Role of non-farm sector was found to be vital with high share in household income (37%). Also, lower values for poverty head count was found for the household with some form of non-farm employment (on average 5.56%) compared with those without it (on average 67.65%). Gini index for household with and without non-farm employment also revealed income-inequality to be higher among the households without non-farm employment (on average gini value was 58.72% compared to 43.05%). Similarly, both hill and terai region were found to follow this pattern.Decomposition analysis revealed that agriculture is the main source of income-inequality in the selected households (contributes 40% to overall gini and has positive elasticity). This might be due to high disparities in the size of cultivated land among the households. Again, both hill and terai region was found to hold these results. However, since agricultural sector is still dominant and contributes a large share for the rural poor, appropriate policy consideration is required to increase agricultural income, may be through increased productivity, subsidies in crucial inputs, price protection, and so forth, with especial emphasis to the poor households so as to minimize further deterioration in income-inequality. On the other hand, livestock sector was found to be negatively related with income-inequality and also with less contribution to gini. Again, it is less important in terai but is important in the hills. Livestock sector, thus, could also contribute significantly and help reduce poverty and inequality with appropriate policy recommendations, especially in the hills. Similarly, on average non-farm income was also found to be inequality-decreasing. The negative elasticity and low contribution of non-farm sector in gini showed the role it can play in the household welfare. But it has less effect in case of hills and hence for instance is of less importance there whereas it has significant and vital role in the terai with inequality-decreasing effects, hence, needs especial consideration and appropriate policy recommendation. On top of this, since the effect was different for hill and terai, different policies suitable for individual settings might be necessary.As the major focus of this research is in the non-farm sector, the major policy implication of this research could be that related with the role of non-farm sector. Since, on average non-farm incomes are found to be reducing poverty as well as income-inequality, availability of more non-farm earning opportunities may be helpful to combat poverty and inequality. This may be useful especially for the rural poor because they still have less access to non-farm economic activities and derive only a small share (around 8% of household income). Hence, policy should be directed to promote rural non-farm economic activities, with focus on poor households. Although a sudden change could not be expected, a gradual and long-term policy may be of use in this case. Moreover, in this research we found that government services are dominant in both hills and terai, but it could not be suddenly increased and hence is beyond the scope of this paper. However, commerce or business activities accounts for nearly one-fourth of the non-farm employment on average and one-third in case of terai, hence policies like availability of loan, may be in the form of micro-credits for poor households may help promote these activities. Similarly, ease in capital formation may help increase the activities of manufacturing sector. Other non-farm sector could also be promoted with appropriate policy measures. However, again a detail study is recommended to find the role of individual sectors and a suitable policy recommendation.
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