albert park, university of michigan sangui wang, chinese academy of agricultural sciences
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PRELIMINARY FINDINGS FOR DISCUSSION ONLY PLEASE DO NOT CITE OR CIRCULATE. Community-based Development and Poverty Alleviation An Evaluation of China’s Poor Village Investment Program. Albert Park, University of Michigan Sangui Wang, Chinese Academy of Agricultural Sciences. - PowerPoint PPT PresentationTRANSCRIPT
Albert Park, University of MichiganSangui Wang, Chinese Academy of Agricultural Sciences
Community-based Development and Poverty Alleviation An Evaluation of China’s Poor Village Investment Program
PRELIMINARY FINDINGS FOR DISCUSSION ONLYPLEASE DO NOT CITE OR CIRCULATE
Community-based developmentMotivation
Definition: “an umbrella term for projects that actively include beneficiaries in their design and management” (Mansuri and Rao, 2004)
Increasing popular model for development assistance: World Bank lending to community-based development
projects increased from $325 million ($2 billion) in 1996 to $3 billion ($7 billion) in 2003 (Mansuri and Rao, 2004).
By 2001, the WB had financed more than 98 social fund projects in 58 countries (Rawlings and Schady, 2002).
But, relatively few cases of local government-led efforts (Chile SF).
Community-based developmentIssues
Increasing popularity of CBD reflects growing belief that sound governance and local accountability are keys to project success (e.g., World Bank, 1999; Easterly 2002)
Many have assumed that decentralization/participatory decision-making improves targeting and impact, although empirical evidence remains limited and mixed
Key issue is whether local elites capture such processes and whether they favor rich or poor, but lack of empirical evidence (Bardhan and Mookherjee, 2005 and 2000)
Growing body of research finds that local governance, and inequality/heterogeneity affects projects chosen, and the amount and quality of public goods (Araujo et al., 2005; Foster and Rosenzweig, 2003; Khwaja, 2004; Besley, Pande, and Rao, 2005)
Community-based developmentPrevious evaluations of community-based development programs Some studies find community-based schemes effectively
target the poor: Galasso and Ravallion (2005): community targeting of
Bangladesh education subsidies were pro-poor but worse with greater land inequality or remoteness
Alderman (2002): communities in Albania targeted better than the center could do using proxy means targeting
Pradhan and Rawlings (2002): Nicaragua social fund was well-targeted to poor
But others find the opposite: Rao and Ibanez (2005): Jamaica social fund did not pick
projects favored by the poor but poor were relatively satisfied with project results
Chase (2002) and Paxson and Schady (2002) find that targeting withing communities in Armenia and Peru were not well-targeted toward the poor
World Bank (2002): review of social fund projects concluded that within-community targeting of poor not very effective
No studies use panel household data or examine the effect of public investments on measurable welfare outcomes (e.g., income and consumption)
Evaluating China’s poor village investment programContributions
First quantitative evaluation of the largest community-based development program and largest targeted poverty investment program in the developing world
First evaluation of the effect of community-based development programs on household welfare using panel data
First empirical evidence on relationship between participatory programs and targeting of income and consumption benefits of public investment projects
New evidence on the relationship between governance factors and the benefits of participatory schemes
Research questions
1. To what extent did the program increase public investments in targeted villages?
2. What were the impacts of the program on household income and consumption growth and poverty?
3. How did the investment program affect the propensity of rural laborers to out-migrate?
4. To what extent did governance factors (elite capture, quality of village government, household heterogeneity) mediate program impacts?
Data
2005 World Bank-National Bureau of Statistics village-level survey Sample includes 3036 villages in all poor counties
(199) and one third of non-poor counties (187) in the NBS national rural household survey sample
2004 and 2001 NBS rural household survey data in the same villages10 households per villageNearly all of the households (97 percent) are the
same in 2001 and 2004, enabling construction of a panel dataset
Sample of designated poor villages includes 666 villages and 5500 households (w/panel data)
China’s Poor Village Integrated Development ProgramKey program features
Shift from county targeting to village targeting in 2001, 148,000 villages (21% of all villages) designated as poor
Each village designs integrated investment plan (with participatory component) to coordinate targeted poverty investments from different sub-programs managed by different agencies:
Subsidized Loans by the Agricultural Bank of China Food for Work by National Development Reform
Commission Budgetary Grants by Ministry of Finance
Village selection and plan development were coordinated by of Offices of the inter-ministerial Leading Groups for Poor Area Development at different government levels.
A key goal of the new strategy was to improve targeting and concentrate resources for poverty alleviation in an integrated fashion
Spending on government poverty alleviation programs: 2001-2004…
A large amount of resources are committed to the official poverty reduction programs, accounting for 5-6% of the central government budget
(billion Yuan)
YearSubsidized
loansFood for
workBudgetary
funds Total
2001 18.5 6.0 6.0 30.52002 18.5 6.0 6.6 31.12003 18.5 6.0 7.4 31.92004 18.5 6.0 8.2 32.7
Total 74.0 24.0 28.2 126.2Source: LGOPAD and MOF
What was the process of designation of poor villages? … A Formula-based Approach
A Weighted Poverty Index (WPI) was used to rank villages based on eight indicators
In practice, the local governments were allowed to change some of the indicators and weights on indicators based on local circumstances (decided through participatory approach)
Substantial mistargeting when evaluated solely using income and consumption data
Grain production/person/year
Cash income/person/year % of poor quality houses % of households with
difficulty of access to potable water
% of natural villages with access to reliable electricity supply
% of natural villages with an all-weather road access to county town
% of women with long-term health problems
% of eligible children not attending school
Regional distribution of poor villages … A Formula-based Approach
RegionTotal no.
of villages
No. ofdesignated
poorvillages
% ofvillages
designatedpoor
Share ofpoor
villages(%)
Coastal 249723 20698 8.3 14.0
Northeast 35540 9182 25.8 6.2
Central 225964 48950 21.7 33.0
Southwest 132879 42647 32.1 28.8
Northwest 65151 26654 40.9 18.0
Total 709257 148131 20.9 100.0Source: LGOPAD
The village planning process, in principle From official guidelines provided to local governments
Principles Projects helping the poor should be favored
Participation of households and different groups (e.g. women) should be emphasized
Plans should integrate resources from different sources to maximize efficiency
Plans should be for 3-5 year time horizon and reflect local conditions and causes of poverty
Plans should follow standardized procedure set by county government for easier management and integration
The village planning process, in principle From official guidelines provided to local governments
Procedures Analyze causes of poverty and project solutions, based on
analysis of village-level data and participatory workshops with 10-20 villagers
With support of technicians, conduct SWOT (Strength, Weakness, Opportunity and Threat) and feasibility analysis to help villagers and leaders gain a better understanding of the potential gap between demand and supply as well as potential impacts
More detailed assessment of project beneficiaries, project requirements, including technical and other support, and project implementation (annual schedule, including budget and labor allocations, monitoring and evaluation)
Selection of projects by a vote of entire village
The village planning process, in practice From field visits and interviews with staff of Poor Area Development Offices
Most official guidelines not followed, especially with regard to participatory methods
Plans often designed by village committees, small group (hamlet) leaders, party representatives, and representatives of households, with help of a township government official (trained by county Poor Area Development Office staff)
County poor area development offices could not “treat” all villages at once because of staff and budget constraints
Plan amounts often far exceeded actual financing, because funds from some programs were not coordinated with plans. Field research found that subsidized loans rarely went toward village plans and Food-for-Work projects sometimes did
By the end of 2004, 55% of poor villages had completed village plans and 37% of poor villages had begun investments based on the plans
LGOPAD reports that a higher percentage (83%) of poor villages completed village plans, but a lower percentage (32%) of poor villages began plan investment
0
10
20
30
40
50
60
2001 2002 2003 2004
%
Poor villages completed plans
Poor villages beginning plan investments
Has village planning been fully implemented?Percent of poor villages completing plan and starting investments based on the plans
Source: World Bank-NBS Special Purpose Survey
Matching methodology
Estimate average treatment effect on the treated, matching control observation to the treated sample
Matching method: weighted nearest neighbors (3 matches per treated observation), with enforcement of exact matching by province (nearly 100 percent)
Propensity scores from logit estimation are used to determine common support, trimming rules
Matching variables: time-invariant or measured prior to start of program.
Common support?Distribution of propensity scores (logit model) for designated poor villages that began program investments and matched poor villages that did not begin investments
0 .2 .4 .6 .8 1Propensity Score
Untreated Treated: On supportTreated: Off support
To what extent did the program increase public investments in targeted villages?
Sources of investment finance: Government finance
Village funds
Village corvee labor
Other
Factors affecting village investments Matching requirements
Complementary investment opportunities
Substitution
Questions: How much did the program increase government investment in projects
in light of coordination problems and potential substitution? Were government poverty investments complements or substitutes for
villages’ own investments?
Impact of program on change in log(investment per capita) Village matching estimates
Financing source All China West Non-west
Total investment ***2.23(0.539)
***1.54(0.345)
***3.70(1.23)
Total monetary investment ***1.38(0.285)
***1.46(0.331)
***1.37(0.548)
Govt monetary investment ***0.99(0.204)
***1.13(0.313)
***0.85(0.284)
Village monetary investment ***0.64(0.232)
0.07(0.179)
***1.43(0.510)
Corvee labor days -0.19(0.164)
**-0.66(0.320)
**0.38(0.172)
N 588 373 215
Impacts on household income and consumption growth and poverty
Main goal of the poor village investment is to reduce poverty
However, evaluation of impacts on income and consumption is likely to understate program benefits
Most “treatment” villages have not completed plans
There may be lag in program benefits
Health and education benefits not captured
Identification of effects on rich and poor: Within-village estimators of effects on rich and poor (defined
by 2001 median income per capita)
Comparison of restricted (villages with both rich and poor households) and unrestricted samples
Impacts on share of labor that migrates
Motivating concerns Concern that poor are not being included in the benefits
of China’s rapid structural change
Concern about congestion effects of high migration rates
Tension between strategies to raise local productivity or facilitate out-migration?
Ambiguity over predicted effects of different infrastructure investments
Impact on household income, consumption, and migration Village matching estimates
∆ln(inc. pc) ∆ln(cons. pc) ∆migration-share
All villages
All 0.030(0.031)
588
0.010(0.029)
588
-0.025(0.017)
588
Poor -0.039(0.062)
552
0.001(0.042)
552
-0.005(0.018)
552
Rich *0.066(0.035)
484
**0.088(0.036)
484
***-0.052(0.018)
484
Villages with both poor and rich households:
All 0.029(0.037)
448
0.054(0.039)
448
-0.031(0.019)
448
Poor -0.061(0.067)
448
0.006(0.045)
448
0.000(0.020)
448
Rich ***0.096(0.039)
448
***0.114(0.038)
448
**-0.047(0.019)
448
Discussion: why didn’t the poor benefit?
Possible explanations
Lack of capacity to take advantage of public investments
Lack of participation in village planning activities
Exclusion by elites
Governance and program impacts
Relationships of interest Did the program affect governance?
Did governance influence the magnitude or distribution of program benefits?
Governance variables (from principle components analysis)
Education of village leaders village secretary years of education
village mayor years of education
share of village committee members with middle school education or above
Quality of the village committee Number of members
Frequency of meetings
Heterogeneity in years of education of household heads
Impact of investment program on village governance in 2004 Village matching estimates
Governance outcome All China West Non-west
Education of leaders ***0.606(0.122)
***0.821(0.204)
***0.754(0.128)
Quality of village committee
0.069(0.099)
0.143(0.105)
-0.057(0.165)
N 583 371 212
Governance and program impacts on the rich and poor within villages Village matching estimates
Education of village leaders Quality of village committee
Low High Diff. Low High Diff.
mean
∆ln(inc. pc) Poor 0.073(0.059)
0.031(0.059)
-0.042 **-0.195(0.082)
0.130(0.096)
***0.325
Rich -0.048(0.072)
0.032(058)
0.080 0.052(0.053)
***0.409(0.070)
***0.357
Diff. -0.121 0.001 0.122 ***0.247 ***0.279 0.032
Mean
∆ln(con. pc) Poor 0.032(0.089)
***-0.121(0.047)
***-0.153 ***-0.159(0.058)
0.047(0.075)
***0.206
Rich -0.057(0.069)
0.023(0.038)
0.080 0.057(0.044)
***0.300(0.059)
***0.243
Diff. -0.089 ***0.144 ***0.233 ***0.216 ***0.253 0.037
Village heterogeneity and program impacts on the rich and poor within villages Village matching estimates
Village heterogeneity in years of education of household heads (Theil index)
Low High Diff.
mean
∆ln(inc. pc) Poor -0.018(0.096)
**-0.126(0.054)
-0.108
Rich 0.037(0.049)
0.033(0.033)
-0.004
Diff. 0.055 0.159 0.104
Mean
∆ln(con. pc) Poor ***0.143 (0.049)
**-0.081(0.040)
-0.224
Rich ***0.199(0.048)
*0.079(0.047)
-0.120
Diff. 0.056 0.160 0.124
Conclusions
There is no evidence that participatory village plans have helped the poor to benefit more from targeted investments or reduced rural poverty in China
Governance factors affect the amount and distribution of benefits under decentralized/participatory decision-making
The relative benefits accruing to the rich increase with the education of village leaders
Greater benefits for both rich and poor increase are associated with high quality village committees
The poor are particularly disadvantaged in more heterogeneous communities (w.r.t. educational attainment)
Priority to improve the design and implementation of the program