A Stochastic Frontier Analysis of Maize Production Efficiency and Its Climate-Smart Agricultural Practice Determinants in Southeast, Nigeria

Abstract

Efficient maize production and resource allocation are crucial for agricultural sustainability, particularly in climate-vulnerable areas like Southeast Nigeria. This study employs stochastic frontier analysis (SFA) to investigate the efficiency of maize production and the determinants of allocative efficiency under climate-smart agricultural practices (CSAPs). The study includes 375 maize farmers selected randomly for the research sample. The analysis begins with estimating the efficiency parameter of maize production, revealing a relatively low Sigma-square value (0.029) and a moderate Gamma value (0.786). The study found a positive association between various inputs such as landholding, seed quality, and organic manure application. The mean TE and AE are 0.894 and 0.747 respectively. Allocative efficiency analysis reveals that while water management practices significantly affect technical efficiency positively, they unexpectedly lead to lower AE. Access to information and adoption of early planting positively influence allocative efficiency. Further examination of socioeconomic determinants indicates the role of extension services (3.07)*** in enhancing AE, while cooperative membership negatively impacts it, possibly due to information asymmetry. These findings emphasize the need for tailored interventions to optimize resource allocation strategies and enhance agricultural productivity and sustainability in Southeast Nigeria, particularly amidst the challenges posed by climate change. Comprehending the complex dynamics of resource allocation and efficiency in agriculture is crucial for crafting efficient policies and interventions aimed at improving productivity and resilience amidst changing climate conditions.