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Modeling Land Competition Modeling Land Competition Modeling Land - - PowerPoint PPT Presentation

Modeling Land Competition Modeling Land Competition Modeling Land Competition Ron Sands Ron Sands Ron Sands Man- -Keun Keun Kim Kim Man Man-Keun Kim Joint Global Change Research Institute Joint Global Change Research Institute Joint


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SLIDE 1

Modeling Land Competition

Ron Sands Man-Keun Kim Joint Global Change Research Institute Battelle – PNNL – University of Maryland Energy Modeling Forum (EMF-22) Land Use Subgroup Tsukuba, Japan 12-14 December 2006

Modeling Land Competition Modeling Land Competition

Ron Sands Ron Sands Man Man-

  • Keun

Keun Kim Kim Joint Global Change Research Institute Joint Global Change Research Institute Battelle Battelle – – PNNL PNNL – – University of Maryland University of Maryland Energy Modeling Forum (EMF Energy Modeling Forum (EMF-

  • 22)

22) Land Use Subgroup Land Use Subgroup Tsukuba, Japan Tsukuba, Japan 12 12-

  • 14 December 2006

14 December 2006

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2

Acknowledgements Acknowledgements Acknowledgements

PNNL Colleagues

Jae Edmonds, Marshall Wise, Steve Smith Cesar Izaurralde, Allison Thomson

Kenny Gillingham Geoff Blanford

Statistics of land allocation mechanism Data for U.S. land classes

U.S. Environmental Protection Agency

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Objectives Objectives Objectives

Extend PNNL partial equilibrium land use framework to general equilibrium

Forestry identified as a priority model development item in review

  • f PNNL general equilibrium framework (Second Generation

Model) by U.S. EPA Science Advisory Board

What is the right level of abstraction for a recursive CGE model?

Forest dynamics Number of crops, animal products, forest products Geographic detail

Improve ability to simulate impact of carbon price on land use

Biofuel incentive Forest management (increased tree rotation age) Value carbon in unmanaged land

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Overview Overview Overview

Modeling Approaches

Forestry optimization Partial and general equilibrium economics

PNNL Agriculture and Land Use Model (AgLU)

Brief history Land allocation mechanism

Disaggregation of US region into land subregions Forest dynamics

Determination of optimal tree rotation age Carbon price and rotation age

Toward General Equilibrium Steady-state simulation Conclusions

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Modeling Approaches Modeling Approaches Modeling Approaches

Intertemporal Optimization

Typical for sector-specific models (e.g. forestry)

Intertemporal Equilibrium (perfect foresight)

Efficiency conditions (first order necessary conditions) from

intertemporal optimization model become system equations

Allows integration with other types of economic systems (such as

agriculture)

Recursive Equilibrium

Absence of look-ahead capability makes it difficult to model

forestry

Steady-State Equilibrium

Exploratory tool Steady-state modeling of forestry may be able to inform recursive

models

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partial general equilibrium equilibrium intertemporal

  • ptimization

TSM, FASOM Ramsey growth model intertemporal equilibrium AgLU 2 intertemporal CGE recursive equilibrium recursive CGE steady-state equilibrium AgLU 2x

Relationship to Specialized Forestry Models

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Brief History of AgLU Brief History of Brief History of AgLU AgLU

First version completed in 1996 Design

Top-down Partial equilibrium Can be run stand-alone or as part of MiniCAM

Studies

Role of biomass in carbon policy Impact of ENSO on North America U.S. climate impacts

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15-year Time Steps from 1990 through 2095 Land Allocation

Land owners compare economic returns across

crops, biomass, pasture, and future trees

Underlying probability distribution of yields per

hectare

Forest Dynamics

Trees in AgLU grow for 45 years Two forest markets (current and future) needed for

model stability

Methodology Highlights Methodology Highlights Methodology Highlights

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Products in AgLU Products in Products in AgLU AgLU

Crops (calories)

Rice and Wheat Coarse Grains Oil Crops Other Crops

Processed Crops (calories)

Vegetable Oils Sweeteners and Alcoholic Beverages

Animal Products (calories)

Beef and other Ruminant Livestock Pork and Poultry

Commercial Biomass (calories or metric tons) Forest Products (cubic meters)

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Food Consumption by AgLU Region

1,000 2,000 3,000 4,000 United States Canada OECD Europe Japan Australia and New Zealand Former Soviet Union China and Centrally Planned Asia Middle East Africa Latin America Other Asia Eastern Europe Korea India kcal per person per day Crops Processed Crops Animal Products

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AgLU Land Allocation AgLU Land Allocation AgLU Land Allocation

unmanaged pasture forest food coarse crops biomass grains grains crops

  • ther

crops

  • il
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Calculation of Land Shares Calculation of Land Shares Calculation of Land Shares

=

k k i i

s

λ λ

π π

1 1

Land share for land use i is an increasing function

  • f profit rate (lambda is

positive).

( )

i i i i

G P y − = π

Profit rate equals average yield times price received less non-land cost of production.

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Efficiency Condition Efficiency Condition Efficiency Condition

Price received for forest at harvest time must cover land rent over lifetime of tree plus cost of harvesting All terms are discounted to the present for comparison (intertemporal efficiency condition) AgLU approximation

( )

( )

forest forest forest forest

G P y r r − − + = ~ 1 1

45

π

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US Land Classes US Land Classes US Land Classes

Why Disaggregate?

Capture geographical heterogeneity Terrestrial mitigation opportunities vary by land class Climate impacts will vary by land class

Hydrologic Unit Areas (HUAs)

18 two-digit water basins in US Fixed location Useful for climate impact studies Link to water supply will be important for future work on water and potential

for biofuels

Base-Year Calibration

No unique way to calibrate base year (calibration is something of an art) Not easy to calibrate all of the following: land area by product and land

class, output by product and land class, prices, costs of production

Exact calibration doesn’t tell you where your model structure can be

improved

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Major Water Resource Regions

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Forest Area

0.0 10.0 20.0 30.0 40.0 50.0

New England Mid-Atlantic

  • S. Atlantic-Gulf

Great Lakes Ohio Tennessee Upper Mississippi Lower Mississippi Souris-Red-Rainy Missouri Arkansas-White-Red Texas Gulf Rio Grande Upper Colorado Lower Colorado Great Basin Pacific NW California

million hectares historical simulated

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SLIDE 17

Coarse Grains Area

0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0

New England Mid-Atlantic

  • S. Atlantic-Gulf

Great Lakes Ohio Tennessee Upper Mississippi Lower Mississippi Souris-Red-Rainy Missouri Arkansas-White-Red Texas Gulf Rio Grande Upper Colorado Lower Colorado Great Basin Pacific NW California

million hectares historical simulated

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Hay Area

0.0 1.0 2.0 3.0 4.0 5.0 6.0

New England Mid-Atlantic

  • S. Atlantic-Gulf

Great Lakes Ohio Tennessee Upper Mississippi Lower Mississippi Souris-Red-Rainy Missouri Arkansas-White-Red Texas Gulf Rio Grande Upper Colorado Lower Colorado Great Basin Pacific NW California

million hectares historical simulated

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Forest Dynamics Forest Dynamics Forest Dynamics

Tree growth curves vary across United States Calibration of growth curve to data provided through GTAP Response of forest production to carbon incentive

Optimal tree rotation age increases with carbon price Faustmann equation (modified by carbon incentive) is an extra

system equation paired with unknown rotation age

Modified Faustmann equation includes term that integrates carbon

stock or increment of carbon sequestered over tree growth curve

Can calculate carbon incentive either as a rental paid for carbon

storage or as full payment for increment sequestered

Computational burden can be reduced by selecting functional form

for tree growth curve that has closed-form integral

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200 400 600 800 1000

20 40 60 80 100 GTAP Yield C1 age^C2 exp(-C3*age)

Tree growth curve for southeastern pine plantations (yield in cubic meters as a function of tree age)

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200 400 600 800 1000 1200 1400 1600 1800 2000 20 40 60 80 100 GTAP Yield C1 age^C2 exp(-C3*age)

Tree growth curve for Pacific Northwest (yield in cubic meters as a function of tree age)

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LNPV with C Incentive

100 200 300 400 500 20 40 60 80 100 120 Age in years LNPV ($/ha)

Pc=0 Pc=50 Pc=100 Pc=150 Pc=200 Pc=250 Pc=300 Pc=350 Pc400

Levelized net present value per hectare at various carbon prices: southern pine plantation trees Assumptions: pt = $49 per cubic meter, cg = $1,000 per hectare, k = 0.2 metric tons carbon per cubic meter of wood, r = 3%, all stored carbon is released to the atmosphere at harvest

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Levelized net present value per hectare at various carbon prices: Pacific Northwest trees

LNPV with C Incentive

100 200 300 400 500 600 700 800 20 40 60 80 100 120 Age in years LNPV ($/ha)

Pc=0 Pc=50 Pc=100 Pc=150 Pc=200 Pc=250 Pc=300 Pc=350 Pc400

Assumptions: pt = $49 per cubic meter, cg = $750 per hectare, k = 0.2 metric tons carbon per cubic meter of wood, r = 3%, all stored carbon is released to the atmosphere at harvest

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Toward General Equilibrium Toward General Equilibrium Toward General Equilibrium

It is possible to embed partial-equilibrium AgLU in a CGE framework This demonstration combines AgLU for the US with an everything else (ETE) sector US (18 land classes) trades with composite Rest of World Approach is to combine system equations for AgLU with CGE system equations

Market clearing for labor and capital Market clearing for “everything else” sector Zero-profit condition for “everything else” sector

Benefits of CGE formulation

Utility-based consumer demand system Walras’ Law test helps find accounting errors Test model integrity by changing numeraire price and checking that

quantities remain unchanged

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Equation Unknowns Primary Agriculture Crop1: Food Grains market clearing price Crop2: Coarse Grains market clearing price Crop3: Oil Crops market clearing price Crop4: Other Food Crops market clearing price Crop5: Hay market clearing price Forestry market clearing price Other Products Processed Food market clearing price Feed1 market clearing price Pork/Poultry market clearing price Feed2 market clearing price Beef market clearing price Other Products Processed Food zero-profit condition

  • utput level

Feed1 zero-profit condition

  • utput level

Pork/Poultry zero-profit condition

  • utput level

Feed2 zero-profit condition

  • utput level

Beef zero-profit condition

  • utput level

ETE zero-profit condition

  • utput level

Primary Factors labor market clearing factor rental capital market clearing factor rental Dropped Equation (Walras' Law test) ETE market clearing numeraire price

AgLU-CGE: Equations that Solver must handle

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Steady-state land use simulation for the United States Steady Steady-

  • state land use simulation

state land use simulation for the United States for the United States

Land use at carbon prices up to US$400 per metric ton of carbon Scenarios

Carbon incentive for biofuel producers only Carbon incentive for biofuel producers and forest land

  • wners

Land prices increase with carbon incentive and the area of managed land increases How can we value the carbon stored in unmanaged land, especially unmanaged forests?

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50 100 150 200 250 300 350 400 450 500 50 100 150 200 250 300 350 400

Carbon pirce ($/ton) million ha

Croplands Biomass Mgd.Forest UnMgd.Forest

Carbon incentive for biofuel producers only (US land use at various carbon prices)

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50 100 150 200 250 300 350 400 450 500 50 100 150 200 250 300 350 400

Carbon pirce ($/ton) million ha

Croplands Biomass Mgd.Forest UnMgd.Forest

Carbon incentive for biofuel producers and forest land owners (US land use at various carbon prices)

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Conclusions Conclusions Conclusions

Disaggregation of US into 18 subregions for agriculture and forest products supply

  • Works well but is data intensive
  • Base-year calibration: exact match to benchmark data at the country level, but

not necessarily for smaller land areas within country

Forest Dynamics

  • Optimal tree rotation age increases with carbon price
  • Endogenous tree rotation age is difficult to handle in recursive models, but the

forestry steady state is not difficult to calculate

Toward General Equilibrium

  • Keep track of equations and unknowns when adding land allocation

framework

  • Recursive models: Consider intermediate strategy of modeling forests in their

steady state

Complexity of Modeling Agriculture, Land Use and Forestry

  • This problem is hard!
  • How can we simplify yet maintain key interactions?

Key Remaining Issues

  • Tropical forests and deforestation
  • Valuing carbon in unmanaged land
  • Role of water in limiting agricultural and biofuel production