Toolkit for RECOFTC

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The PROFOR poverty-forests toolkitRECOFTC
September 2007
Gill Shepherd (IUCN and ODI) for PROFOR
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Introduction

• There has been growing interest in the role that
  forests play in supporting the poor and in
  reducing poverty, as this conference shows. A
  recent World Bank analysis of fifty-four primary
  studies of rural livelihoods in and near forests
  suggests that forest incomes represent at least
  20 of total annual cash and non-cash incomes
  (Vedeld et al).
• However, the case for forests has not yet been
  well-made to policy makers in key Ministries such
  as Finance, Planning or Local Government, or to
  the inter-ministerial bodies where Poverty
  Reduction Strategy (PRS) processes are located.
• PROFOR, IUCN, ODI, CIFOR and Winrock
  International decided to remedy this omission by
  undertaking country case-studies and by devising
  a toolkit for measuring forest dependence, and
  for getting locally gathered data incorporated
  into national level data-gathering. It is this
  second activity which is reported on here.

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Presenting problems

• The problems have been two-fold
• On the poverty side, there is a tendency to
  underestimate the contribution of forests, and
  off-farm natural resources in general, to
  livelihoods
• On the forestry side, reporting is typically in
  terms of the physical resource (trees planted,
  forest cover improved, timber sold) rather than
  livelihoods. Such reporting sheds no light on the
  contributions made by forests to the lives of the
  poor.
• Most countries lack the data to illustrate how
  forests contribute to the livelihoods of poor
  households.
• Such data as exists is not presented in ways that
  can be used by those designing PRSPs or by
  Forestry Ministries wanting to show their
  pro-poor credentials.

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The toolkit in brief

• The toolkit
• rapidly assesses dependence on forests
• provides a means for poor people to comment upon
  forest laws, policies and programmes and their
  impacts on local livelihoods
• delivers snapshot data on topics impossible to
  get at quickly through orthodox quantitative
  methods (but which could be followed up through
  quantitative survey methods subsequently)
• However, it cannot
• systematically monitor progress towards poverty
  reduction over time
• change political hearts and minds where there is
  absolutely no interest in a focus on the poor in
  and near forests, or the contribution of forests
  to their livelihoods.

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The Poverty Reduction Strategy Process

• About seventy poor countries are engaged in PRSP
  processes, and the PRS has become the standard
  planning framework for these countries.
• The process involves a comprehensive and
  participatory diagnosis of poverty, the
  prioritisation of actions to be taken, and the
  development of targets, indicators and systems
  for monitoring and evaluating progress towards
  them.
• Monitoring systems are based partly on data
  gathered by national statistics institutions, and
  partly on sectoral poverty monitoring.
• The first step for the toolkit team (explained in
  the manual) is to discover
• the progress made to date in the PRS process
• The relationship (if any) between the countrys
  forest/natural resource ministry and the PRS
  process

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The PRSP and the Forest sector

• There is demand from Forest Ministries for new
  forms of reporting in the context of demand that
  they supply the PRSP with summary poverty data.
• From the point of view of the PRSP, there are two
  choices
• to modify the way in which forest data is
  collected and processed annually within the
  forest sector
• To seek for ways of inserting forest-relevant
  topics and questions into more general surveys.
• The second is easier in the short run, but in
  the longer run the first will also be essential.
• The toolkits rural data-gathering can contribute
  to both.

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Applying the toolkit in the field to generate
information for the national level
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Wealth ranking can be a difficult topic

• The toolkit exercise begins with wealth ranking
  and sample selection within a chosen village
• In Tanzania, key wealth indicators were cattle
  and land holdings
• A wealthy household owned 30 or more cattle and
  10 or more ha, while at the other end of the
  scale, a very poor household 0-1 cows and 0-1 ha
  of land.
• In Indonesian Papua, wealth and poverty could not
  be discussed directly. It was decided that since
  wealth and age went together, focus groups could
  be chosen from older married, younger married,
  and young unmarried men and women.
• In southern Ghana much difficult discussion was
  finally resolved as follows. The wealthy lived in
  their own houses (not family compounds) and were
  large cocoa farmers. Others ranged from small
  cocoa farmers down through seasonal crop farmers
  to those with no land and no permanent job.

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Wealth Ranking

• Selecting 4 wealth-ranked focus groups (2 male, 2
  female) by
• Writing the names of all village household heads
  on cards.
• Sorting of cards by the village Committee into
  tins representing the 4 wealth categories.
• Selecting male and female wealth groups.
• The tools are subsequently worked through in
  these groups, without explicit discussion of
  wealth or gender.

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Livelihood Analysis

• We explained to the four focus groups in
  Busongo, Shinyanga, Tanzania that a households
  income comes from all the non-cash and all the
  cash sources which enable a household to get
  through the year successfully.
• It includes
• All the items grown on farm or gathered from
  forests (including timber) or other off-farm
  natural resources, and sold.
• All the items, grown on farm or gathered from
  forests (including timber) or other off-farm
  natural resources, and eaten or used at home
  without being sold.
• Money received in wages or through trading.
• Money sent by other family members living and
  working outside the community.
• Some selected results from Tanzania look like
  this.

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Livelihood Analysis poor/very poor women
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Livelihood Analysis poor/very poor women
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Livelihood Analysis rich and middling men
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Livelihood Analysis rich and middling men
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Contribution of forest resources to income

• The village of Busongo had 255 households.
• 2. Using the per capita income figure available
  for this region of Tanzania (242) and the census
  average household size for the area (6), we can
  suggest that Busongos population of 1530 (255 x
  6) owned a total village income of 1530 x 242
  370,260.
• The village wealth ranking had sorted the
  population into 18 rich HHs, 29 middling HHs,
  150 poor HHs, and 58 extremely poor HHs.
• Using a scoring system for wealth by the criteria
  the villagers gave, we found the following
• averaging rich and middle-income households we
  arrive at an annual household income figure of
  3939
• averaging poor and very poor households, the
  figure is 852.
• These figures exclude forest non-cash income.

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Contribution of forest resources to income

• Using proportions derived from the livelihoods
  tool we can see that
• For rich and middle-income households, forest
  non-cash income adds 867 (22) to an annual
  income of 3939, bringing the total up to 4806
  per annum.
• For poor and very poor house-holds, forest
  non-cash income adds 188 (22) to an annual
  income of 852, bringing the total up to 1040
  per annum.

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Example of main forest products sold in the
village of Simpa, Wasa Amenfi West District, S.
W. Ghana

• Notice the prepond-erance of only one or two
  main products for sale, plus a few very minor ones

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Example of main forest products consumed in the
village of Simpa, Wasa Amenfi West District, S.
W. Ghana

• Notice the far far wider range of products to be
  found in the non-cash consumption list, for the
  villagers of Simpa

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Forest Problems and Solutions

• Each of the 4 Groups
• brain-stormed a set of
• what they saw as key
• current problems in the
• landscape, and ranked
• them.
• The ten most important
• problems identified by
• each group were then
• discussed in more detail.
• Possible solutions were identified along with
  suggestions for where the problem could be dealt
  with in the village, in the District or
  nationally.

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Forest Problems and Solutions as seen In
Busongo, Tanzania

• EXAMPLES OF KEY PROBLEMS
• Growing landlessness and reduced access to forest
  resources needs debate at the village and
  district level, and needs raising at higher
  levels too. While illicit use of private forests
  must be dealt with through better surveillance,
  the real problem is that more communal community
  forest need to be assigned.
• Several forest product marketing problems were
  raised, from difficulties with local police on
  the road, to the need for more expertise on gum
  quality, in order to add value to the gum sales
  villagers make.
• Extension help was requested with accessing
  better seed and tree-planting material

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Identifying opportunities for getting
forests-poverty linkages into data-collection
systemsin Tanzania

• With the field-test complete, and some tentative
  preliminary data to argue with, the team returned
  to the national level and revisited the contacts
  they had made before going to the field. The
  following opportunities were identified.
• 1. PRSP Cluster 1 is concerned with growth and
  the reduction of income poverty. Goal 4 aims to
  reduce income poverty of men and women in rural
  areas, with the target of increased
  contributions from wildlife, forestry and
  fisheries to rural incomes.
• Potential action Forestry was not originally
  included in this system due to a lack of
  understanding of forests contribution to poverty
  reduction. The designers of the database are now
  revisiting this assumption.

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Identifying opportunities for getting
forests-poverty linkages into data-collection
systems

• 2. PRSP priorities and targets are linked
  sectorally through the Medium Term Expenditure
  Framework (MTEF) and budgeting processes, which
  is tied to financial resource allocation.
• Potential action The Forestry Division has to
  make a case for its contribution to poverty
  reduction, and to suggest indicators it could use
  to do so. The toolkits findings are being used
  in this process.
• 3. Forest and natural resources contributions to
  poverty reduction are not currently captured by
  the Household Budget Survey (HBS).
• Potential action Additional forestry questions
  are now being debated. Staff were convinced by
  data from the toolkit test that forestry needs to
  be included in the HBS questionnaire.

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Trying out the toolkit

• We are currently testing
• PROFORs Forests-Poverty Toolkit
• widely.
• You can download the current draft
• of the toolkit at
• http//www.profor.info/toolkits.html
• and if you are interested in trying it
• out we are happy to offer support.
• Send an email to
• gillshepherd_at_compuserve.com