Yunjia zhang: All the contents are put into the folder: Nanjing, including: code, data, results and readme.docx. The readme.docx contains analysis ideas, analysis process, analysis results, and reference.
Yingjie:
Note: I realized later that I uploaded the wrong file, so the correct data file should be datadatadata.
dddch all dddch under this project will run with the same result. The contents of dddch1 to dddch4 are roughly the same.
The existing data are all monthly data in 2019 and 2020, and part of the data in 2021. The data comes from kaggle. First of all, I compare house prices in the city by district, and compare whether there are obvious differences in the fluctuations of house prices in each district before and after the occurrence of COVID-19, but in fact I found that for a single area, covid's impact on housing prices in each district is generally fair, and the volatility information of some district with high volatility is not consistent with the time point of the covid control policy, so I believe that the impact of covid on housing prices is not different depending on the district.
Then I compared the total housing prices in the three years from 2019 to 2021. Although the data for 2021 have only 7 months, I can still find some obvious information. Compared with the other two years, house prices in 2020 have dropped significantly in the beginning of the year. However, in June 2020, shortly after COVID-19 was brought under control, housing prices rebounded significantly. I believe this has something to do with people's regaining confidence in the economy.
The trend of house prices in various regions in 2019:
The trend of house prices in various regions in 2020:
The trend of house prices in various regions in 2021:
The sum of three years:
reference: https://www.kaggle.com/dingmaoding/lianjiadatarecent