Empirical Analysis Research on the Influence of Macro-control Policy on Fluctuation of Real Estate Price Index

2013 ◽  
Vol 5 (2) ◽  
pp. 202-211
Author(s):  
MA Ji
Keyword(s):  
Real Estate ◽  
Empirical Analysis ◽  
Price Index ◽  
Control Policy ◽  
Real Estate Price

Design of Real Estate Price Index System Based on Hedonic Price Method

2014 ◽  
Vol 488-489 ◽  
pp. 1463-1466
Author(s):  
Yun Du ◽  
Hui Qin Sun ◽  
Su Ying Zhang ◽  
Qiang Tian
Keyword(s):  
Real Estate ◽  
Price Index ◽  
Real Estate Market ◽  
Hedonic Price ◽  
Hedonic Price Method ◽  
The Real ◽  
The Real Estate ◽  
Real Estate Price ◽  
Price Series ◽  
Research Level

Urban real estate price index (hereinafter referred to as UREPI) is a basic data of the real estate market, its accuracy is very important for enterprises, consumers and housing management department. In view of current research level here in China and popular models, the UREPI system is compiled based on the Hedonic price method because of its advantages such as calculation simple and sample easily etc. Compiled by Eviews the system has three main stages: the data standardization, the benchmark model establishment and the application of two periods chained update method to update price series. UREPI system is combined with the real deal, so it can be used to analysis the market accurately. The results completely meet the design requirements.

A Regression Method for Real Estate Price Index Construction

1963 ◽  
Vol 58 (304) ◽  
pp. 933-942 ◽  
Author(s):  
Martin J. Bailey ◽  
Richard F. Muth ◽  
Hugh O. Nourse
Keyword(s):  
Real Estate ◽  
Price Index ◽  
Regression Method ◽  
Index Construction ◽  
Real Estate Price

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.

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