Forest Income Inequality Essay

The decomposition of income inequality by various income sources allows us to find out whether forest source plays any important role to improve income distributional pattern among these forest fringe households. Tab. 4-6 gives the decomposition of income inequality by income source. The income distribution is similar within rich and medium households giving similar estimate compared to medium household. The question is; does forest income have any role to alleviate inequality between households? And the answer is ‘YES’. Justified with comparison of Lorenz curve with and without CF income. Lorenz curve without CF income is more deviated from the line of equality than the Lorenz curve with CF income (Fig. 4-1). The Gini-coefficient for the total

4-7) followed by the Gini 0.60, 0.54 and 0.48 for rich, medium and poor household within socio-economic group. Supportive result was seen in Chhetri, (2005) with CF Gini 0.50, larger estimate itself, but helps to reduce the total income inequality in the study area. This type of higher inequality is due to the reality that households don’t extract the forest products in the same quantity and there is no reason that every household need to collect each and every forest

19,261 [0.49$/day] and international poverty line NRs. 74842.52 [1.9 $/day] are used to evaluate the level of poverty in the study area. Total household income is converted to average per capita income by multiplying the population share of a household adult equivalent unit (a.e.u.). As national standard, 7.5 % of the sampled population lives in extreme poverty (α = 0; Table 8). This is surprisingly lower than the national figure of 25.16 % (CBS, 2011). And it is also quite lower with the study done by Chhetri et al., (2015) giving the result of 25.1 % sampled population lives in extreme poverty. This is because our study site Jamune VDC is developed than Simjung and Ghyachok VDC of Ghorkha district. The depth of extreme poverty (α = 1) is 2.17 %, while the severity (α = 2) is 0.76 %. Excluding CF income from the total household income, the prevalence of extreme poverty rises to 28.75 %, a relative increase of 283.33 %. That means 21.25% of sampled household are the direct beneficiary with CF to stay above the poverty line. This type of changes was seen in the similar study by Chhetri et al., (2015), with the exclusion of environmental income the prevalence of extreme poverty rises from 39.9% to 59%. With increase in poverty gap (α = 1) and poverty severity (α = 2) indices would increase even more, by 441.47% and 902.63 %, respectively. Further, 13.33 % medium households and 6.67 % poor households lives in extreme poverty (α = 0), quite different