Determinants of Food Security and Technical Efficiency among Agricultural Households in Nigeria

Abstract

The challenge of food security in Nigeria hinges on several factors of which poor technical efficiency is key. Using a stochastic frontier framework, we estimated the technical efficiency of agricultural households in Nigeria and tested for the significance of mean technical efficiency of food-secure and food-insecure agricultural households. We further assessed the determinants of agricultural households’ inefficiencies within the stochastic frontier model and adopted a standard probit model to assess the determinants of households’ food security status. The results of our analyses revealed that; on the overall, the agricultural households had a mean technical efficiency of 52%, suggesting that agricultural households have the tendency of improving their technical efficiency by 48% using the available resource more efficiently. We found that households that are food-secure are more technically efficient than food in-secure households and this was significant at one-percent. Our results provide useful insights into the role of land size and number of assets as determinants of agricultural households’ food security and technical efficiency status.

The Influence of Social Networking on Food Security Status of Cassava Farming Households in Nigeria

“…This is in agreement with the findings of Grootaert [80]. Also, cash contributions or cash commitments by the cassava farming households to the associations were much lower than contributions made by fish farming households involved in a recent study by Adepoju [83] where the fish farming households contributed as much as 43,887.52.…”

“…It is essential to take note of the high level of food security among cassava farming households in the south-south zone of Nigeria. Our results are similar in the pattern of food security status with those of Ahungwa et al [81], Osuji et al [82], Oyetunde-Usman and Olagunju [83], where the numbers and percentages of food-insecure households are more than those of the food secure households. However, in the studies of Abu and Soom [84] and Ahmed et al [85], the number and percentages of food secure households are more than their food-insecure households.…”

What Drives Households’ Payment for Waste Disposal and Recycling Behaviours? Empirical Evidence from South Africa’s General Household Survey

“…On the basis that the dependent variables g i and r i are binary, it is appropriate to fit a binary regression, such as a Probit regression, to determine the recycling behaviour and payment for waste disposal. Studies such as Olagunju, et al [ 49 ], Ogunniyi, et al [ 50 ], Oyetunde-Usman and Olagunju [ 51 ] and [ 52 ], which had a binary dependent variable, used a Probit regression model. However, given that Equations (5) and (6) both have binary dependent variables, the errors of the two models are likely going to be correlated, hence the choice of the Bivariate Probit model, which is stated thus: where , , φ, π, ω and α are the estimated parameters.…”

Does agricultural cooperative membership impact technical efficiency of maize production in Nigeria: An analysis correcting for biases from observed and unobserved attributes

“…Indeed, previous studies on this subject, for example, Hailu et al [ 20 ], Ainembabazi et al [ 3 ], and Wollni and Brümmer [ 21 ] assume that the decision to participate in cooperatives or otherwise is random and may not be affected by unobserved factors. A few studies related to this subject in Nigeria, to our utmost knowledge, also follow suit on this assumption and consequently included cooperative membership as an explanatory variable in the efficiency model (for example [ 23 , 24 ]). However, in reality, farmer’s decision to join cooperatives is non-random which simply implies that such a decision is based on the individual farmer’s self-selection into membership.…”