Phenomenological modelling scenario
of future wood demand by 2050
Roda J.-M., Ainudin, N., Guizol P., Ong C. L.
CIRAD, UR Forest & Societies Universiti Putra Malaysia, INTROP
XXV IUFRO Congress Curitiba, Brazil
29/09-5/10 2019
SALSA
Sustainable Agricultural Landscapes in Southeast Asia
A simplified typology of economic models
•
Theoretical models- Price, Quantities, Offer, Demand, Equilibrium, => how various factors may structurally influence the formers, no forecasts
•
Econometric models- a tea spoon of theory, and a tablespoon of blackbox => precise description, exploration of factors,
limited forecasts
•
Phenomenological models- Observation of phenomena, deconstruction of theories, understanding of domains of validity/extrapolation
=> unprecise description, identification of critical factors, robust but imprecise forecasts
Price
Quantity
Demand Offer
Equilibrium
DEMAND FACTORS CHANGE OFFER FACTORS CHANGE
lnQt = !0 + !1lnPt + !2ln(P.O)t + !3ln(A)t + !4ln(S/A)t + !5ln(Y/N)t + "t
Price Ownership Area Density Income
Demand factors: - construction dynamics, - demographics, - users income, - wood price, - Wood availability - etc.
Theoretical model
Theoretical model
Forecast
Real data
Malaysia Sawntimber demand forecast
Econometric model
Forecast
Real data
lnQt = !0 + !1lnPt + !2ln(A)t + !3ln(Q)t-1 + !4ln(Y)t + "t
Urbanization of
selected countries
Urbanization = construction (formworks, structure,
joinery, furniture)
Phenomenological model
Brazil : “domicilios” vs wood
consumption
Domicilios urbanos
Industrial wood consum
ptio n (RWE) Country: Brazil Country: China Country: India 1.5E7 2E7 2.5E7 3E7 3.5E7 4E7 4.5E7 5E7
5E7 6E7 7E7 8E7 9E7 1E8 1.1E8 1.2E8 1.3E8
China : “Floor space” vs wood
consumption
??Floor Space of Newly Built Residential Buildings in Urban Areas (100 million sq.m) China Floor Space of Newly Built Residential Buildings in Urban Areas (100 million sq.m)
Industrial wood consum
ptio n (RWE) Country: Brazil Country: China Country: India 0 1 2 3 4 5 6 7 8E7 9E7 1E8 1.1E8 1.2E8 1.3E8
An index of construction : urban
population
Urban population (x1000)
Round wood consumption
Country: Brazil Country: China Country: India
0 1E5 2E5 3E5 4E5 5E5 6E5
-2E7 0 2E7 4E7 6E7 8E7 1E8 1.2E8 1.4E8
0 1 2 3 4 5 6 7 110000 115000 120000 125000 130000 135000 140000 145000 150000 155000 160000 Urban population Brazil China India Proportion
Surprisingly consistent proportions
Projections
0 50000000 100000000 150000000 200000000 250000000 300000000 350000000 1950 1960 1970 1980 1990 2000 2010 2020 2030Tropical Wood Prod. BIC consumption Projection Projection Projection
World supply (FAO)
BIC demand (projection)
25% 35% 45% 55% 65% 75% 25% 35% 45% 55% 65% 75% GAP Time Wood quantity
Phenomenological model
Demography predictions are very reliable
United Nations demographic models are extremely robusts, and have been proved as very reliable
Phenomenological model
Secteurs 514 257 128.5 Secteurs Dom Exp So urce ca rt og ra ph iq ue : Art icq ue
Phenomenological model
International wood trade is small compared to
domestic demand :
1e+05 2e+05 3e+05 4e+05 5e+05 6e+05 5.0e+07 1.0e+08 1.5e+08 2.0e+08 2.5e+08 3.0e+08 3.5e+08 Latin America Urban population W ood comsumption 150000 200000 250000 300000 350000 4e+08 5e+08 6e+08 7e+08 8e+08 9e+08 Northern America Urban population W ood comsumption 250000 300000 350000 2.0e+08 2.5e+08 3.0e+08 3.5e+08 4.0e+08 4.5e+08 Europe Urban population W ood comsumption
0e+00 2e+05 4e+05 6e+05 8e+05 1e+06
2.0e+07 4.0e+07 6.0e+07 8.0e+07 1.0e+08 1.2e+08 1.4e+08 1.6e+08 Subsaharan Africa Urban population W ood comsumption 500000 1000000 1500000 1e+08 2e+08 3e+08 4e+08 Tropical Asia Urban population W ood comsumption 140000 160000 180000 200000 1.5e+08 2.0e+08 2.5e+08 3.0e+08 3.5e+08 4.0e+08 Former S U Urban population W ood comsumption 200000 400000 600000 800000 1000000 1200000 1.0e+08 1.5e+08 2.0e+08 2.5e+08 3.0e+08 East Asia Urban population W ood comsumption R2=0.99 R2=0.88 R2=0.97 R2=0.43 R2=0.80 R2=0.24 R2=0.66
L America SS Africa T Asia
N America Europe Former SU E Asia
0e+00 1e+05 2e+05 3e+05
1e+07 2e+07 3e+07 4e+07 Oceania Urban population W ood comsumption R2=0.94 Oceania
1960 1980 2000 2020 2040 50 100 150 200 250 300 350 Latin America Years W oo d co msu mp tio n 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 1960 1980 2000 2020 2040 20 40 60 80 100 120 140 160 Subsaharan Africa Years W oo d co msu mp tio n 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 1960 1980 2000 2020 2040 100 200 300 400 Tropical Asia Years W oo d co msu mp tio n 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 1960 1980 2000 2020 2040 20 30 40 50 60 70 80 Oceania Years W oo d co msu mp tio n 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 1960 1980 2000 2020 2040 400 500 600 700 800 900 North America Years W oo d co msu mp tio n 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 1960 1980 2000 2020 2040 200 250 300 350 400 450 Europe Years W oo d co msu mp tio n 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 1960 1980 2000 2020 2040 150 200 250 300 350 400
East Europe and F USSR
Years W oo d co msu mp tio n 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 1960 1980 2000 2020 2040 100 150 200 250 300 East Asia Years W oo d co msu mp tio n 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050
L America SS Africa T Asia Oceania
235 63 175 40 330 130 349 71 95 67 174 31 0 50 100 150 200 250 300 350 400
L America SS Africa T Asia Oceania 2016 2050 Gap Wood Dem an d (m ill ion m 3)
Phenomenological model
With such demand gaps, reforestation and plantations at large scales seem to be compulsory
•
In the next 30 years, the demand of tropical timber by tropicalcountries will reach unprecedented levels, on domestic markets that are out of the reach of classical market tools suchas
certification, REDD, Lacey act, etc,
•
The pressure on tropical forests will be like never before: it willincrease…
- by 40% in Latin America
- by 100% in tropical Africa and tropical Asia - by 77% in Oceania
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If the society want to prevent further degradation of tropicalforests, it has become absolutely imperative to design very ambitious plantation programs, and restoration programs.
Working together for
tomorrow’s agriculture
SALSA
Sustainable Agricultural Landscapes in Southeast Asia
