PEN in Uganda CIFOR, March 2009 Pam Jagger, Workshop in Political Theory and Policy Analysis School of Public and Environmental Affairs, Indiana University
I. Context • Tropical high forest • Altitudes between 1000-1800 m.a.s.l. • 1000; 700; 800 sq. kms • Villages (n=18) • Range: 43 to 244 (avg.=118) • Households (n=540) • Avg. hhd size 6.0 • Variability: • Market access • Ethnic diversity • Migrant populations Lake Albert
II. Household incomes sources 1 USD = 1817 UgShs.
III. Income sources and seasonality • Forest and env. product harvest inc. when crop production down (Q1/Q3) • Forests support a lot of current consumption – but with critical nutrition implications
IV. Key forest and environmental products • How was pricing done: • Quarterly village level price surveys • Collection of conversion factor data so that average prices per standardized unit could be calculated • Collection of time use and average wage rate data on quarterly basis – but limited data on forest and environmental income harvesting
V. Income composition and poverty 1 USD = 1817 UgShs.
VI. Other patterns • Only 2 percent of households reported using forests to cope with shocks • Most common coping mechanisms: • Spend savings (21.4%) • Do nothing (18.2 %) • Help from friends (15.1 %) • Pathway out of poverty? • The relatively wealthy who cut timber are better off – but no evidence of the poor lifted into higher quintiles • Market access • Hard to make sense of data - + and - correlations
VII. Policies and overall findings • Policy mechanisms to substantively increase forest-based income for the poor are few and a challenge to implement • Forest sector governance reform has had a negative effect on both forest cover and the share of forest income for the poorest households • Forest fragmentation has implications for what we call “forest income” • Most surprising – how forest income has increased for wealthy households in Budongo (partially due to price increases)