4.7 Article

The productivity-environment nexus in space. Granularity bias, aggregation issues and spatial dependence within Italian farm-level data

期刊

JOURNAL OF CLEANER PRODUCTION
卷 415, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2023.137847

关键词

Farm-level data Granularity and aggregation Joint production and total factor productivity GHG emissions Crop diversity Dynamic spatial panel models

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This paper examines the existence of a positive relationship between economic and environmental performance in farming, as implied by the Sustainable Intensification hypothesis. The study estimates the relationship at different spatial scales and highlights the potential biases and reliability issues in the estimation process. Using a panel of Italian farms from 2008 to 2018, the empirical study finds that the relationship between productivity and the environment varies and even changes its sign when aggregating data. The implications of these findings for evidence-based policy making are discussed.
This paper looks for empirical support to the existence of a positive nexus between economic and environmental performance in farming as implied by the Sustainable Intensification hypothesis. As the ecological scale at which this nexus actually occurs is unobservable, the paper juxtaposes its estimation at three spatial scales, the farm level and two regional levels. Starting with a common theoretical background, the paper estimates a dynamic spatial panel model on these alternative scales. Identification issues (granularity, aggregation bias and spatial dependence) may generate significantly discrepant estimates eventually questioning the reliability of these results. The empirical study investigates the relationship between total factor productivity, greenhouse gas emissions and crop diversity using a 2008-2018 panel of Italian farms. Results show that the productivity environment nexus changes and may even revert its sign when passing from farm-level to aggregate data. The implications of these results for evidence-based policy making are discussed.

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