The number of poor people in Nigeria and in many developing economies across the globe has continued to be on the increase within the past two or three decades This is attributable to the economic and socio-political instability experienced in these countries The situation is further aggravated by the declining and irregular income low rate of capital accumulation and declining agricultural output due to the rapidly changing climatic conditions. Meanwhile, it has been established that in many rural areas, agriculture alone does not provide sufficient livelihood opportunities hence diversification into non-farm activities is seen as a form of self-insurance. This is because diversification offers people options for coping with crisis. The resultant effect of
This is that rural households diversify their income sources by combining two or more jobs (multiple job holding) to enhance consumption smoothing and acquire other basic needs. The result presented here relied on data collected from a random sample of 3PS households selected from six states (one state from each of the six geopolitical zones) of the country. Analysis of data revealed that most of the respondents were young, married with fairly large household size. Educational analysis of respondents indicated that a sizeable number had no formal education with only about one-third educated up to tertiary level. However, distribution of respondents by poverty status showed that there were more female-headed households in the study area than male-headed households with over half of those surveyed living on less than one dollar a day. Meanwhile, the result of the tobit regression model employed to ascertain the determinants of livelihood diversification showed that the coefficients of gender, household size, poverty status and access to credit facility were positive. This indicates that any increase in the value of the coefficients of these variables have higher likelihood of influencing the estimated livelihood diversification index positively. Further, the coefficients of years of formal education, income, marital status, primary occupation and location were negative. Thus, an increase in the value of any of the variables will negatively influence the estimated livelihood diversification index. 'n general, male-headed, small-sized, non-poor households with formal education and better income and access to credit facility were not all that engaged in multiple jobs like female-headed, uneducated, large-sized, poor households and those not having access to credit facility.