scholarly journals EXPLORING THE IMPACT OF REAL ESTATE POLICY ON REAL ESTATE TRADING USING THE TIME SERIES ANALYSIS

2020 ◽  
Vol XLII-3/W10 ◽  
pp. 1281-1287
Author(s):  
S. W. Shao ◽  
X. Huang ◽  
L. X. Xiao ◽  
H. Liu
Keyword(s):  
Time Series ◽  
Real Estate ◽  
Time Series Analysis ◽  
Housing Prices ◽  
The Real ◽  
The Real Estate ◽  
Series Analysis ◽  
Registration Data ◽  
The People ◽  
The Impact

Abstract. Housing price is a major issue affecting people's lives, but also closely related to the interests of the people themselves. Housing prices are affected by various factors, such as economic factors, population size factors, social factors, national policy factors, the internal factors of real estate and environmental factors. With the deepening of urbanization and the agglomeration of urban population in China, housing prices have been further accelerated. The Chinese government has also introduced a series of policies to limit real estate transactions and affect property prices. This paper also aims to explore a time series analysis method to analyse the impact of real estate policies on real estate prices. Firstly, the article searches for policy factors related to real estate through government official channels such as state, Prefecture and city, and analyses key words related to policy by means of natural language processing. Then, the real estate registration volume, transaction volume and transaction house price data which are arranged into time series are modelled using ARIMA time series model, and the data are processed according to scatter plot, autocorrelation function and partial autocorrelation function graph of the model to identify its stationarity. Finally, the LPPL (logarithmic periodic power) model and MPGA (multi-population genetic algorithm) are used to fit and detect turning points of real estate registration data, and the time series detection algorithm is used to obtain the inflection time nodes of the sequence, and then the relationship between real estate policy and real estate transactions is analysed. Taking the real estate registration data in Wuhan as an example, this paper validates the above time series analysis method. The results show that some real estate policies (such as purchase restriction policy, public rental policy, etc.) have a certain impact on real estate transactions in a short time. Part of the real estate policy (such as graduate security, settlement policy, etc.) does not have a significant impact on real estate transactions. To sum up, the government's brutal blockade of macro-control of the housing market cannot fundamentally solve the housing difficulties of the people, but also standardize the real estate market trading mechanism, innovate the market trading mode, so as to promote the long-term development of the housing market.

The real estate industry in Turkey: a time series analysis

2018 ◽  
pp. 1-13 ◽  
Author(s):  
Dervis Kirikkaleli ◽  
Seyed Alireza Athari ◽  
Hasan Murat Ertugrul
Keyword(s):  
Time Series ◽  
Real Estate ◽  
Time Series Analysis ◽  
Real Estate Industry ◽  
The Real ◽  
The Real Estate ◽  
Series Analysis

scholarly journals The Impact of Property Tax on the Development of Real Estate Industry

2021 ◽  
Vol 4 (3) ◽  
pp. 73-75
Author(s):  
Ruoke Hu ◽  
Fangke Li
Keyword(s):  
Real Estate ◽  
Rapid Development ◽  
Housing Prices ◽  
Property Tax ◽  
Real Estate Industry ◽  
High Property ◽  
The Real ◽  
The Real Estate ◽  
Significant Growth ◽  
The Impact

In recent years, due to the rapid development of the real estate industry in China, land speculation has begun in addition to the significant growth in economy. However, this rapid development has led to an extreme rise in housing prices, largely owing to high property tax. This article analyzed the impact of property tax on the development of real estate industry and provided countermeasures.

Research on the Impacts of Real Estate on Economic Growth: A Theoretical Model-Based Analysis

2018 ◽  
Vol 06 (04) ◽  
pp. 1850025
Author(s):  
Xiaoxi ZHANG ◽  
Lu GUO
Keyword(s):  
Economic Growth ◽  
Real Estate ◽  
Low Income ◽  
Housing Prices ◽  
Well Being ◽  
Real Estate Market ◽  
The Real ◽  
The Real Estate ◽  
Pillar Industry ◽  
The Impact

As the pillar industry of China’s economy, the real estate sector has a significant impact on macroeconomic growth. We assume that the first stage of economic actors’ working lives is a low-income one, while their second stage is a high-income one. Then, relying on an Overlapping-Generations Model, we analyze how, via real estate, the behaviors of different income groups affect the macroeconomy. The results show that when the supply of real estate market fluctuates then this has an impact on economic growth, but the extent of the impact depends on the relationship between the real estate and the consumer markets. We also find that when economic actors more greatly prefer their current situations of well-being, no matter whether there takes place or not a new increase in real estate stocks, a negative correlation will exist in the relation between real estate stocks and their prices. Lastly, we come to the conclusion that increases in property taxes can effectively reduce housing prices, but the impact of transaction taxes on housing prices can still not be determined.

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.

The Impact of Zoning Changes on Housing Prices: A Time Series Analysis

1986 ◽  
Vol 17 (3) ◽  
pp. 49-70 ◽  
Author(s):  
GEORGE A. CHRESSANTHIS
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Housing Prices ◽  
Series Analysis ◽  
The Impact

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 Impact of the Economic Stimulus Measures on Lithuanian Real Estate Market under the Conditions of the COVID-19 Pandemic

2021 ◽  
Vol 32 (5) ◽  
pp. 459-468
Author(s):  
Vaida Pilinkienė ◽  
Alina Stundziene ◽  
Evaldas Stankevičius ◽  
Andrius Grybauskas
Keyword(s):  
Real Estate ◽  
Housing Prices ◽  
Real Estate Market ◽  
Substantial Part ◽  
Negative Effects ◽  
The Real ◽  
The Real Estate ◽  
The Real Estate Market ◽  
Economic Stimulus ◽  
The Impact

The COVID-19 pandemic caused a number of challenges worldwide regarding not only the human health perspective, but also the economic situation. Quarantine, imposed in many countries, forced a substantial part of businesses to close or narrow down their activities, thus leaving corporations and employees without any or with lower income. If national governments had not undertaken any actions to save national economies, the consequences could have been even more devastating. The real estate market is an important part of economy. Instability in the real estate market can cause financial problems, vulnerability of population’s welfare and other negative effects. This research aims to assess the impact of the economic stimulus measures on the real estate market under the conditions of the COVID-19 pandemic in Lithuania. The research methods include comparative analysis, correlation analysis, stationarity test, regression analysis and the ARDL models. The results indicate that the economic stimulus measures only partially contribute to stabilization of the real estate market in Lithuania. The drop in housing prices was 2.9 percent lower because of the economic stimulus in the second quarter of 2020. Maintenance of household cash and deposits as well as lending to business enterprises are the measures that allow to stabilize the real estate market in the shortest time under the conditions of the economic shock. The other governmental support measures are also important, especially if they are aimed at preserving jobs.

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