this stage, broadening the consumer market, upgrading the consumption system and gradually establishing a consumption-led development concept are key factors in promoting high-quality economic development. At the same time, China's macro economy is also experiencing another test. The rapid development of China's real estate market in recent years has attracted a large number of investors, and real estate prices have produced irrational and substantial increases. Behind the boom of the real estate market is a social system crisis driven by profiteering and the growing seriousness of real estate financial bubble. So exploring the mechanism of the influence of real estate prices on the upgrading of residents' consumption is important for the current stage of China. Therefore, it is important to investigate the mechanism of real estate price impact on consumer upgrading for the coordinated development of real estate industry and national economy. In this paper, we analyze and examine the theory on the consumption improvement by the literature survey method. We also summarize the present research on the correlation and the influence mechanism of the real estate price and the consumption improvement and choose the index which reflects the present state of the real estate industry and the consumption of the inhabitant. Besides the input indicators that qualitatively manage the impact of housing prices on the improvement of residents' consumption, we first use the descriptive statistics method to understand the level of the Chinese real estate market and improve consumer spending. Based on this, the descriptive statistical method is applied to define the current state of China's real estate market and the level of improvement in consumption, and to define the standard for improving consumption in China. On the other hand, based on the spatial and spatial spillover points of view, we use spatial analysis framework combined with exploratory spatial data analysis and GIS to investigate spatial correlation between consumption structure and housing price, and accurately reflect the spatial clustering status of the index by drawing. Moran dispersion plot and Lisa cluster plot, then the spatial Darwinian model, are used to investigate the impact of real estate prices on the increase in occupant consumption from a macro perspective.

FINANCIAL DEVELOPMENT AND HOUSING PRICE CHANGES UNDER THE CONDITION OF FINANCIAL CONTROL: EVIDENCE FROM CHINA

2021 ◽  
pp. 1-27
Author(s):  
XUE LI ◽  
RUO-XI ZHANG
Keyword(s):  
Real Estate ◽  
Financial Development ◽  
Housing Prices ◽  
Housing Price ◽  
Financial Control ◽  
Real Estate Industry ◽  
Price Changes ◽  
The Real ◽  
The Real Estate ◽  
Real Estate Prices

The impact of financial development on the real estate industry has increased with the degree of financial control. This research presented in this paper divides China’s area into strong and weak regions based on the degree of financial control, and then it studies the relationship between housing price changes and the level of financial development using panel data from the period 1994 to 2018. We find that the level of national sample financial development plays an important role in promoting the housing prices. In areas with strong financial control, financial resources tend to be allocated to the real estate industry, boosting real estate prices. In areas with weak financial control, the role of financial development in promoting real estate prices is not obvious. The funds accumulated by financial institutions are more marketable and independent. We have confirmed these findings by our analysis of the transformation of certain financial control and financial development variables, the application of Panel-VAR estimation methods, and other robustness tests.

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.

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.

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.

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