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Do the poor benefit from forest devolution policies? Evidence from forest co-management in Malawi Charles Jumbe, PhD & Arild Angelsen, PhD Bunda College.

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Presentation on theme: "Do the poor benefit from forest devolution policies? Evidence from forest co-management in Malawi Charles Jumbe, PhD & Arild Angelsen, PhD Bunda College."— Presentation transcript:

1 Do the poor benefit from forest devolution policies? Evidence from forest co-management in Malawi Charles Jumbe, PhD & Arild Angelsen, PhD Bunda College of Agriculture Centre for Agricultural Research & Development P.O. Box 219, Lilongwe Malawi

2 Background Women’s popular trade  More than 90% of the 13 million people live in rural areas  Forests as a vital source of energy for cooking (5% with electricity)  Forests a source of income for people living within or adjacent to forests Men’s popular trade

3 The Context  For many years forest policies were restrictive  Forest cover continue to decline  From 59% of total land (9.4 mn ha) in 1960s  to 47% in the 1980s  to 37% by mid 1990s  to 27% currently (FAO, 2005)

4 Government’s response  National forestry policy (1996)  Forestry act (1997)  Key features  Removal of restrictions  Co-management of protected forest areas.  Emphasis on women’s participation in forest management

5 Forest Co-management Program  Designed as an experiment in 1996 in two sites, Chimaliro & Liwonde/Machinga Forest Reserves (WB &DfID)

6 Objectives of the Project  Improve forest management in return for increase access to forest products  Enhance contribution of forests to rural poverty reduction

7 Key distinguishing feature ChimaliroLiwonde Forest size (‘000 ha)160274 Co-area (ha)2101172 Resource stateDenseDegraded Forest Management governance GoodNot good Degree of forest dependence LowHigh EthnicityHomogeneousHeterogeneous Forest product markets UndevelopedHighly developed Pressure on forestsLowHigh Poverty rate45%74%

8 Purpose of Evaluation  Evaluating program effectiveness in harnessing the contribution of forests to poverty reduction  Identifying households adversely affected by the program - designing appropriate interventions  Draw lessons for designing future programs

9 Research Questions  Focus on vulnerable households- defined by participation, gender & poverty class 1. Does participation forest management address the plight of the poor as intended? 2. Who is capturing the rent >>> do the poor benefit?

10 Analytical Framework  Theoretical model  Roy’s self-selection model (Roy, 1951)  Choice whether to participate based on utility  Comparison of utility of participation & non-participation  Econometric methods  Endogenous switching regression model –to estimate forest income  Selection bias correction  Propensity score matching  Measure net gains of participating in the program  Overall program impact (full sample & across the two, Chimaliro & Liwonde)  Impact on vulnerable household (women & poor households)

11 Analytical framework (cont’d)  Decomposition Analyses  Estimate the extent of inequality in benefit sharing between groups of participants (Reimers, 1983)  Male-female income disparity  Poor-rich income disparity

12 Data sources  Part I: Participatory Rural Appraisal: Context Analysis & basic data collection (e.g., household list, persipectives of the program Part II: household survey: Random sampling of participants and non- participants Sample: Total sample 404; Chimaliro 205 & 199 Liwonde 199

13 What do raw data show-A synopsis? SampleP (MK)NP (MK)Differential(%) Full sample244.58431.23-43.28 Chimaliro37.4580.18-53.29 Liwonde442.80815.41-45.60 LOW-INCOME Full sample173.62292.05-40.55 Chimaliro38.9044.11-5.21 Liwonde318.86570.56-44.11 FEMALE Full sample223.55210.21+6.35 Chimaliro35.6843.11-17.23 Liwonde411.42386.11+6.56

14 Results from Matching techniques (impact) ResultsIncome gain (MK/household/month) % Change Overall (Pooled)16.82 - 18.02+47-51% Chimaliro (Site 1)12.14 - 12.37+90% Liwonde (Site 2)-161.48 - 281.76-(54)-(- 68%) Female- participants 15.59 - 29.36+13-65% Low-income13.52 - 27.58+35-68%

15 Decomposition Results: Identifying Sources of inequality in benefit sharing CaseWho benefits most from the program? Source of inequality Discrimination (Coefficients) Endowment (Variables) Male-femaleMale income: 16 % higher 100%- Rich-PoorRich: 23% higher40%60%

16 Summary of key findings  Does participation in the program lead to better outcomes?  Overall, there are marginal benefits to participants  The program drastically reduce forest revenue for participants in Liwonde (23% share of forest income)  Forest income for female & low-income households is enhanced by participating in the program Who captures the benefits of the program?  High-income & male participants!!  Discrimination against female participants.  Differences in endowments (e.g. education, experience, household assets) in favour of high- income participants

17 Key lessons & implications for policy  Forest co-management is not a panacea for addressing poverty in different socioeconomic conditions 1.Sensitive to the short-term needs of the local people  Complimentary interventions to provide alternative livelihood sources (e.g., where forests have low economic value) 2.Discrimination can have adverse affects the disadvantage group Conclusion: FCM has the potential of enhancing rural incomes Design gender & poverty-focussed devolution programs Eliminate capture by the elite Induce greater participation by vulnerable households Increase the allocation to be shared by the community 70% Government & 30% local community

18 Charlesjumbe@yahoo.com Land Economics. November 2006. 82 (4): 562–581


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