Spatial-Temporal Evolution and Risk Assessment of Land Finance: Evidence from China

Zhou De, Ruilin Tian (), Zhulu Lin, Liming Liu, Junfeng Wang and Shijia Feng
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Zhou De: Department of Land Resources Management, China Institute of Land and Urban Governance, Zhejiang Gongshang University, 18 Xuezheng St., Xiasha University Town, Hangzhou 310018, China
Ruilin Tian: Department of Transportation, Logistics and Finance, North Dakota State University, Fargo, ND 58108, USA
Zhulu Lin: Department of Agricultural and Biosystems Engineering, North Dakota State University, Fargo, ND 58108, USA
Liming Liu: College of Land Science and Technology, China Agricultural University, Beijing 100193, China
Junfeng Wang: Department of Land Resources Management, China Institute of Land and Urban Governance, Zhejiang Gongshang University, 18 Xuezheng St., Xiasha University Town, Hangzhou 310018, China
Shijia Feng: Department of Land Resources Management, China Institute of Land and Urban Governance, Zhejiang Gongshang University, 18 Xuezheng St., Xiasha University Town, Hangzhou 310018, China

Risks, 2022, vol. 10, issue 10, 1-27

Abstract: Land finance is a special land financing mode in China under the nationalization of urban land since 1954. The policy authorizes local governments to collect fiscal revenue from land grant premiums and land taxes. As China is experiencing the social and economic transformation, heavily replying on land finance starts causing financial sustainable problems. Based on the spatial panel data of 30 provinces in China in the last two decades, we analyzed the spatial-temporal evolution of land finance. We found that the spatial variation of land finance declined during the period of study and decreased from east to west. The results revealed that land finance had significant positive spatial autocorrelation and robust spatial clustering characteristics. In addition, the spatial distribution of land finance was consistent with the population-based Hu Line. We also assessed land finance risks via a four-dimensional risk matrix through spatial panel regression (SPR). The spatial spillover effects suggested that there is inter-provincial imitation and collaboration but no competition. Our forecast indicates that most provinces will be at a relatively low risk level in the next decade except some southwest provinces. Based on the findings, we highlight the policy implications to mitigate risks and maintain sustainable land finance.

Keywords: land finance; risk assessment; risk factors; spatial-temporal evolution; spatial panel regression (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2022
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