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$: Forest Economics - web.uvic.caweb.uvic.ca/~kooten/resource/ForestEcon.pdf · Forest Management and Rotation Ages Deals with actual harvest (road building, helicopter\horse logging,$
Forest Economics

G Cornelis van Kooten

March 10, 2020 2

Forest Management and Rotation Ages

Deals with actual harvest (road building, helicopter\horse logging, cutting, de-limbing, yarding, transportation, etc), restoration after harvest, silvicultural investment and silvicultural practices (thinking, fertilizing, spacing, etc.), choice of rotation age, decisions about where to harvest and when, etc., etc.

• Two management tools:

• Annual Allowable Cut (AAC)

• Mean Annual Increment (MAI)

• Average growth per year: Sustainability: AAC=MAI

March 10, 2020 3

Rotation Ages in Forest Economics

Rotation age is BIG in literature.

Assume trees grow as: v(t)

Volume

0 time

v(t)

Can think of this as similar to total product function in standard production theory

March 10, 2020 4

t

tvMAI vtv

dt

tdvCAI

)(

CAI Current Annual Increment

MAI Mean Annual Increment

Problem: When to cut trees?

March 10, 2020 5

Timber Yield (m3)

time

CAI

MAI

0

t

tvMAI

vtvdt

tdvCAI

)(

March 10, 2020 6

Timber Yield(m3)

time

I IIIII

CAI

MAI

0

Stages of Production

tMSY

tMSY = Foresters’ Rule is to harvest at age that maximizes the mean annual increment, MAI

March 10, 2020 7

MAI = v(t)/t

CAI = dv(t)/dt

0

Timber

yield

(m3)

Age

v(t)

a1 a3a2

=aMSY

March 10, 2020 8

MSY rotation age occurs at the time when culmination of MAI takes place – where CAI intersects MAI

tv

t

tv

ttv

tv 1

Rate of growth in volume

March 10, 2020 9

Alternative derivation of MSY rotation age

t

tvmax

0

dt

ttv

d 0

112

tvtdt

tdv

t

t

tvtv

ttv

tv 1

Simply:

March 10, 2020 10

Financial Considerations

Let p = log price at the mill

c = costs of felling, bucking, yarding,

loading, transportation

p – c = stumpage price (per m3)

For simplicity, we assume log price and

costs remain constant per m3

March 10, 2020 11

Single (Fisher) Rotation Age (“cut and run”)

rt

tetvcp )(max

1st derivative:

0)()( rtrt etvcpretvcp

rtv

tv

Continuous time problem:

Suppose trees are growing and question is only:

When to cut? Consider two cases:

Single (Fisher) Rotation Age (cont.)

t

t r

tvcp

1

)(max

1st derivative:

01

)1ln()()(

1

)(

tt

r

rtvcp

r

tvcp

instaneous)1ln(

)(rr

tv

tv

Discrete time problem:

Examples: ln(1.04) = 0.03922; ln(1.10) = 0.09531 ln(1.15)=0.13796

March 10, 2020 13

Value of single

harvest= (p – c )v(t) e-rt – K

(K = regeneration costs)

1st order condition:

0

rtrtt etvcpredt

tdvcpetv

dt

cpd

rtv

tv

cp

dtcpd

1st term on LHS is

capital gain; 2nd is rate

of growth of trees

Single (Fisher) Rotation Age (cont.)Suppose now that trees are not growing and you must

plant them, plus price of logs changes over time:

March 10, 2020 14

Financial or Faustmann Rotation Age

ntttn

r

Ktvcp

r

Ktvcp

r

KtvcpKV

1...

112

tnntttt

n

r

Ktvcp

r

Ktvcp

r

Ktvcp

r

K

r

V12

11...

111

Application of the derivation of the ‘bond formula’ in finance. Assume that the

up-front cost of planting at the beginning is –K (and it could be 0).

tntt

t

t

nn

r

Ktvcp

r

Ktvcp

r

KrK

r

VV

111)1(

)1(

1

Thus:

March 10, 2020 15

nttt

t

nt

t

rr

Ktvcp

r

rKV

r

r

1

11

1)1(

]1)1[(

1

11

nttnrr

KtvcpKV

1

11

11

Let n → ∞

11

tr

KtvcpKV

Financial/Faustmann Rotation Age (cont.)

≡ soil (land) expectation

March 10, 2020 16

The continuous time version is (letting q = p – c)

rt

rt

e

eKtvcpKV

1


Vn = – K + [q v(t) – K] e-rt+ [q v(t) – K] e-2rt + … + [q v(t) – K] e-nrt

e-rtVn = –Ke-rt + [q v(t) – K] e-2rt+ … + [q v(t) – K] e-nrt +

[q v(t) – K] e-(n+1)rt

(1–e-rt)Vn = – K(1–e-rt) + [q v(t) – K] e-rt – [q v(t) – K] e –(n+1)rt

Because e–rt→0 as n→∞

March 10, 2020 17

Note that:

V = soil expectation ≡ land value

To find the Faustmann rotation age, find

t* that solves0

dt

dV


March 10, 2020 18

This gives (for K=0)

*1*

*rte

r

tv

tv

If K ≠ 0:

*

1*

*rte

r

Ktqv

tvq

t* refers to optimal financial rotation age


March 10, 2020 19

(1) Trees already growing on stand and at some

age t0 > 0 but t0 < t*.

Then

Implication: Still cut trees when they reach t*

Ktqv

r

Ktqv

rNPV

ttt*

11

*

1

1** 0

Two glitches:


March 10, 2020 20

(2) Suppose the site is part of a larger management area

1 2 3 4 5 6 7 8

1

2

3

4

5

6

7

8

9

Assume rotation age is 72

years.

Removal of the shaded

site means that each of

remaining 71 sites would

need to give up annually

some of their harvest to

maintain sustainable

harvest where AAC=MAI

Removing 1 unit (or site) reduces overall MAI by: maiMAI 72

1

March 10, 2020 21

r

cpmaiVMU

What is the bare land value (soil expectation) of a stand-

alone site vs one in a management unit?

Soil expectation when land is

stand alone (given by Faustmann):

rt

rt

rt

rt

SAe

etmaicp

e

etvcpV

11

Soil expectation when land is part

of larger management unit where it

contributes of overall MAI (from

bond formula) :

March 10, 2020 22

SAMU VV if

0

1

rt

rt

e

ecptmai

r

cpmai

0

1

rte

cptmai

r

cpmai

01

1

rte

t

r 1

1

rte

t

r

1 rtert rtrt 1ln 0, tr

March 10, 2020 23

Discrete version when site is “stand alone”:

11

tSAr

cptmaiV

cpmai

where

t

rt

11 = capitalization rate

March 10, 2020 24

Calculated Interest (Discount) Rates (r) Associated

with Various Capitalization Rates (δ)

Rotation Age

δ 60 80 100 120

4% 2.061% 1.81% 1.62% 1.48%

10% 3.296% 2.79% 2.43% 2.16%

14% 3.805% 3.18% 2.75% 2.43%

March 10, 2020 25

Rotation Age

r 60 80 100

4% 15.87% 27.56% 49.5%

10% 505.80% 2,559.25% 13780%

Calculated Capitalization Rates (δ) Associated

with Selected Interest Rates (r)

March 10, 2020 26

Suppose that bare land is thought of as an initial

investment in land, denoted V, and investment in

upfront planting at cost K. The return from such

an investment is the present value of timber

harvest plus release of land for regeneration:

V + K = {(p – c) v(t) + V} e–rt

An Alternative View of the Financial Rotation

March 10, 2020 27

To find Faustmann rotation age (as before):

0dt

dV

Vtvcprdt

tdvcp

Value of incremental growth of forest

Foregone interest on combined

harvest and land value, V

An Alternative View of the Financial Rotation (cont)

Rewriting this relationship:

See following diagram:

cp

Vtvr

dt

tdv

March 10, 2020 28

v'(t)

v(t)

time

cp

Vtvr

v(t)

t* tMSY

An Alternative View of the Financial Rotation (cont)

maximizedcp

V

cp

V

cp

VtvrSlide the line until it is just

tangent to

v'(t)

dt

tdvv'(t) =

March 10, 2020 29

Comparative dynamics of simple model:

Change in:Optimal rotation

age

Soil/land

Expectation

Higher r – –

Higher p – +

Higher c + –

Higher K + –

March 10, 2020 30

Effect of taxes on rotation age

• Ad valorem tax: % levy on standing timber → harvest sooner

• Yield tax: % levy on value of timber at harvest time → neutral effect

• Land tax: levy on site or land but not timber → neutral effect on harvest time

March 10, 2020 31

M

S

F

r/(1–e–rt)

Discount/growth rate

v(t)/v(t)

20

Faustmann

12%

8%

4%

30 40 50 60Time

0

Fisher MSY

t

1

Diagram comparing rotation ages

March 10, 2020 32

Typical Coastal Douglas Fir

Stand age

(years)

Timber volume

(m3/ha)

CAI

(m3/ha)

MAI

(m3/ha)

40 30 5.5 0.75

50 100 9.3 2.0

60 212 11.4 3.5

70 348 11.8 5.0

80 454 10.4 5.7

90 563 9.0 6.3

100 638 7.7 6.4

110 701 6.3 6.4

120 752 5.3 6.3

Economic rotation at 3.4% is about 70 years; MSY rotation about 110 years

March 10, 2020 33

Artificial vs Natural Regeneration

Long rotation ages and the bogey of compound interest make silvicultural

investments unattractive and artificial regeneration too expensive

Suppose B= benefits of logs at maturity

T= rotation age

∆T= time for natural regeneration to occur

Therefore, benefits of artificial regeneration are:

TTTr

B

r

B

11

March 10, 2020 34

Suppose B=$50,000/ha, r=2%, T=60,

K=$2000/ha, ΔT =5

If T= 60 years, NPV=$13,239 (B/C=7.6)

ΔT =5 then Discounted B=$1,436

NPV= -$654 (B/C=0.7)

However

Suppose that by planting today, you raise

MAI and this raises AAC tomorrow.

March 10, 2020 35

What are the benefits of investing in tree planting and silviculture (fertilizing,

pre-commercial thinning, etc) given the curse of discounting?

One argument: the benefits are ‘immediate’ in the sense that any investment in

growth increases MAI and thus AAC since AAC=MAI is a sustainability

condition.

Counter argument: A $1 investment today needs to earn $23 in 80 years (4%

return) and $4,225 at the 1926-1998 before tax return of U.S. companies (11%)

Does Silvicultural Investment Pay?

The Allowable Cut Effect (ACE)

March 10, 2020 36

Allowable Cut Effect (ACE) (cont)

(1+g)S

ht+1

S hththt

Even

Flow

(1+g)S

production functions

0

March 10, 2020 37

ACE leads to benefit ofPV'-PV

0

If PV'-PV0

>c then there

is a gain to investment


(1+g)S

ht+1

PVo

S hththt

Even

Flow

(1+g)S

PV*PV

slope of net present value

objective = –(1+r)

0

March 10, 2020 38


• Only reason for positive NPV from most tree planting and silvicultural investments lies with the even-flow constraint

• Even-flow imposed as a kind of sustainability constraint: community stability, jobs

• Actual record: Despite such constraints, jobs have been lost and timber dependent communities are unstable because of technological advances and market instability

March 10, 2020 39

Hartman Rotation Age

Environmental amenities correlated with stand age (or volume of

standing timber)

Suppose amenity values are A(t), with A'(t)>0, A''(t)<0

Note: Amenity benefits occur every year

H

H

rt

rt

H

H

e

re

tA

tA

1

where tH is the amenity or pure

Hartman rotation age → may cut

trees even if they have no value

dsesatA rst

0Let

1max

1max 0

rt

trs

trt

t e

dsesa

e

tAPROBLEM:

March 10, 2020 40

IV

III

II

I

0stand age t

(t)

Relationship between stand age and four different amenity values (Calish, Fight and

Teeugarden 1978). How to determine optimal rotation age? Need linear/nonlinear program

(numerical solution)

Amenity value

t1

MOC

MBD

0

rotation age

t

$

12

t2t*

Suppose ‘non-convexity’: Rotation age t1 does not satisfy 2nd-order

conditions; t* is financial age, but optimal age is t2. Need subsidy

for amenity value, but if given too early t1 is chosen and not t2.

MOC is marginal opportunity cost of delaying harvest

MBD is discounted marginal benefit of delay

March 10, 2020 42

Hartman-Faustmann Rotation

rt

rt

t e

eKtAtvcp

1max

Solving: *1**

*'*'rte

r

ctAtvcp

tAtvcp

where t* is the optimal rotation age that takes into account both timber

and non-timber (amenity) values where the latter are related to stand age.

Expression can get more complicated by making non-timber value a

function of Δt (or dt) rather than t (as is case with carbon sequestration.)

Modified Hartman-Faustmann: Carbon Uptake

• Hartman-Faustmann rotation age depends on benefits varying with forest age.

• Consider benefits to vary with the rate of change in forest age

• Example: Carbon uptake benefits depend on growth rate of trees, not volume of stand

(or age of stand) (van Kooten, Binkley & Delcourt, Am J of Ag Econ. 1995)

• Present value of carbon benefits:

rtetvc

pt

dsrs(s)evc

pc

V )()1(

0

'

where converts biomass to carbon, is pickling rate (proportion into long-lived

products), and pc shadow price of carbon.

v′(s) = dv/ds

March 10, 2020 44

Then:

rt

rt

c

e

etvcpVV

1

rt

rtt

rsrt

c

e

etvcpdsesvretvp

1

'0

Integrating by parts

t

rsrt

cc dsesvretvpV0

'

Carbon Uptake Example (cont.)

March 10, 2020 45

Carbon Uptake Example (cont.)The solution looks like this (note the RHS):

e rt

r

v(t)

tdse rss)v

r+

r+

v(t)

(t)v

1

0

(

1

Setting pc = 0 gives the Faustmann result. Otherwise, can only solve for rotation age numerically!!

March 10, 2020 46

Carbon Uptake Example (cont)

Harvest rule is as follows.

Harvest whenever:

0

)(')()1()( dttvpVtvptpv cc

March 10, 2020 47

Carbon Uptake Example (cont.)

Item Boreal Forest Coastal

Rainforest

Parameter values for v(t) = ktae-bt

k

a

b

0.0008

2.766

– 0.0092

0.0006

3.782

– 0.0310

MSY age (years)

Maximum volume (m3 ha-1)

Age of maximum volume (years)

Value of (kg m-3)

192

340

300

203

90

1,020

122

182

Table: Forest Growth Data

Discount Rate (%) / Price of Carbon ($ per tonne)

Item 5% 10% 15%

$20 $50 $200 $20 $50 $200 $20 $50 $200

Coastal Faustmann

43

27

20

= 0,

p = $ 0/m3 15

25

50

* 51

47

45

* 68

56

49

* *

*

77

* 34

31

29

* 52

38

32

* *

*

63

* 25

23

22

* 41

29

23

* *

*

52

= 1/2, p = $ 0/m3

15

25 50

*

50

47 45

*

60

53 48

*

*

88 64

*

32

31 29

*

43

36 32

*

*

78 47

*

25

23 21

*

33

27 23

*

210

68 35

= 1,

p = $ 0/m3 15

25

50

108 49

47

45

108 56

51

48

108 76

68

58

116 32

30

29

116 39

34

31

116 61

51

41

119 24

22

21

119 29

26

23

119 50

40

31

Boreal Faustmann

42

23

16

= 0,

p = $ 0/m3 15

25

50

* 54

49

45

* 100

64

50

* *

*

136

* 31

27

25

* 63

37

28

* *

*

95

* 22

19

17

* 46

26

20

* *

*

72

= 1/2, p = $ 0/m3

15

25

50

*

53

48 45

*

74

59 50

*

*

176 83

*

30

27 25

*

44

34 28

*

*

136 50

*

21

19 17

*

31

24 19

*

*

109 36

= 1,

p = $ 0/m3

15 25

50

269

51 47

45

269

64 56

49

269

111 89

68

287

30 26

25

287

37 32

27

287

73 55

40

293

20 18

17

293

26 22

19

293

53 40

28

Table: Optimal

Rotation Ages with

Carbon Tax-

Subsidy Scheme

March 10, 2020 49

Carbon Uptake Conclusions

There are situations when it does not pay to harvest trees:

Recall: is the pickling parameter

= 0

> 0 but small and price of carbon is high

As the price of carbon increases, rotation age increases

As the discount rate increases, the rotation age falls

Implication is not that old-growth forests should never be

harvested. It depends on economic efficiency.

March 10, 2020 50

Tropical Deforestation

FAO defines tropical forests as ecosystem with a

minimum 10% canopy cover.

Tropical forests range from open savannahs with

limited precipitation to dense tropical forests

with 10m or more of rainfall per year

March 10, 2020 51

Proximate causes of deforestation

Logging (Aisa)

Only very small proportion of logs removed

(<10 m3 /ha sometimes <10 trees per ha)

Roads provide access for peasants

Conversion to agriculture (Amazon)

Land more valuable in agriculture (?)

Earn foreign exchange

Population density, labor markets

March 10, 2020 52

Forest Area and Rates of Deforestation, 1981–90, 1990–95, 1990-2015.

March 10, 2020 53

Annual Change in Forest Cover,

1990-2000 (106 ha)

Domain

Natural forest Forest plantations Total forest

Loss Gain

Net Δ

Gain

Net Δ NetΔDeforestat

ion

Conversion

to forest

plantations

Total

loss

Natural

expansion

of forest

Conversion

from

natural

forest

Afforest-

ation

Tropical areas -14.2 -1.0 -15.2 +1.0 -14.2 +1.0 +0.9 +1.9 -12.3

Non-tropical

areas-0.4 -0.5 -0.9 +2.6 +1.7 +0.5 +0.7 +1.2 +2.9

Global total -14.6 -1.5 -16.1 +3.6 -12.5 +1.5 +1.6 +3.1 -9.4

March 10, 2020 54

Estimates of Forest Cover and Rates of Deforestation, Tropics

Forest Formations

Land Area

Population

Density

1990

Annual

Population Growth

(1981–90)

Forest Area 1990

Deforestation (1981–90)

106 ha #/km2 % 106 ha % 106 ha/yr %

FOREST ZONE 4,186.4 57 2.6 1,748.2 42 15.3 0.8

Lowland formations 3,485.6 57 2.5 1,543.9 44 12.8 0.8

-Tropical rainforest 947.2 41 2.5 718.3 76 4.6 0.6

-Moist deciduous forests

1,289.2 55 2.7 587.3 46 6.1 0.9

-Dry deciduous forests 706.2 106 2.4 178.6 25 1.8 0.9

-Very dry zone 543.0 24 3.2 59.7 11 0.3 0.5

Upland formations 700.9 56 2.9 204.3 29 2.5 1.1

-Moist forests 528.0 52 2.7 178.1 34 2.2 1.1 -Dry forests 172.8 70 3.2 26.2 15 0.3 1.1

NON–FOREST ZONEa 591.9 15 3.5 8.1 1 0.1 0.9

TOTAL TROPICSb 4,778.3 52 2.7 1,756.3 37 15.4 0.8

Region 1990-2000 2000-2005 2005-2010 2010-2015

World -0.18% -0.11% -0.08% -0.08%

Africa -0.51% -0.47% -0.51% -0.45%

Asia -0.04% 0.52% 0.29% 0.13%

Europe 0.08% 0.04% 0.19% 0.04%

North & Central America -0.05% -0.02% 0.06% 0.01%

Oceania 0.05% -0.13% -0.51% 0.18%

South America -0.44% -0.50% -0.38% -0.24%

Forest Type

Boreal 0.00% -0.02% 0.10% -0.01%

Sub Tropical -0.02% -0.05% -0.27% 0.03%

Temperate 0.36% 0.56% 0.43% 0.33%

Tropical -0.50% -0.42% -0.36% -0.31%

Annual Rates of Deforestation/Reforestation by Period for Regions

and Forest Types

March 10, 2020 56

Amazon Region Deforestation

1978-1988 2.20 mil ha per year







2010-2015 neg mil ha per year

March 10, 2020 57

Factor from Farm-Level Models Effect on deforestation

Increased trans costs of ag output ↓

Increased wage rates in ag ↓ or no effect

more off-farm employment ↓

increase in ag credit availability ↑ or ↓

higher ag output prices ↑ or ↓

increase in ag productivity ↑ or ↓

increase in price of fertilizers ↑ or no effect

increase in other ag input prices ↓

population growth ↑

increase in household size ↑ or ↓

Better soil quality ↑

Proximate Causes of Tropical Deforestation

March 10, 2020 58

Factors in global models that appear to increase deforestation:

• Importance of agriculture in economy

• Timber production

• Higher exports of forest products

• Currency devaluation

• Road construction

• Drier climate

• Unequal land tenure

March 10, 2020 59

Factors with no clear effect:

Population density

Population growth

Per capita income

Growth in per capita

External indebtedness

Political stability

democracy

Proximate are NOT ultimate causes

Ultimate causes include:

• Need to alleviate population pressure: move

people from high density island of Java to other

islands, from Rio de Janeiro / Sao Paulo to

Amazon

• Corruption

• Desire for income

Political leaders cause deforestation by the policies they choose to implement

Article in Nature (6 Nov 2003, pp.67-70) supports idea that corruption

and other “governance” factors lead to greater deforestation.

March 10, 2020 61

Regression model:

GDP, GDP2, Ag Output (not forest exports),

Freedom to exchange in capital markets,

corruption, rural population proportion

March 10, 2020 62

Environmental Kuznets Curve

• Countries will initially exploit the environment

for growth, but, as incomes rise, demand for

improved environment (income effect) causes

an improvement in the environment

• Inverse U of EKC

March 10, 2020 63

Traditional Environmental Kuznets Curve (EKC)Negative Environmental Quality

0 Per capita income

March 10, 2020 64

What regression looks like:

+

-

0Per capita income

Rate of deforestation

afforestation

$6,500 $19,500 $30,000

$ 2000

March 10, 2020 65

Forest CertificationInstruments for Addressing Environmental Externality

1. Command and control (regulation)

2. Taxes/subsidies

3. Cap-and-trade schemes (government sets cap)

4. Coasian bargaining (rare, perhaps because of high transaction costs)

March 10, 2020 66

Instruments for Addressing Environmental Externality (cont)

5. Voluntary initiatives are currently in vogue (implicit threat of government intervention if nothing done)

6. Voluntary action sans government is rare

-- Forest certification is maybe the best example

Forest certification is an example of a “non-state, market-driven governance structure” (Ben Cashore)

March 10, 2020 67

Forest Certification

• Perhaps best example of a “non-state, market-driven governance structure” is forest certification.

• Certification of sustainable forest management (SFM)

• Two types:

1. Completely self regulated

2. Private regulation

ITEM

Conditions of non-state market driven Governance

State does

not require

direct

adherence

to rules

State does not

control

standard-

setting

process

Products are

demanded by

purchasers

further down

the supply

chain

Authority is

granted

through

evaluative

process

Compliance

is verified

Forestry

Fisheries

Coffee

Organic foods

Ecotourism Usually

Comparison of non-state market driven governance systems across sectors

Non-State Market Driven

Governance

Shared Private/Public

Governance

Traditional

Government

Location of

authority

Market transactions Government gives

ultimate authority

(explicit or implicit)

Government

Source of

authority

Evaluations by external

audiences, including those it

seeks to regulate

Government’s

monopoly on

legitimate use of force,

social contract

Government’s

monopoly on

legitimate use of

force, social contract

Role of

government

Acts as one interest group, land

owner (indirect potential

facilitator or debilitator)

Shares policy-making

authority

Has policy-making

authority

Comparison of non-state market driven governance sources of authority with

other forms of governance

March 10, 2020 70

Forest Certification Schemes

1. Forest Stewardship Council, FSC

• Failure at Rio to sign global convention on forestry led ENGOs to develop a private, non-mandatory regulatory scheme for sustainable forest management (SFM)

• Led by WWF, it included some private forest firms

• Started in 1993

• Focus on tropical forests

March 10, 2020 71

1. Forest Stewardship Council (cont)

• On-the-ground and chain of custody certification

• International in scope

• As of January, 2004, FSC had issued 116 certificates for forest holdings > 50 000 ha (accounting for 89.2% of FSC-certified area; 451 holdings of < 50 000 ha

• Private (external) regulation

March 10, 2020 72

2. ISO 14001

• Certification of processes rather than forestland

• Discretionary, flexible performance guidelines & requirements

• Not considered here because land is not certified

• International in scope and thus competitive with FSC

• Industry initiative

March 10, 2020 73

3. “Domestic” FSC Competitor Schemes

• Started in various countries by industry (Canada & U.S.) or landowners (Europe) because they felt FSC did not address their concerns

• Non-mandatory, flexible, self-regulation

• Canadian Standards Council (CSA)

• U.S.’s Sustainable Forestry Initiative (SFI)

• Europe’s Pan-European Forest Certification (PEFC): each country operates its own scheme under PEFC

• Evolved into Programme for the Endorsement of Forest Certification (PEFC)

March 10, 2020 74

POINTS:

• Concerns about the environment was what motivated the start-up of FSC

• Concerns about markets, especially export markets, and desire for self-regulation drove domestic competitor schemes

• Interestingly, 60% of SFI certified forests are in Canada; recently SFI certification has been criticized.

March 10, 2020 75

Why do firms/landowners certify SFM?

• Economic reasons:

1. Price premium

2. Reduced costs

3. Market access (retention, penetration)

4. Avoid lawsuits, negative lobbying, etc.

• Utility of managers of firms and/or landowners

March 10, 2020 76

Why do countries certify SFM?

At country level, emergence of voluntary governance depends on:

1. Economic factors

- factors identified above

- higher incomes lead to more D for environment

- opportunity cost of forestland

2. Institutional factors (protection of property, etc)

3. Social capital (trust, empowerment, etc)

0.00

10.00

20.00

30.00

40.00

50.00

60.00

Scand

inav

ia

Oth

er W

. Eur

ope

Cen

&Eas

t Eur

ope

Can

ada

USA

Res

t of W

orld

Area (mil ha)

FSC certified

Domestic competitor

0.00

10.00

20.00

30.00

40.00

50.00

60.00

Scand

inav

ia

Oth

er W

. Eur

ope

Cen

&Eas

t Eur

ope

Can

ada

USA

Res

t of W

orld

Area (mil ha)

FSC certified

Domestic competitor

Situation in 2004

Certification

• Performance-based: programs that focus on creation of mandatory on-the-ground rules governing forest management

• Systems-based: development of more flexible and often non-mandatory procedures to address environmental concerns.

• Verification of performance and compliance• 3rd Party: outside organization (e.g., Forest Stewardship Council certifies certifiers)• 2nd Party: trade association or other industry group• 1st Party: company verifies its own record of compliance.

• Chain of Custody: tracking of wood from certified forests along the supply chain to the final, individual consumer.

• Logo: symbol certification programs use to advertise their programs and can be used by companies when making claims about their forest practices

• Eco-label: used along the supply chain to give institutional consumers the ability to discern whether a specific product comes from a certified source.

Source: www.certificationcanada.org as of December 31, 2018

http://www.certificationcanada.org/

Item FSC PEFC SFI CSA

Origin Environmental

groups, socially

concerned

retailers

Landowner (and

some industry)

Industry Industry

Types of Standards:

Performance or

Systems-based

Performance

emphasis

Combination Combination Combination

Territorial focus International Europe origin,

now international

National/bi-

national

National

Third party

verification of

individual ownerships

Required Required Optional Required

Chain of custody Yes Yes No Emerging

Eco-label or logo Label and Logo Label and Logo Logo & label Logo

Comparison of FSC and FSC competitor programs

IssuePrograms

FSC CSA SFI PEFCPlantations Limit establishment of new

plantations, some existing plantations not eligible

Not specifically addressed



Chemicals Minimize and monitor use. Certain chemicals banned.

Follow gov’t regulations

Minimize use Minimize use

Clearcuts Size and location restricted (varies by region)


Average size ≤ 120 acre No specific policy (varies among national initiatives)

GMOs Prohibited Follow gov’t regulations

Follow gov’t regulations National initiatives do not prohibit use, except UK, France

Exotics Permitted, but not promoted. Monitor use.


Minimize use Permitted, but not promoted

Reserves Identify significant sites and ensure protection.

Identify significant sites and ensure protection

Identify significant sites, management at discretion of company/landowner

Identify significant sites, management at discretion of company/landowner

Streamside riparian zones

Harvesting limited or prohibited in identified areas. Increased rules where harvesting is permitted.

Develop plan Develop plan, follow “best management practices”

Follow gov’t regulations, develop plan (varies among national initiatives)

Comparison of standards influencing on-the-ground aspects (as of mid 2000s)

March 10, 2020 82

Trade in Forest Products

Analysis of Canada-U.S. Softwood Lumber Dispute

Country/region

Production

('000s m3)

Consumption

('000s m3)

Exports

('000s m3)

Imports

('000s m3)

BC Coast 3,659 2,920 3,126 2,387

BC Interior 26,152 1,302 24,850 0

Alberta 8,620 1,651 7,074 105

Atlantic Canada 4,989 1,122 3,916 48

Rest of Canada 15,868 5,596 10,663 391

US North 3,415 38,502 40 35,127

US South 36,972 33,731 5,290 2,050

US West 32,933 24,923 20,349 12,339

Rest of World 218,458 241,320 3,055 25,917

Softwood Lumber Production, Consumption and Trade,

Various Regions, 2014

March 10, 2020 84

Lumber I (1982-1983)

In late 1982 the U.S. Coalition for Fair Canadian Lumber Imports (hereafter Coalition) filed a

petition with DOC alleging that provincial stumpage fee systems and methods of managing

public forestlands constituted countervailable subsidies. The resulting investigation completed

in May 1983 found no evidence for the imposition of a CVD, because the stumpage programs

were considered to provide no preferential treatment to any specific industry or enterprise.

History of the Trade Dispute

Lumber II (1986-1991)

- Coalition filed new petition, DOC rules that stumpage programs are a subsidy and imposes

15% CVD

- Canada–U.S. MOU: Canada collects levy of 15% on lumber exported to U.S. starting 1987.

- MOU allows tax reductions if provinces implement ‘replacement measures’ (e.g., higher

stumpage fees\other charges). Canada terminates MOU in September 1991, as BC, Quebec

and Atlantic provinces had changed their stumpage systems so that export charges could be

substantially eliminated.

March 10, 2020 85

Lumber III and the Softwood Lumber Agreement (1992-1994 and 1996-2001)

• DOC self-initiates 3rd third investigation imposing a CVD of 6.5% in mid 1992 on

lumber imports from all provinces except the Maritimes.

• Canada appeals determination of subsidy and the finding of injury to the binational

panel for dispute resolution under Chapter 19 of the FTA. Panel rules twice against the

DOC

• U.S. requests Extraordinary Challenge Committee to review decisions; request rejected

• August 1994, money collected under CVD ($US 800 million) refunded and consultative

mechanism agreed to

• 1996: U.S. and Canada negotiate 5-year Softwood Lumber Agreement (SLA) to

forestall further petitions and countervail action.

• SLA employs quota device that constrains annual lumber exports to the U.S. from BC,

Alberta, Ontario and Quebec to 14.7 billion board feet (BBF), or 34.7 mil m3, annually

until 2001 with escalating fees on shipments over that volume

• SLA expired on 31 March, 2001 without another agreement in place.

History of the Trade Dispute (cont)

March 10, 2020 86

Lumber IV

• SLA ends in March 2001 → in August U.S. imposes 19.23% CVD and 8.43% anti-

dumping duty; CVD revised down to 18.79% in May 2002 and 13.23% in November

2003

• Canadian appeals to WTO and NAFTA lead to one conclusion: U.S. needs to base its

calculations of duty rates on better information and economics.

• Under NAFTA’s Chapter 19 (Article 1904), three separate dispute resolution panels

submitted a total of seven reports on DOC determinations.

•The panel looking into CVD determination ruled on three occasions (13 August

2003, 7 June 2004 and 1 December 2004) that the DOC needed to lower their CVD

duties

•panel on injury ruled that there was no injury

•WTO rules CVD needed to be reduced, but only by small amount

History of the Trade Dispute (cont.)

March 10, 2020 87

Lumber IV (cont)

• End 2004: $4 billion collected from Canadian producers in escrow with the U.S.

Treasury, with $5.4 million paid out to U.S. producers in December 2004• Producers claim they are entitled to these funds under the “Continued Dumping and Subsidy Offset

Act of 2000” – the Byrd Amendment to the “Agriculture, Rural Development, Food and Drug

Administration, and Related Agencies Appropriation Act, 2001”

• Higher prices and potential CVD payouts constitute a ‘double jeopardy’ encouraging U.S. lumber

producers to continue trade action against Canada, particularly as Canadian provinces have generally

eschewed market forces in the setting of timber prices thereby making them vulnerable to such action.

• January 2003: DOC releases framework for analyzing ‘changed circumstance’ reviews

for CV and AD duties. • Provincially administered stumpage fees need to be established using a ‘market-based system’,

defined as one that “produces results consistent with those the province could expect from the sale of

all its timber at open auction”.

• DOC stated that it has a “strong preference for regression analysis”


March 10, 2020 88

Lumber IV (cont)

• 2004 and 2005: NAFTA panels find errors favoring Canada and requiring DOC to

revise estimated duties five times: CVD lowered from 18.8% (early 2004) to 17.2 %

by end of 2005, and the AD rate dropped from 8.4% to 4%, for total reduction from

27.2% to 21.2%.

• Reduction during 2005 to 16.4% on CVD and 3.8% on AD (total of 20.2%).

• By end of 2005, the combined CVD and AD dropped from 20.2% to 10.8%.


Lumber V

26 April 2006, Canada and the U.S. announced that they had reached a tentative seven-

year agreement, with an option for two additional years

Random Lengths’

Framing Lumber

Composite Price

Option A:

Export

Charge

Option B:

Export Charge + Quota

Over US$355/mbf 0% 0% + no quota

US$336 to US$355/mbf 5%2.5% + regional share of 34% of U.S.

consumption

US$316 to US$335/mbf 10%3.0% + regional share of 32% of U.S.

consumption

US$315 or under 15%5.0% + regional share of 30% of U.S.

consumption

Triggers and Available Options under the 2006 – 2015 Softwood Lumber

Agreement (SLA): Region Specific Tariff Rate Quotas (TRQ)

Alberta and BC chose option A; Saskatchewan, Manitoba, Ontario and Quebec chose option B; after October 2015 there

was a one-year grace period. Immediately when it expired, U.S. Lumber Coalition filed CVD and AD petitions

20%

40%

60%

80%

100%

120%

140%

160%S

urg

e T

rig

ger U

tiliza

tio

n (%

)

BC Coast BC Interior Alberta Alberta(100%-110%) Alberta(>110%)

Alberta

BC Coast

BC Interior

Market price

exceeds trigger:no quota

Quota volume utilization (%) under SLA and indications where surge trigger exceeded, select regions: November 2006 – April 2015


Lumber V

• SLA2006 extended to October 2015, followed by one-year grace period during which U.S. lumber producers could not initiate action against Canada.

• U.S. Coalition initiated a new dispute immediately upon expiration of the ‘cooling-off’ period. • February 2017: four companies investigated by U.S. ITC, including Canfor, West

Fraser, Tolko and Resolute

• Investigations resulted in various company-specific anti-dumping and countervail duties (see Table next slide).

• Latest development: Early September, 2019, a NAFTA panel ruled that the claims of injury by American lumber producers against Canadian producers were flawed. It ruled that the CVD and AD rates imposed on Canadian producers had to be recalculated, and thereby sent the file back to the U.S. International Trade Commission for reconsideration

Rank Company Capacity Rank Sawmill Capacity

1 West Fraser Timber Co Ltd (Can) 8,460,000 1 Klausner Holz Thüringen 1,200,000

2 Canfor (Can) 6,900,000 2 Wismar Sawmill 1,200,000

3 Weyerhaeuser (US) 6,449,000 3 Plateau sawmill 1,054,000

4 Stora Enso (Finland) 4,646,000 4 Houston sawmill 1,020,000

5 Georgia Pacific (US) 4,300,000 5 Quensel West Fraser 940,000

6 Resolute Forest Products (Can) 4,000,000 6 Binderholz sägewerk 825,000

7 Interfor (Can) 3,550,000 7 Mackenzie sawmill 800,000

8 Sierra Pacific Industries (US) 3,200,000 8 Landsberg Am Lech 800,000

9 Hampton Affiliates (US) 3,100,000 9 Offner Wolfberg 800,000

10 Arauco (Chile) 2,800,000 10 Dunkley sawmill 800,000

11 Tolko Industries Ltd (Can) 2,500,000 11 Baur Holz 750,000

12 Schweighofer (Austria) 2,400,000 12 Longview Softwood 720,000

Top Twelve Global Producers of Lumber by Production or Capacity, m3 per year

Company Anti-Dumping Countervail Combined

Canfor Corporation 7.28% 13.24% 20.52%

Forest Products Canada Inc. 3.20% 14.70% 17.90%

Tolko Marketing Sales Ltd. 7.22% 14.85% 22.07%

West Fraser Mills Ltd. 5.57% 17.99% 23.56%

J.D. Irving Ltd. 6.04% 3.34% 9.38%

All Others 6.04% 14.19% 20.23%

Current Anti-Dumping and Countervailing duties by company

Source: Global Affairs Canada

March 10, 2020 95

(a) Canada (b) International Market (c) United States

Lumber quantity

Price

Pc

0 q* qcS

a

b

Sc

ES+ transportation costs

PU

Sus

Dus

00 q*

Dc

Canadian surplus = a + b

U.S. surplus = α + β

Spatial Price Equilibrium Trade Models

March 10, 2020 96


Lumber quantity

Price

Pc

0 q* qcS

a

b

Sc

EDCanada

PU

Sus

Dus

00 q*

Dc

ES = excess supply

ED = excess demand

ESCanada

March 10, 2020 97


Lumber quantity

Price

Pc

0 q* qcS

a

b

Sc

PU

Sus

Dus

00 q*

Dc

ES = excess supply

ED = excess demand

ES

EDUS

P trade

Q trade

March 10, 2020 98


Lumber quantity

Price

Pc

0 q* qcS

a

b

Sc

PU

Sus

Dus

00 q*

Dc

ES

EDUS

PUtrade

Q trade

PCtrade

U.S. and Canadian prices differ by the transportation cost =

PUtrade – PC

trade



Lumber quantity

Price

PcT

Pc

0 qcD q* qc

S

a

b c

de

g

Sc


A

BC

D

E

G

QT

ES

ED

PU

PTU

Sus

Dus

00 qUs q* qU

d

Dc

Full Trade Model

Cdn surplus = a+b+c+g+e+d

U.S. surplus = α+β+φ+δ+γ

Cdn gain = g = B+E

U.S. gain = φ+δ = A

March 10, 2020 100

Price ESQ

ES’

ES

EDED’

P’US

Pus+trans=Pc

P’c

0 QT=Q

QQ* Lumber quantity

r

m

n

y

w

x

Countervail duty (ED') vs export duty (ES') vs quota (QQ)

March 10, 2020 101

Price ESQ

ES

ED

P′US

Pus=Pc

P′c

0 qT=qQ

q*Lumber quantity

r

m

n

y

w

x

Rents/Revenue

Quota rent or tax revenue

Producer gain from quota

q*qR=1/2q* qm

Finding an Optimal Quota

March 10, 2020 102

Mathematics

(1) Pd =

j –

j q

j,

j,

j 0,

(2) PS = a

j + b

j q

j, a

j, b

j 0,

(3) ED = – q, with = UU

UUUU

b

ba

0 and =

UU

UU

b

b

0

(4) ES = a + b q, with a = CC

CCCC

b

ba

+ tR 0 and b =

CC

CC

b

b

0

(5) q* = b

a

.

March 10, 2020 103

Mathematics (cont)

Quota rent QR is a function of the quantity traded:

(6) QR(q) = (ED – ES) q = ( – q – a – b q) q (quota rent)

(7) qR =

)(2 b

a

= ½ q*.

Substituting (7) into (6) gives:

(8) QR(qR) = ¼

b

a 2)(.

March 10, 2020 104

Mathematics (cont)

Sum of producer surplus and quota rent:

(9) B(q) = ½ (PC – aC) (q

CD + q)

=

qbqatatbqa R

C

C

CR )(

1)(

2

1.

B(q=0) = producer surplus from domestic sales only (autarky)

B(q=q*) = benefit from free trade, so the quota benefit is zero.

To find optimal quota, qm

, set first derivative of B(q)=0 and solve:

(10) qm

= 2224

)()(2)2())((

bb

abatbaabCC

CCR

CCC

.

Not possible to demonstrate unambiguously that qR<q

m, but numerically

March 10, 2020 105

Effect on Optimal Quota Level of Changes in U.S. and Canada

Supply and Demand Parameters, Comparative Static Results

Item Canada United States

Shifts in Demand

Changes in Slope of Demand

Changes in Slope of Supply

Changes in Slope of Supply

Change in Transportation Costs

0

C

mq

0

U

mq

0

C

mq

??

U

mq

0

C

m

a

q

0

C

m

b

q

0

U

m

a

q

??U

m

b

q

0

R

m

t

q

March 10, 2020 106

Trade Levels, Economic Surpluses, Prices and Transportation

Costs under Various Model Assumptions

Item Scenarios

SLAaOptimal

Quota

15% CVD 61/2CVD 15% Export

Tax

Quantity traded (*109 mbf) 18.80 16.84 16.99 18.86 18.87

Deadweight Loss ($ mil) 135.95 117.15 107.27 21.96 21.65

Canada

Domestic price ($/mbf) 388.00 368.40 369.93 388.58 388.69

∆Consumer surplus ($ mil) 108.76 253.67 241.86 104.67 103.89

∆Producer surplus ($ mil)b 21.56 192.13 -878.65 -407.23 -404.37

∆Government revenue ($ mil) n.a. n.a. 0.00 0.00 534.06

United States

Domestic price ($/mbf) 467.58 484.23 482.92 467.09 466.99

∆Consumer surplus ($ mil) -810.63 -1,796.29 -1,719.42 -781.35 -775.78

∆Producer surplus ($ mil)b 544.36 1,233.34 1,178.52 524.35 520.55

∆Government revenue ($ mil) n.a. n.a. 1070.42 537.60 0.00

Tariff Rate Quota

Q0

SF

qxD

DF

qxS

P

Canada International

Q0

P

t1

t0

p*

U.S. lumber market

Q

P

quota = q̄

= qxS–qx

D

EDUS

ESX

ESX′

t1

q̄

pu

0

t0

Quota rent

Tax revenue

U.S. market

Softwood

Lumber

Price

quota

U.S. demand

Canadian supply

without tax

Modified Canadian supply

t1P

0

t0

March 10, 2020 109

Conclusions

• Canada’s softwood lumber trade dispute with U.S. is partly of Canada’s making: we are not smart enough

• CVD, export tax or quota create scarcity rents: Who collects them? U.S. gov’t, Canadian gov’t or industry

• Obstacle: Provinces and companies cannot get together

• Canadian softwood lumber cartel may lead to anti-trust action that may lead to free trade

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