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摘要:政府对贫困地区的公共支出可分为一般性公共支出和专项扶贫支出。根据2002—2008年中国贫困重点县的相关数据建立回......

I. Introduction
一、引言
Poverty-stricken areas due to natural, historical and geographical conditions is difficult to rely on their own development out of poverty, government intervention is indispensable. Chinese government early in 1986 opened a large-scale development-oriented poverty reduction journey, and delineate its national poverty counties specifically aimed at poverty alleviation. In the poverty-stricken areas in addition to the general government public expenditure public expenditure, there special poverty reduction in public spending, we can say the government's public spending on poverty and poverty in the region's economic development has played a major role in slowing of China's achievements in rural poverty work can not not. But the 21st century, the population in poverty, diminishing the government's public spending is increasing poverty per capita public spending is rising poverty conditions, there was a poor higher costs, diminishing marginal efficiency of investment in poverty alleviation, poverty alleviation effect of increasing not significant, more difficult issues such as poverty mitigation. How to improve the government's direction and structure of public expenditure, improve the government marginal rate of investment, better play to the government's public spending to promote economic growth and poverty reduction role as the current urgent problem.
贫困地区由于受自然、历史及地理等条件限制难以依靠自身发展脱贫,政府介入不可或缺。中国政府早在1986年就开启了大规模开发式扶贫的征程,并划定国家贫困县对其进行专门瞄准扶贫。在贫困地区政府公共支出除了一般性公共支出外,还有专项扶贫公共支出,可以说政府的公共支出对贫困地区的经济发展和贫困减缓发挥了重大的作用,对中国农村反贫困取得的成绩功不可没。但21世纪以来,在贫困人口不断递减而政府公共扶贫支出还在不断增加即人均扶贫公共投入还在不断上升的条件下,却出现了扶贫成本增高、扶贫投资边际效率递减、扶贫效果越来越不显著、贫困减缓愈加困难等问题。如何改善政府公共支出的方向与结构,提高政府边际投资率,更好地发挥政府公共支出促进经济增长与减贫的作用,成为当前亟待解决的难题。


Few studies have public investment from the government perspective on Chinese government public spending on economic growth and poverty. Huang, Rosegrant and Rozelle (1997) study of public investment (mainly R & D investment) on the Chinese contribution to the growth of crops. Fan et al. (2000) [1] and Lin Bo (2005) [2] are obtained by contacting equation analysis of Chinese government's public investment (R & D, education, roads, electricity, etc.) to economic development rate of return and poverty reduction effects are recognized public investment in education to help the poor best, followed by agriculture R & D investment, and analysis, east, west three different regions of the impact of public investment in the respective difference. Liu Zhi poor (2007) [3] on the fate of the Chinese government is pro-poor public spending empirical study, concluded that: The Government's science, education and social assistance for the poor has been tilted, but the relative lack of social security, the poor get more quick and agricultural services, but the long-term nature of public services get fewer subsidies to the rich, special services and support to the poor.
很少有研究从政府公共投资角度来看待中国政府公共支出对经济增长和贫困的影响。Huang、Rosegrant and Rozelle(1997)研究公共投资(主要是研发投资)对中国农作物增长的贡献。Fan et al. (2000)[1]和林伯强(2005)[2]都通过联系方程分析中国政府公共投资(R&D、教育、道路、电力等方面)对经济发展的回报率及扶贫效果,都认可教育公共投资的扶贫效果最好,其次是农业R&D投入,并分析中、东、西三大地区不同的公共投资各自的影响差异。刘穷志(2007)[3]对中国政府公共支出归宿是否惠及穷人进行实证研究,结论认为:政府的科教文卫和社会救济对贫困人口已经有所倾斜,但社会保障相对不足,贫困人口得到较多见效快的工农业服务,但得到的长远性公共服务较少,补贴给了富人,专项服务和支援给了贫困人口。


As a government anti-poverty funds to poor areas of special public spending, traditionally consists of three parts. FINANCIAL AID funded mainly by the development of the Poverty Alleviation Office responsible for special financial arrangements are budget funds to support economic development in poverty-stricken areas; subsidized loans subsidized by the state is responsible for issuing the Agricultural Bank for loans to support economic development in poor areas; FFW the central government earmarked by the Development and Reform Commission to grant farmers a way to encourage their participation in local infrastructure to improve infrastructure in poor areas and help farmers increase their income. 


Reforestation subsidy as the current implementation of a major project to benefit farmers, China's poverty monitoring report which also serves as the capital of a poverty statistics. Our country is in 1999 started a pilot Grain for Green Project, Grain farmers to make direct payment for food and living allowance. 2007 in order to consolidate the results already achieved Grain, Grain farmers to solve the long-term livelihood issues, the establishment of special funds to consolidate the achievements of converting farmland. Reforestation Project Central special subsidies benefit farmers hundreds of millions, not only improve the ecological environment have become an important source of income poor households, poor areas can also change the mode of development.
T

his study by anti-poverty funds invested by the four components: financial poverty development funds, food for work, subsidized loans, forest subsidies. Currently a lot of research for the conduct and effectiveness of anti-poverty funds to invest, ZHU Qian Yu (2003) on China's poverty alleviation funds for performance analysis, Wang Sangui, etc. (2004), Liu Dongmei (2001) and so the effect on poverty alleviation funds invested empirical research.
This empirical analysis through econometric model between farmers and government 2002-2008 different investment to economic growth and poverty rates change, simulate different government contribution rate of public spending, hoping next public spending on government structure and direction of the adjustment has been Help.


Second, the model set


(A) the government's public spending on economic growth


We focus on economic growth, poverty-stricken counties to represent the per capita net income of farmers, the model in the form of production function using segmented by double logarithmic linear regression model OLS expenditure categories contribution to economic growth. Logarithmic to better reflect the percentage change in the relationship between variables, but there is some cross easily between multiple variables of linear problems, logarithmic can reduce the possibility of serial correlation.
Theoretical models: rural per capita net income = F (poor farmers per capita government spending, general government public spending per capita of farmers, farmers 'per capita raised production costs, farmers' own production conditions, where the village infrastructure and other conditions)


Government expenditure on poverty alleviation in poor areas important public expenditure, in order to better analyze the performance of pro-poor spending, according to invest will be divided into input agriculture, investment in other industries, investment in infrastructure, investment in science, education and other aspects into five categories ; constitute types into financial poverty by development funds, work-relief funds, subsidized loans and grants Grain four categories.


Model 1:
+ Β4ln (jsds) + β5ln (xzqy) + β6ln (xjssf) + ε where, income for farmers per capita net income, fpzj pro-poor growth per capita funding, ygdz per capita work-relief funds, txdk subsidized loans per capita, tghl as Reforestation per capita grants, czznzc per capita fiscal expenditure on agriculture, czkjzc of per capita spending on technology, czjyzc per capita expenditure on education, nmzc raised for farmers per capita expenditure, nyfpzj poor agricultural per capita expenditure, qthyfpzj per capita in other industries poverty spending, jcssfpzj poor infrastructure per capita spending, kjwwfpzj science, education and poverty reduction expenditure per capita, qtfpzj other poor per capita expenditure, nynyzc raised agricultural expenditure per capita for farmers, nygyzc raised industrial expenditure per capita for farmers, nmdscyzc for farmers per capita from raise the tertiary industry expenditures, gdmj for farmers per capita arable land area, hjrk for farmers household population, hjldl for farmers household labor, wcwg for farmers and migrant proportion of the workforce, zxpx had received skills training for the labor proportion, td is powered village proportion, tdh proportion of village phone, tl is the proportion of the village path, jsds village is capable of receiving television programs proportion, xzqy Village number of township enterprises, xjssf as is the proportion of new technology demonstration village.


(Two) the government's public spending on poverty


We focus on the change in poverty poverty poverty rate in the county is represented by a linear regression model OLS expenditure categories for the contribution of the poverty rate.


Theoretical models: the poverty rate = F (poor government spending, government spending general public, non-governmental poverty spending, farmers raised production costs, farmers own production conditions, poverty-stricken areas of natural and infrastructure conditions)


Model 2:
Where H is the poverty rate, fpzj for the poor development funds, ygdz as food for work, txdk as subsidized loans, tghl of returning farmland to forest subsidies, czznzc of fiscal expenditure on agriculture, czkjzc for the financial technology spending, czjyzc of fiscal expenditure on education, nyfpzj poverty expenditures for agriculture, qthyfpzj poverty expenditures for other industries, jcssfpzj for infrastructure pro-poor spending, kjwwfpzj of science, education and poverty reduction expenditures, qtfpzj for other pro-poor expenditures, fzfpzj non-governmental anti-poverty spending, nmzc for farmers raised spending, nynyzc agricultural expenditure for farmers raised, nygyzc industrial spending for farmers raised, nmdscyzc for farmers raised the tertiary industry expenditures, gdmj for farmers per capita arable land area, hjrk for farmers household population, hjldl for farmers household labor, wcwg for farmers accounting for the proportion of migrant labor, zxpx had received skills training for the labor force proportion, cjfp as participated in the proportion of poor farmers, td proportion to electrify villages, tdh is the proportion of the village phone, tl is the proportion of the village path, jsds order to Village proportion receiving television programs, xzqy Village number of township enterprises, xjssf as is the proportion of new technology demonstration village.


Third, the empirical results
Data from China Statistical Publishing House of the calendar year, "China Rural Poverty Monitoring Report", the selected section of the sequence and mixed data through Eview5.0 statistical software for regression analysis. Since China Poverty Monitoring Report was launched in 2000 after a lot of data in 2002 only after statistical norms, so we selected data is key counties 2002-2008 poverty related data. Because the sample is small, fitting results may differ from actual have some bias, but I hope that empirical results also partly reflects the 21st century, the government's public spending on the poor areas of economic development and poverty mitigation some new situations. Here we use the analysis of economic growth in key counties for poverty-stricken rural residents per capita net income to reflect the poverty rate in key counties with poverty rates of poverty and low-income sum to reflect the proportion of the population. Because then put on public spending does not necessarily have immediate effect, so we also had no significant effect when the one-year lag variables look at its effects, such as ln (ygdz) (-1) indicates one-year lag FFW (see Table 1).
Model 1 adjusted R2 value larger than the model fitting described good results. The coefficients of the explanatory variables is indicative promote farmers' per capita net income increase, is that we want to see results. Government spending from the classification see poverty, pro-poor development funds to promote farmers 'per capita income increased 99% confidence level for each 1% increase in pro-poor development funds can significantly increase farmers' per capita income increased 0.9289%. The FFW and subsidized loans after one year lag are statistically significant, the per capita income of farmers but did not play a role in promoting the improvement, it may be because FFW diminishing the quantity of investment in recent years, and to work on behalf of Relief is not necessary for the needs of farmers to provide their public infrastructure. Cai Fang, etc. (2001) [4] that the FFW project "Relief" is becoming increasingly weak demand from the local population, reduced to general infrastructure, so the key counties for poverty-stricken farmers per capita incomes but counterproductive . Subsidized loans may also be because of poor targeting, there is no real benefit poor farmers, so the per capita income of farmers increased also played a negative role. Reforestation special subsidy due to the direct payment to farmers, so the promotion of farmers per capita net income increase was significantly positively correlated. Table 1


Source: The author has been calculated finishing derived.
From the point of view toward poverty reduction spending, investment in agriculture and the secondary and tertiary industries poverty alleviation expenditure per capita net income of farmers increase was a significant positive correlation, the best investment in agriculture, increased by 1 per cent of agricultural investment in poverty alleviation can bring per capita net income of farmers increased 1.3017%, investment in infrastructure investment lagged one year after the income of the farmers are still not significant, which may be due to poor infrastructure still does not meet the real needs of farmers. In the 90% confidence level investment in technological culture, health poor spending lagged significantly after one year brings substantial increase in per capita income of farmers.


General government public spending, whether it is expenditure on agriculture or education and technology expenditures have contributed to increase the per capita income of farmers, and are positively correlated. Which the government's spending on education increased farmers' income the most significant, followed by agriculture and science and technology expenditures.


Farmers raised production expenditures per capita income of farmers with a significant positive correlation. Look from the farmer's own production conditions, and more able to increase revenue per capita arable land, population will reduce revenue, but in the statistical tests were not very significant. The average increase in labor can significantly improve the income of farmers. Increase the proportion of migrant labor can increase farmers' income, did not pass statistical tests, and have received professional training in the proportion of the labor force at the 95% confidence level increases can significantly improve the income of farmers. This shows that the rural labor export alone does not improve farmers' income, we must strengthen professional and technical training for farmers to enable them to benefit.
Farmers living conditions from the village to see, infrastructure can improve the income of farmers, but not statistically significant. This may be because in recent years, rural infrastructure such as electricity, access, telephone, a television in the village has a high proportion (about 90% basically), rural infrastructure construction has achieved great results, so the development of the increase farmers' income now is not so significant. At 95% confidence level village on the number of township enterprises to improve farmers' income is significant, because the village township enterprises to expand revenue streams, leading farmers to non-agricultural income. The village is agriculture and animal husbandry, such as new

本文标签: 经济增长贫困地区政府专项扶贫回归模型

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