精准扶贫政策效果评估——基于贫困人口微观追踪数据

Impact of Targeted Poverty Alleviation:Micro Tracking Data of Poor Populations

本文基于贫困人口微观追踪数据,采用模糊断点回归的方法,评估了“十三五”精准扶贫新政策对贫困户劳动收入和劳动供给的短期影响,并讨论了具体的影响机制。研究发现精准扶贫新政策:(1)显著提高了贫困户的劳动收入;(2)2016—2018年劳动收入效应的主要来源由劳动时间增加转向劳动生产率提升;(3)在前期对男性劳动供给的促进作用大于女性,不过从长期发展趋势来看,带动女性参与劳动的潜力更大。机制分析表明,易地搬迁和产业扶贫是贫困户劳动供给增加的主要渠道,而光伏扶贫对劳动供给的影响呈现负激励,削弱了其他政策的减贫效果。微观数据评估结果表明,精准扶贫新政策总体上增加了贫困户的劳动供给和收入,具体政策的减贫效果存在差异。这些发现对优化扶贫政策具有参考价值。

To end extreme poverty sustainably and as quickly as possible,the Chinese government initiated the Target Poverty Alleviation Strategy(TPA)at the end of 2013 and established a poverty registry system.Through county officials'regular home visits,individual-and household-level data are continuously gathered from poor households.The policy benefits for these households include cash or in-kind transfers—such as rural minimum living standard guarantee(Dibao)and ecological compensation—and expenditure reduction policies—such as free agricultural,life,and medical insurance,free electricity,and college subsidies.Since 2016,or“The Thirteenth Five-Year Plan”,a series of new policies,including industrial poverty alleviation programs,Relocating the Poor(RTP),and the photovoltaic poverty alleviation project(PV),were introduced into the existing welfare system.The focus of these new policies shifted from direct transfer to active labor market stimulation.The industrial poverty alleviation policies encourage private enterprises to employ poor residents via subsidies,or directly reward poor residents who develop agricultural products and breeding industries.With the TPA coming to an end in 2020,the timely evaluation of and quantitative feedback on the new policy package are of great significance to policy makers seeking to optimize the poverty alleviation system.We show that these new policies are likely to target still poor families—that is,families whose incomes are still lower than the government's official poverty line—which provides us an excellent opportunity to estimate the causal effects of the poverty alleviation program with a regression discontinuity(RD)design.We use micro administrative data from a typical poverty-stricken county whose poverty rate,economy development level,industrial infrastructure,and urban rate are around the median level of all poverty-stricken counties.We use a fuzzy regression discontinuity method to examine the likelihood of poor families,as the beneficiaries of these new policies,overcoming the poverty hurdle.We mainly focus on these poor families'labor income and labor supply decisions.Our dataset consists of approximately 12,000 households and 43,000 individuals.The administrative datasets contain income-related variables—such as annual income,wage,working time,and poverty status—and family demographics variables—such as disability status,education level,family structure,and house location.We find the following results.(1)The TPA policies significantly increase poor families'per capita labor income.(2)During 2016-2018,the main source of the TPA policies'income effect changed from the increase in labor supply to labor productivity.(3)The increase in working hours comes mainly from male workers,but the amplifying effect in 2017 comes mainly from female workers.(4)In the TPA new policy package,the active labor market policies,like RTP and the industrial poverty alleviation programs,significantly increase poor families'labor supply,whereas the direct transfer programs,like PV,have a negative impact on labor supply and weaken the poverty reduction effect of other policies.Our study makes several contributions to the literature on anti-poverty alleviation.We use large micro administrative data from a single but typical county covering the poor population from 2015 to 2018.This dataset complements the survey data,which have a much smaller sample size,and overcomes the estimation bias caused by unobservable heterogeneous factors in cross-regional analysis.Our study also has strong policy implications.Our findings indicate that the active labor market policies have effectively activated the latent labor dividend in rural areas in the short term,and that it is important to further enhance the human capital accumulation via the design of incentive mechanisms.This study's findings are useful for the design and assessment of anti-poverty policy.