Examining the competitiveness pressure of wine production in EU nations

Examen de la pression concurrentielle de la production de vin dans les pays de l'UE

K Hervé Dakpo (), Yann Desjeux () and Laure Latruffe
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K Hervé Dakpo: UMR PSAE - Paris-Saclay Applied Economics - AgroParisTech - Université Paris-Saclay - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement
Yann Desjeux: INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, BSE - Bordeaux sciences économiques - UB - Université de Bordeaux - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement

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Abstract: The European Union (EU) is prominent in the global wine industry as the world's largest producer, consumer, and exporter. Moreover, countries like France, Italy, and Spain account for seventy-five percent (75%) of the EU wine production. One of the significant challenges EU winemakers face is competition among EU countries and other global regions. This competition is even exacerbated by the changing consumer preferences towards more environmentally friendly wine, the evolving regulatory framework, and climate change. Our objective in this paper is to examine the competitiveness between six EU countries: France, Italy, Spain, Germany, Portugal, and Greece between 2004 and 2018. To this aim, we rely on the new class of stochastic frontier, which introduces bounds on the inefficiency distribution. From a practical point of view, this bound reflects competitive pressure as extremely inefficient farms are eliminated from the market by competition. This paper extends the model to include variables that may explain the bound level and account for production heterogeneity assessed through a latent class stochastic frontier model. For the estimation, we assume that producers maximize their profit per hectare. Using this behavioural objective, we derived a primal function that is neither a production nor a distance function but allows us to control for the endogenous nature of input and output choices.

Keywords: Latent; classes (search for similar items in EconPapers)
Date: 2024-06-18
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Published in 18th European Workshop on Efficiency and Productivity Analysis, ISEPA - International Society for Effieciency and Productivity Analysis, Jun 2024, Faro (Portugal), Portugal

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