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AES Impact Evaluation With Integrated Farm Data: Combining Statistical Matching and Propensity Score Matching

Riccardo D’Alberto (), Matteo Zavalloni (), Meri Raggi and Davide Viaggi ()
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Riccardo D’Alberto: Department of Statistical Sciences “P. Fortunati”, Alma Mater Studiorum University of Bologna, Via delle Belle Arti 41, 40126 Bologna, Italy
Matteo Zavalloni: Department of Agricultural and Food Sciences, Alma Mater Studiorum University of Bologna, Viale Fanin 50, 40127 Bologna, Italy

Sustainability, 2018, vol. 10, issue 11, 1-24

Abstract: A large share of the Common Agricultural Policy (CAP) is allocated to agri-environmental schemes (AESs), whose goal is to foster the provision of a wide range of environmental public goods. Despite this effort, little is known on the actual environmental and economic impact of the AESs, due to the non-experimental conditions of the assessment exercise and several data availability issues. The main objective of the paper is to explore the feasibility of combining the non-parametric statistical matching (SM) method and propensity score matching (PSM) counterfactual approach analysis and to test its usefulness and practicability on a case study represented by selected impacts of the AESs in Emilia-Romagna. The work hints at the potentialities of the combined use of SM and PSM as well as of the systematic collection of additional information to be included in EU-financed project surveys in order to enrich and complete data collected in the official statistics. The results show that the combination of the two methods enables us to enlarge and deepen the scope of counterfactual analysis applied to AESs. In a specific case study, AESs seem to reduce the amount of rent-in land and decrease the crop mix diversity.

Keywords: agri-environmental schemes; public goods; statistical matching; data integration; propensity score matching (search for similar items in EconPapers)
JEL-codes: Q Q0 Q2 Q3 Q5 Q56 O13 (search for similar items in EconPapers)
Date: 2018
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