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Technical efficiency in the spice based agroforestry sector in Matale district, Sri Lanka
Authors:L. M. J. K. Lindara  F. H. Johnsen  H. M. Gunatilake
Affiliation:1. Department of Export Agriculture, Bandi Para, Labuduwa, Akmeemana, Galle, Sri Lanka
2. Department of International Environment and Development Studies (Noragric),, Norwegian University of Life Sciences, P.O. Box 5003, N-1432, ?s, Norway
3. Department of Agricultural Economics, Faculty of Agriculture,, University of Peradeniya, Peradeniya, Sri?Lanka
Abstract:Spices constitute an important sub-sector of the economy of Sri Lanka. Most perennial spices are cultivated in agroforestry types of farming systems. A field survey was conducted covering 127 agroforestry farmers in six divisional secretariats in Matale district during the period of October to December 2002. Technical efficiency of spice based agroforestry systems was estimated in order to identify the potential increase in production without incurring additional costs for farm inputs. The factors affecting technical efficiency and constraints and potential of the agroforestry system were also investigated. According to a stochastic frontier production function using a Cobb–Douglas model, hired labour, organic fertilizer, inorganic fertilizer, land size, and soil conservation measures showed significant positive effects on the agroforestry production. The mean technical efficiency of the spice based agroforestry systems was 84.32%. According to the inefficiency model the efficiency increased significantly as a result of farm visits by extension officers, participation in farmer training, less sloping lands, more experience, and higher diversity of the agroforestry system. Technical efficiency decreased, however, with higher education level of the farmer and with higher off-farm income. Unsustainability of the agroforestry system is seen as a result of a␣range of constraints related to productivity, market, technology and institutions.
Keywords:Cobb–  Douglas  Export crops  Farm income  Farming systems  Production function  Stochastic analysis
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