The Impact of Real Estate Regulation on Housing Prices: Focus on the Actual Transaction Price of Apartments at Suwon

2020 ◽  
Vol 28 (4) ◽  
pp. 109-132
Author(s):  
Koang-Sung Choi ◽  
Min-Ji Noh
Keyword(s):  
Real Estate ◽  
Housing Prices ◽  
The Impact ◽  
Transaction Price

scholarly journals Le marché immobilier : quelques perspectives à long terme pour la région de Trois-Rivières

2009 ◽  
Vol 59 (1) ◽  
pp. 153-163
Author(s):  
L. M. Farrell
Keyword(s):  
Real Estate ◽  
Housing Prices ◽  
Consumer Price Index ◽  
Listing Service ◽  
Real Estate Markets ◽  
Long Run ◽  
Time Period ◽  
Short Period ◽  
The Impact ◽  
Transaction Price

Abstract The results of any analysis of local real estate markets must be qualified interms of the long run equilibrium conditions assumed in the study. Such propertycharacteristics as: non homogeneity, durability, length of response lag time, etc.,are frequently suggested as major factors which contribute to the inefficiency ofreal estate markets. Periods of prolonged exogeneous inflationary expectations,which may be indicated by changes in the Consumer Price Index (CPI), addfurther complexity to the analysis of real estate markets. This paper presents a brief discussion of the factors which influence thesupply and demand for Real Estate. Special reference is made to the City ofTrois-Rivières, Québec, which is analysed over the ten year period 1971 to 1981. In this market the impact of changes in income on long run demand would appearto be negative. The effect of demographic factors, particularly population in the25 to 34 year age group, is not clear. There is some indication of a shift in supplyacross submarkets over the 1976-1979 time period. Price changes, measured in current dollars using the Multiple Listing Service(MLS) average transaction price, increased approximately 200 per cent over arelatively short period in the early 1970s. Most of this appreciation appears tohave been lost over the longer time period of the study. Average MLS transaction price, adjusted for inflation, fluctuated between$12,000 and $28,000 over the same period. After appropriate qualification of the results, in terms of the data and themethodology used to analyse the data, it would appear that housing prices in theaggregated Trois-Rivières market have not increased appreciably in current orconstant dollars over the period 1971-1981 although this may not have been thecase in particular submarkets.

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 Asymmetric and Spatial Non-Stationary Effects of Particulate Air Pollution on Urban Housing Prices in Chinese Cities

2020 ◽  
Vol 17 (20) ◽  
pp. 7443
Author(s):  
Biao Sun ◽  
Shan Yang
Keyword(s):  
Real Estate ◽  
Quantile Regression ◽  
Housing Prices ◽  
Spatial Relationship ◽  
Well Being ◽  
Urban Housing ◽  
Real Estate Market ◽  
Economic Losses ◽  
Full Account ◽  
The Impact

Fine particulate matter(PM2.5) pollution will affect people’s well-being and cause economic losses. It is of great value to study the impact of PM2.5 on the real estate market. While previous studies have examined the effects of PM2.5 pollution on urban housing prices, there has been little in-depth research on these effects, which are spatially heterogeneous at different conditional quantiles. To address this issue, this study employs quantile regression (QR) and geographically weighted quantile regression (GWQR) models to obtain a full account of asymmetric and spatial non-stationary effects of PM2.5 pollution on urban housing prices through 286 Chinese prefecture-level cities for 2005–2013. Considerable differences in the data distributions and spatial characteristics of PM2.5 pollution and urban housing prices are found, indicating the presence of asymmetric and spatial non-stationary effects. The quantile regression results show that the negative influences of PM2.5 pollution on urban housing prices are stronger at higher quantiles and become more pronounced with time. Furthermore, the spatial relationship between PM2.5 pollution and urban housing prices is spatial non-stationary at most quantiles for the study period. A negative correlation gradually dominates in most of the study areas. At higher quantiles, PM2.5 pollution is always negatively correlated with urban housing prices in eastern coastal areas and is stable over time. Based on these findings, we call for more targeted approaches to regional real estate development and environmental protection policies.

International Real Estate Review

2020 ◽  
Vol 23 (4) ◽  
pp. 467-482
Author(s):  
Fathali Firoozi ◽  
◽  
Abolhassan Jalilvand ◽  
Donald Lien ◽  
Mikiko Oliver ◽  
...  
Keyword(s):  
Real Estate ◽  
Economic Impact ◽  
Population Aging ◽  
Housing Prices ◽  
The Elderly ◽  
Damping Effect ◽  
The World ◽  
Behavioral Divergence ◽  
The Impact ◽  
The U.S

Population aging and its economic impact have been receiving increasing attention in many countries around the world. This study offers an analysis of the impact of aging on the housing prices in Singapore relative to the U.S. as the benchmark. The study uses semiannual series over the period of 1998 to 2019 with the age subgroups organized in 5-year intervals. The literature contains conflicting arguments on the impacts of aging on housing prices. Based on observations made for Singapore and the U.S., this study supports the arguments that the elderly part of a population has a damping effect on housing prices. A novel behavioral divergence between Singapore and the U.S. emerges when the analysis focuses on the impact of the finer age subgroups on housing prices in the two countries. The “turning age”, which is defined as the approximate cut-off age when the impact of aging on housing prices turns from positive to negative, is approximately 55 years old in Singapore and 60 years old in the U.S.

Application of ARMA Regression Model of Housing Prices Influence Factors of Xi'an

2013 ◽  
Vol 405-408 ◽  
pp. 3340-3342
Author(s):  
Hui Zhi ◽  
Yue Fan Wang
Keyword(s):  
Real Estate ◽  
Regression Model ◽  
Housing Prices ◽  
Influence Factors ◽  
Housing Price ◽  
The Real Estate ◽  
Housing Price Index ◽  
Long Run ◽  
The Government ◽  
The Impact

By selecting the relevant factors affect the real estate price, with the qualitative analysis method to analyze the housing prices changes of Xi'an, and then establish ARMA regression model of the housing price index, found that the factors exist long-run co-integration. In order to better reflect the actual, the government policy as a dummy variable is introduced into the model to make regression results more significantly, showing that government policies play an important role in the control of the impact on real estate prices.

Credit expansion, state ownership and capital structure of Chinese real estate companies

2016 ◽  
Vol 34 (3) ◽  
pp. 263-275 ◽  
Author(s):  
Jianfu Shen ◽  
Xianting Yin
Keyword(s):  
Real Estate ◽  
Capital Structure ◽  
Housing Prices ◽  
Debt Financing ◽  
Credit Expansion ◽  
Content Type ◽  
Real Estate Markets ◽  
Credit Supply ◽  
The Impact ◽  
Expansion Period

Purpose – The purpose of this paper is to explore the impact of the credit expansion in 2009 and 2010 in China on the capital structure of listed real estate companies. Design/methodology/approach – Chinese listed real estate companies are divided into two groups, state-owned and non-state-owned, because their access to credit markets have different priority to state-owned banks that dominate bank lending. The difference-in-differences approach is employed to test the impact of changes in leverage ratios and loan ratios before and after the credit expansion period in state-owned firms and non-state-owned firms. Findings – Using quarterly panel regressions, the authors find that during the credit expansion period, state-owned companies exhibit a relatively greater increase in leverage ratios than non-state-owned firms. State-owned firms have greater increases in book leverage ratios, market leverage ratios and long-term debt ratios by 5.2, 4.9 and 1.1 per cent, respectively. It is also shown that loan ratios have increased more in state-owned firms than non-state-owned firms during the credit expansion period. Research limitations/implications – The paper explores only the impacts of credit expansion on capital structure of listed real estate firms in China. Further studies can be conducted to investigate the impact of credit supply on corporate investment decisions of real estate firms and on real estate markets. Practical implications – The findings can help explain the surge in land and housing prices after 2008 in China. Deng et al. (2015) find that state-owned real estate firms paid more for land price than non-state-owned firms, which contributed to upward pressure on housing prices. This paper shows that such “over-investment” may be due to the increase of debt financing and availability of bank loans to real estate firms. Thus the credit market can affect real estate markets through debt financing at company level. Originality/value – This paper is the first to investigate the impact of credit supply on capital structure of real estate companies, and presents evidence of the importance of credit supply as a determinant of capital structure.

scholarly journals International Real Estate Review

2019 ◽  
Vol 22 (2) ◽  
pp. 197-229
Author(s):  
Hui An ◽  
◽  
Qianmiao Zou ◽  
Ying Zhang ◽  
◽  
...  
Keyword(s):  
Real Estate ◽  
Likelihood Ratio ◽  
Housing Prices ◽  
National Level ◽  
Var Model ◽  
Monthly Data ◽  
Regional Characteristics ◽  
Second Tier ◽  
The Impact ◽  
The City

In recent years, China has uniquely implemented various policies to control housing prices, particularly its property- purchasing limitation policy. This research proposes a vector autoregression (VAR) model with likelihood-ratio (LR) tests to examine the effects of such a policy on housing prices at the national, provincial and city levels in China, with the use of monthly data from 2002 to 2013. The results show that at the national level, the effect of the policy is very significant, and the impact on housing prices is far greater than monetary and credit policies. However, the policy is not applicable at the provincial level. The policy has a significant role at the city level in first-tier cities, but no significant effect in second- tier cities. Overall, property-purchasing limitations inhibit the growth of housing prices to some extent, and the effects show strong regional characteristics, especially at the city level. Policymakers should therefore take into account regional characteristics in the formulation and implementation of a property-purchasing limitation policy.

scholarly journals International Real Estate Review

2012 ◽  
Vol 15 (3) ◽  
pp. 325-346
Author(s):  
Chu-Chia Lin ◽  
◽  
Chien-Liang Chen ◽  
Ya-Chien Twu ◽  
◽  
...  
Keyword(s):  
Real Estate ◽  
Negative Impact ◽  
Daily Life ◽  
Housing Prices ◽  
Chinese Society ◽  
Feng Shui ◽  
Data Set ◽  
Body Of Knowledge ◽  
The Impact ◽  
Housing Units

Feng-shui is an old and traditional body of knowledge in Chinese society. Feng-shui has a significant influence on many aspects in daily life for most Chinese, including choosing locations for dwelling units, offices, burial sites, and so on. However, there have been few studies on the impact of feng-shui on housing prices. By applying a housing hedonic equation and a data set of 77,624 observations in Taiwan, we have attempted to estimate the impact of feng-shui on housing prices. We find that all six types of bad feng-shui have a significantly negative impact on housing prices. Moreover, by applying a quantile regression, we find that most of the bad feng-shui has a stronger negative impact on expensive dwelling units. Our findings confirm that people who buy expensive housing units care about feng-shui more than those who buy less expensive housing units.

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