1 of 33 © FAO January 2008 Commodity Chain Analysis A Tool for Quantitative Analysis of Socio-Economic Policy Impacts Module 1: Policy Framework Session

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© FAO January 2008

Commodity Chain Analysis

A Tool for Quantitative Analysis of Socio-Economic

Policy Impacts

Module 1: Policy Framework

Session 6: Commodity Chain Analysis

F A O P o l i c y L e a r n i n g P r o g r a m m e

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© FAO January 2008

By

of the

FOOD AND AGRICULTURE ORGANIZATION OF THE UNITED NATIONS

Lorenzo Giovanni Bellù, Agricultural Policy Support Officer Agricultural Policy Support Service, Policy Assistance and Resource Mobilization Division, FAO, Rome, Italy

and

Nathalie Guilbert, ConsultantAgricultural Policy Support Service, Policy Assistance and Resource Mobilization Division, FAO, Rome, Italy

Commodity Chain AnalysisA Tool for Quantitative Analysis of Socio-Economic

Policy Impacts

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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FAO Policy Learning ProgrammeModule 1: Policy Framework


Objectives

At the end of this session the

participants will be able to:

Name the constituting elements of a commodity chain

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.

Session based on the case of

the formal firewood chain

in Burkina Faso, Ouagadougou area

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The concept of a commodity chain

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.

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.

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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

89%

11%

firewood

other energies

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A pilot study at smaller scale for policy making

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.

A Pilot study at a reduced scale; regions analyzed are Center-West & Center-South.

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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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The firewood chain chart

Firewood woodcutters organized in Forest Administration Groups

(GGF) & Unions of GGF

Collectors –Wholesalers –processors of firewood

organized in Associations

Self -consumption

Main flows of firewood

Other flows of firewood

Self consumption flows

Final Consumers of firewood

Retailers of firewood organized in Associations

Firewood woodcutters

Informal

Collectors –Wholesalers –processors of

firewood Informal

Retailers of firewood Informal

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Actors of the chain

Three main types of actors:

Firewood producers (sale price of one ton : US$ 17.6)

Wholesalers (sale price of one ton : US$58.4)

Retailers (sale price of one ton : US$ 68)

Value added:

Firewood producers: US$ 12.8 VA per ton

Wholesaler : US$ 24 VA per ton

Retailer : US$ 1.9 VA per ton

Value Added Distribution per group of economic agents

36%

59%

5%

producers

wholesalers

retailers

Net benefits for each group of economic agents

39%

53%

8%

producers

wholesalers

retailers

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Income and margins of fallers

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.

Sell price of one ton of firewood (in US$) for organized chain

Allocation of the revenue per ton (US$)

Fund for Village

investment

Fund for Land

Development

Forest Tax (concession

fee)

Margin to Faller

17.6 1.6 4.8 2.4 8.8

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

Market increase for producers

High current and future demand of firewood

Gas used by only 2% of the population

Gas subsidy very expensive for the budget

Gas used by urban and richer part of population

Deforestation & environmental issues

Substitution of firewood, less deforestation

Gas subsidy implemented

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Lack of forestry management

No forestry control (agro-pastoral appropriation of the land)

Unfair competition vs fallers in managed areas

Loss of income for the State

Non respect of rotation delays and environment Rationalize downstream activities

Facilitate grouping of fallers

Enforce forestry regulations

Vulnerable Rural population

Severe Poverty and food insecurity of small-holders and landless people

Create employment within the chain

Unfair distribution of income among fallers and traders

Rationalize downstream activities

Reallocate subsidy resources to invest in forests management

Policy issues Facts Opportunities/solutions

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The objectives of the policy measures are:

To increase income generated and distributed in rural areas

To fight against deforestation and other environmental issues

Policy objectives

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Proposal: a «package» of two policies measures:

1. Demand side policy: Stop the butane gas subsidy to sustain demand.

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.

2. Supply side policy : investing in forest management to increase the productivity of forests (1.364.25 tons/ha) through improved reforestation, technical and organizational capacities.

National annual gas consumption 155,042,000 kg A

Subsidy price US$/kg 0.68 B

Subsidy cost to the budget US$ 105,118,476 A * B

Policy measures Identified

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Expected socio-economic impacts of the demand-side policy

Stop subsidy Price of gas

Price firewood Ouaga Po

Revenue traders

Demand firewood Ouaga

WHY? Because firewood is a substitute of gas

Quantities actually sold ?

Depends on supply:1) Supply rigid Po, Q2) Supply elastic: Po, Q (likely)

WHY? Because Po x Q as P and Q

Margins traders Mt

?Revenue fallers Rf

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Quantity (Q) Price (P) PxQ000 Tons $/Ton 000$

trader revenue 23.6 68 1604.8Costs 23.6 17.6 415.36

Without Policy margin 1189.44

faller revenue 23.6 17.6 415.36Cost 23.6 4.4 103.84Margin 311.52

Quantity (Q) Price (P) PxQ

trader revenue 73.4 68 4991.2Cost 73.4 17.6 1291.84

With policy margin 3699.36(stop subsidy)

faller revenue 73.4 17.6 1291.84Cost 73.4 4.4 322.96Margin 968.88

Quantity (Q) Price (P) PxQ Var %

trader D revenue 49.8 0 3386.4 211.0%With policy - D Cost 49.8 0 876.48 211.0%Without policy Dmargin 2509.92 211.0%

faller D revenue 49.8 0 876.48 211.0%D Cost 49.8 0 219.12 211.0%D Margin 657.36 211.0%


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Margin fallers Mf ?Depend on production costs Cf. Without supply policy: Cf , Mf

Envir. Externalities Ee ? Without supply policy: Ee

Negotiating power of faller:

Zero Low High

Inelastic SupplyMT RF

MT RF

MT RF

Elastic SupplyMTRF

MT RF

MT RF

Mt =Margins traders Rf = Revenue fallers


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Depends on demand:1) No shift: Pf , Qf2) Shift due to demand policy: Pf ,

Qf

Investment Marginal cost prod instead of

Supply firewood Fallers

WHY? Because firewood availability per ha

?

Envir. Externalities Ee

? Depends on demand:1) No shift: Ee 2) Shift due to demand policy: Ee

instead of

Expected socio-economic impacts of the supply-side policy

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Summary of combined expected policy impacts

5. Likely changes in the negotiating power of woodcutters versus traders

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

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9. Sustainable firewood supply to meet demand of present and future generations.

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;

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Combined economic impact of policies: Value added generation

Value Added per group of economic agents without and with policy (000US$)

0

500

1000

1500

2000

producers wholesalers retailers

without policy

with policy

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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 -

Larger firewood supply Employment creation

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

Combined economic impact of policies: Socio economic impacts

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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:

The gas subsidy represents 117% of the price paid by consumers:

1 Ton of firewood 0.35 Ton Equivalent Petroleum (TEP)

0.296 Tons of gas

1 Ton of gas 1.18 TEP 3.37 Tons firewood

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

Total cost of gas 1266 US$/Ton

Firewood equivalent of one ton of gas 3.37 tons firewood

price of one ton of firewood as Gas Equivalent (Us$1266/3.77)

375.7 US$/ton

Gas equivalent Economic price of 1 Ton of firewood

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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

Without policy With policy

Adjusted firewood price 150.3 US$/Ton 150.3 US$/Ton

Environmental externality per ton of firewood (estimated)

15 US$/Ton 0 US$/Ton

Firewood price applied 135.3 US$/ton 150.3 US$/Ton

Firewood use may generate deforestation:

International competitiveness of the sector: Economic pricing

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Source: Tables extracted from the FAO CCA software

Scale factor 1000

International competitiveness of the sector: Policy Analysis Matrix

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Combined impacts of policy measures on poverty: Selected indicators

Additional revenue to the poorest

Additional revenue to the closest to the poverty line

Additional revenue (random selection)

Without policy: incidence 49.52%

With policy: incidence 49.52% 49.15% 49.52%

Without policy P. Gap 34.5% of the poverty Line

With policy P. Gap 34.2% 35.0% 34.4%

For this pilot exercise, poverty impacts are calculated at regional level*.

With policy additional revenue of US$ 260/year for 1706 households.

* based on total expenditures (% of population)

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Time matters: policy implementation requires time to invest in reforestation, educate and train people in forest management.

Time matters: policy implementation requires time to invest in reforestation, educate and train people in forest management.

Combined impacts of policy measures on poverty

Remarks:Remarks:

The importance of poverty reduction impacts of policies depends on how policy measures are targeted on different social groups.

The importance of poverty reduction impacts of policies depends on how policy measures are targeted on different social groups.

Different poverty indicators could lead to rank policy options differently, e.g. poverty incidence versus poverty gap.

Different poverty indicators could lead to rank policy options differently, e.g. poverty incidence versus poverty gap.

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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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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 socio-economic 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 programmeCapacity Building Programme on Policies and Strategies for Agricultural and Rural Development

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1 of 33 © FAO January 2008 Commodity Chain Analysis A Tool for Quantitative Analysis of Socio-Economic Policy Impacts Module 1: Policy Framework Session