Common Agricultural Policy support, technical efficiency and productivity change in French agriculture

Latruffe, Laure; Desjeux, Yann

doi:10.1007/s41130-016-0007-4

Cited by 58 publications

(50 citation statements)

References 31 publications

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“…These authors indicate that TFP in French agriculture grew at an annual rate of 1.44% during 1959-2011, but the annual rate was lower than 1% (namely 0.94%) during 2003-2011, a discrepancy that the authors attribute to a lack of increase in output during this later period. Similarly, for the period 1990-2006, Latruffe and Desjeux (2016) report a deterioration of TFP of about 2% yearly, as well as slight technological regress for several types of farming (field crop, dairy, and beef) in France. Baráth and Fertő (2014) also find that TFP decreased by 2% during 2000-2010 for the whole French agricultural sector.…”

Section: Introductionmentioning

confidence: 93%

Productivity, technical efficiency and technological change in French agriculture during 2002-2015: a Färe-Primont index decomposition using group frontiers and meta-frontier

Dakpo

Desjeux²,

Jeanneaux

et al. 2018

Applied Economics

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The objective of the article is to assess productivity change in French agriculture during 2002-2015; namely, total factor productivity (TFP) change and its componentstechnological change and efficiency change. For this, we use the Färe-Primont index which verifies the multiplicatively completeness property and is also transitive, allowing for multi-temporal and -lateral comparisons. We investigate the extent of heterogeneity within each type of farming sub-sample in terms of TFP change, with the help of the Herfindahl-Hirschman index (HHI). In addition, to compare the technologies among the five types of farming considered, we extend our analysis to the meta-frontier framework. Results indicate that during 2002-2015, all farms experienced TFP progress. The smallest average increase was experienced by the dairy farms and the largest by the field crop farms and the beef farms. The latter had the strongest technological progress but a deterioration in efficiency, while the opposite was found for field crop farms. The analysis of HHI reveals that sheep or goat farms are the most homogenous in terms of the direction of TFP change experienced over the period 2002-2015. The meta-frontier analysis shows that field crop farms' technology is the most productive of all the types of farming. KEYWORDS

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Section: Introductionmentioning

confidence: 93%

Productivity, technical efficiency and technological change in French agriculture during 2002-2015: a Färe-Primont index decomposition using group frontiers and meta-frontier

Dakpo

Desjeux²,

Jeanneaux

et al. 2018

Applied Economics

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“…Z tego powodu metoda DEA jest powszechnie stosowana w sektorze rolniczym [Parlinska, Bezet 2008, Fogarasi, Latruffe 2009, Rusielik 2010, Smędzik 2010, Kagan 2014, Kulawik 2014, Syp i in. 2015, Kusz, Sobolewski 2016, Latruffe, Desjuex 2016, Borecka, Cieślik 2017. Jednak w literaturze przedmiotu nie znaleziono badań, które swoim zasięgiem obejmowałyby teren województwa lubelskiego.…”

Section: Wstępunclassified

“…Zastosowany dobór zmiennych po stronie nakładów ma wpływ na wartość produkcji, a to jest głównym celem funkcjonowania gospodarstwa. Ponadto, jest zgodny z doborem stosowanym w literaturze [Fogarasi, Latruffe 2009, Kulawik 2014, Latruffe, Desjuex 2016. W analizie danych wykorzystano statystyki opisowe.…”

Section: Materiał I Metodyka Badańunclassified

Efficiency and Productivity Change in Field Crop and Milk Farms in Lublin Province in 2014-2016

Syp

Osuch

2018

Annals PAAAE

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The aim of the study was assessment of efficiency and productivity of farms in the Lublin province in the years 2014-2016. The analysis was based on the Data Envelopment Analysis (DEA) model oriented on inputs and Malmquist indices with its components. The calculations were made for medium-sized field and dairy farms that continuously collected data for the FADN system during the period under consideration. In our research all efficiency indicators for dairy farms were larger than for field crop farms. In the years 2014-2016, the average technical efficiency of dairy farms was 0.752, which means that in those farms it is possible to reduce inputs on average by 25% and the value of production will remain at the same level. In the case of field crop farms, inputs should be limited by 33%. The applied decomposition of calculated Malmquist indices allowed to define what factors influenced changes in productivity.

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“…Surveys regarding changes in the total productivity of agriculture most frequently referred either to a selected group of farms, e.g. dairy farms (Čechura et al, 2014;Madau et al, 2017;Bokusheva and Čechura, 2017), or to selected countries (Latruffe and Desjeux, 2016;Leimane et al, 2017;Zaman and Meunier, 2017;Duguleana and Duguleana, 2016), or the analysis covered the previous study period (Coelli and Rao, 2005). Baráth and Fertő (2014) indicate that no studies have been carried out concerning the comparison of TFP in agriculture between old and new member states, especially after 2007.…”

Section: Introductionmentioning

confidence: 99%

Changes in Agricultural Productivity in New and Old Member States of the European Union

Nowak¹,

Kubik²

2019

ERSJ

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Purpose: This paper aimed at evaluating changes in agricultural productivity in the group of new (NMS) and old (OMS) member states of the European Union. Design/Methodology/Approach: The analysis covered the years 2007-2016. The calculations made use of unit data from farms participating in FADN (Farm Accountancy Data Network). Surveys were carried out based on the Malmquist productivity index and partial indicators of land, workforce and capital productivity. Findings: The outcome pointed to increased total productivity of agriculture in NMS (9.5%), resulting from positive technological changes and improvement in technical efficiency. A small decrease in productivity was noted in a group of EU-15 countries, which was due to a decrease in technical efficiency. Despite the growth in total productivity, the value of partial productivity indicators in NMS remained at a much lower level than in OMS. Practical Implications: Identification of the determinants of growth in agricultural productivity is the precondition to make up differences occurring between member states in this respect. Originality/Value: This study contributes to reference literature concerning productivity of agriculture for a number of reasons. First, the scope of the survey is extensive, as it covers a group of 27 EU member states split into new and old members. The second aspect of the survey is taking into account both changes in total factor productivity and in productivity of respective production factors. Thirdly, the Malmquist index adopted for the needs of the survey made it possible to identify the sources of change in total factor productivity.

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Common Agricultural Policy support, technical efficiency and productivity change in French agriculture

Cited by 58 publications

References 31 publications

Productivity, technical efficiency and technological change in French agriculture during 2002-2015: a Färe-Primont index decomposition using group frontiers and meta-frontier

Productivity, technical efficiency and technological change in French agriculture during 2002-2015: a Färe-Primont index decomposition using group frontiers and meta-frontier

Efficiency and Productivity Change in Field Crop and Milk Farms in Lublin Province in 2014-2016

Changes in Agricultural Productivity in New and Old Member States of the European Union

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