| Summary: | This study examined economic market decisions among marginal maize farmers in Abuja, Nigeria: applications of double hurdle model and factor analysis. Specifically, the objectives were designed and stated to achieve the following; describe the socio-economic characteristics of marginal maize farmers, analyze the costs and returns of marginal maize production, determine the marginal productivities of maize farmers, estimate the factors influencing output of marginal maize production, evaluate factors influencing market decisions among marginal maize farmers, and identify the constraints facing marginal maize farmers. Multi-stage sampling technique was adopted and used. Primary data were collected from marginal maize producers through the use of well-structured and well-designed questionnaire. Data obtained were coded and analyzed using descriptive statistics, gross margin analysis, financial analysis, double-log functional model, marginal productivity, double-hurdle model, and principal component analysis. The results show that 60% of marginal maize farmers were less than 50 years of age. About 80% of farmers had less than 20 years experiences in maize farming. The mean farm size was 1.19 hectares of land. The gross margin and net farm income were 577,300 Naira and 525,300 Naira respectively. The gross margin ratio, operating ratio, and rate of return on investment were 0.82, 0.21, and 3.01 respectively. The gross margin ratio of 0.82 implies that for every one Naira invested in maize production by marginal farmers 82 kobo covered profits, taxes, interest, expenses, and depreciation. Marginal productivity analysis revealed that resources such as fertilizers, seeds, and land were under-utilized. Factors influencing output of maize production by marginal farmers were: farm size (<0.01) , family labour (P<0.05), hired labour (P<0.05), fertilizers (P<0.01), seed input (P<0.05), and volume of pesticide used (P<0.10). The double-hurdle model revealed that age (P<0.01), prices output of maize (P<0.05), education status (P<0.10), distant to nearby market (P<0.05) , access to extension agents (P<0.01) and access to credit facilities (P<0.05) were statistically and significant variables influencing marginal maize farmers decisions to market participation. The retained constraints facing marginal maize farmers explained 96.46% of variables included in the model. Factors analysis shows that retained constraints facing marginal maize farmers were; bad road infrastructures, lack of access to credit facilities, inadequate extension officers, poor storage facilities, lack of production inputs, and lack of new, improved technologies.
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