Table 2. Inputs and sources of uncertainty in profit assessment and methods by which uncertainty is dealt with in this study.

Input Source of uncertainty Method to deal with uncertainty Values used
Project risk Uncertain impact and success of project A nontradable buffer of emission reductions is set aside to deal with leakage (Sohngen and Brown 2004) and nonpermanence (Sedjo and Marland 2003). Under high project risks faced in the Bale Mountains, 25% of emission reductions are set aside for leakage and 40% for permanence nondelivery risk.
 
Carbon price Subjective judgment,
variability
Best guesses of over-the-counter voluntary carbon market prices are made given lack of price trends and the unclear future role of forestry emission reductions in climate policy.
 
The sensitivity to market price is assessed by modeling two carbon market prices: US$3/tCO2e and US$6/tCO2e.
 
Implementation costs Subjective judgment,
variability
Expert judgment of the implementing agencies in the Bale Mountains generated realistic cost estimates as implementation and transaction costs of REDD are often high and underappreciated (Grieg-Gran 2006, Antinori and Sathaye 2007, Nepstad et al. 2007, Boucher 2008, Böttcher et al. 2009). Brokerage costs of 2.5% of emission reductions; registry costs of US$0.1/tCO2e; one-off costs of US$3,225,000 to establish participatory forest management; and annual costs of US$650,000, as predicted by UNIQUE (2010).
 
Discount rate Subjective judgment,
variability
The choice of discount rate follows best practice in environmental cost-benefit analysis and forestry (Weitzman 1998, Pearce et al. 2003, Groom et al. 2005, Hepburn and Koundouri 2007). The sensitivity to discount rate is shown by modeling discount rates of both 5% and 10% following Greig-Gran (2006) of the Stern Review (Stern 2007).