Impacts of choice of forest sector model in policy and economic analyses

(1)

2111 2005

Hanne K. Sjølie (UMB) Erik Trømborg (UMB) Torjus F. Bolkesjø (UMB)

Greg Latta (OSU) Birger Solberg (UMB)

(2)

EGIAN UNIVERSITY OF LIFE SCIENCES

Outline

 FSM for policy analyses: dynamic-recursive and intertemporal optimization models

 Quantitative comparison

 Discussion of model fitness

(3)

UNIVERSITY OF LIFE SCIENCES

The FSM family tree

3

What are the main

underlying differences

between these two groups of models, and how can these differences be

expected to impact on the

results?

(4)

A PRIORI INFORMATION AND OPTIMIZATION ROUTINE Intertemporal optimization vs. Dynamic recursive



Based on the assumption that the agents have all information (in the model) available at all points of time



Optimizes over all periods alltogether



Based on the assumption of the agents having no a

priori information, i.e. only information of previous and current period



Optimizes for one period at

the time

(5)

Intertemporal optimization vs. Dynamic recursive



Usually endogenous forest management and growth;

detail of growth simulations vary considerably between models



Timber supply based on the forest data (yield, costs) in the model; decision to

harvest similar to Faustmann



Time horizon several decades - century



Forest growth exogenous, forest management not included



Timber supply based on econometric relations, i.e.

based on historical data or age-classes



Time horizon 2-3 decades (as long as timber supply is

5

(6)

Quite substantial differences between the types of models..

.. Which can be expected to impact on the results

However, few comparative analyses exist of these two types of models, mainly due to the lack of comparative models (with two market levels and endogenous forest growth)

There are now two FSM of Norway - the dynamic recursive NTM3.0

- the intertemporal optimization model NorFor

(7)

NTM3.0 NorFor

 EFI-GTM «family member»

 Exogenous forest growth,

econometrically-derived timber supply

 Dynamic-recursive

 Time horizon 15-20 years

 Forest growth endogenous

 Forest growth from stand

simulator Gaya, industry as in NTM3.0, incorporation of forest yield into harvest decision from regional models of Oregon

 Time horizon up to 100 years

7

Both

 Base year 2010

 Region = 19 counties + 2 foreign regions

 P&P industry on mill level, bioenergy and saw mills on county level

 Bioenergy market segments with demand functions and capacity constraints: stoves, water heating central , industry

(8)

Market shifts impacts in intertemporal opt. models and in dynamic recursive model?

Analysis of two market shifts, one «shock» and one gradual change 1. Installation of biodiesel plant in 2020, producing 1 million liters of fuel from

0.6 mill cbm spruce pulpwood;

0.3 mill cbm pine pulpwood;

0.1 mill cbm birch pulpwood

(Compared to annual harvest of about 6.5 M cbm in Base)

2. Extra demand for sawnwood of 2% per year from 2010

GDP-related demand growth kept the same as in Base, 0.2-0.9% per year

(9)

Base : Harvest levels

9

6 000 000 7 000 000 8 000 000 9 000 000 10 000 000 11 000 000 12 000 000cbm

Year

Base NorFor Base NTM

(10)

BioDiesel scenario: Harvest levels

6 000 000 7 000 000 8 000 000 9 000 000 10 000 000 11 000 000 12 000 000cbm

Year

Total harvest

(11)

Biodiesel Scenario: Industrial production

11

0 500 000 1 000 000 1 500 000 2 000 000 2 500 000 3 000 000 3 500 000cbm

Year

Production of sawnwood

Base NorFor Base NTM BioDiesel NorFor BioDiesel NTM

(12)

BioDiesel : Industrial production

0 500 000 1 000 000 1 500 000 2 000 000 2 500 000tons

Year

Production of pulp and paper

(13)

BioDiesel : Industrial production

13

0 1 000 000 2 000 000 3 000 000 4 000 000 5 000 000 6 000 000

MWh

Year

Production of stationary bioenergy

(14)

BioDiesel scenario: Prices

0 50 100 150 200 250 300 350

NOK/cbm Spruce pulpwood prices

(15)

Sawnwood scenario: Harvest levels

15

6 000 000 7 000 000 8 000 000 9 000 000 10 000 000 11 000 000 12 000 000 13 000 000 14 000 000cbm

Year

Total harvest

Base NorFor Base NTM Sawnwood shift NorFor Sawnwood shift NTM

(16)

Sawnwoood scenario : Industrial production

0 500 000 1 000 000 1 500 000 2 000 000 2 500 000 3 000 000 3 500 000

cbm

Year

Production of sawnwood

(17)

Sawnwood scenario: Industrial production

17

0 500 000 1 000 000 1 500 000 2 000 000 2 500 000tons

Year

Production of pulp and paper

Base NorFor Base NTM Sawnwood shift NorFor Sawnwood shift NTM

(18)

Sawnwood scenario: Industrial production

0 1 000 000 2 000 000 3 000 000 4 000 000 5 000 000 6 000 000 7 000 000 8 000 000

MWh Production of stationary bioenergy

(19)

Sawnwood scenario: Prices

19

0 100 200 300 400 500 600 700

NOK/cbm

Year

Spruce sawlog prices

NorFor Base NTM Base NorFor Sawnwood shift NTM Sawnwood shift

(20)

Sawnwood scenario: Prices

0 50 100 150 200 250 300 350

NOK/cbm Spruce pulpwood prices

(21)

Sawnwood scenario: Prices

21

0 500 1 000 1 500 2 000 2 500 3 000

NOK/cbm

Year

Spruce sawnwood prices

NorFor Base NTM Base NorFor Sawnwood shift NTM Sawnwood shift

(22)

Summing up quantitative comparison



Harvest levels:

– Biodiesel: Less impact in NorFor than in NTM

– Sawnwoood: Timber is withheld the first periods in NorFor



Sawnwood production:

– BioDiesel: More impact in NorFor than NTM

– Sawnwoood: In NorFor less production first periods than in NTM



NorFor: Increased demand for sawnwood increases the

(23)

Intertemporal optimization vs. Dynamic recursive



Is the harvest decision best described by profit/utility- maximizing optimization,

Or

by econometric-derived relationship between harvest and price, interest rate and growing stock, etc.

What about outside historical ranges?

23

(24)

PROS AND CONS?

Intertemporal optimization vs. Dynamic recursive



First, which problem is to be analyzed?

 Forest carbon, forest management?

 Impacts of policies and market changes on industry?

 Year-to-year changes?



Forecast vs. Potentials

 Reflection of actual behavior

 Potentials: Smoothness in sector economy



Data intensity vs. the problem in question

(25)

www.umb.no

25

Impacts of choice of forest sector model in policy and economic analyses

Outline

The FSM family tree

What are the main

underlying differences

between these two groups of models, and how can these differences be

expected to impact on the

results?

A PRIORI INFORMATION AND OPTIMIZATION ROUTINE Intertemporal optimization vs. Dynamic recursive

Based on the assumption that the agents have all information (in the model) available at all points of time

Optimizes over all periods alltogether

Based on the assumption of the agents having no a

priori information, i.e. only information of previous and current period

Optimizes for one period at

the time

Intertemporal optimization vs. Dynamic recursive

Usually endogenous forest management and growth;

detail of growth simulations vary considerably between models

Timber supply based on the forest data (yield, costs) in the model; decision to

harvest similar to Faustmann

Time horizon several decades - century

Forest growth exogenous, forest management not included

Timber supply based on econometric relations, i.e.

based on historical data or age-classes

Time horizon 2-3 decades (as long as timber supply is

Quite substantial differences between the types of models..

NTM3.0 NorFor

Market shifts impacts in intertemporal opt. models and in dynamic recursive model?

Base : Harvest levels

BioDiesel scenario: Harvest levels

Biodiesel Scenario: Industrial production

BioDiesel : Industrial production

BioDiesel : Industrial production

BioDiesel scenario: Prices

Sawnwood scenario: Harvest levels

Sawnwoood scenario : Industrial production

Sawnwood scenario: Industrial production

Sawnwood scenario: Industrial production

Sawnwood scenario: Prices

Sawnwood scenario: Prices

Sawnwood scenario: Prices

Summing up quantitative comparison

Harvest levels:

– Biodiesel: Less impact in NorFor than in NTM

– Sawnwoood: Timber is withheld the first periods in NorFor

Sawnwood production:

– BioDiesel: More impact in NorFor than NTM

– Sawnwoood: In NorFor less production first periods than in NTM

NorFor: Increased demand for sawnwood increases the

Intertemporal optimization vs. Dynamic recursive

Is the harvest decision best described by profit/utility- maximizing optimization,

Or

by econometric-derived relationship between harvest and price, interest rate and growing stock, etc.

What about outside historical ranges?

PROS AND CONS?

Intertemporal optimization vs. Dynamic recursive

First, which problem is to be analyzed?

Forecast vs. Potentials

Data intensity vs. the problem in question

Thank you!

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