1. 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

2. 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)

3. Model • Base year: 2007 • Steady-state forestry model links to the CGE • NZ—small open economy • 12 sectors, 5 types of land, factors (labor, capital) are mobile among sectors, land is mobile among 5 land-used sectors, joint production • one household, government, enterprise, investment-savings, rest of world • Four carbon tax scenarios ($0, $25, $50, $100)

4. Sectors Land-used sectors

5. 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 forester’s profit () • [Steady-state: equalized annual profit]

6. CGE production • Three-level nesting, Leontief function at the top level and between domestic and imported • Allow substitution between value-added input Sector Leontief Intermediate Value-added CES Leontief Import Labor Domestic Capital

7. Land allocation • Five types of land; assuming a composite land used in the sector production. The Armington substitution (CET) is allowed for land allocation

8. 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)

9. 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

10. 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)

11. Results - Forestry

12. Results - Land price change Land price is increasing due to the strong demand. Forestry land increases the most.

13. Results - Forestland change

14. Results-Other land change

15. Results-grassland change

16. Results-scrubland change

17. Results-cropland

20. Commodity price

22. 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

23. 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 β 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.

24. 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 (, , )

25. Appendix -equations

27. Market clearing • Commodity market:

28. Market clearing • Factor market