Benefits and costs of deforestation: implications for climate policy Oscar Cacho AARES Conference 215 SCION Pre-conference workshop on Forest Ecosystem Services This study was funded by ACIAR Project FST/27/52 Improving Governance, Policy and Institutional Arrangements to Reduce Emissions from Deforestation and Degradation (REDD)
This presentation is largely based on the paper: Cacho, O.J., Milne, S., Gonzalez, R. and Tacconi, L. 214. Benefits and costs of deforestation by smallholders: Implications for forest conservation and climate policy. Ecological Economics. 17: 321 332. With some updates from more recent analyses 2
The Economist June 29th 213 3
The Problem - Deforestation Conservation of tropical forests is particularly complex because: 1. Tropical forests contain high concentrations of both biodiversity and carbon, but their exploitation can be highly profitable 2. Much of the land in the tropics is managed by semi-subsistence farmers and shifting cultivators 3. Poor governance and corruption are prevalent 4
Deforestation reduces the quantity and quality of ecosystem services Schemes such as REDD+ and various forms of PES provide funding to conserve forest carbon, but their effectiveness depends on the willingness of forest residents to participate 5
Case Study Rokan Hilir (Sinaboi) Siak (Dayun) Riau Province, Sumatra Riau has suffered one of the highest rates of deforestation in Indonesia ~65% of its original forest cover was lost between 1982 and 27.
Cumulative area converted (ha) Conversion to oil palm Dayun Sinaboi 25 2 15 1 5 198 1985 199 1995 2 25 21 215 Year 7
Carbon losses from peat forest conversion to oil palm over 25 years Source Mg C / ha Ceasing peat accumulation in forest 19 6 Burnt peat from land-clearing fires 1 5 Change in biomass C stocks 156 39 Peat C loss in oil-palm plantation 131 28 Total 45 7 =1,486 Mg CO 2 Source: Murdiyarso et al. (21) PNAS 8
Opportunity cost and abatement cost opportunity cost ($/ha) abatement cost A C NB C O F NB C O F $ CO 2 e emissions from deforestation (CO 2 e/ha) NB i = net benefit per ha (benefit - cost) C i = CO 2 stock per ha O = oil palm F = forest 9
The Marginal Abatement Cost (MAC) curve is derived by aggregating the abatement costs of individual farmers* * With the data sorted by increasing value of abatement cost (A C ) 1
Probability Probability Calibrating the model 1.8 (A) 1.8 (B).6.6.4.4.2.2 Norm (.25, 6.82) Lognorm (7.15,.19) -2-1 1 2 5 1 15 2 25 Yield deviation FFB Price (IDR/kg) 1.8 (C) 1.8 (D).6.6.4.4.2 Lognorm (1.62,.64) 1 2 3 Farm area (ha).2 Lognorm (-.57,.65) 1 2 3 4 Adults / ha 11
Measures of performance 14 12 1 (A) Mean: 78M Rp Median: 73M Rp 25 2 (B) Mean: 4,683 Median: 3,774 8 15 6 1 4 2 5 2 15 1-1 1 2 3 4 NVP (Rp1,/ha) x 1 5 5 (C) Mean: 38,688/pd Median: 39,348/pd -5 5 1 15 Return to labour (Rp1,/pd) 7 6 5 4 3 2 1.5 1 1.5 2 2.5 3 Emissions (tco2e/farm) x 1 4 (D) Mean: 6 Median: 5 5 1 15 2 25 3 Years to positive cash flow 12
Carbon price ($/tco 2 e) Marginal abatement cost curves 1 9 8 7 6 5 4 3 2 1 mineral peat 1 2 3 4 5 6 7 8 9 1 Emissions avoided (Mt CO 2 e) 13
Carbon price ($/tco 2 e) Marginal abatement cost curves 1 9 8 7 6 5 4 3 2 mineral b peat a 1 c 1 2 3 4 5 6 7 8 9 1 Emissions avoided (Mt CO 2 e) 14
WTA ($/ha) Willingness to Accept (WTA) payment 4, 35, 3, 25, 2, 15, 1, 5,.1.2.3.4.5.6.7 Proportion of farmers 15
WTA ($/ha) Willingness to Accept (WTA) payment 4, 35, 3, 25, NPV (5%) 2, 15, 1, NPV (14%) 5,.1.2.3.4.5.6.7 Proportion of farmers 16
Carbon price ($/tco 2 e) C price required based on soil type 5 mineral 45 4 35 3 25 peat 2 15 1 5.1.2.3.4.5.6.7 Proportion of farmers 17
Willingness to Accept (WTA) - probability Probability that farmer will accept payment to keep forest* farmer's age people per ha farm area years since plot was planted years living in area household size income from agriculture -3-2.5-2 -1.5-1 -.5.5 1 1.5 Elasticity of WTA probability *Only significant coefficients in Probit regression are shown 18
Willingness to Accept (WTA) - probability Probability that farmer will accept payment to keep forest* obtained land as forest no subsistence activities had to clear land -.7 -.6 -.5 -.4 -.3 -.2 -.1.1.2 Change in WTA probability *Only significant coefficients in Probit regression are shown 19
Willingness to Accept (WTA) - amount Payment requested by farmer to keep forest* years since plot was planted dependency ratio obtained land as forest income from agriculture -1 -.5.5 1 1.5 2 Elasticity of WTA amount *Only significant coefficients in OLS regression are shown 2
Concluding comments MAC curves are useful tools in the design of climate policies Their application to PES schemes for forest conservation requires knowledge of opportunity costs faced by individual landholders. Carbon payments required to conserve forest may be higher than suggested by opportunity cost calculations for a number of reasons to be discussed another time 21