<![CDATA[This study aims to examine the effect of capital expenditure, poverty, and the Human Development Index (HDI) on GRDP per capita across 11 regencies/municipalities in Jambi Province during 2017–2024. Secondary panel data (88 observations) from Statistics Indonesia (BPS) Jambi Province and the Directorate General of Fiscal Balance were analyzed using panel data regression, with model selection through the Chow and Hausman tests. The tests establish the Fixed Effect Model (FEM) as the best model (Chow: Prob. Cross-section Chi-square = 0.0000; Hausman: Prob. Cross-section random = 0.0474). Simultaneously, capital expenditure, poverty, and HDI significantly affect GRDP per capita (Prob. F-statistic = 0.000000), with high explanatory power (R-squared = 0.703572; Adjusted R-squared = 0.615086). Partially, however, none of the three variables is statistically significant (Prob. t of 0.9353, 0.7573, and 0.6815, respectively), with capital expenditure and poverty showing negative coefficients and HDI a positive one. This pattern suggests that the model's high explanatory power is driven largely by cross-sectional fixed effect time-invariant structural characteristics of each regency/municipality rather than by the annual dynamics of the three policy variables themselves. These findings are interpreted through the lens of Fiscal-social decoupling: a disconnection between annual fiscal-social instruments and regional economic outcomes, in light of Jambi's economic structure, which remains dominated by primary and commodity-based sectors. The novelty of this study lies in operationalizing decoupling through the pattern of partial insignificance amid a strong joint model, read as policy evidence of the dominance of regional structural factors rather than mere model failure. The article recommends shifting capital expenditure from an input-based to an outcome-based approach, strengthening productive infrastructure linked to leading sectors, integrating poverty-reduction and HDI programs with regional economic strategy, and using economic-benefit indicators in local budget evaluation. These findings should be read within the limitations of a model that has not yet incorporated structural variables, private investment, commodity prices, or lagged capital expenditure.]]>
