ABSTRACT<\/strong><\/p>\n\n\n\n

The study was conducted in Taraba State. Multistage and proportionate sampling techniques were adopted in sampling nine hundred and forty nine (949) respondents. Both primary and secondary data was used for the study, and was obtained through the use of structured questionnaire which was administered directly to the respondents. Both descriptive and inferential statistics was used in analyzing the data obtained. Descriptive statistics such as frequencies, percentages and means were used to categorized respondents based on socio-economic characteristics, income level and livelihood activities of respondents (objectives. i, ii, and v.).Inferential statistics such as multiple regression model, multinomial logistic model and Gini coefficient was employed to determine relationships between variables. Multiple regression was used to examine socio-economic factors affecting income of respondents. The study shows that majority (75%) of the respondents were male while 25% were females with a mean age of 42 years. The result reveals that about 39% had farming experience of between 11 \u2013 20 years with 53% of them belonging to farming association. The major source of income of the respondents was faming with 83% of them having 1 \u2013 5 hectares of farm. Marital status, household size, educational level attained, number of years spent in acquiring formal education and farm size were all significant at 5% level, while gender, age, farming experience, membership of farmers organizations and access to loan though not statistically significant all have positive coefficients, meaning they have positive influence on the income level of the farming households in the study area. The results shows that income from farm (GE \u03b1 =0, 0.072, GE \u03b1 =1, 0.075 and GE \u03b1 =2, 0.078) activities contributed more to income inequality than any other livelihood strategy and may be attributed to the fact that farming activities yield higher returns than non -farm activities in the study area largely due to the fact that the research targeted mainly farming population. As a result, there is high income disparity among the households engaged in farm activities. It is recommended that government should formulate policies that will lead to job creation, poverty reduction and wealth creation to combat income inequality among crop farming households.<\/p>\n\n\n\n