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Box T4. Measuring Impacts Against a Nominal Baseline Stakeholder or focus group project participants were asked if they have experienced any increase or decrease in income since the project started. This was done by firstly giving the focus group 10 counters in a basket representing their income before the project. They were then given another 10 counters and asked to show any relative changes in their household income by either adding counters to the original basket of counters or by removing them (e.g., if four counters were added to the original basket this would denote a 40% increase in income). The participants are then asked to discuss how and why they decided on this (e.g.) 40% increase. This can be done separately for all income sources if it is felt to be necessary and useful. If it is repeated with sufficient groups, arithmetic means and standard deviations can be estimated. Source: Catley et al., 2008. Another approach is to use the same number of counters (say 100) for both the ‘before project’ and ‘current’ scoring, and asking participants to distribute the 100 counters between all the possible explanatory factors or variables. This will show the relative importance of these factors at the two time points in time, but not their absolute importance. This method could be used, for example, to assess the distribution of household income from different sources. The most important parts of these exercises are the discussions of what has caused any change in the scores, and what consequences they think the identified change will have on their lives. It is possible to repeat these exercises in subsequent years, although the comparison would only be valid if it is done with the same people. Matrix scoring and pairwise ranking Matrix scoring can be used to identify and prioritize impact indicators or as a means of attributing impacts to a project or project activity. In an example involving the selection of indicators for a livelihoods and food security project in Niger, there were five main stages: a) Identification by focus groups of five current food sources: (own farm) millet production; (own farm) vegetable production; cereal bank (millet) purchases; other purchased food; and (own farm) livestock production (milk and meat); b) a pair-wise ranking of these food sources to identify the preferred food sources: these turned out to be millet and vegetable production (Table T10); c) a discussion of the reasons for preferring these food sources – the main reasons were the volume and availability of the food produced, and the ease of selling them (millet and vegetables are easier to sell than milk); d) discussion and selection of possible food preference indicators, resulting in four main indicators being selected: availability (quantity/volume); accessibility (easy to obtain/cheap); income earning or saving potential; and nutritional or health value; e) scoring of the food sources against the selected food preference indicators: this was done for each indicator, with the participants scoring 50 counters between the five food sources (see Table T11). Social Impact Assessment of Land-Based Carbon Projects (1.0) – Part II | 51
Table T10: Pair-Wise Ranking Showing Food-Source Preferences in Niger Food Source Millett Production Millet Production Vegetable Production Purchased Food Cereal Bank Vegetable Production Millet production Purchased Food Millet production Vegetable production Cereal Bank Livestock Production Millet Millet production production Vegetable Vegetable production production Cereal Bank Purchased food Cereal Bank Livestock Production Source: Reproduced with permission from Catley, A., Burns, J., Abebe, D. and Suji, O. (2008). Participatory Impact Assessment: A guide for practitioners. Feinstein International Center, Medford Table T11: Matrix Scoring of Food Sources against Indicators of Preference Indicators Millett Vegetable Purchased Cereal Bank Livestock Total Production Production Food Production Availability 15 12 5 13 5 50 Accessibility 22 8 3 13 4 50 Income/savi ngs potential 12 13 0 8 17 50 Nutritional value 6 17 6 6 15 50 Total 55 50 14 40 41 200 Source: Reproduced with permission from Catley, A., Burns, J., Abebe, D. and Suji, O. (2008). Participatory Impact Assessment: A guide for practitioners. Feinstein International Center, Medford It is interesting to note that while livestock production ranked lowest in the pairwise ranking exercise, it was the third most important food source when scored against the preference indicators. This shows that matrix scoring can be a valuable tool for measuring different indicators, and captures information which might otherwise be overlooked. Figure T16 also shows how matrix scoring was used to score different indicators in a comparison of livestock and other interventions during a drought in Southern Ethiopia. Social Impact Assessment of Land-Based Carbon Projects (1.0) – Part II | 52
Page 1 and 2:
MANUAL FOR SOCIAL IMPACT ASSESSMENT
Page 3 and 4:
Table of Contents T1 Introduction t
Page 5 and 6:
List of Boxes Box T1. General Data
Page 7 and 8:
Forest Trends’ mission is to main
Page 9 and 10: List of Acronyms (Core Guidance and
Page 11 and 12: Sections T5 and T6 present a range
Page 13 and 14: Figure T1: The Main Stages and Step
Page 15 and 16: Figure T2: Example of a Conceptual
Page 17 and 18: Figure T4: Generic Conceptual Model
Page 19 and 20: Stages 3-5 of Open Standards The re
Page 21 and 22: Figure T7: Diagram of the ROtI Anal
Page 23 and 24: table so they can be read, discusse
Page 25 and 26: Table T1: Theory of Change for Seyc
Page 27 and 28: T2.4 Participatory Impact Pathways
Page 29 and 30: Table T4: The PIPA Outcomes Logic M
Page 31 and 32: Main Sources and Further Guidance h
Page 33 and 34: T3 Sustainability Framework Approac
Page 35 and 36: Figure T12: SAPA Initiative Modifie
Page 37 and 38: 1. Identify a small group of key in
Page 39 and 40: Table T6: Example of LOAM Livelihoo
Page 41 and 42: T4 Matching Methods T4.1 Introducti
Page 43 and 44: Advantages and Disadvantages of ‘
Page 45 and 46: Box T1. General Data Collection and
Page 47 and 48: Box T3. Data Collection Methods Pro
Page 49 and 50: T6 Specific Data Collection Methods
Page 51 and 52: Table T8: Example of a Household BN
Page 53 and 54: The poverty index can range from 0%
Page 55 and 56: The PIA guide proposes the followin
Page 57 and 58: day. The ‘before project’ score
Page 59: Figure T15: “Before and After”
Page 63 and 64: Impact calendars Impact calendars c
Page 65 and 66: A large sample is needed to be conf
Page 67 and 68: Table T15: Scoring of Changes in Ag
Page 69 and 70: Table T17: QPA Scoring of Social Eq
Page 71 and 72: T6.4 Participatory Economic Valuati
Page 73 and 74: Advantages and Disadvantages of Par
Page 75 and 76: The stories are collected from thos
Page 77 and 78: Main Sources and Further Guidance D
Page 79 and 80: Table T19: Stakeholder Analysis Pro
Page 81 and 82: Figure T18. Venn Diagram with Stake
Page 83 and 84: T7.2 Problem Trees Assuming it is p
Page 85 and 86: T7.3 Scenario Analysis Scenarios ar
Page 87 and 88: Box T7. Driving Forces in a Communi
Page 89 and 90: Maack, J.N. 2001. Scenario analysis
Page 91 and 92: In terms of non-monetary benefits,
Page 93 and 94: and duration of employment, the sta
Page 95 and 96: Physical Capital Positive changes i
Page 97 and 98: these strategic resource off-limits
Page 99 and 100: einforce existing institutions or n
Page 101 and 102: PROJECT: PROFAFOR TYPE: Plantations
Page 103 and 104: their occurrence will depend in lar
Page 105 and 106: HUMAN CAPITAL Increase in perceptio
Page 107 and 108: Table T26: Potential Mid- to Long-T
Page 109 and 110: Figure T20: Example of Relationship
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Figure T22: Additional Potential So
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T9 Further Guidance on Indicator Se
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Box T9. Goals and Indicators Defini
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When selecting indicators, it is be
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Table T27: Indicator Quality Assess
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Box T10. Indicators Derived from th
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T9.5 Disaggregating Indicators Mult
Page 125 and 126:
Mayoux, L. 2001. What Do We Want to
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Landscape Outcomes Assessment Metho
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• Access to essential services (w
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T10.3 Social Indicators Derived fro
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Empowerment of women indicators:
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CCBA, 2008. Climate, Community & Bi
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James A., Pangtey V., Singh P. & Vi
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SEEP Network. 2006. Social Performa
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