This study examined the effect of production and climate-related risks on small-holder cassava and maize farmers’ output in Southwestern Nigeria. Cross-sectional and time series data were used for this study. The analytical tools used in the study are Descriptive statistics, J-P (Just and Pope) Production Function Model, Growth Function Analysis, Stochastic Frontier Translog Cost and Production Function Analysis, Auto-regressive Distributed Lag (ARDL) Model Approach to Co-integration and Ordered Probit Regression Model. The study concluded that quantity of cassava cuttings, quantity of fertilizer, proportion of family labour and farm size increased the production risk of the cassava farmers in the study area, while quantity of seed and fertilizer increased the production risk of the maize farmers in the study area. Temperature increased the production risk of the cassava and maize farmers in the study area. Temperature, rainfall and relative humidity were important climate factors that influenced the output of both cassava and maize in the long and short run in the area. Majority of the respondents in the two enterprises were risk averse and risk neutral.
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Taschenbuch. Condition: Neu. Production And Climate-related Risks Among Crop Farmers In Nigeria | Effect Of Production And Climate-related Risks On Small-holder Cassava And Maize Farmers' Output In Southwestern Nigeria | Lawrence Olusola Oparinde (u. a.) | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9786200287731 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 117475511
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This study examined the effect of production and climate-related risks on small-holder cassava and maize farmers' output in Southwestern Nigeria. Cross-sectional and time series data were used for this study. The analytical tools used in the study are Descriptive statistics, J-P (Just and Pope) Production Function Model, Growth Function Analysis, Stochastic Frontier Translog Cost and Production Function Analysis, Auto-regressive Distributed Lag (ARDL) Model Approach to Co-integration and Ordered Probit Regression Model. The study concluded that quantity of cassava cuttings, quantity of fertilizer, proportion of family labour and farm size increased the production risk of the cassava farmers in the study area, while quantity of seed and fertilizer increased the production risk of the maize farmers in the study area. Temperature increased the production risk of the cassava and maize farmers in the study area. Temperature, rainfall and relative humidity were important climate factors that influenced the output of both cassava and maize in the long and short run in the area. Majority of the respondents in the two enterprises were risk averse and risk neutral. Seller Inventory # 9786200287731
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