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Will agricultural
intensification
save tropical forests?
Arild Angelsen
School of Economics and Business,
Norwegian University of Life Sciences (UMB), Ås , Norway
& CIFOR , Bogor, Indonesia
arild.angelsen@umb.no

Warzaw
12.11.2013
School of Economics and Business

NORWEGIAN UNIVERSITY OF LIFE SCIENCES

Three major roles of agriculture in climate change
mitigation
1. Agric land encroaching forests (defor & A/R)

2.

Fluxes on (existing) agric land

3.

Substitution effects from changes in agric production (e.g.
biofuel replacing fossil fue: l)

Focus only on 1., and ask one main question
Can/will agric intensification save forests?
Land consuming vs. land sparing (Jevons vs. Borlaug)
(A related: land sharing vs. land sparing)
Agric intensification (increase output/ha = yield):
– Technological progress (more outputs with same inputs)
www.umb.no
– Factor substitution (more inputs per ha)

2
School of Economics and Business

NORWEGIAN UNIVERSITY OF LIFE SCIENCES

The Borlaug world
(the full belly or subsistence model)
Food

= Food

Food/pop * pop

= Food/ag land * ag land

Subs req. * pop

= yield * ag land

Ag land

= (subs req * pop) / yield

Land = ag land + forests
A simple theory of deforestation
Ag intensification (higher yield) reduce need for ag land
=> less encroachment into natural forests
Can be apllied at various scales (e.g. global food
equation)
www.umb.no

3
School of Economics and Business

NORWEGIAN UNIVERSITY OF LIFE SCIENCES

Example: cereals
1961-63

2006-08

Pct .
increase

Pop (bn)

3.13

6.62

111.6

Consumption
(kg per capita)

294.3

358.3

21.8

Area harvested
(mill ha)

653.7

697.2

6.7

Yield

1.41

3.40

141.5

Demand

Supply

Source: Stevenson et al. (2011),
based on: http://data.un.org/
www.umb.no

4
School of Economics and Business

NORWEGIAN UNIVERSITY OF LIFE SCIENCES

The Jevon world:
(A market/partial equilibrium/von Thünen model)
 Define ag rent per ha as

profit = gross sales – costs
r = py – wl – qk –vd

$

p(rice), y(ield), w(age), l(abour) per ha, q(cost of k),
k(capital), v(distance costs per km & ha), d(istance)

Policy: reduce ag rent:
Lower yield will save
the forest!

Ag rent

Deforestation (d)
www.umb.no

5
School of Economics and Business

NORWEGIAN UNIVERSITY OF LIFE SCIENCES

Can the two worlds be reconciled?
 Two very different logics

– Subsistence model and global food equation:
higher yield saves forests
– von Thünen model:
higher yield gives encroachments into forests
 How can they be reconciled?

1. Extending global food equation

2. Market demand conditions

www.umb.no

6
School of Economics and Business

NORWEGIAN UNIVERSITY OF LIFE SCIENCES

National deforestation equation (NDE) (Angelsen, 2010)
Pop * (Food cons/Pop) = (Food cons/Food prod) * (Food
prod/Ag prod) * (Ag prod/Ag land) * (Ag land/Forest) *
Forest
deforestation ≈ pop growth + ∆ food cons per capita - ∆
self-sufficiency ratio (inverse) - ∆food share - ∆yield ∆ag/forest ratio
One among several factors
Yield change can affect other factors:
Self sufficiency (more competitive)
Food share, e.g. biofuel

Be careful with identities:
they are always correct (a warning sign!)

cannot assume ceteris paribus (other factors will change)
www.umb.no

7
School of Economics and Business

NORWEGIAN UNIVERSITY OF LIFE SCIENCES

It’s the demand elasticity, stupid!
 Demand elasticity: how sensitive is demand to price

changes (1% ∆ price => x% ∆ quantity)
 What is the impact of technological change (supply shift)?

Inelastic (quantity given – 1. Borlaug world: B) vs.
Elastic (price given – 2. Jevons/von Thünen world: C)

Price

Perfectly
inelastic
demand

Supply
Supply after
tech progress

Perfectly
elastic
demand

A=C
B

A=B

www.umb.no

C

Quantity
8
School of Economics and Business

NORWEGIAN UNIVERSITY OF LIFE SCIENCES

What is the demand elasticity?
Depends on:
 How widespread is the tech change; market share
 Scale of analysis:

– The higher scale, the more inelastic demand
 Type of commodity:

– Inelastic: food
– Elastic: non-food with substitution (e.g. rubber, biofuel)

www.umb.no

9
School of Economics and Business

NORWEGIAN UNIVERSITY OF LIFE SCIENCES

Empirical studies – macro level
 Area & yield links at national level over time (by crop or

total)
 Ewers et al. (2009):

– 23 staple crops, 1979-1999, 124 countries
– The yield-area elasticity
– Borlaug hypotheses: -1
– Developing countries: -0.152 (t=-1.78)
– Developed countries: -0.089 (t=-0.57)
– Weaker and non-significant for total cropland
– Weak tendency in developing countries for the per
capita area to decline as cropland increase

www.umb.no

10
School of Economics and Business

NORWEGIAN UNIVERSITY OF LIFE SCIENCES

… empirical studies

www.umb.no

filled: developing; countries
open: developed countries
11
School of Economics and Business

NORWEGIAN UNIVERSITY OF LIFE SCIENCES

Case studies summary
Reduced
(win-win)
Intensive (high)

Impact on
deforestation
L & K intensity

Increased
(win-lose)
Saving (low)

Constrained

Farmer
characteristics
Output market

Well-off

Technology
Labour market

Cost-saving
Mobile
(migration)
Frontiers
(upland)
Local
Long term

Local

Yield increasing
Local,
segmented
Intensive
(lowland)
Global
Short term

Sector experiencing
tech. change
Scale of adaptation
Time horizon
www.umb.no

Global

12
School of Economics and Business

NORWEGIAN UNIVERSITY OF LIFE SCIENCES

Win-win outcomes
 Agricultural technologies suited specifically for forest-

poor areas
 Labour-intensive technologies where labour is scarce

and migration limited
 Promote intensive systems where farmers are also

involved in low-yielding extensive farming practices
 Agricultural technologies that substantially raise the

aggregate supply of products with inelastic demand
BUT, some of win-win technologies are least likely to be
adopted by farmers
– Produce commodities for local markets where prices
quickly drop
– Choose technologies that use the most scarce resources
intensively
www.umb.no

13
School of Economics and Business

NORWEGIAN UNIVERSITY OF LIFE SCIENCES

Win-lose outcomes
 Agricultural technologies that encourage production

systems that require little labour and/or displace labour
 New agricultural products for sale in large markets in

labour-abundant contexts
 Eradication of diseases that limit agricultural expansion
 Technological changes in forest margin areas with

rapidly growing labour forces

www.umb.no

14
School of Economics and Business

NORWEGIAN UNIVERSITY OF LIFE SCIENCES

Some trends
1. Globalization – increased

market integration; more likely
to be price takers
2.

land sparing
less likely

Deforestation driven by
commercial actors

3. Separation of forest and agric

land

www.umb.no

agric int.
less important

15
School of Economics and Business

NORWEGIAN UNIVERSITY OF LIFE SCIENCES

So what?
 Mistake 1: assume that technological change & agric

intensification will save forests
 Mistake 2: be against new technologies & intensification

because it may put pressure on forests
 Agric intensification needed for a number of reasons, but

forest conservation is not on top of that list
 BUT, will enable and make other forest conservation

measures more effective and politically feasible
 It’s not the solution, but part of the package

www.umb.no

16
School of Economics and Business

NORWEGIAN UNIVERSITY OF LIFE SCIENCES

Deforestation policies – what works
 Selective agric technologies
 Agric rent in frontier areas

– Roads

– Subsidies
 Forest rent and its capture

– Community management
– PES schemes
 Regulations

– Protected areas (enforcement)
– Land use planning

www.umb.no

17
School of Economics and Business

NORWEGIAN UNIVERSITY OF LIFE SCIENCES

Will agricultural intensification
save tropical forests?
“… no one can guarantee that
economic development –
whether agriculturally driven
or not – will lead to a forest
transition and an end to
inappropriate deforestation.
Informed proactive policies will
have to do that.”

www.umb.no

18

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Will agricultural intensification save tropical forests? - Arild Angelsen

  • 1. Will agricultural intensification save tropical forests? Arild Angelsen School of Economics and Business, Norwegian University of Life Sciences (UMB), Ås , Norway & CIFOR , Bogor, Indonesia arild.angelsen@umb.no Warzaw 12.11.2013
  • 2. School of Economics and Business NORWEGIAN UNIVERSITY OF LIFE SCIENCES Three major roles of agriculture in climate change mitigation 1. Agric land encroaching forests (defor & A/R) 2. Fluxes on (existing) agric land 3. Substitution effects from changes in agric production (e.g. biofuel replacing fossil fue: l) Focus only on 1., and ask one main question Can/will agric intensification save forests? Land consuming vs. land sparing (Jevons vs. Borlaug) (A related: land sharing vs. land sparing) Agric intensification (increase output/ha = yield): – Technological progress (more outputs with same inputs) www.umb.no – Factor substitution (more inputs per ha) 2
  • 3. School of Economics and Business NORWEGIAN UNIVERSITY OF LIFE SCIENCES The Borlaug world (the full belly or subsistence model) Food = Food Food/pop * pop = Food/ag land * ag land Subs req. * pop = yield * ag land Ag land = (subs req * pop) / yield Land = ag land + forests A simple theory of deforestation Ag intensification (higher yield) reduce need for ag land => less encroachment into natural forests Can be apllied at various scales (e.g. global food equation) www.umb.no 3
  • 4. School of Economics and Business NORWEGIAN UNIVERSITY OF LIFE SCIENCES Example: cereals 1961-63 2006-08 Pct . increase Pop (bn) 3.13 6.62 111.6 Consumption (kg per capita) 294.3 358.3 21.8 Area harvested (mill ha) 653.7 697.2 6.7 Yield 1.41 3.40 141.5 Demand Supply Source: Stevenson et al. (2011), based on: http://data.un.org/ www.umb.no 4
  • 5. School of Economics and Business NORWEGIAN UNIVERSITY OF LIFE SCIENCES The Jevon world: (A market/partial equilibrium/von Thünen model)  Define ag rent per ha as profit = gross sales – costs r = py – wl – qk –vd $ p(rice), y(ield), w(age), l(abour) per ha, q(cost of k), k(capital), v(distance costs per km & ha), d(istance) Policy: reduce ag rent: Lower yield will save the forest! Ag rent Deforestation (d) www.umb.no 5
  • 6. School of Economics and Business NORWEGIAN UNIVERSITY OF LIFE SCIENCES Can the two worlds be reconciled?  Two very different logics – Subsistence model and global food equation: higher yield saves forests – von Thünen model: higher yield gives encroachments into forests  How can they be reconciled? 1. Extending global food equation 2. Market demand conditions www.umb.no 6
  • 7. School of Economics and Business NORWEGIAN UNIVERSITY OF LIFE SCIENCES National deforestation equation (NDE) (Angelsen, 2010) Pop * (Food cons/Pop) = (Food cons/Food prod) * (Food prod/Ag prod) * (Ag prod/Ag land) * (Ag land/Forest) * Forest deforestation ≈ pop growth + ∆ food cons per capita - ∆ self-sufficiency ratio (inverse) - ∆food share - ∆yield ∆ag/forest ratio One among several factors Yield change can affect other factors: Self sufficiency (more competitive) Food share, e.g. biofuel Be careful with identities: they are always correct (a warning sign!) cannot assume ceteris paribus (other factors will change) www.umb.no 7
  • 8. School of Economics and Business NORWEGIAN UNIVERSITY OF LIFE SCIENCES It’s the demand elasticity, stupid!  Demand elasticity: how sensitive is demand to price changes (1% ∆ price => x% ∆ quantity)  What is the impact of technological change (supply shift)? Inelastic (quantity given – 1. Borlaug world: B) vs. Elastic (price given – 2. Jevons/von Thünen world: C) Price Perfectly inelastic demand Supply Supply after tech progress Perfectly elastic demand A=C B A=B www.umb.no C Quantity 8
  • 9. School of Economics and Business NORWEGIAN UNIVERSITY OF LIFE SCIENCES What is the demand elasticity? Depends on:  How widespread is the tech change; market share  Scale of analysis: – The higher scale, the more inelastic demand  Type of commodity: – Inelastic: food – Elastic: non-food with substitution (e.g. rubber, biofuel) www.umb.no 9
  • 10. School of Economics and Business NORWEGIAN UNIVERSITY OF LIFE SCIENCES Empirical studies – macro level  Area & yield links at national level over time (by crop or total)  Ewers et al. (2009): – 23 staple crops, 1979-1999, 124 countries – The yield-area elasticity – Borlaug hypotheses: -1 – Developing countries: -0.152 (t=-1.78) – Developed countries: -0.089 (t=-0.57) – Weaker and non-significant for total cropland – Weak tendency in developing countries for the per capita area to decline as cropland increase www.umb.no 10
  • 11. School of Economics and Business NORWEGIAN UNIVERSITY OF LIFE SCIENCES … empirical studies www.umb.no filled: developing; countries open: developed countries 11
  • 12. School of Economics and Business NORWEGIAN UNIVERSITY OF LIFE SCIENCES Case studies summary Reduced (win-win) Intensive (high) Impact on deforestation L & K intensity Increased (win-lose) Saving (low) Constrained Farmer characteristics Output market Well-off Technology Labour market Cost-saving Mobile (migration) Frontiers (upland) Local Long term Local Yield increasing Local, segmented Intensive (lowland) Global Short term Sector experiencing tech. change Scale of adaptation Time horizon www.umb.no Global 12
  • 13. School of Economics and Business NORWEGIAN UNIVERSITY OF LIFE SCIENCES Win-win outcomes  Agricultural technologies suited specifically for forest- poor areas  Labour-intensive technologies where labour is scarce and migration limited  Promote intensive systems where farmers are also involved in low-yielding extensive farming practices  Agricultural technologies that substantially raise the aggregate supply of products with inelastic demand BUT, some of win-win technologies are least likely to be adopted by farmers – Produce commodities for local markets where prices quickly drop – Choose technologies that use the most scarce resources intensively www.umb.no 13
  • 14. School of Economics and Business NORWEGIAN UNIVERSITY OF LIFE SCIENCES Win-lose outcomes  Agricultural technologies that encourage production systems that require little labour and/or displace labour  New agricultural products for sale in large markets in labour-abundant contexts  Eradication of diseases that limit agricultural expansion  Technological changes in forest margin areas with rapidly growing labour forces www.umb.no 14
  • 15. School of Economics and Business NORWEGIAN UNIVERSITY OF LIFE SCIENCES Some trends 1. Globalization – increased market integration; more likely to be price takers 2. land sparing less likely Deforestation driven by commercial actors 3. Separation of forest and agric land www.umb.no agric int. less important 15
  • 16. School of Economics and Business NORWEGIAN UNIVERSITY OF LIFE SCIENCES So what?  Mistake 1: assume that technological change & agric intensification will save forests  Mistake 2: be against new technologies & intensification because it may put pressure on forests  Agric intensification needed for a number of reasons, but forest conservation is not on top of that list  BUT, will enable and make other forest conservation measures more effective and politically feasible  It’s not the solution, but part of the package www.umb.no 16
  • 17. School of Economics and Business NORWEGIAN UNIVERSITY OF LIFE SCIENCES Deforestation policies – what works  Selective agric technologies  Agric rent in frontier areas – Roads – Subsidies  Forest rent and its capture – Community management – PES schemes  Regulations – Protected areas (enforcement) – Land use planning www.umb.no 17
  • 18. School of Economics and Business NORWEGIAN UNIVERSITY OF LIFE SCIENCES Will agricultural intensification save tropical forests? “… no one can guarantee that economic development – whether agriculturally driven or not – will lead to a forest transition and an end to inappropriate deforestation. Informed proactive policies will have to do that.” www.umb.no 18