Spatial Dependence and Spillover Effects on Very Low-Income Agricultural Enterprises at the Provincial Level in Indonesia
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https://doi.org/10.32665/statkom.v5i1.6453Keywords:
Spatial Regression, Spatial Lag Model, Spatial Autocorrelation, Spillover Effects, Agricultural WelfareAbstract
Background: Agricultural welfare disparities across Indonesian provinces remain substantial, as reflected in the high percentage of agricultural enterprises with very low income. These disparities are influenced by regional characteristics and spatial interactions among neighboring provinces.
Objective: This study analyzes the determinants of the percentage of agricultural enterprises with very low income at the provincial level while accounting for spatial dependence and spillover effects.
Methods: Cross-sectoral data from 38 provinces in Indonesia were obtained from the 2024 Agricultural Economic Survey. The analysis was conducted using spatial regression models, the Spatial Lag Model (SLM) and the Spatial Error Model (SEM). The spatial weight matrix was constructed using the KNN approach with k = 5. Moran's I test was used to detect spatial autocorrelation. The LM test and AIC were used to select the best model.
Results: Significant positive spatial autocorrelation was detected in the dependent variable and OLS residuals. The SLM was selected as the best model. The explanatory variables were shown to have both direct and indirect effects through spatial spillover effects.
Conclusion: Incorporating spatial dependence is essential for effective agricultural policymaking. Coordinated interprovincial policies on credit access, production facilities, and agricultural input supply are needed to improve agricultural welfare.
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