Calibration and Validation of Global Forest Products Model

(GFPM)

Joseph Buongiorno, Shushuai ZhuUniversity of Wisconsin - Madison

Acknowledgements

USDA Forest Service Southern Research Station

James Turner

Jeff Prestemon

Objectives

• Synchronize GFPM and FAO data cycles

• Correct data errors

• Reconcile data with theory

• Assist users with automated procedures

• Check predictions with observations

Methods

• DataFAOSTATWorld Bank World Development IndicatorsElasticities and other parameters

• CalibrationData smoothingStatic or dynamic calibration with data correction

• ValidationCheck data consistencyCompare data and solution

Data 1: FAO Statistics

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Data 2: World Bank WDI

Data 3: Forest Resource AssessmentExtent of forest and other wooded land 2010

Country/area

Land area

Inland water(1 000

ha)

Countryarea

(1 000 ha)

Forest Other wooded land Other land (1 000 ha)

1 000 ha% of

land area 1 000 ha% of

land area Total

of which with

tree cover

Angola 58480 47 0 0 66190 - 0 124670

Botswana 11351 20 34791 61 10531 - 1500 58173

Comoros 3 2 0 0 183 - 0 186

Djibouti 6 n.s. 220 9 2092 - 2 2320

Eritrea 1532 15 7153 71 1415 - 1660 11760

Ethiopia 12296 11 44650 41 52685 - 799 110430

Kenya 3467 6 28650 50 24797 10385 1123 58037

Lesotho 44 1 97 3 2894 - 0 3035

Madagascar 12553 22 15688 27 29913 - 550 58704

Malawi 3237 34 0 0 6171 - 2440 11848

GDP Price Year

Fuelwood-developing countries 0.05 -0.10

Fuelwood-developed countries 0.22 -0.10

Sawnwood 0.22 -0.10 -0.003

Standard error 0.03 0.02 0.001

Plywood & veneer 0.41 -0.29 -0.009

Standard error 0.04 0.02 0.002

Particleboard 0.54 -0.29 -0.006

Standard error 0.07 0.02 0.002

Fiberboard 0.35 -0.46 -0.002

Standard error 0.06 0.02 0.002

Newsprint 0.58 -0.25 -0.008

Standard error 0.04 0.02 0.001

Printing & Writing 0.45 -0.37 0.003

Standard error 0.03 0.02 0.001

Other paper & Paperboard 0.43 -0.23 -0.004

Standard error 0.03 0.02 0.001

Data 4: Elasticities of Demand

Calibration Goal = GFPM InputsGFPM

Spreadsheet

Content Calibration

Demand Initial condition+elasticities Yes

Supply Initial condition+elasticities Yes

Forest Initial condition+elasticities+ forest growth parameters

Yes

Manufacture I/O coefficients, costs Yes

Recycling Max recycling Yes

Transportation Initial import, export, cost Yes

ExogChange GDP growth and other changes No

Calibration Procedure

Smooth data (optional)

world price (net exporter)Local price =

world price + transport cost (net importer)

Then, for each country, simultaneously:Estimate I/O coefficients & manufacturing

costsCorrect data if needed

Goal Programming

Minimize (calibrated - reported production) +(calibrated - expected input)

Subject to:

– Observed imports, exports, and prices

– Prior bounds on:• I/O coefficients• Manufacturing costs• Recycling rates

Objective Function

2/1)()()1()(min jwiwi j

ijYijYβwiYi

iYβZ i

Deviationfrom reportedproduction

Deviation from expectedinput

Weight=world price

Deviation of estimated from reported production

Deviation of estimated from expected input

iiYiYiqiY 0

jiijYijYjYijaijY ,0

Reported production

Prior I/O coefficient

Material balance

Non-negative manufacturing cost

iiYiwjwjjiY 0

ixmYYj

iji 0ii

Import & export, given

Output valueInput cost

Feasible range of input i for output j

Feasible post-consumer recovery

jiUijajYijY

LijajY ,

iUijr

jjxjm

jijYjYiY

Lijr

jjxjm

jijYjY )()(

bounds on I/O coefficients

Paper consumption

Recovery bounds

Calculated I/O coefficient

jiY

YA

j

ijij ,

Dynamic Calibration

• Purpose: Smooth yearly change of I/O coefficients

• Method:– Static calibration for each last 3 years– “Average” of calibrated I/O coefficients, production,

imports, and prices

GFPM Calibration Interface

Post Calibration Data Checks

• Consumption = production + import – export

• Prices:Net Exporter=World Price

Net Importer=World Price + Transport Cost

• Manufacturing cost= Output Price – Input Costs

• Recovered paper >= consumed waste paper

Input Data Check Results

Inputmanufacturing cost

Algeriaplywood

Derivedmanufacturing cost

GFPM Validation - Base YearCheck predicted = calibrated:Demand

QuantityPrice

Supply Quantity

Price

Manufacturing QuantityPriceManufacturing cost

Net Trade

GFPM Validation - Base Year

Algeria

sawnwood price

consumption

Long Term validation

• Set base year (e.g. 1980)

• Set exogenous variables (e.g. 1980-1995)• GDP

• GDP/capita

• Compare predictions and observations

Industrial Roundwood Production

Actual (1980 - 1994) Projections (1980 - 1994)

0

400000

800000

1200000

1600000

2000000

1980 1985 1990 1980 1985 1990

Year

Th

ou

san

d c

ub

ic m

ete

rs

Africa North/Central America South America Asia Oceania Europe Former USSR

Industrial Roundwood Net Trade

Actual (1980 - 1994) Projections (1980 - 1994)

-75000

-60000

-45000

-30000

-15000

0

15000

30000

45000

1980 1985 1990 1980 1985 1990

Year

Th

ou

san

d c

ub

ic m

ete

rs

Africa North/Central America South America Asia Oceania Europe Former USSR

Soldid Wood World Prices

Actual (1980 - 1994) Projections (1980 - 1994)

0

100

200

300

400

500

1980 1985 1990 1980 1985 1990

Year

1994 U

S$ p

er

cu

bic

mete

r

Industrial Roundwood Sawnwood & sleepers

Further Work

• Extend dynamic calibration– I/O and costs (consider all data simultaneously)

– Demand (elasticities of demand)

– Supply (elasticities of supply)

• Explore alternative trade theories– Export (monopolistic competition)

• Update long-term validation

GFPM Software, Data, Manuals

http://fwe.wisc.edu/staticsites/buongiorno/book/GFPM.html