Author:
Olufunke Olufunmilayo Ilemobayo, Mohammed Abdul Yekeen Rajhi, Sina Basil Johnson and Jacobs Mobolade Adesina

Doi: 10.26480/fabm.02.2025.79.85

This is an open access article distributed under the Creative Commons Attribution License CC BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

This study examines production efficiency in Nigerian agriculture over 62 years (1960–2021) using a stochastic production frontier model and the Cobb-Douglas functional form. The analysis focused on output- and input-oriented efficiency to measure the potential for improving outputs without increasing input usage. An annual, secondary, time series data from the Nigerian agricultural industry, spanning 1960 to 2021 were used. Data sourced from the Food and Agriculture Organisation (FAO) and the National Bureau of Statistics (NBS) databases. Key variables analysed include the sector’s agricultural gross domestic product (GDP), fertiliser usage measured in kilograms, agricultural labour quantified in man-days, and the number of tractors available within the sector. The study employed the Augmented Dickey-Fuller (ADF) test, confirming that all variables are integrated of order one (1), thus fit for co-integration analysis. The VAR lag selection criteria identified lag 2 as best. Johansen cointegration tests (trace and maximum eigenvalue) revealed the existence of at least one cointegrating relationship, indicating a long-run equilibrium among the variables. The Stochastic Frontier Production Function (SFPF) estimation revealed a technically efficient agricultural sector with a 78% output-oriented technical efficiency (TE) and 22% inefficiency, suggesting potential for increased productivity without input augmentation. The returns to scale (RTS) of 0.9226 confirm decreasing returns, implying reduced output gains from proportional input increases. Economic analysis further revealed that the sector is only 58% economically efficient (EE), with a cost inefficiency of 42%, indicating room for substantial cost reduction. The cost efficiency (CE) of 1.7115 supports this inefficiency, expressing that actual costs exceed minimum required costs by 71%. Input-oriented measures revealed lower efficiency scores compared to output-oriented ones. Input-oriented TE and EE were 74.6% and 53.8%, respectively, indicating relatively less efficiency when adjusting inputs than outputs. Cost inefficiency under the input route is particularly high at 85.7%. Output-oriented strategies yield higher efficiency measures than input-oriented strategies, validating that policy and production strategies should focus on maximising output from given resources, rather than simply minimising inputs.