The Impacts of Urbanization to Improve Agriculture Water Use Efficiency—An Empirical Analysis Based on Spatial Perspective of Panel Data of 30 Provinces of China

Abstract

China has witnessed accelerated urbanization since the reforms and open policies which began in 1978. This eventually resulted in increased residential water requirements and worsening water shortages, particularly in the current century. In the context of resource and environmental constraints, improving agricultural water use efficiency (AWUE) is a crucial issue to ensure food security, improve the ecological environment, and meet the needs of sustainable agricultural development. Based on the panel data of 30 provinces in China from 1999 to 2018, the article uses the Super-SBM model to measure the AWUE. Moreover, the study uses the entropy method to establish the urbanization evaluation index system from the dimensions of population, land, economy, measures the comprehensive level of urbanization development, and further constructs a dynamic spatial econometric model. We use the unconditional maximum likelihood estimation method to evaluate the impact of urbanization development on AWUE and its heterogeneity. The findings reveal that the AWUE considering undesired outcomes has generally shown a steady improvement, but there is ample space for resource conservation and environmental protection, and there are noticeable differences among regions. The decomposition of spatial effects shows that urbanization development in each region has a short-term positive effect on AWUE in the region and neighboring regions, and a long-term effect exists only in the western region. The impact of urbanization in different dimensions has been found that both land urbanization and economic urbanization contribute to the improvement of AWUE, while population urbanization helps to improve AWUE by improving the awareness level of the farmers.

The Impact of the Urbanization Process on Agricultural Technical Efficiency in Northeast China

“…In contrast, DEA is a non-parametric approach used to measure the efficiency of decisionmaking units (DMUs) of the same type, according to multiple inputs and multiple outputs. It uses a linear programming mathematical approach to evaluate the relative efficiency of the DMUs [23,24], and it can also reduce the subjective influence of ring-index weighting through automatic weighting, and it can clearly show the combinations of multiple inputs and multiple outputs [25]. However, the traditional DEA method has difficulty in comparing and evaluating multiple effective decision-making units, and it cannot explain cases where the efficiency value is greater than 1.…”

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“…The findings exhibit that GDP positively and significantly influences FPI and WPROD despite the break years considered. The outcomes of the research are analogous to the conclusions of (Lu et al, 2022;Zhou et al, 2022). The economic rationale underlying the positive impact of GDP growth lies in the increased investments and technological advancements within T A B L E 4 squares method.…”

“…Moreover, the authors recommend that water production and its resources should be allocated towards higher productivity. (Lu et al, 2022) examined the factors of water productivity in provincial data and concluded that urbanization and income have a specific role in water and food productivity across provinces. The authors also claimed that sustainable growth in macro-economic factors reduces the influence of water misuse and low food production.…”

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