International Real Estate Review

2010 ◽  
Vol 13 (2) ◽  
pp. 190-217
Author(s):  
Jie Chen ◽  
◽  
Qianjin Hao ◽  
Keyword(s):  
Real Estate ◽  
Empirical Analysis ◽  
Prediction Accuracy ◽  
Large Scale ◽  
Real Estate Market ◽  
Real Estate Price ◽  
Real Estate Projects ◽  
Real Estate Prices

This paper contributes to the literature by examining how much the prediction accuracy of real estate prices could be improved by applying hedonic equations at suitably defined disaggregate levels and incorporating directional heterogeneity of distance gradients. We build our empirical analysis on a large-scale database of real estate projects sold between 2005 and 2007 in Shanghai. Our analysis suggests that the Shanghai real estate market is a complex aggregate and taking into account submarket and directional heterogeneity in hedonic regressions could provide considerable benefits in improving the precision of real estate price predictions.

Influence Factors of Chinese Real Estate

2013 ◽  
Vol 405-408 ◽  
pp. 3391-3395 ◽  
Author(s):  
Xue Li Wang ◽  
Shan Hua
Keyword(s):  
Real Estate ◽  
Influence Factors ◽  
Real Estate Market ◽  
Policy Recommendations ◽  
The Real Estate ◽  
Real Estate Price ◽  
The Real Estate Market ◽  
Regulation Policy ◽  
Process Of Urbanization ◽  
Real Estate Prices

This paper studied that the factors influencing Chinese real estate price. And that the land prices, the macroeconomic situation, the annual income of the households, the process of urbanization, the credit policy, the psychological expectations of consumers, the market investment or speculation, the governments regulation policy etc, Are all the influence factors of real estate prices. And the analysis results to develop appropriate policy recommendations for the healthy and sustainable development of the real estate market.

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.

Research on Supply and Demand of Xi'an Real Estate Market

2011 ◽  
Vol 368-373 ◽  
pp. 3078-3082
Author(s):  
Zhou Ji Meng ◽  
Tao Zhou ◽  
Shu Hua Gao
Keyword(s):  
Principal Component Analysis ◽  
Spectral Analysis ◽  
Real Estate ◽  
Spectral Density ◽  
Supply And Demand ◽  
Principal Component ◽  
Real Estate Market ◽  
Medium Term ◽  
Real Estate Price ◽  
Synthetic Indicators

In the passage, the indicators of supply and demand of real estate market in Xi'an are established, and such indicators are synthesized into a class of synthetic indicators using “principal component analysis”. After the spectral analysis of synthetic indicators, periodic change of supply and demand of real estate through spectral density could be determined. Through the analysis, great randomness existed in supply and demand of real estate in Xi’an. Furthermore, in the medium term, a 3.3 years’ secondary cycle still existed in synthetic indicators of demand, while randomness existed in synthetic indicators of supply. Such findings suggest a declined trend existed in real estate price in medium term of Xi’an.

scholarly journals Evaluation of the Applicability of Statistical Methods in Studies on Price Dynamics on the Real Estate Market

2013 ◽  
Vol 21 (1) ◽  
pp. 49-58 ◽  
Author(s):  
Sebastian Kokot ◽  
Marcin Bas
Keyword(s):  
Real Estate ◽  
Traditional Approach ◽  
Real Estate Market ◽  
Price Dynamics ◽  
The Real ◽  
The Real Estate ◽  
Transaction Prices ◽  
Time Period ◽  
The Real Estate Market ◽  
Real Estate Prices

Abstract The specific character of the real estate market is the reason why observations of transaction prices seen as statistical variables are taken in a non-standard way. In the traditional approach each time period or specific moments of time are attributed with one observation of a studied variable per one object. In the case of the real estate market, this is not possible since transactions relate to different objects, i.e., properties, and occur at irregular, or even random, moments. This is why traditional methods used to examine the dynamics of economic phenomena must be adapted to specific conditions on the real estate market. Keeping that in mind, the aim of this paper is to adapt classical statistical examination methods of dynamics to specific conditions of the real estate market followed by the actual examination of the dynamics of real estate prices in three sub-segments of the housing market in Szczecin. On its basis, the authors evaluate various methods of examining real estate price dynamics in terms of their applicability in real estate appraisal procedures and, in a broader perspective, present characteristic phenomena that can be observed on the real estate market.

scholarly journals Use of Statistical Models for Simulating Transactions on the Real Estate Market

2015 ◽  
Vol 23 (2) ◽  
pp. 102-111 ◽  
Author(s):  
Radosław Cellmer ◽  
Katarzyna Szczepankowska
Keyword(s):  
Probability Distribution ◽  
Real Estate ◽  
Statistical Models ◽  
Real Estate Market ◽  
Model Parameters ◽  
The Real ◽  
The Real Estate ◽  
Transaction Prices ◽  
The Real Estate Market ◽  
Real Estate Prices

Abstract The regularities and relations between real estate prices and the factors that shape them may be presented in the form of statistical models, thanks to which the diagnosis and prediction of prices is possible. A formal description of empirical observation presented in the form of regressive models also offers a possibility for creating certain phenomena in a virtual dimension. Market phenomena cannot be fully described with the use of determinist models, which clarify only a part of price variation. The predicted price is, in this situation, a special case of implementing a random function. Assuming that other implementations are also possible, regressive models may constitute a basis for simulation, which results in the procurement of a future image of the market. Simulation may refer both to real estate prices and transaction prices. The basis for price simulation may be familiarity with the structure of the analyzed market data. Assuming that this structure has a static character, simulation of real estate prices is performed on the basis of familiarity with the probability distribution and a generator of random numbers. The basis for price simulation is familiarity with model parameters and probability distribution of the random factor. The study presents the core and theoretical description of a transaction simulation on the real estate market, as well as the results of an experiment regarding transaction prices of office real estate located within the area of the city of Olsztyn. The result of the study is a collection of virtual real properties with known features and simulated prices, constituting a reflection of market processes which may take place in the near future. Comparison between the simulated characteristic and actual transactions in turn allows the correctness of the description of reality by the model to be verified.

scholarly journals The use of mean values for reporting real estate prices

2021 ◽  
Vol 64 (04) ◽  
pp. 513-532
Author(s):  
Melita Ulbl ◽  
Andraž Muhič
Keyword(s):  
Real Estate ◽  
Real Estate Market ◽  
Mean Values ◽  
The Real ◽  
The Real Estate ◽  
The Real Estate Market ◽  
Special Challenge ◽  
The Republic ◽  
Real Estate Prices ◽  
The One

The proper and unambiguous reporting of the real estate market is one of the main requirements for ensuring its transparency. Reporting on the prices of real estate realised on the market is a special challenge here. For this purpose, averages are generally used, requiring both the reporter and the reader to be well acquainted with the rules of individual types of averages on the one hand and the specificities and heterogeneity of the real estate market on the other. In this paper, we present the specifics of individual mean values that can be used for this purpose. These characteristics are analysed in more detail and presented in the case of the Slovenian housing market. The purpose of this paper is to present the dilemmas faced in Slovenia when reporting on real estate prices on the market and present the solutions that the Surveying and Mapping Authority of the Republic of Slovenia will begin to introduce in its reports on the real estate market.

scholarly journals An Assessment of the Functioning of Shopping Centres in Central‑Eastern Europe on the Example of “Posnania Mall” in Poznań (Poland) and “Grand Mall” in Varna

2021 ◽  
Vol 15 (3) ◽  
pp. 99-113
Author(s):  
Sławomir Palicki ◽  
Stoyan Stoyanov ◽  
Ivo Kostov ◽  
Tsvetelina Atanasova ◽  
Patrycjusz Ostrowski
Keyword(s):  
Real Estate ◽  
Large Scale ◽  
Local Development ◽  
Real Estate Market ◽  
The European Union ◽  
Market Reactions ◽  
Shopping Centre ◽  
Shopping Centres ◽  
Central Eastern ◽  
The Impact

The article explores the issue of the function of shopping centres, in particular the analysis of the impact of their presence on society and the local development of cities and regions. Regarding the empirical aspect, the examples of Poznań (Poland) and Varna (Bulgaria) will be presented. As a result of similar socio‑economic conditions and joining the European Union at almost the same moment, all comparative studies reflecting preferences and market reactions seem both viable and interesting. In addition, the two cities chosen for the studies occupy a similar place in the hierarchy of the settlement network in their countries. They are large, well‑developed centres that attract the attention of investors from various segments of the real estate market. The research is part of the modelling of preferences of shopping centre customers areas, which in particular supports the investment decisions of developers operating in the analysed real estate market, and at the same time permits a diagnosis of social satisfaction. A derivative of the research is also the reconstruction of the effects of the functioning of large‑scale shopping malls in two Central‑Eastern European countries.

scholarly journals Cap rates and risk: a spatial analysis of commercial real estate

2018 ◽  
Vol 35 (1) ◽  
pp. 25-43
Author(s):  
Florian Unbehaun ◽  
Franz Fuerst
Keyword(s):  
Real Estate ◽  
Risk Perceptions ◽  
Large Scale ◽  
Risk Premia ◽  
Real Estate Market ◽  
Commercial Real Estate ◽  
Data Series ◽  
Large Set ◽  
Content Type ◽  
The Impact

Purpose This study aims to assess the impact of location on capitalization rates and risk premia. Design/methodology/approach Using a transaction-based data series for the five largest office markets in Germany from 2005 to 2015, regression analysis is performed to account for a large set of asset-level drivers such as location, age and size and time-varying macro-level drivers. Findings Location is found to be a key determinant of cap rates and risk premia. CBD locations are found to attract lower cap rates and lower risk premia in three of the five largest markets in Germany. Interestingly, this effect is not found in the non-CBD locations of these markets, suggesting that the lower perceived risk associated with these large markets is restricted to a relatively small area within these markets that are reputed to be safe investments. Research limitations/implications The findings imply that investors view properties in peripheral urban locations as imperfect substitutes for CBD properties. Further analysis also shows that these risk premia are not uniformly applied across real estate asset types. The CBD risk effect is particularly pronounced for office and retail assets, apparently considered “prime” investments within the central locations. Originality/value This is one of the first empirical studies of the risk implications of peripheral commercial real estate locations. It is also one of the first large-scale cap rate analyses of the German commercial real estate market. The results demonstrate that risk perceptions of investors have a distinct spatial dimension.

Data Analysis on the Influencing Factors of the Real Estate Price

2021 ◽  
pp. 52-66
Author(s):  
Huang-Mei He ◽  
Yi Chen ◽  
Jia-Ying Xiao ◽  
Xue-Qing Chen ◽  
Zne-Jung Lee
Keyword(s):  
Data Analysis ◽  
Real Estate ◽  
Influencing Factors ◽  
Real Estate Market ◽  
Training Data ◽  
Market Demand ◽  
Data Set ◽  
The Real ◽  
The Real Estate ◽  
Real Estate Price

China has carried out a large number of real estate market reforms that change the real estate market demand considerably. At the same time, the real estate price has soared in some cities and has surpassed the spending power of many ordinary people. As the real estate price has received widespread attention from society, it is important to understand what factors affect the real estate price. Therefore, we propose a data analysis method for finding out the influencing factors of real estate prices. The method performs data cleaning and conversion on the used data first. To discretize the real estate price, we use the mean ± standard deviation (SD), mean ± 0.5 SD, and mean ± 2 SD of the price and divide it into three categories as the output variable. Then, we establish the decision tree and random forest model for six different situations for comparison. When the data set is divided into training data (70%) and testing data (30%), it has the highest testing accuracy. In addition, by observing the importance of each input variable, it is found that the main influencing factors of real estate price are cost, interior decoration, location, and status. The results suggest that both the real estate industry and buyers should pay attention to these factors to adjust or purchase real estate.

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