Spatial determinants of public forest subsidies: Insights from the EU and China

Forests provide critical environmental services and support rural livelihoods. Recognizing the multifunctionality of forests, governments have developed public subsidy programs to support forest management and rural development. Here, we presented two major programs, more specifically through the forestry measure of the EU's Rural Development Programme (RDP) and the Grain for Green Program (GFGP) in China. We examined their policy objectives, measures taken, actors involved, expenditure patterns, and factors that influence funding allocations using spatial regression analysis, including socio-economic farmer attributes, land-use indicators, and environmental, socioeconomic and political contextual settings. Spatial econometric analysis reveals significant heterogeneities in average forestry expenditure per year across regions, with both comparable and distinct patterns observed between the EU and China. Southern and Eastern Europe spent more on forestry measures than Western European countries. Funding allocations were strongly correlated with biophysical environmentalconditions: regions with high habitat quality, low water retention capacity, and high soil erosion risk received greater funding. In China, GFGP funds were allocated preferentially to areas with high species richness, low carbon sequestration and high capacity for preventing sandstorms. GFGP also prioritized municipalities with low agricultural productivity and underdeveloped areas in Western China. In both programs, we found positive spatial autocorrelation, indicating that funding was regionally clustered. Our findings highlight that while both RDP and GFGP consider environmental and socio-economic criteria, their de facto revealed priorities also differed substantially, reflecting underlying policy goals and contextual needs. Improving spatial targeting and accounting for regional interdependencies could strengthen the alignment between funding mechanisms and stated policy objectives.