INTEGRATING PRODUCTION RISK IN EFFICIENCY ANALYSIS:
EVIDENCE FROM RICE PRODUCTION IN YOBE STATE, NIGERIA
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The estimation of technical efficiency using the conventional stochastic model proposed by Aigner et al. (1977) fails to adequately address this important aspect of production which is production risk. Not accounting for production risk with respect to input use, results in biased estimates of technical efficiency which may be misleading to policy makers. This study analyzed the production risk of rice production in Yobe state using a stochastic frontier model with a flexible risk component. It estimates the production risk with respect to the input factors. The findings from the production ri...
The estimation of technical efficiency using the conventional stochastic model proposed by Aigner et al. (1977) fails to adequately address this important aspect of production which is production risk. Not accounting for production risk with respect to input use, results in biased estimates of technical efficiency which may be misleading to policy makers. This study analyzed the production risk of rice production in Yobe state using a stochastic frontier model with a flexible risk component. It estimates the production risk with respect to the input factors. The findings from the production risk component give insight into how the individual inputs affects variations in output. Farm size, fertilizer, labour, insecticide, herbicide and irrigation service input factors tend to reduce output variance while seed, machine and green manure increase output variability. This information is necessary for input allocation decisions.
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