Program assessment and the EU's agrienvironmental Measure 214: An investigation of the spatial dynamics of agrienvironmental policies in Sardinia, Italy

• We examine the agricultural scenario in the EU policy, using agriscience approach.
• We model this approach using a Geographical Weighted Regression and validate the model.
• We validate the GWR results to show consistency toward the agricultural EU policy.

This paper examines the observed impact of Measure 214, an EU agrienvironmental policy initiative, on the economic landscape of Sardinia. Using both geographically weighted regression (GWR) and ordinary least squares (OLS) regression, the paper observes the relationship between participation in Measure 214 programs and the region's socioeconomic structure through the examination of agriculturally related factors. In our analysis, GWR demonstrates the spatial dynamics and impact of Measure 214 on the region's economy. The GWR model illustrates regions with vibrant spatial patterns, as evaluated by parameter estimates and clarified through explanatory variables. Moreover, the GWR model performs better than the OLS model, as calculated by lower Akaike index AICc and higher adjusted R Squared (adjusted R2) values, reduced spatial autocorrelation of residuals, and higher F values from Analysis of Variance ( ANOVA). The results also suggest that non-participating communities, although influenced by the wave of industrial development, show a different pattern of economic development. The paper concludes that future funding of agrienvironmental and climate change initiatives under EU Measures will expand the observed pattern of organic production, agricultural employment, and integrated husbandry systems and provide further opportunities for sustainable development.