Andere Kunden interessierten sich auch für
![Technical Efficiency Artisanal Shrimp Fishers Coastal Areas Delta State Nigeria]( "Technical Efficiency Artisanal Shrimp Fishers Coastal Areas Delta State Nigeria")
Technical Efficiency Artisanal Shrimp Fishers Coastal Areas Delta State Nigeria30,99 €![Determination of Factors Affecting Technical Efficiency]( "Determination of Factors Affecting Technical Efficiency")
Determination of Factors Affecting Technical Efficiency26,99 €![Integrating the Formal and Informal Seed Supply system]( "Integrating the Formal and Informal Seed Supply system")
Integrating the Formal and Informal Seed Supply system35,99 €![Urban Agriculture Indices in Selected Towns in Tanzania]( "Urban Agriculture Indices in Selected Towns in Tanzania")
Urban Agriculture Indices in Selected Towns in Tanzania51,99 €![Camel and Cow Milk Marketing Chain Analysis: The Case of Ethiopia]( "Camel and Cow Milk Marketing Chain Analysis: The Case of Ethiopia")
Camel and Cow Milk Marketing Chain Analysis: The Case of Ethiopia39,99 €![Value Chain Analysis: Theory and Practice]( "Value Chain Analysis: Theory and Practice")
Value Chain Analysis: Theory and Practice36,99 €![Potato Value Chain Analysis: Implications For Employment Generation]( "Potato Value Chain Analysis: Implications For Employment Generation")
Potato Value Chain Analysis: Implications For Employment Generation29,99 €
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.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.