本文選題：多尺度　切入點(diǎn)：多維貧困　出處：《首都師范大學(xué)》2014年碩士論文　論文類(lèi)型：學(xué)位論文

【摘要】：2010年,中國(guó)農(nóng)村絕對(duì)貧困發(fā)生率從2000年的3.5%下降到2008年的1%,2013年,國(guó)家統(tǒng)計(jì)局調(diào)整絕對(duì)貧困收入標(biāo)準(zhǔn)為2300元,保守估計(jì)貧困人口還有8000萬(wàn)人。此外,中國(guó)的貧困人口開(kāi)始向西部地區(qū)集中,山區(qū)農(nóng)村貧困人口占全國(guó)農(nóng)村貧困人口的比重逐年上升。貧困向老少邊區(qū)的“小集中大分散”趨勢(shì)越來(lái)越明顯。 目前,國(guó)內(nèi)貧困的識(shí)別僅僅停留在依靠收入指標(biāo)的基礎(chǔ)上,貧困的表達(dá)也僅僅通過(guò)統(tǒng)計(jì)圖表來(lái)進(jìn)行表達(dá)。這樣的貧困識(shí)別與測(cè)量技術(shù)并不能有效地分析貧困地區(qū)的致貧機(jī)制,不能幫助政府制定相關(guān)的扶貧政策。隨著多維貧困理論逐漸成為國(guó)內(nèi)外學(xué)者研究的熱點(diǎn),從多維分析貧困的特征已經(jīng)成為近年來(lái)貧困識(shí)別與測(cè)量的焦點(diǎn)。此外,由于貧困具有地域性特征,所以,對(duì)多維貧困人口所處地域的可持續(xù)能力進(jìn)行評(píng)估分析,是貧困地區(qū)致貧機(jī)制研究不可缺少的部分。 根據(jù)阿瑪?shù)賮喩睦碚?量化貧困就必須對(duì)貧困進(jìn)行識(shí)別與測(cè)量。識(shí)別的目的是為了能夠劃分貧困與非貧困個(gè)體；而測(cè)量的目的是通過(guò)數(shù)值指標(biāo)表示貧困的程度。本文采用多尺度的研究方法,首先參考以往政府部門(mén)以及相關(guān)學(xué)者的貧困識(shí)別與測(cè)量指標(biāo)體系,在衡量了研究區(qū)地域條件的情況下構(gòu)建了貧困人口、村級(jí)、縣級(jí)的多維貧困識(shí)別與測(cè)量指標(biāo)體系。其次,在貧困人口尺度,使用“雙臨界值法”對(duì)研究區(qū)多維貧困人口進(jìn)行識(shí)別與測(cè)量；在村級(jí)尺度,使用“參與式評(píng)估”法對(duì)村級(jí)貧困程度進(jìn)行識(shí)別與測(cè)量；在縣級(jí)尺度,使用“PI指數(shù)法”對(duì)縣級(jí)貧困程度進(jìn)行識(shí)別與測(cè)量。最后,通過(guò)維度分解分析各個(gè)維度對(duì)貧困的貢獻(xiàn)情況,以此分析地區(qū)的致貧原因；通過(guò)GIS的空間分析方法分析地區(qū)貧困空間分布狀況；基于不同尺度致貧原因的關(guān)系研究,分析貧困人口與其所處環(huán)境之間的致貧關(guān)系。實(shí)證方面,本文首先以秦巴山區(qū)南陽(yáng)市四個(gè)國(guó)家級(jí)貧困縣為例,在調(diào)查數(shù)據(jù)不足的情況下運(yùn)用Kriging插值技術(shù)實(shí)現(xiàn)了對(duì)研究區(qū)多維貧困人口空間分布的模擬；其次,以武陵山區(qū)重慶市黔江區(qū)為例,對(duì)其多維貧困人口、村級(jí)貧困、縣級(jí)貧困進(jìn)行了識(shí)別與測(cè)量,分析研究區(qū)的致貧原因以及貧困的空間分布情況,并探討了貧困人口與其所處環(huán)境之間的致貧關(guān)系,以此研究為政府提供政策建議。其貧困分析結(jié)果如下： 1)通過(guò)數(shù)據(jù)檢驗(yàn),南陽(yáng)市四縣多維貧困測(cè)量指標(biāo)符合插值條件。結(jié)果顯示：淅川縣山區(qū)部分的多維貧困人口發(fā)生率最高,鎮(zhèn)平縣MPI最低,但健康對(duì)貧困的貢獻(xiàn)度最高。 2)村級(jí)貧困主要分布在黔江區(qū)中部以及中南部,且分布較零散,聚集程度不明顯。在與多維貧困人口的關(guān)系分析中,發(fā)現(xiàn)造成黔江區(qū)健康問(wèn)題嚴(yán)重的原因與黔江區(qū)醫(yī)療基礎(chǔ)設(shè)施不全,缺乏有經(jīng)驗(yàn)的醫(yī)護(hù)人員以及參與醫(yī)療保險(xiǎn)的農(nóng)戶(hù)數(shù)量少有關(guān)。 3)在縣級(jí)尺度上,黔江區(qū)的綜合貧困指數(shù)在整個(gè)武陵山區(qū)片區(qū)縣的排名較低,整體貧困較其他武陵山區(qū)片區(qū)縣輕。但是,從其貧困致貧機(jī)制分析以及內(nèi)部村級(jí)的貧困分布可以看出,黔江區(qū)也屬于多因素致貧類(lèi)型。其致貧模式為：由于區(qū)域條件差導(dǎo)致的區(qū)域封閉,致使信息閉塞,優(yōu)厚的生態(tài)資源不能通過(guò)科學(xué)技術(shù)轉(zhuǎn)換為經(jīng)濟(jì)效益；加之,依然以自給自足的農(nóng)業(yè)經(jīng)濟(jì)無(wú)法滿(mǎn)足黔江區(qū)的人口需求以及發(fā)展需求,另外,黔江區(qū)內(nèi)部分行政村由于頻發(fā)地質(zhì)類(lèi)災(zāi)害導(dǎo)致農(nóng)業(yè)經(jīng)濟(jì)受損,單一的產(chǎn)業(yè)經(jīng)濟(jì)無(wú)法支持區(qū)域的發(fā)展,導(dǎo)致區(qū)域發(fā)展的失衡,區(qū)域差距日漸擴(kuò)大。
[Abstract]:In 2010, Chinese absolute rural poverty rate dropped from 3.5% in 2000 to 1% in 2008, 2013, the National Bureau of statistics to adjust the absolute poverty income standard is 2300 yuan, a conservative estimate of poverty population and 80 million people. In addition, Chinese poverty began to focus on the western region, the poor mountainous rural areas accounted for the impoverished rural population year by year the young and old poverty to rise. "Small concentrated dispersion" trend is more and more obvious.
At present, the identification of poor domestic only in rely on income index, poor expression only by statistical charts to express. This poor recognition and measurement technology can not effectively analyze the mechanism of poverty in poor areas, can help the government formulate related poverty reduction policies. With the Multidimensional Poverty Theory has gradually become the focus of domestic foreign scholars, from the multidimensional analysis of the characters of poverty in recent years has become the focus of poverty identification and measurement. In addition, due to the poor with regional characteristics, therefore, the ability of sustainable development at the domain of Multidimensional Poverty Assessment and analysis, study on poverty in poor areas is the mechanism of the indispensable part.
According to Amartya Sen's theory, we must identify and quantify the poverty measurement of poverty. The purpose is to be able to identify into poor and non poor individuals; and the purpose of measurement is through numerical index to show the extent of poverty. This research method using multi scale, the first reference to poverty identification and measurement index system in government departments and some scholars, in the measure of the geographical conditions in the study area under construction of poverty village, Multidimensional Poverty identification and measurement index system at county level. Secondly, the poverty population scale, the use of "double threshold method" for the recognition and measurement of Multidimensional Poverty Population in the study area; village scale, the use of "participatory evaluation method for identifying and measuring on the village level poverty level; at the county scale, the county level of poverty were identified and measured using" PI index ". Finally, through The dimension of each dimension decomposition analysis of contribution to poverty, to analyze the causes of poverty area; through the GIS spatial analysis method to analyze the distribution of poverty in the region space; Study on the relationship between different scales based on the analysis of the causes of poverty, poverty and environment between poverty. The empirical aspect, firstly in the Qinba Mountain District of Nanyang City, four a national poverty county as an example, in the case of lack of survey data by using Kriging interpolation technique to realize the simulation of the spatial distribution of poverty population in the study area of multidimensional; secondly, in Qianjiang District of Chongqing city in Wuling mountainous areas as an example, the multidimensional poverty village, poverty, poverty county is the identification and measurement, analysis of the study area the causes of poverty and poverty of the spatial distribution, and discusses the poverty population and its environment in order to study the relationship between poverty and provide policy for the government The results of its poverty analysis are as follows:
1) through data inspection, Nanyang city four county of Multidimensional Poverty Measurement Indicators in line with interpolation conditions. The results show that the Multidimensional Poverty County of Xichuan mountainous area had the highest incidence, Zhenping county MPI is the lowest, but the highest contribution to poor health.
2) village poverty mainly distributed in the Qianjiang area of central and south central, and the distribution is scattered, the aggregation degree is not obvious. In the analysis of the relationship between the population and the Multidimensional Poverty, found the cause of serious health problems in Qianjiang district and Qianjiang district medical infrastructure is not complete, lack of experienced staff and participate in the medical insurance of farmers a small number of related.
3) at the county scale, comprehensive poverty index of Qianjiang District in the area of the whole county in mountainous area of Wuling ranked lower overall poverty than other area in the mountainous area of Wuling county. But the light from the poverty, poverty and internal mechanism analysis of village level poverty distribution can be seen, Qianjiang district also belong to multiple types. The model for poverty poverty due to regional conditions due to poor areas closed, resulting in the lack of information, ecological resources can not be paid by the science and technology into economic benefits; in addition, still in the self-sufficient agricultural economy can not meet the demand of Qianjiang district population and development needs, in addition, the Qianjiang district administrative villages due to frequent geological disaster caused agricultural economic damage the single industrial economy cannot support the development of the region, resulting in the imbalance of regional development, regional disparity is increasing.

【學(xué)位授予單位】：首都師范大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：F323.8;F224

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