Exploring Housing Rent by Mixed Geographically Weighted Regression: A Case Study in Nanjing
In China, the housing rent can clearly reveal the actual utility value of a house due to its low capital premium. However, few studies have examined the spatial variability of housing rent. Accordingly, this study attempted to determine the utility value of houses based on housing rent data. In this...
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-09-01
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| Series: | ISPRS International Journal of Geo-Information |
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| Online Access: | https://www.mdpi.com/2220-9964/8/10/431 |
| _version_ | 1818279923921453056 |
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| author | Shiwei Zhang Lin Wang Feng Lu |
| author_facet | Shiwei Zhang Lin Wang Feng Lu |
| author_sort | Shiwei Zhang |
| collection | DOAJ |
| description | In China, the housing rent can clearly reveal the actual utility value of a house due to its low capital premium. However, few studies have examined the spatial variability of housing rent. Accordingly, this study attempted to determine the utility value of houses based on housing rent data. In this study, we applied mixed geographically weighted regression (MGWR) to explore the residential rent in Nanjing, the largest city in Jiangsu Province. The results show that the distribution of residential rent has a multi-center group pattern. Commercial centers, primary and middle schools, campuses, subways, expressways, and railways are the most significant influencing factors of residential rent in Nanjing, and each factor has its own unique characteristics of spatial differentiation. In addition, the MGWR has a better fit with housing rent than geographically weighted regression (GWR). These research results provide a scientific basis for local real estate management and urban planning departments. |
| first_indexed | 2024-12-12T23:41:03Z |
| format | Article |
| id | doaj.art-99f6dd4530564a94a7ccb07342feb294 |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-12-12T23:41:03Z |
| publishDate | 2019-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-99f6dd4530564a94a7ccb07342feb2942022-12-22T00:07:11ZengMDPI AGISPRS International Journal of Geo-Information2220-99642019-09-0181043110.3390/ijgi8100431ijgi8100431Exploring Housing Rent by Mixed Geographically Weighted Regression: A Case Study in NanjingShiwei Zhang0Lin Wang1Feng Lu2School of Geographic Science, Nanjing Normal University, Nanjing 210097, ChinaSchool of Geographic Science, Nantong University, Nantong 226000, ChinaSchool of Geographic Science, Nantong University, Nantong 226000, ChinaIn China, the housing rent can clearly reveal the actual utility value of a house due to its low capital premium. However, few studies have examined the spatial variability of housing rent. Accordingly, this study attempted to determine the utility value of houses based on housing rent data. In this study, we applied mixed geographically weighted regression (MGWR) to explore the residential rent in Nanjing, the largest city in Jiangsu Province. The results show that the distribution of residential rent has a multi-center group pattern. Commercial centers, primary and middle schools, campuses, subways, expressways, and railways are the most significant influencing factors of residential rent in Nanjing, and each factor has its own unique characteristics of spatial differentiation. In addition, the MGWR has a better fit with housing rent than geographically weighted regression (GWR). These research results provide a scientific basis for local real estate management and urban planning departments.https://www.mdpi.com/2220-9964/8/10/431residential renthousing priceprice–rent ratiomgwrutility valuespatial non-stationarity |
| spellingShingle | Shiwei Zhang Lin Wang Feng Lu Exploring Housing Rent by Mixed Geographically Weighted Regression: A Case Study in Nanjing ISPRS International Journal of Geo-Information residential rent housing price price–rent ratio mgwr utility value spatial non-stationarity |
| title | Exploring Housing Rent by Mixed Geographically Weighted Regression: A Case Study in Nanjing |
| title_full | Exploring Housing Rent by Mixed Geographically Weighted Regression: A Case Study in Nanjing |
| title_fullStr | Exploring Housing Rent by Mixed Geographically Weighted Regression: A Case Study in Nanjing |
| title_full_unstemmed | Exploring Housing Rent by Mixed Geographically Weighted Regression: A Case Study in Nanjing |
| title_short | Exploring Housing Rent by Mixed Geographically Weighted Regression: A Case Study in Nanjing |
| title_sort | exploring housing rent by mixed geographically weighted regression a case study in nanjing |
| topic | residential rent housing price price–rent ratio mgwr utility value spatial non-stationarity |
| url | https://www.mdpi.com/2220-9964/8/10/431 |
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