scholarly journals Impact of Property Tax on Housing-Market Disequilibrium in Different Regions: Evidence from Taiwan for the period 1982–2016

2018 ◽  
Vol 10 (11) ◽  
pp. 4318 ◽  
Author(s):  
Sheng-Hau Lin ◽  
Jia-Hsun Li ◽  
Jing-Chzi Hsieh ◽  
Xianjin Huang ◽  
Jia-Tsong Chen
Keyword(s):  
Housing Market ◽  
Supply And Demand ◽  
Property Tax ◽  
Housing Price ◽  
Housing Demand ◽  
Tax System ◽  
Interest Rate Policy ◽  
Long Run ◽  
The Impact ◽  
Market Disequilibrium

Although Taiwan has had a unique property tax system for a long time, oversupply and increasing prices have persisted in the regional market during recent decades. In order to shed light on this problem, this study investigated the impact of property taxation on housing markets in different regions from a disequilibrium viewpoint based on the stock-flow model. The panel data of 20 counties or cities in Taiwan for the period from 1982 to 2016 was examined. The empirical findings verified that housing price was the most important factor for influencing the long-run housing supply and demand in regions both with and without oversupply. The low interest rate policy was an important factor driving the long-run housing demand, but only in over-supply regions. The current property tax system cannot impact the long-run housing demand, only the short-run demand in both regions. Moreover, the property tax cannot effectively disturb the supply behavior in the long-run in both regions. This study also confirmed that housing-market disequilibrium existed in regions both with and without oversupply, making up the gap. The property tax’s impact on the adjustment speed to long-run equilibrium in over-supply regions was weaker than under-supply regions.

scholarly journals International Real Estate Review

2017 ◽  
Vol 20 (3) ◽  
pp. 375-396
Author(s):  
Gary Wai Chung Wong ◽  
◽  
Lok Sang Ho ◽  
Keyword(s):  
Interest Rate ◽  
Housing Market ◽  
Supply And Demand ◽  
Housing Prices ◽  
Housing Price ◽  
Price Expectations ◽  
Price Expectation ◽  
Long Run ◽  
Property Price ◽  
Explicit Consideration

This paper builds on the literature that shows policy often plays a key role in housing cycles. Using the cointegration approach which focuses on the supply and demand dynamics of the housing market, and with explicit consideration of housing price expectations proxied by the price-earning ratio in financial markets, this paper identifies two cointegrating relations: a long run demand-side relation that involves housing property price, interest rate, price expectation and income; and a supply-side relation that involves private housing completion, property price, interest rate, and building and land costs. Based on Hong Kong data from 1990 a£á¡§ 2012, which covers big cycles in the housing market, this paper suggests that policies to augment or restrain housing supply in the attempt to stabilize housing prices have been counterproductive.

scholarly journals Housing Price Forecasting in Selected Polish Cities During the COVID-19 Pandemic

2021 ◽  
Vol 15 (4) ◽  
pp. 59-80
Author(s):  
Mirosław Bełej
Keyword(s):  
Housing Market ◽  
Supply And Demand ◽  
Housing Price ◽  
Housing Markets ◽  
Housing Demand ◽  
Price Forecasting ◽  
Arima Models ◽  
Housing Price Dynamics ◽  
Near Future ◽  
Negative Shock

The COVID-19 pandemic represents a combined supply and demand shock to the financial and housing market but also an unusual negative shock in terms of the health of society (households) and national economy. The fall in housing demand was initially assumed together with price decreases as a consequence of the uncertainty of the health of society, significant falls in stock markets and corporate solvency. However, the results of research in selected Polish cities do not indicate such a significant market recession. This article examines the housing price dynamics and forecasting in Polish cities during the COVID-19 pandemic. The TRAMO/SEATS and ARIMA models were used for the decomposition and forecasting of dwelling time series. The Polish housing market, represented by selected local housing markets, still shows a growing trend despite the COVID-19 pandemic throughout 2020. The housing market may slow down in 2021, but the strong forecasted growth trends in Warszawa and Poznań suggest that there will be no significant price decline in Poland in the near future.

Research about the Disequilibrium Degree of Supplying and Demanding Market for Newly-Built Commodity-Housing from 1998 to 2011 in Xian

2013 ◽  
Vol 838-841 ◽  
pp. 3115-3118
Author(s):  
Jian Ping Yang ◽  
Fan Ming Meng
Keyword(s):  
Supply And Demand ◽  
Housing Price ◽  
Housing Demand ◽  
The State ◽  
Land Supply ◽  
Equilibrium Degree ◽  
Load Rate ◽  
Per Capita ◽  
Spss Software ◽  
Disequilibrium Theory

Basing on the disequilibrium theory, taking use of SPSS software, taking advantaging of multiple linear regression methodology, this article analyzed the state of supply and demand of newly built commodity-housing market from1998 to 2011 in Xian, constructed the equation about land supply, housing price, load rate and housing-supply, and constructed the equation about per capita disposable income, and housing-demand. Basing on the supply-equation and demand-equation, this article obtained the state of supply and demand of new-built commodity- housing in Xian, at last, calculated the non-equilibrium degree and drew a conclusion.

Hangzhou Housing Demand Forecasting Model Based on BP Neural Network of Genetic Algorithm Optimization

2014 ◽  
Vol 587-589 ◽  
pp. 37-41 ◽  
Author(s):  
Yi Hua Mao ◽  
Meng Bo Zhang ◽  
Ning Bo Yao
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Real Estate ◽  
Housing Market ◽  
Bp Neural Network ◽  
Housing Demand ◽  
Forecasting Model ◽  
Algorithm Optimization ◽  
Genetic Algorithm Optimization ◽  
The Impact

Hangzhou, the capital of Zhejiang province and a famous scenic tourist city in China, goes at the forefront of the country for its high real estate prices, which hold a very important position of orientation to pricing in the real estate markets of the Yangtze River Delta region and of the whole country as well. The price trend of Hangzhou's real estate is even related to the sustainable development of the city. This paper uses the macro data on the housing market in Hangzhou during 1999-2012 to establish a forecasting model which is based on BP neural network of genetic algorithm optimization. With MATLAB software exploited for programming and simulation, the prediction made by the model about the housing demand in Hangzhou and the subsequent re-examination show that the model has high precision. But due to the impact of the national macro-control policies on housing market, the predictive value of some years may fluctuate to a certain extent.

scholarly journals International Real Estate Review

2018 ◽  
Vol 21 (3) ◽  
pp. 397-418
Author(s):  
Chin-Oh Chang ◽  
◽  
Shu-Mei Chen ◽  
Keyword(s):  
Housing Market ◽  
Home Ownership ◽  
Housing Prices ◽  
Housing Price ◽  
Poor Quality ◽  
Housing Demand ◽  
Vacancy Rate ◽  
Income Ratio ◽  
Holding Cost ◽  
Housing Vacancy

This paper discusses the contradicting phenomenon of housing demand in Taiwan. First, an introduction is given on the three primary characteristics of the housing market in Taiwan, which are a high housing vacancy rate, high housing prices and high home ownership. Secondly, we explore the motivation and preferences behind housing purchase. Since the housing price-income ratio continues to increase, unaffordable housing prices cause households to suffer from poor quality of life. The issues of housing justice are highlighted. Recently, the demographics and social values have rapidly changed. Therefore, even if homebuyers face unaffordable housing prices, they still prefer to buy housing instead of renting due to the traditional cultural belief that ¡§to have land is to have wealth¡¨. This has resulted in the phenomenon with high home ownership rate yet high housing prices. On the other hand, the low holding cost of housing and imbalance in urban and rural development perpetuate the high housing vacancy rate in the housing market. This results in an unhealthy housing market and misallocation of resources. Finally, recommendations for related government policy making are made based on the findings.

scholarly journals The impact of aging on urban housing demand based on CGE

Filomat ◽  
2016 ◽  
Vol 30 (15) ◽  
pp. 4151-4171
Author(s):  
Zhu Linlin ◽  
Li Xiuting ◽  
Dong Jichang
Keyword(s):  
General Equilibrium ◽  
Housing Market ◽  
Equilibrium Model ◽  
Urban Housing ◽  
Housing Demand ◽  
General Equilibrium Model ◽  
Overlapping Generation ◽  
Generation Structure ◽  
Change Trend ◽  
The Impact

The population of China has been aging quickly in recent years, which will profoundly affect the housing market. This paper aims to analyze the effect of aging on urban housing demand. First, a general equilibrium model with an overlapping generation structure is established to analyze theoretically the effect of aging. Then, this paper uses GAMS software to simulate and forecast the change trend in urban housing demand. Finally, based on the research sample of 287 large and medium-sized cities in China in 2010, this paper uses ArcGis9.3 software to study empirically the influence of aging on urban housing demand and concludes that aging can increase urban housing demand.

Long-run drivers and integration in interprovincial Canadian housing price relations

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Vijay Kumar Vishwakarma
Keyword(s):  
Housing Market ◽  
Granger Causality ◽  
Global Financial Crisis ◽  
Housing Prices ◽  
Housing Price ◽  
Housing Markets ◽  
Content Type ◽  
Stochastic Trend ◽  
Long Run ◽  
Long Run Equilibrium

Purpose This paper aims to examine the integration of housing markets in Canada by examining housing price data (1999–2016) of six metropolitan areas in different provinces, namely, Calgary, Vancouver, Winnipeg, Toronto, Montreal and Halifax. The authors test for cointegration, driver cities of long-run relationships, long-run Granger causality and instantaneous causality in light of the global financial crisis (GFC) (2007–2008). Design/methodology/approach The authors use Johansen’s system cointegration approach with structural breaks. Moving average representation is used for common stochastic trend(s) analysis. Finally, the authors apply vector error correction model-based Granger causality and instantaneous causality. Findings Cities’ housing prices are in long-run equilibrium. Post-crisis Canadian housing markets became more integrated. The Calgary, Vancouver, Toronto and Montreal markets drive the Canadian housing market, leading all cities toward long-run equilibrium. Strong long-run Granger causality exists, but the authors observe no instantaneous causality. Price information takes time to disseminate, and long-run price adjustments play a significant role in causation. Practical implications The findings of cointegration increasing after the GFC and strong lead–lag can be used by investors to arbitrage and optimize portfolios. This can also help national and local policymakers in mitigating risk. Incorporating these findings can lead to better price forecasting. Originality/value This study presents many novelties for the Canadian housing market: it is the first to use repeat-sales regional pricing indices to test long-run behaviors, conduct common stochastic trend analyzes and present causality relations.

The impact of COVID-19 on home value in major Texas cities

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mira R. Bhat ◽  
Junfeng Jiao ◽  
Amin Azimian
Keyword(s):  
Housing Market ◽  
Mixed Model ◽  
Negative Relationship ◽  
Housing Price ◽  
Single Family ◽  
Related Factors ◽  
Content Type ◽  
Home Value ◽  
Business Cycle Index ◽  
The Impact

Purpose This study aims to analyze the impact of COVID-19 on housing price within four major metropolitan areas in Texas: Austin, Dallas, Houston and San Antonio. The analysis intends to understand economic and mobility drivers behind the housing market under the inclusion of fixed and random effects. Design/methodology/approach This study used a linear mixed effects model to assess the socioeconomic and housing and transport-related factors contributing to median home prices in four major cities in Texas and to capture unobserved factors operating at spatial and temporal level during the COVID-19 pandemic. Findings The regression results indicated that an increase in new COVID-19 cases resulted in an increase in housing price. Additionally, housing price had a significant and negative relationship with the following variables: business cycle index, mortgage rate, percent of single-family homes, population density and foot traffic. Interestingly, unemployment claims did not have a significant impact on housing price, contrary to previous COVID-19 housing market related literature. Originality/value Previous literature analyzed the housing market within the first phase of COVID-19, whereas this study analyzed the effects of the COVID-19 throughout the entirety of 2020. The mixed model includes spatial and temporal analyses as well as provides insight into how quantitative-based mobility behavior impacted housing price, rather than relying on qualitative indicators such as shutdown order implementation.

Perspectives of SiC Power Devices in Highly Efficient Renewable Energy Conversion Systems

2009 ◽  
Vol 615-617 ◽  
pp. 889-894 ◽  
Author(s):  
Peter Zacharias
Keyword(s):  
Fossil Fuels ◽  
Supply And Demand ◽  
Energy Sources ◽  
Power Conditioning ◽  
Long Run ◽  
Ac Power ◽  
Energy Conversion Systems ◽  
Decentralized Energy ◽  
Regenerative Energy ◽  
The Impact

In the long run, regenerative energy sources represent the most important alternatives to fossil fuels. In general, they are characterized by decentralized logistics and supply capabilities due to ihnerent lower energetic densitiy per are, when compared with the fossil counterparts. As a result, the increased use of regenerative energy sources will require decentralized structures for energy supply, consumption optimisation and regional balancing between supply and demand. Both, the more efficient utilization of fossil energy sources and the utilization of regenerative energy sources, lead to increasingly decentralized supply structures and can be understood as being both complementary and convergent in relation to each other. Most of the converter units for utilization of decentralized energy resources (DER) use power electronics for the AC power conditioning with grid quality. The current paper shows market perspectives of DER applications and the impact of SiC on these application.

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.

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