Spatiotemporal Variations in Farmland Rents and Its Drivers in Rural China: Evidence from Plot-Level Transactions
Reasonable rent is the key to promoting land transfer and realizing agricultural operations on a moderate scale in rural China. The purpose of this study was to reveal the spatiotemporal variations in farmland rents and their drivers by employing a multilevel model based on 3547 plot-level transacti...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | Land |
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| Online Access: | https://www.mdpi.com/2073-445X/11/2/229 |
| _version_ | 1797478766077804544 |
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| author | Aoxi Yang Yahui Wang |
| author_facet | Aoxi Yang Yahui Wang |
| author_sort | Aoxi Yang |
| collection | DOAJ |
| description | Reasonable rent is the key to promoting land transfer and realizing agricultural operations on a moderate scale in rural China. The purpose of this study was to reveal the spatiotemporal variations in farmland rents and their drivers by employing a multilevel model based on 3547 plot-level transactions in Sichuan Province of China. The results show that the rents of paddy field, irrigated land, dry land and other types of farmland have all maintained an upward trend since 2014, rising by 61%, 53%, 44% and 224%, respectively. The average rent per ha for these properties reached CNY 13,920, 12,285, 10,230 and 7980 in 2020 (1 USD = CNY 6.90 in 2020), respectively. Farmland rents have shown a significant spatial agglomeration phenomenon, and the regions with higher rent were mainly distributed in Chengdu and its surrounding areas, while the regions with lower rent were distributed in the east and northeast of Sichuan Province. The differences in farmland rent were influenced by multilevel factors such as plot level and regional level, and the former explained 73.4% of the farmland rent variation. The plots with a larger area, longer transfer period, clear ownership, better location and good-quality land had higher rents; otherwise, the rents were lower. |
| first_indexed | 2024-03-09T21:36:17Z |
| format | Article |
| id | doaj.art-5e9ec04534e148508ffc84ef220fe451 |
| institution | Directory Open Access Journal |
| issn | 2073-445X |
| language | English |
| last_indexed | 2024-03-09T21:36:17Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Land |
| spelling | doaj.art-5e9ec04534e148508ffc84ef220fe4512023-11-23T20:42:59ZengMDPI AGLand2073-445X2022-02-0111222910.3390/land11020229Spatiotemporal Variations in Farmland Rents and Its Drivers in Rural China: Evidence from Plot-Level TransactionsAoxi Yang0Yahui Wang1School of Geographical Sciences, Southwest University, Chongqing 400715, ChinaSchool of Geographical Sciences, Southwest University, Chongqing 400715, ChinaReasonable rent is the key to promoting land transfer and realizing agricultural operations on a moderate scale in rural China. The purpose of this study was to reveal the spatiotemporal variations in farmland rents and their drivers by employing a multilevel model based on 3547 plot-level transactions in Sichuan Province of China. The results show that the rents of paddy field, irrigated land, dry land and other types of farmland have all maintained an upward trend since 2014, rising by 61%, 53%, 44% and 224%, respectively. The average rent per ha for these properties reached CNY 13,920, 12,285, 10,230 and 7980 in 2020 (1 USD = CNY 6.90 in 2020), respectively. Farmland rents have shown a significant spatial agglomeration phenomenon, and the regions with higher rent were mainly distributed in Chengdu and its surrounding areas, while the regions with lower rent were distributed in the east and northeast of Sichuan Province. The differences in farmland rent were influenced by multilevel factors such as plot level and regional level, and the former explained 73.4% of the farmland rent variation. The plots with a larger area, longer transfer period, clear ownership, better location and good-quality land had higher rents; otherwise, the rents were lower.https://www.mdpi.com/2073-445X/11/2/229farmland rentspatiotemporal variationsdriversnon-grainrural China |
| spellingShingle | Aoxi Yang Yahui Wang Spatiotemporal Variations in Farmland Rents and Its Drivers in Rural China: Evidence from Plot-Level Transactions Land farmland rent spatiotemporal variations drivers non-grain rural China |
| title | Spatiotemporal Variations in Farmland Rents and Its Drivers in Rural China: Evidence from Plot-Level Transactions |
| title_full | Spatiotemporal Variations in Farmland Rents and Its Drivers in Rural China: Evidence from Plot-Level Transactions |
| title_fullStr | Spatiotemporal Variations in Farmland Rents and Its Drivers in Rural China: Evidence from Plot-Level Transactions |
| title_full_unstemmed | Spatiotemporal Variations in Farmland Rents and Its Drivers in Rural China: Evidence from Plot-Level Transactions |
| title_short | Spatiotemporal Variations in Farmland Rents and Its Drivers in Rural China: Evidence from Plot-Level Transactions |
| title_sort | spatiotemporal variations in farmland rents and its drivers in rural china evidence from plot level transactions |
| topic | farmland rent spatiotemporal variations drivers non-grain rural China |
| url | https://www.mdpi.com/2073-445X/11/2/229 |
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