Land use change between forestry and agriculture under
Land use change between forestry and agriculture under the NZ ETS Author: Yue Wang Co-authors: Stephen Poletti, Golbon Zakeri, Joon Hwan(John) Kim, Basil Sharp Motivation How does the NZ ETS effect land use change between forestry and agricultural sectors? ETS is a key pillar approach to NZ climate change Largest emissions come from agriculture, forestry sequestrate carbon and was first enter into the ETS(MPI, 2012) Model Base year: 2007 Steady-state forestry model links to the CGE NZsmall open economy 12 sectors, 5 types of land, factors (labor, capital) are mobile among sectors, land is mobile among 5 landused sectors, joint production one household, government, enterprise, investmentsavings, rest of world Four carbon tax scenarios ($0, $25, $50, $100) Sectors Land-used sectors Forestry Model is based on Sands & Kim (2009), Van Kooten et al. (1995) Select the NZ pruned without thinning radiate pine Biomass timber yield function:
: shape parameter a: rotation age Derive the optimal rotation age by maximizing foresters profit () [Steady-state: equalized annual profit] CGE production Three-level nesting, Leontief function at the top level and between domestic and imported Sector Leontief Intermediate Value-added CES Leontief Domestic Import Capital Allow substitution between value-added input Labor Land allocation Five types of land; assuming a composite land used in the sector production. The Armington substitution (CET) is allowed for land allocation Rest of world
Domestic consumption: domestic output and imported goods (CET) The exchange rate is endogenous, world price is exogenous Foreign savings are exogenous Export consumption: exported output and domestic commodities (CET) Agents Representative household: maximize utility, using the Linear expenditure system (LES) to seek the optimal level of commodity demand Government: Supply capital, collect tax from production, income, carbon emission, Leontief consumption Investment-Savings: Johanson macro-closure; exogenous investment and endogenous savings Enterprise: capital supplier Market clearing: both factor and commodity markets clear Data The National Exotic Forest Description (NEFD) (MPI, 2011) is used for estimating the shape parameters in biomass timber yield c1: 0.075316; c2: 3.227245; c3: 0.06344, convert factor 0.86 metric tons CO2-e per cubic meter of wood, pickling factor is 0 Interest rate is constant of 0.08, the initial timber price is set as the average export price of log per JAS m3 f.o.b. $187
March 2007 Supply-use table, Agribase and LCDB v2 for land hectares MPSGE language (mathematical programming system for general equilibrium) Results - Forestry Rotation Age 22.5 22 21.5 21 20.5 20 19.5 19 18.5 18 pc=0 Timber Yield tonne/ha 400 rotation age 200 100 0 pc=0 pc=25 pc=50 200 15000 10000 195 5000
1.678 LCrop Land price is increasing due to the strong demand. Forestry land increases the most. Results - Forestland change Forest Land Use Change (value) 300 million $/ha 250 200 pc=0 150 pc=25 100 pc=50 50 pc=100 0 Horticulture and fruit growing Sheep-beef Dairy Other agriculture Forestry Industry demand Forest land demand by ind (hectares) Forestland use by ind/total Forestland hectares
pc=0 Horticulture and fruit growing pc=25 pc=50 pc=100 0% 0% 0% 0% 42% 3% 1% 0% Dairy 6% 0% 0% 0% Other agriculture 2% 0% 0% 0% 50%
96% 99% 100% Sheep-beef Forestry Results-Other land change Other Land Use Change (value) 70 million $/ha 60 50 pc=0 40 pc=25 30 pc=50 20 pc=100 10 0 Horticulture and fruit growing Sheep-beef Dairy Other agriculture Forestry Industry demand
Otherland demand by ind (hectares) Horticulture and fruit growing Otherland use by ind/total otherland hectares 1% 0% 0% 0% 91% 62% 30% 9% Dairy 4% 2% 1% 0% Other agriculture 3% 1% 0% 0% Forestry 2%
34% 69% 91% Sheep-beef Results-grassland change million $/ha Grassland Use Change (value) 800 700 600 500 400 300 200 100 0 Horticulture and fruit growing pc=0 pc=25 pc=50 pc=100 Sheep-beef Dairy Other agriculture Forestry Industry demand Grassland demand by ind (hectares) Horticulture and fruit growing Grassland use by ind/total grassland hectares 0%
Scrubland Use Change (value) 160 140 million $/ha 120 100 pc=0 pc=25 pc=50 pc=100 80 60 40 20 0 Horticulture and fruit growing Sheep-beef Dairy Other agriculture Forestry Industry demand Scrubland demand by ind (hectares) Scrubland use by ind/total scrubland hectares Horticulture and fruit growing Sheep-beef Dairy Other agriculture Forestry 0% 84% 4% 3% 9% 0% 26%
1% 1% 73% 0% 8% 0% 0% 92% 0% 2% 0% 0% 98% Results-cropland Cropland Use Change (value) 90 80 million $/ha 70 60 pc=0 pc=25 pc=50 pc=100 50 40 30 20 10 0 Horticulture and fruit growing Sheep-beef Dairy Other agriculture Forestry
Industry demand Cropland demand by ind (hectares) pc=0 pc=25 pc=50 pc=100 Cropland use by ind/total cropland hectares Horticulture and fruit growing 17% 15% 12% 3% Sheep-beef 73% 71% 61% 36% Dairy 7% 6% 4% 0% Other agriculture 3%
772.826 35393.46 35086.39 35012.41 35365.46 6.999 6.889 6.853 6.787 178.018 179.53 179.968 185.91 9532.22 9611.594 9633.297 9627.454 Future work Contribution: First linking the steady state forestry model to the CGE for analyzing the land use change in NZ study. Results are more comprehensive. Future work: Estimation of the market clear domestic carbon credit (NZU) price Appendix I (Forestry carbon payment) Forester pays liability for harvested trees but receive the return for carbon sequestration from growing trees Annual carbon sequestration payment: Carbon emission amount: Where is pickling factor, implies how much carbon would be sunk into the wood permanently; is amount of the harvested tree each year from the beginning to rotation age a. Appendix II (Timber
production) Due to the biomass timber yield function, we assume a Leontief function for timber production (). Harvested timber production is used as the intermediate for other industries (), determined by the Leontief coefficient (, , ) Appendix -equations Market clearing Commodity market: Market clearing Factor market
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