This document summarizes IFRI-related activities at the University of North Carolina at Chapel Hill, including a 3ie-funded project on forest sector decentralization outcomes in Tanzania from 2011-2014 led by UNC, TFCG, and the University of Michigan. It also mentions a World Bank funded project on community forestry and REDD+ integration in Tanzania led by the University of Michigan. Finally, it provides details on Lauren Persha's current project "Is Tanzania’s Participatory Forest Management Program a Triple Win?" which uses a counterfactual, quasi-experimental research design to analyze the average effects and causal pathways of forest decentralization on livelihoods, governance, and forest conditions in Tanzania.

1. IFRI-related activities at
University of North Carolina at Chapel Hill
Lauren Persha
Department of Geography, Curriculum for the Environment and Ecology
University of North Carolina at Chapel Hill
lpersha@email.unc.edu
[IFRI SESYNC Workshop, Annapolis, MD; 28 October 2013.]
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2. IFRI-related activities at UNC
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3ie-funded project on forest sector decentralization outcomes in Tanzania
– 2011-2014
– UNC, TFCG, Umich
– Development & piloting of IFRI HH survey and data entry program
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World Bank funded project on Community Forestry and REDD+ integration
(Umich-led)
– 4 CBFM sites in Tanzania, among others
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IFRI-related pubs:
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Social and Ecological Synergy: Local Rulemaking, Forest Livelihoods and Biodiversity Conservation
(Persha, Agrawal & Chhatre, Science, 2011).
Elite capture risk and mitigation in forest governance regimes (Persha & Andersson, GEC, accepted
w/ minor revision).
Benefit-sharing in community forestry (Andersson et al, in prep).
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3. “Is Tanzania’s Participatory Forest Management Program a Triple Win?
Understanding Causal Pathways for Livelihoods, Governance & Forest Condition Impacts”
L. Persha (UNC, PI), C. Meshack (TFCG, co-I), A. Agrawal (U Michigan, co-I),
Counterfactual, quasi-experimental research design
• 130 sites (forest+village), balanced across PFM treatment & controls
• Matching across pre-T confounders that bias where PFM is implemented in Tz
• Data Collection Methods:
• HH survey (N ~4,000),
• group discussions w/ village institutions (N~130),
• semi-structured key informant interviews,
• plot-based forest sampling (N~130)
• Analyses focus on:
• Average effects of decentralization on Livelihoods, Governance, Forest
Conditions policy objectives (ATT);
• Outcome heterogeneity;
• Causal mechanisms.
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