Research Context and Case Study Approach
Malawi is one of the world’s most climate vulnerable countries (Barrett 2013). It faces multiple interrelated social, political, economic and environmental stressors, ranking 173rd out of 187 countries assessed by the Human Development Index (UNDP 2015), and its population faces various forms of deprivation (OPHI 2013). High levels of financial and resource poverty; food insecurity; population growth; limited access to safe water and hygiene; a high prevalence of HIV/AIDS; low literacy rates, poor access to clean, modern energy supply; and a limited coverage of transport and communications infrastructure across the country, present persistent challenges. Malawi is also highly aid dependent, with international support accounting for approximately 37 per cent of government spending and severe budgetary constraints restricting investment in public services and social protection (AidData 2016).
Dominant economic sectors (notably agriculture) and associated livelihoods are highly sensitive to climate change impacts (GoM 2006). People in the country already contend with extreme weather events, such as droughts and floods. Future climate projections suggest a high probability that extreme weather events in Malawi will increase and worsen throughout the 21st century but climate information is poorly integrated into national level policymaking (Vincent et al. 2017). Due to wider development problems, adaptive capacity is also low.
Projects pursuing CCD goals are increasingly being implemented across the country. ECRP comprised two projects: (1) the Developing Innovative Solutions with Communities to Overcome Vulnerability with Enhanced Resilience project (DISCOVER), and: (2) the Enhancing Community Resilience Project (ECRProject). ECRP projects were chosen for study because they have the most wide-reaching distributive justice implications of all CCD projects we identified as being implemented in Malawi (Online Appendix A).
The projects were financed by the UK, Norwegian and Irish Governments and were predominantly designed to help households overcome development challenges, with particular emphasis on improving food and nutrition security; increasing income and asset ownership; lessening dependence on unclean inefficient forms of energy; and reducing environmental resource degradation (DFID No Date). They also aimed to help households in Malawi adapt to climate impacts (Ibid.). In addition, the projects sought to contribute to carbon savings, therefore incorporating mitigation. In programmatic literature, projects were discussed in terms of their propensities to achieve CCD (Ibid.).
DISCOVER and the ECRProject provided direct support to 305,000 and 298,500 local people, respectively, with a range of ecosystem—and community-based activities: conservation agriculture (CA), small-scale irrigation, livestock production, solar lighting, improved cookstoves, post-harvest management, seed multiplication schemes, forestry activities and village savings and loans associations (VSLAs). Both projects began in September 2011 and ran until March 2017. The projects aimed to provide direct benefits to local people that received project support as well as indirect benefits to these peoples’ households and members of the wider community.
The ECRP targeted households that are considered particularly vulnerable in the Malawi context: female-headed, elderly, extremely resource-poor, and those with disabled or chronically ill adults (Ibid.). It professed to take measures to ensure that these households could participate in project activities alongside other local people. This represents a contractarian approach to distributive justice.
Extremely resource-poor households were considered by the projects to be particularly vulnerable because they lack the material assets to adapt to climate and development stresses and shocks (Ibid.). Elderly, disabled and chronically ill people were considered to lack the physical capabilities to do so (Ibid.). Women fare worse than men against a range of socio-economic indicators in Malawi (GoM 2006), meaning female-headed households are also considered a particularly vulnerable group.
Research was conducted in three ECRP target districts: Kasungu (ECRProject), Dedza (DISCOVER) and Nsanje (both projects) (Fig. 2). Dedza and Kasungu are both in Malawi’s Central Region and have similar socio-economic characteristics and comparable average rainfall patterns (MVAC 2005). Nsanje is located at Malawi’s southern-most point and is considered to have a lower socio-economic status than Dedza and Kasungu (Ibid.). It is one of the most climate vulnerable districts in Malawi and afflicted by more regular and severe floods and droughts than other study districts (Ibid.).
Two study villages were chosen in each district. Project field workers helped ensure that villages comprised similar household numbers; were geographically close to each other; and implemented similar project activities. In Dedza and Kasungu, two villages where households had, on average, different average levels of resource wealth (an important indicator of vulnerability in Malawi) were purposively chosen. This facilitated consideration of whether and how households’ experiences of project outcomes differed accordingly.
Framework Development
A framework was developed to evaluate CCD project outcomes (Fig. 3). A systematic literature review was conducted on English language, peer-reviewed literature to identify parameters for classifying project outcomes. Methods of Ford et al. (2011) were adopted to guide the systematic review process and identify seven parameters: (i) type; (ii) direction; (iii) stakeholder; (iv) magnitude; (v) governance level; (vi) spatial scale; and (vii) temporal scale. Table 1 summarises the results of the systematic literature review and defines outcome parameters (see Online Appendix B for supporting references).
Table 1 Descriptions of outcome parameter categories identified using a systematic literature review
Articles were sought that presented empirical findings related to outcomes of projects aiming to achieve CCD double—or triple-wins in developing countries. The scarcity of literature focussing on triple-wins meant the analysis of articles focussing on both double—and triple-wins was important for capturing a sufficiently broad list of outcome parameters
Articles were located online using the Web of Knowledge electronic database. The following search terms were used:
(“climat* change” or “climat* change adaptation” or “carbon” or “climat* change mitigation”) AND (“development” or “livelihoods”) AND (“project*” or “action*” or “activit*” or “intervention*”) AND (“Africa” or “Asia” or “South America” or “Central America” or “developing nation” or “developing country”)
The search yielded 2122 results. Articles were manually reviewed to filter-out those that did not present empirical findings related to CCD project outcomes, leaving 34 articles for final review.
A realist review approach was adopted, which has an explanatory focus and enabled understanding of why project outcomes differ across parameter categories (Pawson et al. 2005). Review findings highlight that interactions between project design and implementation processes and contextual factors can explain differences. Accordingly, the framework in Fig. 3 considers how project processes shape particular outcomes in the context of socio-ecological and political-economic factors.
Material Collection and Analysis
Data collection in Malawi took place between September 2014 and May 2015. Information was sought from ECRP stakeholders—individuals, collectives or organisations with the potential to have experienced one or more project outcome. A comprehensive stakeholder analysis was undertaken for each case study project. An initial sample of 10 stakeholders (three donor agency employees; seven NGO employees managing the ECRProject and DISCOVER) was identified through ECRP project design documentation. Additional stakeholders were identified using a snowball sampling approach. Identified stakeholders included: village households; donor agencies; NGOs implementing the projects; the national government of Malawi; and local governments.
Questionnaire surveys (n = 457) and semi-structured interviews (n = 140) enabled data to be collected from households across study villages. Intra-household distributive justice implications of the projects were beyond the scope of this study. Responses were obtained from all available and consenting households in each village, including those that were not participating in projects. In all cases, the household head or another adult household member was surveyed.
Survey data were analysed to identify project outcomes and categorise them according to outcome parameters set out in Fig. 3. Contextual factors that shaped the outcome characteristics were coded (Babbie 2008). A purposive approach was then adopted to select a sample of surveyed households to be revisited in order to conduct semi-structured interviews.
Semi-structured interviews were also used to gather qualitative data from 32 professional stakeholders: two donor agency employees; 21 NGO employees; one national and eight local government employees. Household and professional stakeholder interviewees were asked about benefits and NSEs they had experienced as a result of projects. Project outcome categories presented in Table 2 were used to structure survey and interview questions to guide data collection. Information on project design and implementation processes and contextual factors that interact to create benefits and NSEs was also sought.
Table 2 Categories for classifying project outcome type and direction
Local people’s participation within wealth ranking exercises can help enhance their precision and contextual appropriateness (Chambers 1994). Indicators were developed using a participatory approach (Jefferies et al. 2005) in order to distinguish between responses of “lower-than-average wealth”, “average wealth” and “higher-than-average wealth” households in the context of particular villages. This enabled analysis of the extent to which projects had targeted benefits towards households considered extremely vulnerable owing to the extent of their resource poverty.
Documentary material was collected and analysed. The ECRP mid-term evaluation report produced by independent consultants (LTSI 2014) provided further information on project outcomes in target districts. Both the mid-term evaluation report and the following documents were used to estimate mitigation outcomes that result from projects’ forestry, improved cookstoves and solar light components: CU (No Date); CA (No Date); SA (2015); CDI (2011).
Univariate analysis techniques were used to analyse statistics derived through amalgamating household survey responses within and across villages. CA was used to analyse survey, interview and documentary data (see Babbie 2008). Categories presented in Table 2 were used to classify outcome “type’ and “direction”. Data analysis uncovered four governance levels at which project outcomes were experienced: international; national; district; and household.
Households and professional stakeholders who reported experiencing project outcomes were asked to assess the magnitude of development, adaptation and auxiliary outcomes in interview and survey responses. Stakeholders reporting experience of benefits and/or NSEs were asked to rate outcomes in terms of their perceived importance (positive or negative). A rating scale of 1–3 was used (1 = outcomes had a near-negligible significance for stakeholders; 3 = outcomes had a very significant impact). Mean importance ratings were calculated for each outcome. The mean was calculated as a measure of central tendency because the data were neither skewed nor based on categorical variables. Constant comparison techniques were used to determine how reported project outcomes differed within and between: (a) stakeholder groups, and; (b) different household types (demarcated by wealth categories and whether households were female-headed and/or elderly-headed).
Ratings from stakeholder testimonies are inappropriate for measuring mitigation benefits. Climate inertia and variability make mitigation benefits and NSEs very hard to detect (Tebaldi and Friedlingstein 2013). When successful mitigation occurs, benefits are usually evidenced only several decades after the activities creating these benefits are instigated. Some mitigation activities, especially those involving land-use changes, can also take a long time to yield benefits. Because case study projects only began in 2011, this study took place before most mitigation outcomes had occurred or affected the climate. The magnitude of mitigation outcomes was therefore estimated in terms of tonnes of CO2 (t/CO2) expected to be saved through project activities.
Direct mitigation benefits of solar lighting and improved cookstove activities were estimated by multiplying projected household adoption figures with average carbon savings resulting from product use. No data exist concerning the quality and quantity of biomass cover resulting from ECRP forestry activities; only numbers of households participating in activities have been recorded. Making estimations of possible carbon savings is therefore extremely difficult. The Clinton Development Initiative Trees of Hope project, operating in Neno and Dowa Districts in Malawi, monitors carbon savings that result from forestry activities—woodlot regeneration, boundary planting—that were analogous with the ECRP in terms of species planted. Carbon savings are estimated using the Plan Vivo methodology, which is used to accredit projects across Africa, Latin America and the Asia-Pacific region (Plan Vivo 2017). The average expected carbon sequestration per participating smallholder farming household across the 50-year Trees of Hope crediting period was calculated (total expected carbon sequestration divided by total households). This number was then multiplied by figures projecting future ECRP household forestry activity participation rates to arrive at estimates of forestry mitigation benefits.
CA was also considered both by ECRP staff (CA No Date) and within the wider literature (Giller et al. 2015) to be able to contribute to carbon savings. Yet, no projects that measure soil carbon sequestration from CA are operational in Malawi. As such, no estimates of enhanced soil carbon storage can be provided, meaning results may underestimate direct mitigation benefits provided by the ECRP. In any case, given the discrepancies in definitions and techniques that are labelled as “CA” (Whitfield et al. 2015), it may be spurious to estimate CA carbon savings based on data from other projects.