Transcript Policy Framework Session 6: Commodity Chain Analysis

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FAO Policy Learnin g Programme
Module 1: Policy Framework
Session 6: Commodity Chain Analysis
Commodity Chain Analysis
A Tool for Quantitative Analysis of
Socio-Economic Policy Impacts
© FAO January 2008
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Commodity Chain Analysis
A Tool for Quantitative Analysis of Socio-Economic Policy Impacts
By
Lorenzo Giovanni Bellù, Agricultural Policy Support Officer Agricultural
Policy Support Service, Policy Assistance and Resource Mobilization Division, FAO,
Rome, Italy
and
Nathalie Guilbert, Consultant
Agricultural Policy Support Service, Policy Assistance and Resource Mobilization
Division, FAO, Rome, Italy
of the
FOOD AND AGRICULTURE ORGANIZATION OF THE UNITED NATIONS
About EASYPol
The EASYPol home page is available at:
www.fao.org/easypol
This presentation belongs to a set of modules which are part of the EASYPol Training Path
Policy Learning Programme – Module 1: Policy Framework, Session 6: Commodity Chain
Analysis (CCA): A tool for quantitative analysis of socio-economic policy impacts
EASYPol has been developed and is maintained by the Agricultural Policy Support Service,
Policy Assistance and Resource Mobilization Division, FAO.
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Module 1: Policy Framework
Session 6: Commodity Chain Analysis
Objectives
At the end of this session the
participants will be able to:
Name the constituting elements of
a commodity chain
Session based on the case of
the formal firewood chain
in Burkina Faso, Ouagadougou area
Explain why it is important to
analyse whole commodity chains
(CCA) for policy formulation
purposes
Mention some examples of CCA for
policy formulation
Recognize situations in which
policy objectives may not be
achieved due to “leakages” in the
commodity chain.
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Module 1: Policy Framework
Session 6: Commodity Chain Analysis
The concept of a commodity chain
The term “Commodity chain” denotes the group of
agents related activities and markets, who contribute
directly to the production, the transformation and
distribution to final markets of a single product.
Commodity Chain Analysis is a technique applied to assess
how public policies, investments and institutions affect
existing or planned chains for agricultural commodities.
CCA consists of quantitative analysis of inputs and outputs,
prices, value added and margins of the different agents
under different policy scenarios.
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Module 1: Policy Framework
Session 6: Commodity Chain Analysis
The global situation of the firewood chain in Burkina Faso
National firewood annual production: 4,151,642 tons (400kg
per capita)
Around 60 000 people are involved in the chain
Estimated firewood consumption in Ouagadougou: 1,100,000
tons/year
Source of energy consumed
at national level
11%
firewood
other energies
89%
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Module 1: Policy Framework
Session 6: Commodity Chain Analysis
A pilot study at smaller scale for policy making
A Pilot study at a reduced scale;
regions analyzed are Center-West &
Center-South.
Poverty incidence is higher in
these regions (around 50%) than
the average of the country
(around 46%).
Around 800 woodcutters involved;
most of them are also farmers.
17 296 ha of managed forests 
production of 1.37 tons of
firewood/ha  total production
around 24,000 tons.
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Module 1: Policy Framework
Session 6: Commodity Chain Analysis
A pilot study at smaller scale for policy making
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The production situation
Formal chain: regulated wood production in publicly managed sites.
Producers are organized in socio-professional structures called (Forest
Administration Groups (“Groupements de Gestion Forestière”) .
Groups are concessionaires of the forests.
Producers carry out activities to preserve forest resources like:
reforestation, fights against bush fires, land protection against
cattle...
Informal chain: uncontrolled wood extraction.
More numerous.
Economic agents are not grouped.
No care/worry about forest preservation.
Tax evasion.
Unfair and illegal concurrence vs. activities under public regulation.
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Module 1: Policy Framework
Session 6: Commodity Chain Analysis
The firewood chain chart
Firewood woodcutters organized
in Forest Administration Groups
(GGF) & Unions of GGF
Collectors –Wholesalers –
processors of firewood
organized in Associations
Firewood
woodcutters
Informal
Self consumption
Retailers of firewood
organized in
Associations
Collectors –
Wholesalers –
processors of
firewood Informal
Retailers of
firewood
Informal
Final Consumers
of firewood
Main flows of firewood
Other flows of firewood
Self consumption flows
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Module 1: Policy Framework
Session 6: Commodity Chain Analysis
Actors of the chain
Three main types of actors:
Value Added Distribution per group of economic
agents
Firewood producers (sale price
of one ton : US$ 17.6)
5%
36%
Wholesalers (sale price of one
ton : US$58.4)
Retailers (sale price of one ton :
US$ 68)
Value added:
producers
wholesalers
retailers
59%
Net benefits for each group of economic agents
Firewood producers: US$ 12.8
VA per ton
8%
39%
Wholesaler : US$ 24 VA per ton
producers
wholesalers
Retailer : US$ 1.9 VA per ton
retailers
53%
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Income and margins of fallers
Sell price of one
ton of firewood
(in US$) for
organized chain
17.6
Allocation of the revenue per ton (US$)
Fund for
Village
investment
Fund for
Land
Development
Forest Tax
(concession
fee)
Margin to
Faller
1.6
4.8
2.4
8.8
The average net benefit per farmer/faller earned during the campaign (3
months) is around US$ 260, which represents an important part (more
than one fourth) of the total annual income of its household (US$907).
The national average household poverty line of around US$ 1060.
Thanks to firewood production activities, farmers are
able to keep out of extreme poverty and vulnerability.
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Policy issues
Facts
Opportunities/solutions
High current and future
demand of firewood
Deforestation & environmental issues
Market increase for producers
Gas subsidy implemented
Gas used by only 2% of the population
Substitution of firewood, less
deforestation
Gas used by urban and richer part of
population
Gas subsidy very expensive for the
budget
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Policy issues
Facts
Opportunities/solutions
Vulnerable Rural population
Severe Poverty and food insecurity
of small-holders and landless people
Unfair distribution of income among
fallers and traders
Create employment within the chain
Rationalize downstream activities
Lack of forestry management
No forestry control (agro-pastoral
appropriation of the land)
Reallocate subsidy resources to invest
in forests management
Unfair competition vs fallers in
managed areas
Facilitate grouping of fallers
Loss of income for the State
Enforce forestry regulations
Non respect of rotation delays and
environment
Rationalize downstream activities
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Policy objectives
The objectives of the policy
measures are:
To increase income generated and
distributed in rural areas
To fight against deforestation and
other environmental issues
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Policy measures Identified
Proposal: a «package» of two policies measures:
1.
Demand side policy: Stop the butane gas subsidy to sustain demand.
2.
Supply side policy : investing in forest management to increase the
productivity of forests (1.364.25 tons/ha) through improved
reforestation, technical and organizational capacities.
Remark: The objective of the gas subsidy was to preserve forests.
The assumption is that this objective can be achieved by investing
resources of the gas subsidy in forest management.
National annual gas consumption
Subsidy price
Subsidy cost to the budget
155,042,000 kg
A
US$/kg 0.68
B
US$ 105,118,476
A*B
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Session 6: Commodity Chain Analysis
Expected socio-economic impacts of the demand-side policy
Demand firewood Ouaga
Stop subsidy
Price of gas
WHY?
Because firewood is a substitute of gas
Price firewood Ouaga Po
?
Quantities actually sold
WHY?
Revenue traders
Margins traders
Mt
Revenue fallers
Rf
Depends on supply:
1) Supply rigid Po, Q
2) Supply elastic: Po, Q  (likely)
Because Po x Q  as P   and Q 
?
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Expected socio-economic impacts of the demand-side policy
Quantity (Q) Price (P)
000 Tons
$/Ton
PxQ
000$
trader
revenue
Costs
margin
23.6
23.6
68
17.6
1604.8
415.36
1189.44
faller
revenue
Cost
Margin
23.6
23.6
17.6
4.4
415.36
103.84
311.52
Without Policy
Quantity (Q) Price (P)
PxQ
trader
revenue
Cost
margin
73.4
73.4
68
17.6
4991.2
1291.84
3699.36
faller
revenue
Cost
Margin
73.4
73.4
17.6
4.4
1291.84
322.96
968.88
With policy
(stop subsidy)
Quantity (Q) Price (P)
PxQ
Var %
trader
D revenue
D Cost
Dmargin
49.8
49.8
0
0
3386.4
876.48
2509.92
211.0%
211.0%
211.0%
faller
D revenue
D Cost
D Margin
49.8
49.8
0
0
876.48
219.12
657.36
211.0%
211.0%
211.0%
With policy Without policy
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Expected socio-economic impacts of the demand-side policy
Negotiating power
of faller:
Zero
Low
High
Inelastic Supply
MT 
RF 
MT 
RF 
MT 
RF 
Elastic Supply
MT
RF 
MT 
RF 
MT 
RF 
Mt =Margins traders
Margin fallers
?
Mf
Envir. Externalities
Rf = Revenue fallers
Ee
?
Depend on production costs Cf.
Without supply policy: Cf , Mf 
Without supply policy: Ee 
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Expected socio-economic impacts of the supply-side policy
Investment
Marginal cost prod instead of 
WHY?
Because firewood availability per ha 
Supply firewood Fallers
?
Depends on demand:
1) No shift: Pf , Qf
2) Shift due to demand policy: Pf ,
Qf 
Envir. Externalities
?
Depends on demand:
1) No shift: Ee 
2) Shift due to demand policy: Ee 
instead of  
Ee
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Summary of combined expected policy impacts
1. More forests managed  less deforestation and more wood
available
2. Higher level of firewood demand  larger market 
employment created  more revenues available for
woodcutters better conditions for farmers
3. More people benefit from public financial resources
4. Technical and organizational capacities of the chain’s actors
improved
5. Likely changes in the negotiating power of woodcutters
versus traders
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Summary of combined expected policies impacts [cont’d]
6. Increased Income to State through the forest tax, and to
villages through the investment village tax;
7. Employment created to manage forests
8. Less informal circuits and better sensitization on
environmental issues;
9. Sustainable firewood supply to meet demand of present and
future generations.
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Combined economic impact of policies: Value added generation
Value Added per group of economic agents without
and with policy (000US$)
2000
1500
without policy
1000
with policy
500
0
producers
wholesalers
retailers
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Combined economic impact of policies: Socio economic impacts
Larger firewood supply Employment creation
Scenarios
Total
production of
firewood
(tons)
Production per
woodcutter per
year/campaign
(tons)
Number of
woodcutters
involved
Revenue per
faller (US$)
per campaign
Without policy
(1.36 tons/ha)
23 652
29.25
809
257
With policy
(4.25 tons/ha)
73 510
29.25
2 513
257
Difference
49 857
-
1 706
-
US$ 439 124 of net revenues created at firewood producers level
1706 households will benefit from the policy
In addition more jobs will be created to manage and control the forests
VA of the whole regional chain increased by +/- US$ 2 million
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CCA software: A facility for computations
Tables extracted from the FAO CCA software
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Competitiveness of the sector with and without policy: Economic pricing
Economic prices needed for competitiveness assessment
Economic price of firewood based on price of imported gas
We know the following equivalences:
1 Ton of firewood
0.35 Ton Equivalent
Petroleum (TEP)
1 Ton of gas
1.18 TEP
0.296 Tons of gas
3.37 Tons firewood
The gas subsidy represents 117% of the price paid by consumers:
US$/Ton
Subsidised Gas price
580
Subsidy
678
Cost of gas for the country
1258
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International Competitiveness of the Sector: Economic pricing
The gas generates greenhouse effects (environmental externalities):
US$/Ton
Cost of gas for the country
1258
Environmental externalities (estimated)
8
Total cost of gas
1266
Gas equivalent Economic price of 1 Ton of firewood
Total cost of gas
Firewood equivalent of one ton of gas
price of one ton of firewood as Gas Equivalent
(Us$1266/3.77)
1266 US$/Ton
3.37 tons firewood
375.7 US$/ton
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International competitiveness of the sector: Economic pricing
Firewood energy is more difficult to use:
Price of one ton of firewood as Gas Equivalent
375.7 US$/ton
Adjustment factor (estimated)
0.4
Adjusted firewood price (375.7 US$ ton x0.9)
150.3 US$/Ton
Firewood use may generate deforestation:
Adjusted firewood price
Environmental externality per ton
of firewood (estimated)
Firewood price applied
Without policy
With policy
150.3 US$/Ton
150.3 US$/Ton
15 US$/Ton
135.3 US$/ton
0 US$/Ton
150.3 US$/Ton
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International competitiveness of the sector: Policy Analysis Matrix
Scale factor 1000
Source: Tables extracted from
the FAO CCA software
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Combined impacts of policy measures on poverty: Selected indicators
For this pilot exercise, poverty impacts are calculated at regional level*.
With policy  additional revenue of US$ 260/year for 1706 households.
Additional
revenue to
the poorest
Without policy: incidence
49.52%
With policy: incidence
49.52%
Without policy P. Gap
With policy P. Gap
Additional revenue
to the closest to
the poverty line
Additional revenue
(random selection)
49.15%
49.52%
34.5% of the poverty Line
34.2%
35.0%
34.4%
* based on total expenditures (% of population)
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Combined impacts of policy measures on poverty
Remarks:
1
The importance of poverty reduction impacts
of policies depends on how policy measures
are targeted on different social groups.
2
Different poverty indicators could lead to
rank policy options differently, e.g. poverty
incidence versus poverty gap.
3
Time matters: policy implementation
requires time to invest in reforestation,
educate and train people in forest
management.
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Conclusions
This analysis has been carried out
following the commodity chain
approach combined with the use of
household-level data.
The FAO CCA software enabled the
authors to analyze value added,
margins and competitiveness of
the chain without and with policy.
Household data + STATA software
allowed the authors to calculate
income/expenditure distribution
without and with policy and related
socio-economic indicators.
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Module 1: Policy Framework
Session 6: Commodity Chain Analysis
Links to Module 1 : Sessions 1-8
FAO Policy learning programme
Module 1: Policy Framework
Session 1:
Global socio-economic, nutritional and
environmental facts. Future trends in
world food and agriculture
Session 2:
Conceptual framework to analyse global
policy processes
Session 3:
Role of FAO
Session 4:
Right to food
Session 5:
Policy making in the national context
Session 6:
Commodity Chain Analysis (CCA): A tool
for quantitative analysis of socioeconomic policy impacts
Session 7:
Policy impact analysis, using Partial
Equilibrium Analysis (PEA) Multi Market
Models (MMM)
Session 8:
The Southland case study
FAO Policy
learning programme
Capacity Building Programme
on Policies and Strategies for
Agricultural and Rural
Development
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Module 1: Policy Framework
Session 6: Commodity Chain Analysis
T hank you!
© FAO January 2008