Understanding government support for rural development in Hubei Province, China

Rural development, unlike urban development, involves simpler economic and social activities primarily centered around the productive use of land. While land allocation globally involves governments and private individuals, in China, the government holds absolute authority. Legal rural construction land expansion (LRCLE) data, included in land use change surveys, accurately reflects government support for rural development. Existing research highlights the crucial role of government support in rural development, encompassing financial, agricultural, and smart village policies. The relationship between land use transition and rural development is strong, with rural construction land playing a central role. This study aims to quantify government support for rural development in Hubei Province using LRCLE data, focusing on its intensity, spatial direction, and agglomeration, and analyzing the orientations of this support based on existing rural development indicators.

Numerous studies emphasize the key roles of government, social capital, and villagers in rural development, with the government often acting as a trust endorser. The importance of government support for SMEs in rural development is also highlighted. Research on the impact of rural policies underscores the significance of financial, agricultural, and smart village policies, all largely driven by government initiatives. Studies on land use transition and rural development show their close relationship, with rural construction land being a critical element of this interaction. Existing research evaluates rural development across various types, such as farmland-based, garden-based, and woodland-based agriculture, each demanding rural construction land for infrastructure, public services, and other developments. The direction of rural construction land allocation is selective, reflecting the prioritized focus of rural development.

This study uses Hubei Province, China, as its study area. Data sources include spatial vector data on LRCLE from 2009 to 2018 (obtained from the Ministry of Natural Resources of Hubei Province) and statistical data from yearbooks and bulletins. Three key indicators capture government support characteristics: 1. **Intensity of support:** Measured using the Dynamic Degree of Single Land Use (DDSLU), reflecting the area change of LRCLE across three periods (2009-2011, 2012-2014, and 2015-2018). 2. **Spatial direction of support:** Analyzed using the Standard Deviation Ellipse (SDE) to quantify the centrality, distribution, and directionality of LRCLE. 3. **Spatial agglomeration of support:** Assessed using a 10km x 10km grid to count LRCLE patches and calculate the Discrete Degree of Legal Rural Construction Land Expansion (DDLRCLE), along with landscape pattern indices (patch density, edge density, largest patch index, landscape shape index, fractal dimension, and Euclidean nearest-neighbor distance). An indicator system is established to define the orientations of rural development, encompassing four dimensions: farmers' life and social security, rural public services, farmers' production, and industrial development. Finally, panel data regression is employed, using county-level administrative regions as units. The Augmented Dickey-Fuller (ADF) test ensures data stationarity, while the Variance Inflation Factor (VIF) test addresses multicollinearity. Three panel data regression models (pooled, fixed effect, and random effect) are considered, with model selection based on F-test, Breusch-Pagan test, and Hausman test.

The findings reveal strong spatiotemporal characteristics of government support for rural development in Hubei Province. **Intensity of Support:** DDSLU values significantly increased from 2009 to 2018, indicating growing support intensity. Higher values concentrated in metropolitan areas and gradually expanded outwards. **Spatial Direction of Support:** The SDE analysis reveals a clear directional trend in LRCLE, with the center of gravity shifting gradually northwest. **Spatial Agglomeration of Support:** The number of grids with higher DDLRCLE values increased, indicating local agglomeration. Landscape pattern indices showed an increase in patch complexity despite a decrease in overall area, suggesting a more nuanced approach to support. **Orientations of Government Support:** Panel data regression results, using LRCLE area as the dependent variable, indicate different effects based on individual and time fixed effects. Factors such as population of permanent residents (PPR), oilseed production output (OPO), and total meat production output (TMPO) positively affected LRCLE area, while cotton production output (CPO) showed a negative effect. When using the number of LRCLE patches as the dependent variable, PPR, per capita disposable income of rural permanent residents (PCDIRPR), gross domestic product of primary industry (GDPPI), and total grain output (TGO) showed significant effects, with PPR, PCDIRPR and TGO having negative impacts and GDPPI and TMPO showing positive effects.

The findings demonstrate that government support for rural development in Hubei Province, as reflected in LRCLE, has intensified, exhibited clear spatial directionality and shown local agglomeration. The trend of increasing complexity of LRCLE patches suggests a shift toward a more targeted and cautious approach under stricter construction land controls. This contrasts with some previous studies which focused on the overall expansion of rural construction land without considering the nuances of government support. This research highlights the importance of considering both the area and number of LRCLE patches in understanding government support orientations. The different effects of various factors on LRCLE area and number suggest that government support aims to balance multiple priorities, such as food production and economic development, while adhering to land use policies.

Government support for rural development in Hubei Province through LRCLE increased from 2009 to 2018, showing clear spatial patterns and orientations. The study reveals a shift towards more targeted, cautious support under stricter land controls. Future research could explore the impact of specific policies on LRCLE, investigate the effectiveness of different support mechanisms, and expand the study area to other regions of China to assess the generalizability of these findings. Further investigation into the underlying mechanisms driving the spatial patterns of LRCLE and the effectiveness of government policies would be valuable.

The study relies on LRCLE data as a proxy for government support, which might not fully capture the complexity of government interventions in rural development. The focus on Hubei Province limits the generalizability of the findings to other regions. Future research incorporating other data sources and broader geographical scope could strengthen the analysis.