This paper investigates how farmers respond to targeted policy measures under the EU Common Agricultural Policy (CAP), focusing on whether voluntary adoption, often driven by private motivations, also leads to outcomes of societal interest. To address the methodological challenges posed by staggered and sparse treatment adoption, the study employs a Synthetic Difference-in-Differences (SDID) approach. A theoretical framework is developed to distinguish between private and societal outcomes of policy adoption. The empirical analysis uses a balanced panel of Italian farms from 2014 to 2022 and focuses on selected second-pillar CAP measures. Results reveal that while some measures significantly affect private outcomes (e.g., farm income or productivity), their impact on societal outcomes (e.g., environmental indicators) is weaker and more volatile. The paper discusses key challenges in identifying and estimating effects with few, heterogeneous treated units and staggered policy uptake. While SDID is well-suited to such contexts, its real-world application may face practical limitations.

Evaluating policy impact under sparse and staggered adoption. A synthetic difference-in-differences application to EU rural development measures / Esposti, Roberto. - In: EVALUATION AND PROGRAM PLANNING. - ISSN 0149-7189. - ELETTRONICO. - 116:(2026). [10.1016/j.evalprogplan.2026.102751]

Evaluating policy impact under sparse and staggered adoption. A synthetic difference-in-differences application to EU rural development measures

Esposti, Roberto
2026-01-01

Abstract

This paper investigates how farmers respond to targeted policy measures under the EU Common Agricultural Policy (CAP), focusing on whether voluntary adoption, often driven by private motivations, also leads to outcomes of societal interest. To address the methodological challenges posed by staggered and sparse treatment adoption, the study employs a Synthetic Difference-in-Differences (SDID) approach. A theoretical framework is developed to distinguish between private and societal outcomes of policy adoption. The empirical analysis uses a balanced panel of Italian farms from 2014 to 2022 and focuses on selected second-pillar CAP measures. Results reveal that while some measures significantly affect private outcomes (e.g., farm income or productivity), their impact on societal outcomes (e.g., environmental indicators) is weaker and more volatile. The paper discusses key challenges in identifying and estimating effects with few, heterogeneous treated units and staggered policy uptake. While SDID is well-suited to such contexts, its real-world application may face practical limitations.
2026
Causal Inference in Policy Evaluation; Farmers’ Decision-Making; Rural Development Policy; Staggered Treatments; Synthetic Difference-in-Differences
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/355572
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