The study investigates the impact of urban-rural migration on income and occupation. The research aims to estimate the probabilities and significance of income and occupational change across different socio-economic characteristics and demographic profiles upon return to the rural areas from Nairobi city, particularly after the enactment of the 2013 Kenya devolution policy. The paper draws upon exploratory research using data comprising 69 interviews with the return migrants after they had established a stay in rural areas, two years subsequently after migrating from Nairobi city. By applying the empirical methods of probit regression model, the study finds that significant probability for income change varies across different socio-economic attributes and demographic profiles. Occupational change and associated probabilities are significantly determined by low education level, female gender, the old age, huge rural land size, and low migrant’s job-related expertise level. For both income and occupational change, rural land size more than 2.5 acres is a significant incentive for urban-rural migration; given the likelihood of return migrants shift to agriculture and in a long run establishes a robust source of income. This, after assigning other dummy variables, and setting the baseline at two years.

Reverse migration is on a steady increase under the devolved system of governance in Kenya. The situation could be attributed to an array of triggers such as; the ongoing rural development programmes, backdrop of non-availability of livelihood and job opportunities in the city. Upon return to the rural areas, it could be perceived that the returnees encounter some socio-economic shocks, which tend to impact their income and career. To ascertain the impact, we use a binomial probit model to estimate the probability of income and occupational change. We postulate that harsh encounters in the city inspire those with savings, newly acquired entrepreneurial acumen, and land to migrate out of the city and exploit rural job opportunities. Study participants were people that had moved from Nairobi to their rural counties. Using snowball sample selection, we obtained 49 adult participants mean age = 41years, SD = 15.95, female 48%, employed 68%, married 59%, and 29% educated up to university Results found that significance for career and income changes varies across participants socio-economics status or demographics. For instance, those aged 35–59 years (r2 = 0.399, ME = 0.421); land size greater than 2.5 acres (r2 = 0.507, ME = 0.473) and postgraduate degree (r2 = 0.513, ME = 0.591) had significant income increment. For 60 + years (r2=-0.369, ME=-0.312), primary-leavers (r2=-0.459, ME=-0.226) had significant decrease in income upon return. Conversely, females (r2 = 0.326, ME = 0.348), and migrants aged 60 + years (r2 = R2 = 0.797, ME = 0.651) were more prone to career change; all at .01 significance level. Attributes such as marital status, age 25-34yrs, secondary or college-level education are weak income or career change determinants. We conclude that rural land size, more than 2.5acres was a significant incentive for reverse migration, since the likelihood of shifting to agriculture and establishing a robust livelihood source and income after assigning other dummy variables, and setting the baseline at two years was evident across groups.