本文選題：重點(diǎn)國(guó)有林區(qū)　切入點(diǎn)：多維貧困　出處：《東北林業(yè)大學(xué)》2015年碩士論文

【摘要】：貧困問題是世界研究的一個(gè)重要課題,區(qū)域性的貧困和反貧困問題是當(dāng)前學(xué)界對(duì)貧困問題關(guān)注的焦點(diǎn),如何認(rèn)識(shí)貧困和測(cè)度貧困是制定扶貧政策的基礎(chǔ)。重點(diǎn)國(guó)有林區(qū)雖然不是《中國(guó)農(nóng)村扶貧開發(fā)綱要(2011-2020)》所確定的11個(gè)連片特困地區(qū)之一,但是這里正經(jīng)歷著由木材生產(chǎn)為主向生態(tài)保護(hù)為主而轉(zhuǎn)型的“陣痛”,林區(qū)的職工名義上是產(chǎn)業(yè)工人,但長(zhǎng)期以來其工資水平不及當(dāng)?shù)爻擎?zhèn)職工的工資,據(jù)調(diào)查,內(nèi)蒙古伊圖里河林業(yè)局職工人均年工資不及呼倫貝爾市的40%。更重要的是林區(qū)的基礎(chǔ)設(shè)施投資也跟不上農(nóng)村更跟不上城市。已有對(duì)重點(diǎn)國(guó)有林區(qū)貧困的研究是基于收入貧困的,然而,更多的研究表明,收入只能反映貧困的一個(gè)方面,而不能充分反映除收入之外其他維度的貧困。近年來,已經(jīng)有學(xué)者開始了對(duì)中國(guó)農(nóng)村進(jìn)行多維貧困的測(cè)度,從多個(gè)維度測(cè)量貧困是當(dāng)今貧困問題研究的趨勢(shì)所在。本文從多維貧困視角對(duì)重點(diǎn)國(guó)有林區(qū)的貧困問題進(jìn)行研究,利用“2013年重點(diǎn)國(guó)有林區(qū)民生監(jiān)測(cè)”項(xiàng)目的調(diào)研數(shù)據(jù),運(yùn)用Alkire和Foster提出的A-F多維貧困測(cè)量方法,從教育、健康和生活水平3個(gè)維度共8個(gè)指標(biāo)對(duì)重點(diǎn)國(guó)有林區(qū)的多維貧困進(jìn)行測(cè)量,并對(duì)指標(biāo)和地區(qū)進(jìn)行分解。研究結(jié)果表明：(1)重點(diǎn)國(guó)有林區(qū)存在收入以外的多維貧困,35.7%的職工家庭存在8個(gè)指標(biāo)中至少3個(gè)指標(biāo)的貧困。(2)衛(wèi)生設(shè)施的貧困剝奪情況最為嚴(yán)重,貧困發(fā)生率42.1%；其次,健康狀況、飲用水和生活燃料的單維貧困剝奪情況也很嚴(yán)重,貧困發(fā)生率依次為31.4%、35.0%、33.6%；受教育程度的單維貧困發(fā)生率為17.3%,剝奪情況也很嚴(yán)重。(3)指標(biāo)分解結(jié)果表明,衛(wèi)生設(shè)施、飲用水和生活燃料3個(gè)指標(biāo)對(duì)重點(diǎn)國(guó)有林區(qū)多維貧困指數(shù)的貢獻(xiàn)率最大；林區(qū)分解結(jié)果表明,重點(diǎn)國(guó)有林區(qū)的四大國(guó)有森工林區(qū)都存在不同程度的多維貧困,其中,內(nèi)蒙古森工林區(qū)多維貧困狀況最為嚴(yán)重。根據(jù)重點(diǎn)國(guó)有林區(qū)的貧困現(xiàn)狀以及測(cè)度的結(jié)果,本文提出了重點(diǎn)國(guó)有林區(qū)多維貧困治理的思路和政策建議。首先,提出貧困治理的總體框架,主要包括重點(diǎn)國(guó)有林區(qū)多維貧困的治理目標(biāo)、治理原則、治理路徑。其次,提出重點(diǎn)國(guó)有林區(qū)貧困治理的政策建議,主要包括：加大對(duì)林區(qū)的支持力度,制定覆蓋更多維度的多維貧困政策,提高貧困群體的自身發(fā)展能力,建立針對(duì)性的扶貧機(jī)制和風(fēng)險(xiǎn)預(yù)警機(jī)制。本文的研究,希望對(duì)重點(diǎn)國(guó)有林區(qū)扶貧政策的制定提供參考和借鑒。
[Abstract]:The problem of poverty is an important subject in the world study. Regional poverty and anti-poverty are the focus of the current academic attention on poverty. How to understand poverty and measure poverty is the basis for formulating poverty alleviation policies. Although key state-owned forest areas are not one of the 11 special hardship areas identified in the "China Rural Poverty Alleviation and Development Program 2011-2020", However, this place is experiencing a "labor pain" from timber production to ecological protection. Workers in forest areas are nominally industrial workers, but their wages have long been lower than those of local urban workers. According to an investigation, The Ituri River Forestry Bureau in Inner Mongolia has less than 40% of the average annual wage of the employees in Hulunbeir. More importantly, the investment in infrastructure in the forest areas cannot keep up with the rural areas, let alone the cities. Research on poverty in key state-owned forest areas has been based on income poverty. However, more studies have shown that income can only reflect one aspect of poverty, but not poverty in other dimensions except income. In recent years, some scholars have begun to measure the multidimensional poverty in Chinese rural areas. Measuring poverty from multiple dimensions is the trend of poverty research today. This paper studies poverty in key state-owned forest areas from the perspective of multidimensional poverty, and makes use of the survey data of "people's livelihood Monitoring in key State-owned Forest areas in 2013". Using the A-F multidimensional poverty measurement method proposed by Alkire and Foster, the multi-dimensional poverty in key state-owned forest regions was measured from the three dimensions of education, health and living standard. The results show that 35.7% of the workers and families in key state-owned forest areas have poverty deprivation of at least 3 of the 8 indicators) and the deprivation of sanitation facilities is the most serious. The incidence of poverty is 42.1; secondly, the state of health, the single-dimensional deprivation of drinking water and fuel for domestic use is also serious. The incidence of poverty in turn was 31.4% 35.0% and 33.6%; the incidence of single-dimensional poverty with education was 17.30.The deprivation was also very serious. The breakdown of the indicators showed that the sanitation facilities, The three indexes of drinking water and domestic fuel contributed most to the multi-dimensional poverty index in key state-owned forest regions, and the results of forest decomposition showed that the four major state-owned forest regions in key state-owned forest regions all had multi-dimensional poverty to varying degrees, among which, The situation of multi-dimensional poverty is the most serious in the forest region of Inner Mongolia. According to the present situation of poverty in the key state-owned forest area and the result of measurement, this paper puts forward the ideas and policy suggestions for the management of multidimensional poverty in the key state-owned forest region. Put forward the overall framework of poverty management, mainly including the governance objectives, governance principles, governance path of multi-dimensional poverty in key state-owned forest areas. Secondly, put forward policy recommendations on poverty management in key state-owned forest areas. It mainly includes: increasing the support for forest areas, formulating multidimensional poverty policies covering more dimensions, improving the ability of the poor groups to develop themselves, establishing targeted poverty alleviation mechanisms and risk early warning mechanisms. Hope to provide reference and reference for key state-owned forest area poverty reduction policy formulation.
【學(xué)位授予單位】：東北林業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：F323.8

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