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Measuring Efficiency of Maize Production in Uganda: A Data Envelopment Analysis Approach
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Abstract
The study measured efficiency of maize production in Uganda. The study aimed at achieving two objectives i.e., to establish the performance of maize production in Uganda (at ZARDI and District level) and to determine how much inputs are required for the inefficient Decision Making Units to achieve maximum efficiency. The study used secondary data collected by National Agricultural Research Organisation(NARO) on 1445 maize and bean farmers in Uganda in 2020. The study used the Output oriented Data Envelopment Analysis model that basically answers two questions i.e., which DMUs performs better than the other and what is required to make the inefficient ones efficient. From the findings, only Bulindi ZARDI was established inefficient only operating at 95% among the ZARDIs. At district level, Kiryandongo, Masindi, Bugiri, Kiboga, Sironko, Nakaseke, Bukwo, Kole, Kakumiro, Kyankwanzi, Mityana and Iganga were marked as inefficient implying operating below 100% capacity. Sensitivity analysis on benchmarks, shadow price and slacks were done to answer the second objective. The bench mark analysis was done to establish where inefficient DMUs should draw lessons from. The shadow price analysis was done to show the unit worth of inputs ie the marginal effect/productivity of a resource to the final efficiency score. The slack analysis showed room for improvement for inefficient DMUs to be efficient. Bulindi which is inefficient among the ZARDIs has a considerable surplus of excess capacity of inputs i.e., 89.02 acres, 974 persons of Hired Labour, 16.4 litres of herbicides, 29.7 litres of pesticides, 6.45kgs of inorganic fertilizers and 4.63 litres of inorganic fertilisers suggesting optimum resource allocation and utilization of underutised resources. The inefficient districts have an excess capacity of Acreage under Maize Production, Hired Labour, Family Labour, Herbicides in litres, Pesticides in litres, Organic Fertilisers (Manure)-kg, Inogarnic Fertilisers(kg) and Inorganic Fertilisers in litres by 267.89, 968, 1463, 29.34, 37.17, 4.84, 45.16 and 18.46 units respectively suggesting suggesting need for improvement in the utilization of resources (since the resources are underutilized). The study suggested recommendations that include redistributing excess inputs, optimizing resources and improving input usage,, facilitating knowledge transfer, capacity building and training, monitoring and evaluation, research & innovation and financial support for technology adoption to improve maize production in Uganda.
Springer Science and Business Media LLC
Title: Measuring Efficiency of Maize Production in Uganda: A Data Envelopment Analysis Approach
Description:
Abstract
The study measured efficiency of maize production in Uganda.
The study aimed at achieving two objectives i.
e.
, to establish the performance of maize production in Uganda (at ZARDI and District level) and to determine how much inputs are required for the inefficient Decision Making Units to achieve maximum efficiency.
The study used secondary data collected by National Agricultural Research Organisation(NARO) on 1445 maize and bean farmers in Uganda in 2020.
The study used the Output oriented Data Envelopment Analysis model that basically answers two questions i.
e.
, which DMUs performs better than the other and what is required to make the inefficient ones efficient.
From the findings, only Bulindi ZARDI was established inefficient only operating at 95% among the ZARDIs.
At district level, Kiryandongo, Masindi, Bugiri, Kiboga, Sironko, Nakaseke, Bukwo, Kole, Kakumiro, Kyankwanzi, Mityana and Iganga were marked as inefficient implying operating below 100% capacity.
Sensitivity analysis on benchmarks, shadow price and slacks were done to answer the second objective.
The bench mark analysis was done to establish where inefficient DMUs should draw lessons from.
The shadow price analysis was done to show the unit worth of inputs ie the marginal effect/productivity of a resource to the final efficiency score.
The slack analysis showed room for improvement for inefficient DMUs to be efficient.
Bulindi which is inefficient among the ZARDIs has a considerable surplus of excess capacity of inputs i.
e.
, 89.
02 acres, 974 persons of Hired Labour, 16.
4 litres of herbicides, 29.
7 litres of pesticides, 6.
45kgs of inorganic fertilizers and 4.
63 litres of inorganic fertilisers suggesting optimum resource allocation and utilization of underutised resources.
The inefficient districts have an excess capacity of Acreage under Maize Production, Hired Labour, Family Labour, Herbicides in litres, Pesticides in litres, Organic Fertilisers (Manure)-kg, Inogarnic Fertilisers(kg) and Inorganic Fertilisers in litres by 267.
89, 968, 1463, 29.
34, 37.
17, 4.
84, 45.
16 and 18.
46 units respectively suggesting suggesting need for improvement in the utilization of resources (since the resources are underutilized).
The study suggested recommendations that include redistributing excess inputs, optimizing resources and improving input usage,, facilitating knowledge transfer, capacity building and training, monitoring and evaluation, research & innovation and financial support for technology adoption to improve maize production in Uganda.
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