Working Paper SMART -LERECO N°13.04 Les Working Papers SMART-LERECO ont pour vocation de diffuser les recherches conduites au sein des unités SMART et LERECO dans une forme préliminaire permettant la discussion et avant publication définitive. Selon les cas, il s'agit de travaux qui ont été acceptés ou ont déjà fait l'objet d'une présentation lors d'une conférence scientifique nationale ou internationale, qui ont été soumis pour publication dans une revue académique à comité de lecture, ou encore qui constituent un chapitre d'ouvrage académique. Bien que non revus par les pairs, chaque working paper a fait l'objet d'une relecture interne par un des scientifiques de SMART ou du LERECO et par l'un des deux éditeurs de la série. Les Working Papers SMART-LERECO n'engagent cependant que leurs auteurs. The SMART-LERECO Working Papers are meant to promote discussion by disseminating the research of the SMART and LERECO members in a preliminary form and before their final publication. They may be papers which have been accepted or already presented in a national or international scientific conference, articles which have been submitted to a peer-reviewed academic journal, or chapters of an academic book. While not peer-reviewed, each of them has been read over by one of the scientists of SMART or LERECO and by one of the two editors of the series. However, the views expressed in the SMART-LERECO Working Papers are solely those of their authors. Téléphone / Phone: +33 (0)2 23 48 53 83 Fax: +33 (0)2 23 48 53 80 Les Working Papers SMART-LERECO n'engagent que leurs auteurs. The views expressed in the SMART-LERECO Working Papers are solely those of their authors 1 Working Paper SMART -LERECO N°13-04 AbstractAgricultural land fragmentation is widespread around the world and may affect farmers' decisions and therefore have an impact on the performance of farms, in either a negative or a positive way. We investigated this impact for the western region of Brittany, France, in 2007. To do so, we regressed a set of performance indicators on a set of fragmentation descriptors. The performance indicators (production costs, yields, revenue, profitability, technical and scale efficiency) were calculated at the farm level using Farm Accountancy Data Network (FADN) data, while the fragmentation descriptors were calculated at the municipality level using data from the cartographic field pattern registry (RPG). The various fragmentation descriptors enabled not only the traditional number and average size of plots, but also their scattering in the geographical space, to be taken into account. Our analysis highlights the fact that the measures of land fragmentation usually used in the literature do not reveal the whole set of significant relationships with farm performance and that, in particular, measures accounting for distance should be taken into consideration more systematically.Keywords: agricultural land fragmentation, farm performance, cartographic field pattern registry, France JEL classifications: Q12, Q15, D24 Le morcellement parc...

Ever since Ellsberg (1961), the distinction between risk, where agents assign well-defined probabilities to possible outcomes, and ambiguity, where agents do not, has been of particular interest. Using a carefully-designed field experiment, we elicit information about risk and ambiguity preferences among 197 French farmers and structurally estimate these preferences. We use cumulative prospect theory and a multiple-prior model in order to model risk and ambiguity preferences, respectively. We find that farmers are risk, ambiguity, and loss averse, and that probability distortion differs in gains vs. losses, as well as in risk vs. ambiguity. These findings can have important implications for policy design.

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Accounting for spatial interactions between farms is highly relevant for the analysis of agricultural policy impacts. Existing studies, however, only account for homogeneous (average) spatial interactions. We develop a mixture modelling framework to account for unobserved heterogeneity, allowing spatial interaction to vary across endogenously-defined farm types. We apply this approach to study farmer decisions to exit the farming business using a large panel dataset covering all registered farms in Brittany, France, for the period 2004-2014. While exiting is on average positively correlated with neighbouring farm size, we find substantial variation between farm types, and a negative correlation for a significant proportion of farms. The approach we develop not only enables us to identify different correlations between neighbouring farm size and exits from farming, but it also yields different results than pooled estimations.

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Cet article propose une typologie qui décrit la diversité des territoires d’élevage européens, en s’appuyant sur deux critères simples et disponibles : la part des prairies permanentes dans la surface agricole utile (SAU) et la densité animale exprimée en Unité de Gros Bétail (UGB) par hectare de SAU. Appliquée aux données de l’Enquête sur la Structure des Exploitations Agricoles, cette typologie distingue six types de territoires d’élevage, que nous avons projeté sur une carte de l’Union européenne. En utilisant les données du Réseau d’Information Comptable Agricole (RICA), nous mettons en évidence la forte diversité des exploitations européennes d’élevage (en termes de structures, de niveau d’intensification, de productivité, de dépendance aux aides directes…) entre territoires et au sein de chacun d’eux. Ce travail apporte des éléments de cadrage aux autres articles publiés dans ce même numéro de la revue et ciblés sur des territoires ou des types d’élevage particuliers.

Summary The paper investigates whether accounting for unobserved heterogeneity in farms' size transition processes improves the representation of structural change in agriculture. Considering a mixture of two types of farm, the mover–stayer model is applied for the first time in an agricultural economics context. The maximum likelihood method and the expectation–maximization algorithm are used to estimate the model's parameters. An empirical application to a panel of French farms from 2000 to 2013 shows that the mover–stayer model outperforms the homogeneous Markov chain model in recovering the transition process and predicting the future distribution of farm sizes.

We contribute to understanding the impact of potential drivers of farm income inequality and the redistributive impact of Common Agricultural Policy (CAP) payments. Our approach provides information at any quantile of the income distribution, in contrast to the widely used Gini coefficient. Income growth and inequality dynamics of French commercial farms between 2000 and 2017 are found to be explained by a change in both income levels and farm characteristics. Further, CAP payments are shown to participate in levelling off income inequalities, with Pillar 1 and 2 payments performing differently along the distribution. Our results may help inform on-going policy debates about fairness in the distribution of farm support and structural change implications for the future of European agriculture.