Abstract

Data envelopment analysis (DEA) is a non-parametric research technique based on a mathematical optimization method. Since was first developed in ‘78, the method is used in various sectors of economy and at different levels (companies, counties, regions, etc.). Our purpose is to apply DEA at regional level by using various inputs and outputs to analyse the performance of agriculture practiced in plain, hill and mountain areas. Thirty-six counties were classified into three categories based on their geographical main characteristics, respectively: group I – with 50-100% plain areas (20 counties); group II - with 50-80% hill areas (8 counties); group III - with 50-80% mountain areas (8 counties). For these groups were computed, under input-oriented option, CRS and VRS technical scores from which we calculated scale efficiencies. This empirical research shows that exists clear differences of performance between areas with similar geographical characteristics in terms of production factors (work, land and mechanization) allocation and outputs. Our results show that there are only 14 counties (5 in plain areas, 5 in hill areas and 4 in mountain areas) completely achieving DEA efficiency and operate at their optimal scale. In conclusion, in majority of areas the overall efficiency of agriculture is not reached, these regions needing to decrease the input levels (especially work hours that are too high compared with productivity) or to increase the output levels (production value) through a better use of fix capital and higher yields.

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