<![CDATA[Research Originality – This research shifts from yearly national datasets to a quarterly sub-national analysis using a dual Fixed Effect Model (FEM) and output-oriented Data Envelopment Analysis (DEA) framework. It establishes an empirical benchmark for sub-national climate finance synergy, addressing a significant gap in global literature. Research Objectives – The study aims to determine the impacts of agricultural credit and climate spending on regional GRDP, construct provincial efficiency benchmarks via DEA, and assess credit-expenditure synergy to inform performance-based fiscal management. Research Methods – A two-stage analysis was employed. First, an FEM—validated by Chow and Hausman tests—measured input impacts on agricultural GRDP. Second, a DEA based on Variable Returns to Scale (VRS) captured structural differences and economic capacities for benchmarking. Empirical Results – The FEM analysis shows that although credit instruments generated substantial marginal returns, the impact of climate-tagged expenditures was mixed. CA_SE demonstrated positive multipliers, while CM_SE and AGRI_LE were either non-significant or associated with negative impacts, indicating potential fiscal inefficiencies. The model had a high degree of fitness and passed the robust diagnostic tests, validating the coefficients. The analysis revealed a resource-performance gap where high-input provinces did not achieve efficient outputs, whereas eight provinces achieved an optimal resource-output efficiency ratio. Implications – The study advocates for performance-based fiscal policies over volume-based finance. It highlights that credit access requires optimized governance to ensure effectiveness and recommends transitioning from administrative mitigation spending toward performance-based infrastructural investments.]]>
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