Uptake of Ecological Farming Practices by EU Farms: A Pan‐European Typology

Understanding and measuring the sustainability of farms is key to evaluating progress towards policy goals for a more sustainable agriculture. In the LIFT project, a farm typology was developed to classify farms according to their ecological performance, based on farm-level variables from the Farm Accountancy Data Network (FADN). Selected variables are used to assess three key ecological dimensions of farming: total input intensity; degree of circularity (reliance on own-produced versus external inputs); and avoidance of the use of specific inputs of concern for the environment and consumers. The combination of these aspects is considered as a measure of the farm proximity to a full agroecological approach. The typology allows comparison of farms across farm types, countries and years. We briefly present the method and discuss two key aspects: 1) how the proposed farm typology can inform policymaking in the context of a new EU policy framework; 2) how it can inform the foreseen transformation of the FADN into a Farm Sustainability Data Network (FSDN). We suggest that the use of a typology approach under the new FSDN provides useful information on the impacts of the implementation of agroecological practices with an acceptable additional effort in terms of data collection.</p

Retrospective Analysis of Six Years of Acute Flaccid Paralysis Surveillance and Polio Vaccine Coverage Reported by Italy, Serbia, Bosnia and Herzegovina, Montenegro, Bulgaria, Kosovo, Albania, North Macedonia, Malta, and Greece

Here we analyzed six years of acute flaccid paralysis (AFP) surveillance, from 2015 to 2020, of 10 countries linked to the WHO Regional Reference Laboratory, at the Istituto Superiore di Sanità, Italy. The analysis also comprises the polio vaccine coverage available (2015–2019) and enterovirus (EV) identification and typing data. Centralized Information System for Infectious Diseases and Laboratory Data Management System databases were used to obtain data on AFP indicators and laboratory performance and countries’ vaccine coverage from 2015 to 2019. EV isolation, identification, and typing were performed by each country according to WHO protocols. Overall, a general AFP underreporting was observed. Non-Polio Enterovirus (NPEV) typing showed a high heterogeneity: over the years, several genotypes of coxsackievirus and echovirus have been identified. The polio vaccine coverage, for the data available, differs among countries. This evaluation allows for the collection, for the first time, of data from the countries of the Balkan area regarding AFP surveillance and polio vaccine coverage. The need, for some countries, to enhance the surveillance systems and to promote the polio vaccine uptake, in order to maintain the polio-free status, is evident

Integrating rather than collecting: statistical matching in the data flood era

Statistical matching is progressively emerging as a straightforward approach to data integration. This method of increasing importance and interest is useful to address the unsolved challenges posed by data shortage as well as the several opportunities occurring in the present data flood era. This paper offers an exhaustive review of the methodology from its early beginnings up to the most recent developments, considering also the most relevant applications. The links that statistical matching has with other integration methods are discussed, analysing how a 50-year-old method has been only recently proposed under a consistent but (yet) incomplete framework. Strengths and weaknesses of statistical matching are compared, considering different data features and sample representativeness frameworks, also, given future research ideas, always keeping an eye on uncertainty, the key problem to which statistical matching tries to answer

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

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