O.R. ApplicationsThe impacts of regulated notions of quality on farm efficiency: A DEA application
Introduction
In 1991 and 1992, a series of European Union Regulations introduced a formal institutional framework of rules and procedures for the production of (i) organic agricultural products, and (ii) denominated food products, namely, foodstuffs labeled as products of Protected Geographical Indications (PGIs), products of Protected Designations of Origin (PDOs), and products of Traditional Specialty Guaranteed (TSGs) (Commission of the European Communities, 1991, Commission of the European Communities, 1992a, Commission of the European Communities, 1992b). These policy measures form an integral part of the ongoing effort of EU planners to reform the Union's Common Agricultural Policy (CAP) in the face of: (i) increasing consumer preference for food quality (e.g., Eurobarometer, 1996; Dimara and Skuras, 2003) and food safety, following recent alarming events such as the BSE outburst and dioxine-poisoned food, (ii) concerns about environmental problems linked to current farming practices, and (iii) concerns about the survival of EU farm operations in an increasingly liberalized, international marketplace.
Institutionalizing the production of organic and denominated farm products may be viewed as a strategy which attempts to address all three considerations above. On the one hand, it addresses preferences for food quality and safety and environmental concerns. On the other hand, it introduces a distinctly defined mechanism for farm product differentiation, which may help European farmers develop market niches in an increasingly competitive global economy.
The actual implementation of these quality-oriented regulations provides the applied economic research with an interesting field of study. In the first place, the adoption of these new farming modes, which are governed by specific rules, may be expected to affect farm management, and more specifically, the farm's technical efficiency, that is the ability of the farmers to obtain maximal output from the inputs they actually use. In the case of Greece, the technical efficiency of farms that have adopted organic farming techniques has recently been studied for a number of crops (Tzouvelekas et al., 2002).
An additional issue of interest to applied economists is how farm efficiency will be affected when more than one of these quality-oriented regulations are simultaneously adopted by farmers. The exploration of this question is largely empirical and worth pursuing, primarily for policy reasons. More explicitly, if all such regulations can become available to every farmer, with no restrictions whatsoever as to how many or which ones the farmer can adopt, and this adoption has an implicit impact on farm efficiency, then useful insights may emerge for policy planners. For example, there might be cases wherein allowing farmers to register with one additional quality regulation will reduce efficiency differentials existing for farms operating under another quality regulation.
Within this context, the objective of this paper is to assess the implicit impact of multiple EU quality-oriented regulations on farm efficiency and discuss its policy implications. To that end, we utilize existing methodological developments in the area of data envelopment analysis (DEA) to study the case of Greek black currant producers who are eligible for both denominated (i.e., PDO) as well as organic currant production. Clearly, the focus of this study is not on advancing methodological procedures, but rather on assessing possible conflicting or complementary facets in the implementation of the EU quality-oriented regulations.
The remainder of the paper is organized as follows: the regulated notions of quality and the institutional framework of currant production in Greece are described in the next section; the methodological framework and the data used are presented in Section 4; the estimation results are discussed in Section 5; policy implications and concluding remarks follow.
Section snippets
The changing notions of food quality
In recent years, the outbreak of many food-related crises (i.e., E. coli, BSE, dioxines, foot-and-mouth disease-FMD) and safety scares over genetically modified food, the excessive use of chemical fertilizer/pesticides in plant production, and antibiotics in animal raising have eroded consumer trust in conventionally produced food, forcing the implementation of food standards and `science' in general (Bromley, 2001; McNaghten and Urry, 1998). Consumers are becoming increasingly concerned about
Data envelopment analysis (DEA)
The objective is to determine the relative efficiency for each farm. Efficiency is a multi-faceted phenomenon. From an output point of view, a firm may be called (technically) efficient if it produces the maximum output in a certain technological regime (environment) with given input quantities. From an input point of view, a firm may be called (technically) efficient if it produces a given level of output in a certain technological regime, using minimal quantities of inputs. Efficiency is
Results
The DEA model is applied to conventional and organic farms separately, due to the fact that conventional and organic farming represent two distinct technologies. Relevant references in the international literature tend to assume that conventional and organic cultivation represent two distinct modes of production and, thus, should be modeled under two different production frontiers (Tzouvelekas et al., 2001a, Tzouvelekas et al., 2001b). Indeed, compared with their conventional colleagues,
Discussion and policy implications
Recent EU regulations have attempted to regulate the quality of agricultural production through schemes which allow (i) the production of denominated products with emphasis on the physical properties and the geographical zone of production and (ii) the production of organic products with emphasis on methods and processes of production. This paper has attempted to examine quantitatively the effects of these two distinct regulated notions of quality on farm efficiency. Taking into account the
Acknowledgements
This work arises from a program of collaborative research by the following: the Department of Geography at the Universities of Coventry, Leicester, Lancaster, Caen, Valencia, Galway and Trinity College Dublin; the Scottish Agricultural College (Aberdeen); Institute of Rural Studies (Aberystwyth); CEMAGREF (Clermont-Ferrand); Teagasc (Dublin); Department of Economics (University of Patras); and Seinajoki Institute for Rural Research and Training (University of Helsinki). The research was funded
References (45)
- et al.
Technical efficiency and economies of scale: A non-parametric analysis of REIT operating efficiency
European Journal of Operational Research
(2002) - et al.
Measuring the efficiency of decision making units
European Journal of Operational Research
(1978) - et al.
Capacity utilisation and profitability: A decomposition of short-run profit efficiency
International Journal of Production Economics
(2002) - et al.
Quality farm food in Europe: A possible alternative to the industrialised food market and to current agri-environmental policies: Lesson from France
Food Policy
(1998) New rural territories: Regulating the differentiated rural space
Journal of Rural Studies
(1998)- et al.
The use of parametric and non-parametric methods to measure productive efficiency in the industrial sector: A comparative study
International Journal of Production Economics
(2001) - et al.
The role of international trade on environmental efficiency: A DEA Approach
Economic Modelling
(2001) - et al.
Exploring output quality targets in the provision of perinatal care in England using data envelopment analysis
European Journal of Operational Research
(1995) - et al.
Technical efficiency of alternative farming systems: The case of Greek organic and conventional olive farms
Food Policy
(2001) The effect of incentive regulation on productive efficiency in telecommunications
Journal of Policy Modeling
(2001)
Some models for estimating technical and scale inefficiencies in data envelopment analysis
Management Science
Mad cows, drugged cows, and juggled genes
Choices
Data Envelopment Analysis: Theory Methodology and Applications
Sport in Society: Issues and Controversies
An Introduction to Efficiency and Productivity Analysis
Greek Agriculture in a Changing International Environment
Consumer evaluations of product certification, geographic association and traceability in Greece
European Journal of Marketing
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