Análisis de la característica – Seguridad

DEA studies in agricultural sectors deal with efficiency from different points of view and they focus on various subject areas. Some subject areas of interest commonly appear. Most common ones can be listed as environment, irrigation, productivity change, regional level evaluations and subsidies. Below, we provide a brief reviewing of studies on such common areas of interest. In addition to those, studies with emphasis on subjects as competitiveness (Reig-Martínez and Picazo-Tadeo, 2004), financial management (Davidova and Latruffe, 2007), strategic management (De Koeijer et al., 2003), sustainability (Kim, 2001), decision making (André et al., 2010) and quota reallocation (Andersen and Bogetoft, 2007; Bogetoft et al., 2007) can also be found in the literature.

• Environment: Environmental performance is one of the key issues taken into consideration in many DEA studies in agriculture. Several research attempts to measure the efficiency of environmental practices of agricultural establishments. Examples include studies by Reinhard et al. (2000), which measure the environmental efficiency of Dutch dairy farms, De Koeijer et al. (2002), which deal with agricultural sustainability with an environmental perspective in sugar beet growing sector of Netherlands and De Koeijer et al. (2003), in which the quality of farmers’ environmental performance is assessed through DEA using environmental variables together with the performance indicators in a case study of Dutch arable farms. In addition, Wossink and Denaux (2006) evaluate the pesticide use efficiency in a sample of cotton farms in North Carolina, USA. A regression analysis is performed following DEA in order to analyse the factors affecting efficiency. The study reveals a significant difference in efficiency between different types of cotton produced. Asmild and Hougaard (2006) aim to demonstrate how economic and environmental improvement potentials of Danish pig farms can be estimated using

DEA in the presence of undesirable outputs. The results of the study point out the improvement potentials, especially on the environmental variables.

• Irrigation: Water use is an inseparable part of agriculture production process. This draws researchers’ attention to evaluate the efficiency of water use at both farm and regional level. Therefore, irrigation efficiency is one of the key topics, in agricultural DEA studies. One example can be given from a research conducted in Andalusia region of Spain by Rodríguez-Díaz et al. (2004). The study evaluates the efficiency of irrigation districts in a specific region and depending on the efficiencies, the entire region is divided into three large districts. In the districts, authors identify specific crops, which are cultivated in highly efficient areas. They advocate that this kind of an evaluation can help the policy in terms of considering reductions in labour or water use and substitutions of crops since the results show some relevancy between specific crops and high efficiency.

In another study, Lilienfeld and Asmild (2007) are looking at the irrigation efficiency, which is conducted in Western Kansas and evaluations are carried out from the perspective of irrigation system type and other factors. DEA models are designed in a water use specific way, which enables the measurement of water use efficiency and excess irrigation water used. A weak relationship between irrigation system types and excess water use is one of the findings of the study. Relationship of excess water use between different factors such as age of farmer, farm size or ground water management is also investigated.

Also, in a recent study related to irrigation, Frija et al. (2011) investigate farmers’ technical efficiency through DEA models considering water use as one of the inputs

approach in Tunisia. The study brings out important implications for the Tunisian water policy.

• Productivity change: In principle, DEA models are based on relative measurement of efficiency at the same point in time. However, for some problem types, investigation of change in the productivity can be of interest. For this purpose, Malmquist Productivity Index (MPI) approaches (Malmquist, 1953; Caves et al., 1982; Färe et al., 1992) are developed and widely used to observe the changes in productivity during a period of time. Considerable amount of studies in the agricultural efficiency literature deal with the evaluation of the productivity changes overtime. Usually, Malmquist Productivity Index methods and their variations are applied in order to assess the changes. An example is Balcombe et al. (2008a) aiming to evaluate the productivity change in Polish crop and livestock farms between years 1996 and 2000. Productivity indices and farm specific changes in efficiency are calculated through MPI approach. Similarly, Odeck (2009) focuses on the use of a variation to Malmquist Indices and measure the productivity changes. The study designs a procedure for Malmquist Indices with stages and applies this procedure in a sample of grain farms in Norway between years 1987 and 1997.

Measuring the productivity change has also been studied at regional level as well as the farm level. Millian and Aldaz (1998) and Aldaz and Millian (2003) are examples of regional productivity change studies in Spain. In addition, Thirtle et al. (2003) employ Malmquist Indices and statistical tests in evaluating efficiency change of regional agriculture production in Botswana. Study compares different regions and reveals an interesting finding that the gap between productive and poorer regions is widened. Furthermore, a number of studies on evaluating agricultural production growth at country level through Malmquist Productivity Index approaches are listed by Thirtle et al. (2003). Examples can be given as Thirtle et al. (1995) evaluating

Sub-Saharan Africa countries from 1971 to 1986, Trueblood (1996) and Arnade (1998) working on Worldwide samples of countries from 1961 to 1993, Fulginiti and Perrin (1997) using a sample of Least Developed Countries, from 1961 to 1985 and Suhariyanto et al. (2001) dealing with African and Asian samples of countries, from 1961 to 1991.

• Regional level evaluations: Although majority of studies in agricultural efficiency studies focus on the evaluations at the farm level, a substantial number of research can be found which is conducted at regional level. Efficiency studies at regional level evaluate the efficiency, changes in efficiency or factors affecting efficiency at a more macro level considering the districts, provinces or regions as decision making units. Examples of regional level DEA studies in agriculture include Zhang (2008) and Monchuk et al. (2010) both conducted in China, where in the former, environmental efficiency of provinces in terms of agricultural production is evaluated and in the latter a derivation of DEA approach is used to determine the technical efficiency at the county level. Some other examples dealing with regions can be given as Millian and Aldaz (1998) and Aldaz and Millian (2003) in Spain, Karkazis and Thanassoulis (1998) in Greece and Thirtle et al. (2003) in Botswana.

• Subsidies: There are a number of DEA studies dealing with the agricultural efficiency from the perspective of subsidies. These studies focus on the impact of policies related to subsidies or direct payments on the efficiency and investigate the relationship between them. Such studies are usually conducted in European countries and touch the issues of Common Agricultural Policy (CAP) of European Union, which regulates the agricultural subsidies and programmes. One example can be given as Latruffe et al. (2008b), in which relationship with CAP direct payments

system for subsidies through DEA efficiency scores in Spain, considering the aspects of the Common Agricultural Policy in European Union. In a recent study, Zhu and Lansink (2010) evaluate the impact of policy reforms in CAP on the technical efficiency through Stochastic Frontier Analysis (SFA) approach with a large scale study conducted in Germany, Netherlands and Sweden.