Analysis of Production Efficiency of Rice Farms in Gambia

Abstract

This study analyzed the production efficiency of rice farms in Gambia using the output-oriented DEA approach on a large dataset comprised of 541 farmers from 70 villages across the six agricultural regions of the country. The OLS Linear regression model was also applied to determine factors that have impact on production efficiency. The DEA results revealed that more than 98 percent of the farms were technically inefficient and would have to improve their output levels by 58 and 56.4 percent, respectively, under CRS and VRS technologies in the first year (2005) and by 59.1 and by 56.2 percent, respectively in the second year (2006). The results also show that more than half of the efficient farms were found in the Central River North region of the country. Despite not being a major issue of the research, the Malmquist TFP measurement for the study period revealed that 25.5 percent (138 farms) experienced TFP growth with an average growth rate of 1.88 percent which mainly was as a result of efficiency change (gains) during the study period. The regression results revealed socio-economic factors (like gender, age, education, vocational training, and farming experience under lowland ecologies), as well as cultivation under lowland and upland ecologies, all demographic locations, and infrastructures (such as existence of electricity, tarred road, improved water services, schools, and health services) in the farming communities to exert significant impacts on farm efficiency and productivity change of the rice farms in the sample.

This study analyzed the production efficiency of rice farms in Gambia using the output-oriented DEA approach on a large dataset comprised of 541 farmers from 70 villages across the six agricultural regions of the country. The OLS Linear regression model was also applied to determine factors that have impact on production efficiency. The DEA results revealed that more than 98 percent of the farms were technically inefficient and would have to improve their output levels by 58 and 56.4 percent, respectively, under CRS and VRS technologies in the first year (2005) and by 59.1 and by 56.2 percent, respectively in the second year (2006). The results also show that more than half of the efficient farms were found in the Central River North region of the country. Despite not being a major issue of the research, the Malmquist TFP measurement for the study period revealed that 25.5 percent (138 farms) experienced TFP growth with an average growth rate of 1.88 percent which mainly was as a result of efficiency change (gains) during the study period. The regression results revealed socio-economic factors (like gender, age, education, vocational training, and farming experience under lowland ecologies), as well as cultivation under lowland and upland ecologies, all demographic locations, and infrastructures (such as existence of electricity, tarred road, improved water services, schools, and health services) in the farming communities to exert significant impacts on farm efficiency and productivity change of the rice farms in the sample.