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This work aims to investigate scale, scope and nature of spatial dependence of agricultural total factor productivity (TFP) by using farm‐level survey data. TFP is measured using transitive index numbers, and the spatial properties of TFP are assessed within a dynamic spatial panel data model designed to separate production fundamentals from productivity spillovers. Because of the statistical issues that typically affect spatial analyses based on survey data, a Bayesian model selection procedure is used to inspect the spatial properties of TFP at different aggregation levels and to search for the most appropriate spatial scale to conduct the investigation. The application concerns Italian FADN farm‐level data over the period 2008–2015 then aggregated at the NUTS3 level. Results suggest that agricultural productivity spillovers significantly occur though over a limited spatial range. The cumulated effects of the estimated diffusion mechanism are described through a set of spatial indicators and presented graphically.
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Baldoni et al. (2020) studied this question.
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