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Study Of Measuring And Governance On Multidimensional Poverty In Key National Forest Areas

Posted on:2016-09-10Degree:MasterType:Thesis
Country:ChinaCandidate:L YuanFull Text:PDF
GTID:2309330470482809Subject:Forestry Economics and Management
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Poverty is an important research topic in the world, and regional issues of poverty and anti-poverty is the focus of the current academic focus on poverty, how to understand poverty and measure poverty is the foundation of formulating poverty alleviation policy. Although the key national forest areas is not one of the 11 Contiguous destitute areas identified by the " Rural Poverty Alleviation and Development Program(2011-2020) in China", but it is experiencing a "labor pains" transformed from timber production oriented to ecological protection. The forest workers nominally industrial workers, but their wages level less than local urban workers for a long time. According to the survey, the Ituri River Forest Bureau of Inner Mongolia annual average wage of workers less than the 40% of Hulun Buir. What’s more, forest infrastructure investment cannot follow the rural areas and more to keep up with the city. Existed researches of the poverty in key national forest areas were based on income poverty. However, more recent research shows, revenue can reflect only one aspect of poverty, but cannot be enough to reflect other dimensions of poverty in addition to income. In recent years, some scholars begin to measure multidimensional poverty of rural in China, it is the current trend in poverty study to measured poverty from the multiple dimensions.This paper makes research from the perspective of the multidimensional poverty problems in the key national forest areas. Based on the survey data of Monitoring Project of People’s livelihood of the key national forest areas in 2013, according to the A-F method of multidimensional poverty measurement proposed by Alkire and Foster, to measure the multidimensional poverty in key national forest areas from eight indexes in education, health and living standards three dimensions, and decomposition multidimensional poverty according to the areas and dimensions. The research results show that:(1) the key national forest areas exists poverty in other dimensions besides income, there are 35.7% households which are in poverty at least 3 indexes. (2)The deprived situation in sanitation facilities is the most serious, the incidence of poverty is 42.1%. Simultaneously, the deprived situation in health, drinking water and domestic fuel single dimensional are very serious, the incidences of poverty were 31.4%、35.0% 33.6%. The deprivation of educational level is also serious, the incidences of poverty is 17.3%. (3) The decomposition results show that:sanitation facilities, drinking water and domestic fuels contribute the most to multidimensional poverty index. Meanwhile, there are different degrees in multidimensional poverty among the four major national forest areas, and the multidimensional poverty situation of Inner Mongolia national forest areas is the most serious.According to the poverty situation and Measure results in key national forest areas, this paper presents some ideas and policy recommendations for multidimensional poverty governance of the key national forest areas. First, this paper puts forward the overall frame of poverty governance, including the objectives of governance, the principles of governance and the paths of governance. Then, the paper proposes the policy recommendations of multidimensional poverty governance of the key national forest areas. The suggests include increasing the support of government, formulating multidimensional poverty policy of covering more dimensions, improving their self- development capability of poor population and establishing targeted poverty alleviation mechanism and risk warning mechanism. This study hopes to provide reference for making poverty alleviation policy in key national forest areas.
Keywords/Search Tags:The key national forest areas, Multidimensional poverty, Poverty measurement, Poverty governance
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