The study is undertaken in four sample villages of the two sample districts in Jharkhand state, namely, Ranchi and Dumka to track the changes in rural poverty in eastern states of India. The data pertains to these two representative districts, one representing socioeconomically developed district (Ranchi) and other representing the socioeconomically backward district (Dumka).Primary data collected from four villages of Jharkhand i.e., two villages each from Ranchi and Dumka districts of Jharkhand state. A sample of 40 households from each village, making a total household sample of 160 was selected for detailed investigation in project entitled “Tracking Change in Rural Poverty in Households and Village Economies in South Asia”. Besides simple statistical tools, loreze curve are plotted. Gini Ratio is computed to measure income inequality among villages of Jharkhand. Diversification index is computed to have an idea about diversity of income sources. Linear regression model is adopted to identify the determinants of income. The study reveales Per capita income reflects the purchasing power and living standard of the people. The per capita income/annum in sample villages ranged from 6, 378 to 14,871 which shows a difference of more than doubles ( 8, 493). There are various sources of income however; non-farm activity was prominent source of income among all villages (37.19% to 63.67%). More interestingly, Jajmani system is still prevalent in the state and accumulating a considerable income. This shows that income diversification is a long practiced strategy by many livelihoods in order to reduce risk of external shocks. State has great diversity of income. Livestock system is an integral part of livelihoods of rural poor however its contribution is negligible. Livestock sector could be revived through the technological intervention from research institutes, development departments and policy planners. Study shows that age, education, size of households, non-farming income, and adoption of high yielding varieties are the main determining factors who had a significant impact on households’ income. Gini ratio shows that highest inequality was found in Dumariya village (0.43). The ranges of Gini ratio were 0.33-0.43. The highest inequality was observed among labour class (0.55) followed by large (0.50), medium (0.37) and small (0.34) category. Income inequality is higher across villages and households and education and income level emerged as important sources of inequality. The findings have important policy implications. At government point of view, there is dire need for generating more non-farm labour opportunities through public works. These opportunities could lead to the better infrastructure facilities and rural livelihoods in rural India. Providing labour opportunities outside the agricultural activities can serve manifold and can reduce the income inequalities among the rural poor. It can play an important role in poverty reduction intervention and will provide safety mesh for income shocks. It will assist in reducing unemployment and under-employment in rural area. Education is an instrument for change. It brings the changes in the thinking process, knowledge, skills and attitude of people. Hence it could be an instrument for reducing inequality among the rural poor.
