Abstract
In this paper, time series analysis, geographic information, cluster analysis, causality test and other techniques and means are used to analyze the housing prices of mainland China in the past 10 years. Kmeans clusters after comparison of house prices between provinces and neighboring provinces, provinces of the same category are continuously distributed on the map; the highest price area and the lowest price area on the time series are also continuously distributed on the map; the time series-based causality test found that the growth rate of house prices in six provinces was affected by the surrounding provinces, and the growth rate of house prices in one province affected the growth rate of house prices in neighboring provinces.
Highlights
The house prices among all provinces, autonomous regions and municipalities across China show a clear inclining trend, but the patterns of incline vary a lot across regions
The average sales price of residential commercial housing in Shandong Province increases from 2904.14 Yuan/m2 (Year 2007) to 5855 Yuan/m2 (Year 2016), with an overall growth rate of 6.45%; the average sales price of residential commercial housing in the Ningxia Hui Autonomous Region shows a lower rate of increment, which increases from 2722.58 Yuan/m2 (Year 2007) to 5485 Yuan/m2 (Year 2016) with an overall growth rate of 14.78%
This paper uses time series analysis, geographic information, cluster analysis, causality test and other techniques to study the relationship of house prices among the all provinces, autonomous regions and municipalities
Summary
The house prices among all provinces, autonomous regions and municipalities across China show a clear inclining trend, but the patterns of incline vary a lot across regions. The average sales price of residential commercial housing in Shandong Province increases from 2904.14 Yuan/m2. This paper uses time series analysis, geographic information, cluster analysis, causality test and other techniques to study the relationship of house prices among the all provinces, autonomous regions and municipalities. Previous researches in China have proved the practicability of using time series analysis in studying house prices. This research proved that time series analysis is reasonable in analyzing the trend of house prices. Li He (2014) predicted commercial residential housing price index in Beijing in 2014, using time series analysis [2]. This paper conducts time series analysis and spatial analysis of house prices in mainland China in the past 10 years
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