Evaluation of Transformational Change in the Climate ...

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Final Evaluation Report Annexes

Evaluation of Transformational Change in the Climate Investment Funds

Date: January 2019 Submitted by Itad In association with Ross Strategic and ICF

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Annexes

Contents

Annex 1 Description of the Climate Investment Funds (CIF) 3

Annex 2 TCLP Evaluation Methodology 8

Annex 3 TCLP Evaluation Key Informant Interviews 27

Annex 4 TCLP Evaluation Bibliography 37

Annex 5 Additional Examples of Contributions to Transformational Change in the Energy Sector 67

Evaluation of Transformational Change in the CIF- Annex 1

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Annex 1 Description of the Climate Investment Funds (CIF)

The CTF and the three SCF programs each have a different focus. The sections below provide a brief description of each of the main programs, as well as an overview of the funding approval and disbursement status of the portfolio. Please note that the data in these tables is based on disaggregated data by country until 30 June 2018. The summary tables in the main body of the report have more recent data dating 30 September 2018 from the draft Operational Reports. However, this data is not yet disaggregated by country.

1.1 Clean Technology Fund (CTF)

The $5.4 billion CTF is empowering transformation in developing countries by providing resources to scale up low-carbon technologies with significant potential for long-term greenhouse gas emissions savings. Over $4 billion (75 percent of CTF resources) is approved for implementation in renewable energy, energy efficiency, and clean transport. CTF funding is expected to leverage another $47 billion in co-financing from other sources.1

Nineteen countries and one regional program make up the CTF. These include Algeria, Chile, Colombia, Egypt, India, Indonesia, Jordan, Kazakhstan, Libya, Mexico, Middle East and North Africa Region, Morocco, Nigeria, Philippines, South Africa, Thailand, Tunisia, Turkey, Ukraine, and Vietnam.

Figure 1: CTF Portfolio Overview

1 https://www.climateinvestmentfunds.org/topics/clean-technologies

https://www.climateinvestmentfunds.org/topics/clean-technologies


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1.2 Scaling up Renewable Energy Program (SREP)

The $720 million Scaling Up Renewable Energy Program in Low-Income Countries (SREP) is empowering transformation in the world’s poorest countries by demonstrating the economic, social, and environmental viability of renewable energy. It supports scaled-up deployment of renewable energy solutions like solar, geothermal, and biomass to increase energy access. It has a significant focus on mini-grids, providing more than $200 million for projects in 14 countries.

Twenty-seven countries in total are participating in the SREP. These include the following: Armenia, Bangladesh, Benin, Cambodia, Ethiopia, Ghana, Haiti, Honduras, Kenya, Kiribati, Lesotho, Liberia, Madagascar, Malawi, Maldives, Mali, Mongolia, Nepal, Nicaragua, Rwanda, Sierra Leone, Solomon Islands, Tanzania, Uganda, Vanuatu, Yemen, and Zambia.

Figure 2: SREP Portfolio Overview


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1.3 Pilot Program for Climate Resilience (PPCR)

The $1.2 billion PPCR supports developing countries and regions in building their adaptation and resilience to the impacts of climate change.

The PPCR program has two stages. The first phase is the preparation of a Strategic Program for Climate Resilience (SPCR), followed by an investment implementation phase. First, the PPCR assists governments in integrating climate resilience into strategic development planning across sectors and stakeholder groups. Second, it provides concessional and grant funding to put the plans into action and pilot innovative public and private sector solutions.2

There are 28 PPCR countries and two regional programs, including Bangladesh, Bhutan, Bolivia, Cambodia, Caribbean Region, Dominica, Ethiopia, Gambia, Grenada, Haiti, Honduras, Jamaica, Kyrgyz Republic, Madagascar, Malawi, Mozambique, Nepal, Niger, Pacific Region, Papua New Guinea, Philippines, Rwanda, Samoa, St. Lucia, St. Vincent & the Grenadines, Tajikistan, Tonga, Uganda, Yemen and Zambia.

Figure 3: PPCR Portfolio Overview

2 https://www.climateinvestmentfunds.org/topics/climate-resilience

https://www.climateinvestmentfunds.org/topics/climate-resilience


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1.4 Forest Investment Program (FIP)

The Forest Investment Program (FIP) is empowering developing countries to manage natural resources in a way that achieves the triple win of being good for forests, good for development, and good for the climate. It provides direct investments to address the drivers of deforestation and forest degradation. FIP grants and low-interest loans help governments, communities, and business stakeholders work together to achieve sustainable solutions supporting the people and economies that rely on forests while maintaining the important environment services that forests provide.3 23 countries participate in the FIP, including the following: Bangladesh, Brazil, Burkina Faso, Cambodia, Cameroon, Congo Republic, Cote d'Ivoire, Democratic Republic of Congo, Ecuador, Ghana, Guatemala, Guyana, Honduras, Indonesia, Lao People's Democratic Republic, Mexico, Mozambique, Nepal, Peru, Rwanda, Tunisia, Uganda and Zambia.

The Dedicated Grant Mechanism (DGM) established in 2009 is intended to enhance the ability of Indigenous Peoples and Local Communities (IPLCs) to engage with to enhance their capacity to engage in and contribute to local, national, and international REDD+ dialogue and actions. The DGM is managed by the World Bank, and provides a combination of grant funding and capacity building to IPLC groups. It features both a country-level component, whereby a National Steering Committee (NSC) governs sub-project grant-making with the support of a National Executing Agency (NEA), and a global component whereby IPLC representatives in a Global Steering Committee engage in international climate and forestry processes, supported by a Global Executing Agency. The DGM included 14 country projects and a global learning and knowledge exchange program.4

Figure 4: FIP Portfolio Overview

3 https://www.climateinvestmentfunds.org/topics/sustainable-forests 4 https://www.dgmglobal.org/about-us/

https://www.climateinvestmentfunds.org/topics/sustainable-forests

https://www.dgmglobal.org/about-us/


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1.5 The CIF are also supporting a set of dedicated private sector programs

Under the CTF, the dedicated private sector programs (DPSP) are dedicated funding windows that provide risk-appropriate capital to finance high-impact, large-scale private sector projects in clean technology, such as geothermal power, mini-grids, energy efficiency, and solar photovoltaic (PV). Launched in 2013, the programs serve as a platform for CIF partner MDBs to work together and identify DPSP funding opportunities that can be deployed rapidly, efficiently, and in large enough volumes to move markets in CIF target countries. DPSP is supporting 22 projects with over $420 million in investment.5

For the SCF programs, there are Private Sector Set Asides (PSSAs). These allocate concessional financing on a competitive basis to projects that engage the private sector in sustainable forestry (FIP), climate resilience (PPCR), and energy access through renewable energy in low-income countries (SREP). They are designed to spur innovation and flexible delivery of financing. The set asides serve a complementary role to country investment plans, which generally favor public funds in these sectors, with their aim to provide the risk-appropriate capital needed to drive private sector investments in some of the world’s most challenging markets6.

5 https://www.climateinvestmentfunds.org/dedicated-private-sector-programs 6 https://www.climateinvestmentfunds.org/private-sector-set-asides

https://www.climateinvestmentfunds.org/dedicated-private-sector-programs

https://www.climateinvestmentfunds.org/private-sector-set-asides


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Annex 2 TCLP Evaluation Methodology

1 Introduction

1.1 Context

1. Supporting the transformation to low-carbon, climate-resilient development is an overarching goal of Climate Investment Funds (CIF) and a global priority, as articulated in the Sustainable Development Goals and the Paris Agreement. Recognizing the important learning CIF could contribute on the topic of transformational change, CIF’s Evaluation and Learning (E&L) Initiative established the Transformational Change Learning Partnership (TCLP) in 2017. The overall purpose of TCLP is to increase the transformative impact of CIF investments and those of other funds by establishing a more systematic and thorough understanding of transformational change in CIF context.

2. In its first phase of work, TCLP identified and defined four dimensions of transformation, on the understanding that these dimensions may look different in different circumstances. CIF-supported investments and processes are intended to catalyze and advance activities that lead to long-term transformational impacts. Incremental processes may also be combined or used in sequence to create transformational change. Through an analysis of CIF’s portfolio of investments (Phase 1 Portfolio Analysis—see below,) TCLP also identified nine arenas of intervention: financing; governance and engagement; institutions; knowledge and information; markets; natural capital; policies and regulations; practices and mindsets; and technologies and infrastructure. However, the independent evaluation of CIF in 2014, as well as the recently completed CIF Phase 1 Portfolio Analysis, found that not all projects or programs were clear about how they would produce or contribute to transformational change, especially in terms of replicating or scaling successful CIF projects.7

3. In Phase 2, the TCLP continued to deepen the understanding of transformational change through a combination of evaluation, facilitated learning, and evidence synthesis. This work was divided into three related work areas (see Box 1.) These work areas were integrated and synergistic: they each involved discrete activities, but they were also interrelated, iterative with each other, and dynamic and reinforcing in this way. Each work area informed and was informed by the others.

Box 1: TCLP Phase 2 work area

Work area 1: Evaluation of transformational change in CIF

Work area 2: Facilitated learning process with TCLP

Work area 3: Evidence synthesis on transformational change in CIF

1.2 Evaluation purpose and scope

4. According to the Terms of Reference (ToR), the purpose of the evaluation was to “carry out evaluative activities to better understand and assess transformational change in the CIF context.” With a view to the complex and “wicked” nature of the climate change challenge, the evaluation placed great emphasis on learning from what has worked and in what contexts or conditions and what lessons can be drawn from this that can inform other investments. It aimed to understand how and to what extent CIF has contributed to transformational change in the context of those countries and partnerships through which it operates. Its primary focus was to systematically identify evidence of a) CIF’s role in contributing toward transformational change,

7 https://www.afdb.org/fileadmin/uploads/opev/Documents/Independent_Evaluation_of_the_Climate_Investment_Funds.pdf.

https://www.afdb.org/fileadmin/uploads/opev/Documents/Independent_Evaluation_of_the_Climate_Investment_Funds.pdf


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b) understand what barriers exist to transformation, and c) understand in what context transformation is most likely to occur. The evaluation was primarily a learning exercise and did not seek to evaluate the overall performance of CIF across its portfolio.

5. The evaluation approach was principled, pragmatic, and utilization-focused, following CIF’s guiding principles for E&L in terms of being strategic (responding to E&L learning priorities,) applied (with a practical orientation and applied focus,) fit-for-purpose (using approaches and methods driven by intended users,) learning-oriented (linked to evidence-based facilitated learning practices), and innovative (using data collection methods with systems- and complexity-informed analyses).8 The evaluation design used a clearly defined approach for selecting methods and a theory-informed evaluation design to answer TCLP’s questions.

1.3 Evaluation audience

6. The evaluation is intended to be useful to a broad range of audiences. The key audiences for and users of this evaluation include CIF recipient countries, CIF donors, multilateral development banks (MDBs), CIF’s Administrative Unit (AU), local CIF stakeholders, the broader climate finance community, and others, possibly to include private sector interests—each of which may have its own areas of interest, as described in TCLP’s Approach Paper (circulated in 2017.) The evaluation report will be circulated to the CIF Trust Fund Committees to inform strategic discussions at their meeting in January 2019.

7. Key stakeholders, particularly members of TCLP, called for credible, reliable, and rigorous evidence of CIF achievements, as well as key areas where improvements will be required. Likewise, there was a need to ensure the evaluation process is fit-for-purpose and the findings useful and actionable for improving the design and implementation of interventions. Overall, we employed a pragmatic, practical approach to the evaluation, including an engaging and interesting process for the key stakeholders and real, actionable recommendations to CIF and beyond. We also worked closely with the other work area teams to ensure that approaches and data were shared in real time to maximize cross-learning and synergies.

2 Evaluation Questions and Definitions

2.1 TCLP questions

8. TCLP had previously developed a set of suggested TCLP “Evaluation Research and Learning Questions” (hereafter referred to as TCLP questions)9 to guide work in both Phase 1 and Phase 2, which were included in the ToR for this assignment (dated November 2017.)10 These questions were partly addressed through the Phase 1 Portfolio Analysis and facilitated learning processes. Phase 2 activities—including this evaluation, the facilitated learning process, and the evidence synthesis—built on this prior work and generated new evidence and analysis to further address these questions.

9. At the kick-off meeting for TCLP Phase 2—held in early 2018—these questions were further discussed and some suggested refinements were made. This evaluation made the greatest contribution to addressing Questions 2 and 3, and through this contributed to Question 4 in terms of its recommendations and Question 1 in terms of refining the definition of transformational change in this field. TCLP’s questions are summarized in Table 1.

8 Evaluation Research and Analysis Plan. 9 We believe it is simpler and more accurate to identify the set of questions simply as “TCLP questions” rather than as “Evaluation Research and Learning Questions.” 10Annex 1 of the ToR.


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Table 1: Proposed questions to be addressed by Phase 211

High-level question Sub-question

1. Definitions: How is transformational change conceptualized in the international field of climate finance?

1.1 How have CIF and other climate finance institutions and researchers conceptualized transformational change?

1.2 What conceptualizations, definitions, and theories of transformational change would be most useful for CIF?

2. Process and design: To what extent and how does CIF’s approach for planning, designing, and implementing its investments work to advance transformational change?

2.1 To what extent and how have processes for planning, designing, and implementing CIF-supported investments supported transformation?

2.2. To what extent and how have CIF partnerships and implementation modalities supported transformation?

3. Results: To what extent, how, and under what conditions are CIF-supported investments and activities contributing to transformational change?

3.1 What is the emerging evidence for transformation (including interim signals) in CIF’s investment portfolio?

3.2 How is transformation being delivered by CIF investments and what can be learned about the nature of the transformation process?

4. Learning: How can CIF and others increase their contributions to transformational change?

4.1 What might CIF do differently going forward to maximize the likelihood of transformational impact?

4.2 What can others learn from the experience of CIF to deliver more transformational climate finance programming?

3 Concepts and Theories of Transformation

3.1 Definition of transformational change

10. In Phase 1, TCLP established a working definition of transformational change to provide a conceptual framework for its work, as shown in Box 2. Building on this definition, TCLP’s Phase 1 process also developed a high-level theory of change (ToC) (see below,) supported by four program-level ToCs. The high-level ToC identifies four dimensions of transformational change.

• Relevance defines the strategic focus of CIF investments that accelerate or shift the trajectory of progress toward low-carbon development and climate-resilient development, with sustainable development co-benefits.

• Systemic change refers to fundamental shifts in system structures and functions—in patterns of individual, institutional, community, and/or private sector decision-making, actions, and behaviors in targeted markets or other systems that advance low-carbon and climate-resilient development.

• Scale refers to contextually large-scale transformational processes and impacts—catalytic processes that significantly expand and diffuse (upward, downward, or outward) the development and deployment of low-carbon and climate-resilient technologies, infrastructure, and other innovations, increasing their supply and access.

• Sustainability refers to the robustness and resilience of changes that are financially, economically, environmentally, socio-politically, or physically robust and resilient. These changes are durable and lasting in ways that lessen the likelihood of reverting back to past practices, and persist over time.

11 The darker shaded questions illustrate the evaluation’s primary analytical focus.

Box 2: TCLP definition of transformational change in climate action

Strategic changes in targeted markets and other systems with large-scale, sustainable impacts that accelerate or shift the trajectory toward low-carbon and climate-resilient development.


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Table 2: TCLP Phase I draft CIF theory of transformational change


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11. The evaluation team reviewed the transformational change definition, ToCs, arenas, and dimensions and considered them a sufficient starting point for framing and setting the boundaries of the evaluation. Through its hypothesis-driven approach, the evaluation added further detail to some of these theorized change processes, also factoring in contextual factors, improving the evaluability of the ToCs.

12. The Phase I Portfolio Analysis document summarized the definitions of arenas, pathways, and impacts. Activities across up to nine different arenas of intervention addressed a range of implementation barriers. The arenas focused on what types of interventions and activities were being used across CIF’s portfolio.

13. Interventions were configured to address identified barriers and to advance systemic changes, so-called implementation pathways. The evaluation hypotheses further specified some of these implementation pathways. Outcomes and impacts were recorded as signals of progress in advancing systemic changes or scaling that could be indicative of transformation.12

Through the exploration of the dimensions of transformation and particularly the dynamics between these dimensions, the evaluation also assessed the transformational processes that support the links from one dimension to another. It considered how transformation works, also in interaction with the external context. The evaluation reviewed the extent to which the dimensions are sequential (i.e., relevance > systemic change > scale-up > sustainability,) interdependent but non-sequential, or potentially independent (depending on program context.) We explored the pathways implicit in these relationships, as well as signals of change that captured the dynamics of the transformation process.

3.2 Signals of transformational change

14. The evaluation identified different types of signals of transformational change in those countries reviewed and from across the wider CIF portfolio. We defined “signals of transformational change” as pieces of evidence suggesting that transformational change is likely to occur (or has already done so.) This built on work undertaken with TCLP to identify typical signals of transformational change and to create a taxonomy for how they might be classified and understood. Notably, a working definition and examples of signals at various levels for the transformational change dimensions was developed for the internal purposes of the evaluation. The ambition was not to design indicators of transformational change. While the evaluation contributed to the conceptual definition and testing of these signals through the evaluation, further work on these concepts and related definitions is recommended for the future (see section 8.) An understanding of the signals of transformational change helped inform what transformation is and how signals might differ between programs or sectors, across

12 Ross Strategic and Community Science (2018).

Box 3: Evolving signals of transformational change

Recognizing that transformational change occurs as a process and that signals of transformational change become more robust over time, the evaluation identifies three stages of signals.

▪ Early signals are evidence that programs are not only thematically relevant but have also been designed and implemented in such a way as to promote transformational impact (e.g., integrating political economy considerations, engaging national support from key champions, and aligning with regional initiatives likely to support change processes.)

▪ Interim signals indicate that external change processes linked to direct program outputs are underway and that these are likely to result in future climate benefits (e.g., greenhouse gas (GHG) mitigation, improved resilience, sustainable forests,) but have not yet been fully realized.

▪ Advanced signals indicate that climate impacts core to the mandate of CIF’s programs are being delivered at scale, with systemic underpinning and in a sustainable manner beyond CIF’s program boundary.


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dimensions, and along a continuum of change. Box 3 summarizes our understanding of early, interim, and advanced signals. Key questions to recognize transformation better include:

a. What do concepts of scaling, systemic change, or sustainability actually mean in a climate finance context?

b. How do signals of transformation emerge and strengthen over time, given the incremental nature of change processes?

c. How do different programs achieve transformation through different pathways (and what are the implications for which signals are likely to be associated with each)?

15. In line with the working definition of transformational change, we focused particularly on changes that have occurred (or are likely to occur) beyond the direct boundaries of CIF project activities and outputs during or after the lifetime of the intervention. For the purposes of this evaluation, evidence that project beneficiaries are themselves experiencing transformational changes was often not sufficient to be identified as signals of transformational change. As a result, it is possible that a program implemented successfully may still not have delivered transformation if it fails to influence systems or support the scaling of outcomes beyond its defined project boundaries.

4 Evaluation approach

16. We undertook a theory-based evaluation approach to develop hypotheses that enabled us to address the evaluation questions across the range of programs in CIF’s portfolio.

17. The theory-based, hypothesis-driven evaluation utilized a well-defined approach, including contribution analysis and comparison across cases, drawing on a broad range of data sources to establish the evidence base for its findings. We used primarily contribution analysis and comparative analysis as the defining approach of the evaluation. Contribution analysis was best suited to increasing our understanding of transformational change and the mechanisms of how, and under what circumstances, transformation may take place. The approach is summarized in the Figure 2, and the following sections describe it in more detail.

Figure 5: Overview of the evaluation approach


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4.1 A theory-based, “hypothesis-driven” approach

18. The evaluation explored the transformational change process through five core mechanisms of transformational change (hypotheses.) These five hypotheses clustered around concepts of 1) scale and demonstration effect; 2) policy and institutional support to create market tipping points; 3) mainstreaming and investment incentives; 4) multi-level efforts to address complex socio-economic systems; and 5) financial and supply chain intermediation. While each hypothesis may be relevant to multiple thematic areas (energy, resilience, sustainable forests,) the scope of inquiry for each was bounded for the purposes of this evaluation. The first two hypotheses were explored in the context of CTF and SREP; the third hypothesis was examined in PPCR; the fourth hypothesis was taken up for FIP; and the fifth hypothesis was applied to a cross-cutting analysis across CIF’s portfolio.

19. These hypotheses were developed and refined in a participatory manner in the early stages of the evaluation work and were iteratively refined and tested through the desk review and fieldwork. The full set of working hypotheses is summarized below:

20. In addition to these hypotheses, we also examined three cross-cutting themes that were relevant to all seven core hypotheses. These were:

• the structure and operating model of program design and implementation as a key element

in supporting transformational change

• the context in which programs are implemented as a key determining factor in the

likelihood and scale of transformation

Box 4: TCLP hypotheses

H1. The provision of long-term concessional finance at scale can be a crucial factor in changing perceptions

of risk among investors, particularly in the context of infrastructure projects with high capital costs, complex supply chains, or innovative technology profiles.

H2. Combining climate mainstreaming with investment programming creates incentives for policy makers

to engage on the climate agenda, while also providing learning opportunities to inform the better development of relevant policies, planning, and institutional frameworks across sectors.

H3. Coordinated, multi-level efforts that strengthen policy, institutional, social, and market capacities are

needed to address fundamental market and policy failures to value natural capital and wider environmental externalities.

H4. It is possible to create market tipping points for (near) cost-competitive low carbon technologies by

combining policy reform with support for market development, incentive frameworks, and other innovative approaches to mitigate investor and developer risk.

H5. Working through intermediaries and supporting value chain development is an effective way to deliver

transformation in the context of smaller-scale investments in climate goods and services. H6. Working through the MDBs has enabled CIF to influence the climate orientation of much larger

development finance institutions and funding flows. H7. Gender equality efforts in institutional, policy, and investment processes help CIF support

transformational change.


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• transformation as a dynamic, complex, and non-linear process, but one for which it is

possible to identify signals of imminent change.

4.2 Mixed-Methods Evaluation and Data Collection

21. TCLP’s evaluation team (EVT) applied a mixed-methods approach to the evaluative analysis and data collection process. This process is summarized in Figure 2 and can be divided into three stages. Stage 1 was data collection, which involved four main primary data collection tools: 1) supplemental analyses of data and information from the broader CIF portfolio (Phase 2 Portfolio Analysis activities); 2) KIIs and Focus Group Discussions (FGDs); 3) secondary research on external context; and 4) an e-survey. These data sources informed two key data collation exercises: 5) data-informed case studies; and 6) more contextual and thematic analyses. These collation exercises served as the key inputs for the evaluative analysis. This analysis was focused on: 7) testing the hypotheses, using contribution analysis and comparative analysis; 8) the signals of transformation along the four dimensions of transformational change; which in turn informed the process of 9) addressing the four TCLP questions.

Figure 6: Data Collection, Collation and Analysis Process

Each stage of this process is briefly summarized below.


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4.3 Phase 2 Portfolio Analysis activities

22. The Phase 1 Portfolio Analysis13 played a useful role in testing the transformational change concepts developed in Phase 1 and in informing the design of the Phase 2 hypothesis-driven evaluation approach. During Phase 2, the evaluation team conducted targeted analyses to update and supplement the Phase 1 Portfolio Analysis information to further explore transformational change concepts in CIF’s portfolio. The Phase 1 Portfolio Analysis included desk reviews of 32 CIF country and regional programs.14 Phase 2 Portfolio Analysis activities included updating the analyses from Phase 1 to include more recent program and project monitoring and reporting data. Phase 2 Portfolio Analyses also included desk reviews of an additional 11 country programs not covered in the Phase 1 analyses, resulting in 43 total CIF country and regional programs being covered by Phase 1 and 2 Portfolio Analysis desk reviews.15 The Phase 2 Portfolio Analysis activities focused primarily on supporting the hypothesis-driven approach to the overall evaluation, identifying and elevating information across CIF’s portfolio that was relevant to informing inquiry around specific hypotheses.

23. As during Phase 1, Phase 2 Portfolio Analysis activities relied predominantly on standard program and project planning monitoring data, such as CIF Project Information System data and monitoring and reporting data.16 Phase 2 Portfolio Analysis activities were used 1) to identify specific types of signals to indicate interim progress toward transformational change and to further develop the transformational change rubric; 2) to compile and update Phase 1 Portfolio Analysis data to support the exploration of the identified hypotheses (e.g., barriers relevant to CIF programs; examples from additional countries beyond the case study countries to complement specific evaluation findings); 3) new country-level research and analysis to inform the country case studies (particularly the light-touch case studies); and 4) portfolio-wide analysis on specific topics (e.g., geothermal energy; MDB approval and disbursement status for countries across CIF’s portfolio.)

4.4 KIIs

24. The evaluation team conducted semi-structured KIIs face-to-face with selected stakeholders, as well as working remotely by telephone with stakeholders and counterparts around the world. In total, 250 KIIs were conducted.17 This included 105 representatives from all six MDB partners, with a focus on the staff responsible for CIF at both headquarters and in country. Eighty-five government representatives were interviewed, where the initial sample was identified with support from CIF’s AU and the lead MDB in the country. Likewise, the private sector (23), civil society (29), and donor representatives were also identified and interviewed. The semi-structured interviews were conducted based on interview guides ensuring the systematic coverage of topics by team members consulting with stakeholders possibly at different times, while retaining the flexibility to pursue unforeseen avenues of inquiry as they arose. The guides were designed and iteratively tested and improved. All KIIs were documented and anonymized with a view to research ethics, data security, analysis, and comparison across cases.

13 Ross Strategic and Community Science (2018), “Climate Investment Funds: Exploring Transformational Change in CIF’s portfolio, Phase 1 Research Findings from the Transformational Change Evaluation Team.” March. 14 This included 31 country programs across 30 countries (document review for Mexico covered both FIP and CTF programs) plus the MENA CTF regional program. 15 The 43 CIF country and regional programs reviewed covered 37 countries (note: Bangladesh, Honduras, Mexico, Mozambique, and Nepal each had two programs included) plus the MENA region. The Phase 1 and 2 Portfolio Analysis covered all 23 countries (and 26 country programs) covered by the Phase 2 evaluation case studies, as well as 14 additional CIF countries (representing 17 additional country programs). 16 CIF Country investment plans; CIF and MDB project documentation; CIF results reports and semi-annual CIF portfolio reports; CIF Knowledge and Evaluation products; CIF Project Information System database information; selected CIF and MBD knowledge products and reports. 17 The total sample included representatives from MDBs, government, civil society, private sector, donors, and some independent experts (10). Final beneficiaries were mainly interviewed through FGDs.


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25. Three FGDs were conducted in Niger during a site visit with primary beneficiaries to gather the first-hand account of any co-benefits and other results CIF has delivered or could be delivering in pathways toward mitigation and resilience-building and the contexts in which they take place. A gender-sensitive approach was taken to the FGDs, with discussions conducted privately among women—for example, in Niger.

26. The interview guide provided guidance on a limited set of simple topics to be covered, focusing on any perceived positive or negative changes resulting from CIF investments. Like the KIIs, the FGDs were documented.

4.5 Secondary research on external context and trends

27. The hypotheses were developed, together with an initial desk-based review of the most relevant documentation, including the most substantial CIF research on the main programs, the Phase I Portfolio Analysis, and relevant and available external data and research. Evidence gathering was closely coordinated with CIF’s AU and ODI-led evidence synthesis work area,18 also with a view to ensuring research quality.

28. Beyond the Phase 2 Portfolio Analysis, the work of ODI, and the wider E&L initiative, our understanding of the general context (and of individual cases and hypotheses) was also informed by additional secondary research. Our contextual understanding was particularly

18 ODI and Itad have liaised closely during the inception period and, for example, have held joint workshops on the design of the two studies. We have agreed to closely coordinate our data collection work and have identified the broad overlaps with respect to this. In broad terms, TCLP’s EVT will collect primary data while the ODI team will collect and synthesize secondary data (including the TCLP–EVT reports.)

Box 5: KII sampling strategy

The sampling strategy for identification of KIIs for this study was predominantly a purposive snowball approach (Palinkas et al., 2016.) The objective was to reach as many people as possible across a representative spectrum of positions capable of providing an in-depth level of knowledge and insights across the evaluative areas of interest and specifically the evaluation hypotheses (Holwreck & Yin, 2014.)

Working with the technical/subject area leaders in CIF’s AU (and in close coordination with other TCLP teams,) we started by identifying a core list of suitable KII subjects based on their knowledge of the key technical areas covered in the hypotheses. The topic areas included signals of transformational change, enabling conditions and barriers to change, the process of change, and the explicit testing of the hypotheses. As we started interviews and went into the evaluation process in more detail, this core list was expanded through snowball techniques and cross-referencing across the job. The following purposive criteria were also deployed to maximize the insights that could be garnered through the KII process.

1. The initial sample was drawn up with support from the lead MDB and government focal point, with

representation across the MDBs, the government, the private sector (10 percent of interviewees,)

and civil society (10 percent of interviewees.) Efforts were made to include voices from more

vulnerable groups, particularly women (30 percent of interviewees.)

2. Snowball integration was used to identify additional individuals who had a diverse range of views

and insights into the performance of CIF.

3. Active efforts were also made to identify interviewees responsible for similar initiatives that were

not funded through CIF.

The resulting list of 250 KII represented a diverse range of opinions and viewpoints across CIF program areas and beyond (see annex 3 for a full list if KII subjects.)

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4012002/#R21

https://www.researchgate.net/publication/308385754_Robert_K_Yin_2014_Case_Study_Research_Design_and_Methods_5th_ed_Thousand_Oaks_CA_Sage_282_pages



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informed by a trends analysis of energy markets/systems and country-specific cost curves (e.g., Bloomberg New Energy Finance) and World Economic Forum Energy Transition Index, as well as by comparative data on the enabling environment and energy access (e.g., the Regulatory Indicators for Sustainable Energy Index.) Comparison across programs, countries, technologies, and other themes was further enhanced by a number of KIIs with relevant CIF AU and MDB staff (e.g., gender specialists.)

4.6 E-survey

29. An e-survey was designed with a view to gathering data from the broadest possible group of CIF stakeholders. The e-survey questionnaire was modeled on the KII interview guide, with integrated skip logic for different programs and types of stakeholders. Due to the complexity of the concept of transformational change, the questions were tested and piloted prior to the launch with a number of groups, including CIF AU staff. Twenty percent of respondents nevertheless did not fully complete their survey entries, perhaps due to the complexity of the subject matter. The survey was open for slightly more than a month, with the deadline extended twice, to increase the response rate during the vacation period in August. Reminders circulated by CIF’s AU had an immediate influence upon the response rate. The response was also high from the countries visited by the evaluators.

Box 6: E-survey sampling strategy

An e-survey was designed with a view of gathering data from the broadest possible group of CIF stakeholders.

Respondents were identified by CIF’s AU, based namely upon internal databases and meeting participation lists from MDBs, the government, the private sector, and civil society. The total list of identified emails was 1,057, of which 19 emails did not function, reducing the total potential population to 1,038. This figure was based on the so-called “hard” failure rate used by Survey Monkey.

The e-survey was successfully circulated to 1,038 potential respondents identified by CIF’s AU. One hundred and forty-four individuals responded (two-thirds being men) resulting in a response rate of 13.87 percent, with a survey completion rate of approximately 80 percent. There were 21 incomplete returns. While it is not possible to ensure that this purposefully selected group is representative of the whole population of CIF stakeholders and there are generally also concerns about the response rate in e-surveys, the reasonable response did capture a good spread among CIF’s programs, as well as geographic regions, including responses relating to almost all CIF countries (except Algeria and Libya.)


19

5 Data Collation

30. One of the main challenges of the evaluation was to manage and create coherence from the scale and volume of primary and secondary information gathered across the selected sample of country programs and stakeholders. The evaluation synthesis stage consisted of data collation across the different data sources into 5) in-depth, remote, and light-touch case studies, as well as 6) contextual and thematic analyses on energy, resilience, and forestry.

5.1 Case studies

31. The evaluation gathered information across CIF’s portfolio in developing and middle-income countries, with case studies of 23 countries, based on 1) country visits to five programs; 2) remote research and interviews in ten countries; and 3) light-touch desk research on eight countries. As the gathering of primary evidence focused on 15 countries, comparison of evidence is focused particularly on this group. The country programs for more in-depth review were purposively selected based on the following criteria:

• Maturity of the country portfolio—Countries with disbursement rates above 20 percent and/or more than two years in project implementation, to ensure that sufficient evidence was available on signals of transformational change.

• Relevance of country portfolio to hypotheses and representation19 across hypotheses—Countries with projects that aligned with the hypotheses being tested. The selected countries ensured sufficient coverage across all hypotheses.

• Presence of signs of transformational change (including identification of negative or mixed cases)—Countries with potential early signs of transformational change, as indicated through TCLP’s Phase 1 Portfolio Analysis, scoping consultations, and TCLP workshop feedback. The selected countries also included those with mixed or negative experiences, for instance, where early signals of transformational change were not identified in all targeted sectors.

• Representation across CIF programs, geographical regions, MDBs, technologies and sectors, country income levels—The selected countries covered all four CIF programs (with more CTF and PPCR countries covered, reflecting the higher amount of endorsed funding for these programs); all four geographical regions; all six MDBs; a range of technologies and sectors; and all three relevant country income categories.

• Adjustments for practical considerations—Where country selection was not constrained by the above-mention criteria, adjustments were applied. Countries that were recently visited under CIF’s programmatic approach evaluation were included, where feasible and appropriate, and were “topped up” as remote case studies. Countries that had substantial documentation of the results of their CIF-funded activities (e.g., through E&L or other studies) were prioritized for remote studies. Countries that had respondent fatigue or ongoing fieldwork from E&L activities were deprioritized in the selection.

32. Country candidates were assessed against these criteria based on data from CIF’s Project Information System, TCLP Phase 1 Portfolio Review, a first and second round of scoping consultations with CIF’s AU, and feedback received during the first TCLP Phase 2 Workshop (May 2–3.)20 Additional, light-touch cases were added in order to achieve the broadest sample possible. The final list of selected countries can be found in Table 2.

19 Note that representation does not equate to an objective to achieve an equal balance in coverage. 20 Note that representation does not equate to an objective to achieve an equal balance in coverage.


20

Table 3: Country case selection summary

Hypotheses to test CIF program Geographical

region Technology / sector MDBs

Income level

H1 H2 H3 H4 H5 H6 H7

CTF

PP

CR

FIP

SREP

Afr

ica

Asi

a

ECA

LAC

Ge

oth

erm

al

CSP

Sola

r

Win

d

Oth

er

RE

EE

Ad

apta

tio

n

Fore

sts

AD

B

AfD

B

EBR

D

IBR

D

IDB

IFC

Low

Low

er-

mid

Up

pe

r-m

id

IN-DEPTH CASE STUDIES:

Morocco x x x x x x x x x x

Mexico x x x x x x x x x x x x x x x x

Nepal x x x x x x x x x x x x

Niger x x x x x x x x

Honduras x x x x x x x x x x

REMOTE CASE STUDIES:

Thailand x x x x x x x x x x x

Turkey x x x x x x x x x x x x x

Chile x x x x x x x x x x

Mozambique x x x x x x x x x x x

Tajikistan x x x x x x x x x x

Zambia x x x x x x x Jamaica x x x x x x x

Kenya x x x x x x x x x

Armenia x x x x x x x x x

Burkina Faso x x x x x x x x COUNT 8 6 3 7 6 6 5 6 3 4 6 2 3 4 5 2 5 4 3 4 5 3 3 6 3 13 4 6 4 5 6

LIGHT TOUCH CASE STUDIES:

Bangladesh x x x x x x x x x x x x Maldives x x x x x x x

South Africa x x x x x x x x x x x

Indonesia x x x x x x x x x x x Samoa x x x x x x x x

Ethiopia x x x x x x x x x

Grenada x x x x x x x x x x

St. Vincent and the Grenadines

x x x x x x x x

TOTAL 12 9 3 11 11 0 10 7 10 3 8 8 6 3 6 7 3 8 5 3 5 8 3 6 8 3 21 5 10 8 7 8


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5.2 In-depth, remote, and light-touch case studies

33. The in-depth case studies were developed based on country visits of approximately five working days and consisted namely of gathering additional documentation, meetings with key stakeholders (KIIs and FGDs), and site visits (where logistics allowed.) Additional documentation consisted both of more recent program documentation, and more specific, regional or country-specific research. Photographic evidence was gathered during site visits.

34. The remote cases were populated namely from secondary sources (program documentation and research,) as well as a more limited number of interviews with the lead MDB, key government representatives, and implementing partners. The light-touch cases included only reference to secondary sources, with no primary data gathering.

35. All of the cases were documented in country reports based on a standard reporting template reflecting contextual factors, enabling conditions, barriers, arenas, hypotheses, and the signals and dimensions of transformational change.

36. What this meant in practice was that we selected cases that were as varied as possible. This is illustrated in Box 5, which highlights how countries were purposively selected to ensure variation by geographical region, type of technology and sector, type of MDB presence, and income level.

37. The outcome of this sampling exercise—published in the inception report—was a selection of case studies that TCLP’s EVT were confident would generate a rich and varied set of experiences to allow testing of the seven transformational change evaluation hypotheses.

38. As case studies were selected using purposive sampling, the issue of statistical significance is not relevant. This would only be the case in a study that was trying to present a measure of effect or impact. A multiple case study design, such as this one, allows the relationship between different variables within a case to be explored in a multitude of settings. Learning was generated at a more theoretical level which can then possibly be tested later in a more formal study design.

5.3 Contextual analysis

39. Additional, contextual analysis was prepared on energy, resilience, and forestry, as well as for

the individual case studies. The contextual analysis relied mainly upon reliable, high quality

secondary data, such as that provided by Bloomberg New Energy Finance. The contextual

analysis was incorporated into the country, hypotheses, and overall evaluation report (where

relevant.)


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Box 7: Case study sampling strategy

As with any development focused intervention across a complex operational space, CIF interventions

have the potential to create negative as well as positive transformative dynamics. For example:

• Positive dynamics: CIF projects may either be disruptive (e.g., CIF has played a significant

catalytic role in facilitating transformation beyond the scope of its project outputs) or simply

aligned (e.g., CIF's role makes a pro rata contribution to transformation, but does not catalyze

other actors.)

• Neutral dynamics: There may be no evidence of transformational impact beyond the project

outputs, or a positive contribution may have been at the expense of the displacement of other

actors or stakeholders.

• Negative dynamics: There may be evidence that CIF has slowed or prevented transformation by

investing in non-transformative areas (e.g., legacy technologies or non-sustainable markets) or

has created dependency (e.g., on concessionality or technical assistance) that prevents or

distorts market development.

We selected a case study approach to investigate these dynamics within CIF interventions. A case study

approach is best when investigating complex and multi-dimensional issues such as project

implementation in diverse settings (Holwreck & Yin, 2014.) Case studies are mainly qualitative and are

not designed to generate measures of effect. As such, the sampling strategy is not designed to give a

sample that is statistically significant.

Our case studies were selected using purposive sampling. This approach is often contrasted to

probabilistic or random sampling, which is used to ensure the generalizability of findings by minimizing

the potential for bias in selection and to control for the potential influence of known and unknown

confounders. Purposive sampling is a technique widely used in qualitative research for the identification

and selection of information-rich cases, and this allows for the most effective use of limited resources

(Patton, 2002; our italics.) This allowed us to select cases that were particularly relevant to the

dimensions of interest (Cresswell & Plano Clark, 2011.)

In this evaluation, we used our seven evaluation hypotheses as the principle drivers in the selection of

our case studies. The sample was designed to capture the range of dynamics (positive, neutral, or

negative) described above. Case studies were selected across a range of countries which covered CIF’s

programs. Each case study represented a program within a country, so in some cases, we had more than

one case in a country. A program may also include several technical areas.

There exist numerous purposeful sampling designs (Palinkas et al., 2015; Patton, 2002.) For this

evaluation, the purposeful sampling design we deployed for the selection of case studies combined two

purposive design approaches, namely the “theory-based’ approach and a “maximum variation’

approach (Patton, 2002.)

Theory-based purpose design approach: As highlighted in the main text, the central tenet of our

evaluation approach was to test a number of predefined hypotheses (or theories.) The key evaluative

objective was to find “information-rich” manifestations of the theoretical construct (the hypothesis) so

as to elaborate and examine the construct and its variations. As such, the main consideration we had

from the outset was to ensure we identified a sample of case studies which would maximize the

opportunities for us to observe potential manifestation or representation of each of the hypotheses,

with the aim of exploring the dimensional range or varied conditions along which the hypothesis played

out (Bernard, 2012.)

Maximum variation purposive design approach: The key objective of this approach was to identify shared patterns that cut across cases and derived their significance from having emerged out of heterogeneity. The approach required case selection to be focused on unique or diverse variations that have emerged in adapting to different conditions.




https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4012002/


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6 Data Analysis

40. The data synthesis “worked back” across our evaluation approach allowing us to collate data collected through the fieldwork in order to 7) inform our understanding of the seven hypotheses and the cross-cutting learning themes and 8) update our understanding of the evidence across the dimensions of transformational change. The data was collated and analyzed across the main hypotheses and signals along the four dimensions of transformational change.21 The four dimensions of transformational change served as a unifying analytical framework, shared also by the ODI-led evidence synthesis work area. This analysis, in turn, allowed us to systematically 9) address TCLP’s questions. Evidence was traced back to the primary data sources through systematic referencing protocols.

6.1 Hypothesis testing

41. The hypotheses were tested through contribution analysis for their internal coherence and logic, as well as their comparative strength across cases, based on evidence from the case studies, as well as secondary literature. Contribution analysis was employed to trace hypothesized pathways of change. Multiple data sources were gathered and used to test the steps along the way of these pathways in an iterative way. Comparison was employed in assessing different arenas of change, sectors or contextual factors, such as the maturity of markets, institutional capacity, or national income level. Particular attention was given to cases where transformation was not yet achieved, to understand any related challenges.

6.2 Transformational change signals

42. We structured the collection of evidence for signals of transformational change according to the four dimensions of transformation. Relevance was a cross-cutting dimension and was reflected in early signals. We also reviewed the interaction with external drivers of transformation. The strength of signals—whether early, interim, or advanced—was assessed for each country and program.

43. The findings from the case studies also helped us draw some conclusions regarding the combination, sequencing, and interaction of intervention arenas with contextual barriers and factors. Although it was challenging to make meaningful comparisons between different countries (e.g., the case studies may serve to highlight the differences rather than the similarities between contexts,) it was still possible to synthesize some common success factors, synergies between arenas of intervention, and shared outcomes.

44. During review of individual programs, the team then sought to identify potential signals and categorize them against the dimension and stage of maturity developed earlier. This classification was done primarily for the case studies, with other information (e.g. drawn from the wider portfolio or CIF results reporting) used in a supporting fashion where appropriate.

45. The overall rating for the maturity of signals for each dimension for the overall program represent the simple arithmetic mean of the individual country programs examined (3-advanced, 2 interim and 1 early) with all country programmes weighted equally (i.e. no weighting by country program value or size).

46. We have not sought to present these at country level in the report as this is not a performance review and progress in each country reflects a whole range of factors (maturity, context, size etc.). As such comparative measures are potentially misleading and could be counterproductive (see limitations below).

21 These inputs into the Evaluation Report do not form a part of the formal, published annexes of the report, but function rather as a data source for the main report.


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6.3 Assessing strength of evidence

47. The strength of evidence across 1) the program documentation gathered through the Phase 2 Portfolio Analysis, 2) KIIs and FGDs, 3) secondary research, and 4) the e-survey underlying the transformational change signals was assessed in a harmonized way to establish the basis for the program and hypothesis findings along the dimensions of transformational change.

48. Overall, the assessment of evidence was in line with the ODI-led evidence synthesis work area.

6.4 Addressing TCLP questions

49. The Evaluation Report responded to 9) each of the four TCLP questions (and sub-questions), drawing on the evaluative findings synthesized across the seven hypotheses, signals against the four dimensions of transformational change, and other evaluative work conducted. TCLP Question 2 was addressed primarily through the assessment of early, interim, and advanced signals along the four dimensions of transformational change. The process of change was addressed through the testing of the seven hypotheses. We also addressed alternative contributing factors to change beyond CIFs and proactively sought to identify lessons learned, including an analysis of the barriers to transformation.

50. We also assessed the relationship between the four dimensions of transformational change and revisited the original definition of transformation. These reflections, with cross-cutting learning theme 1, informed TCLP Question 1. TCLP Question 2 was addressed through the first cross-cutting learning theme, as well as more specifically Hypotheses 6 and 7. TCLP Question 4 is addressed through the actionable, practical recommendations on how to improve upon the transformational potential of CIFs.

51. The evaluation was guided and closely coordinated with the broader E&L initiative (TCLP) as well as the related work streams, with a view to disseminating learning. The analytical work of TCLP’s EVT was closely aligned with and integrated with the ODI-led evidence synthesis work area. As with the design of the evaluation, the findings were validated through a series of workshops with the Advisory Group and TCLP community. These workshops were used:

• to discuss what the evidence suggests as a whole, and talk through and challenge interpretations

• to discuss the implications for CIF, the wider climate sector, and transformation as a concept

• to identify audiences and communication strategies for the outputs

7 TCLP Evaluation Limitations

52. Every choice of evaluation methodology entails trade-offs and means limitations to the inferences made.

53. The choice to employ a generative, theory-based approach to causality ultimately cannot provide definitive answers if CIF was the critical catalyst of change and the extent of its influence. Nevertheless, we considered it the most appropriate approach to understanding the wicked problem of climate change, with its difficulties in defining and agreeing on the problem and the solution, multiple interdependencies, with unforeseen, unpredictable and even maladaptive outcomes.

54. Considering the pilot nature of the intervention, we were also more interested in a better understanding of transformational change and the mechanisms of how and under what circumstances transformation may take place, for which the chosen approach was considered the best suited.


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55. The purposive, theory-based, maximum variation sampling strategy, while appropriate for the theory-based approach, also made it difficult to generalize findings across the entire CIF population of programs, countries, and projects. As data was gathered from a limited sample of cases, the findings do not necessarily represent the entire CIF portfolio. Attempts were nevertheless made to mitigate any potential sampling bias through the triangulation of evidence 1) utilizing secondary literature, 2) an e-survey across all CIF programs, and 3) adding remote and light touch cases to contextualize observations and findings in the broader CIF context. Broader experiences, whether from secondary literature or the e-survey, were referred to, where relevant, and compared with those more specific ones of individual cases. Where the cases did not align with broader trends, this is was indicated. The chosen approach, due to its inherent nature, did not attempt to generalize findings across a statistically significant population. However, the evaluation did contextualize findings in the full CIF environment by reference to contextual factors and secondary literature. This also allowed conclusions to be drawn referring to CIF’s contribution to transformation in relation to other, external factors, such as broader renewables market forces. An e-survey was designed and successfully implemented with data gathered from respondents with exposure across all CIF countries (except Algeria and Libya.) The initial five in-depth case studies were supplemented by ten remote case studies with a limited set of interviews, and an additional eight light-touch case studies based on literature alone.

56. The sample generated a rich and varied set of experiences to allow testing of the seven transformational change evaluation hypotheses in a diversity of contexts. The seven evaluation hypotheses were the principle driver in the selection of the case studies, which varied by geographical region, type of technology and sector, type of MDB presence, and income level.

57. Efforts were also made to identify positive, neutral or negative transformative dynamics across the total sample, as well as within individual case studies. While more mature country programs were selected, as a basic condition for transformation to take place, in each country, there were both more and less successful projects, as well as project phases with a varying degree of challenges. Within each case, efforts were made to actively probe for positive and negative changes through the opening question of the interviews. The learning purpose of the evaluation was emphasized, together with the fact that we often learn more from experiences that do not go so well, than from success. Efforts were also made to identify interviewees external to CIF, such as civil society and private sector representatives, each group representing approximately 10-16% of the respondent pool, in the interviews and e-survey, respectively.

58. There were also some limitations in the specific data collection tools employed. Potential confirmation bias was managed through the triangulation of evidence by 1) cross-referencing contextual factors, the broader literature, and findings of the ODI-led evidence synthesis work area; 2) ensuring the geographic coverage of the e-survey; and 3) the consultation of a broad range of internal and external stakeholders.

59. The main focus of the evaluation workstream was on gathering of primary data through the e-survey and the case studies, with reliance upon the ODI-led evidence synthesis work area for a more comprehensive review of the related literature. The evaluation therefore did not conduct a comprehensive literature review, but relied substantially upon the other work-stream to do this more comprehensive mapping, referring to collected secondary evidence, where relevant to the selected cases. This may appear as circular referencing, to some degree, but was complemented by the substantial primary evidence gathered by the evaluation. While ideally, the evidence synthesis would have been conducted prior to the evaluation, the two teams worked in close synergy to cross-reference this work, where relevant.

60. While the e-survey encompassed a large population of CIF stakeholders, the method for the identification of the respondents could not ensure that we covered the full population and


26

could have introduced attribution bias. The main reason for this is that respondents were already active participants in CIF meetings (respondents were largely identified through meeting participant logs.) The response rate, as tends to be the case in e-surveys, was not very high, but nevertheless geographically comprehensive with some exposure across all CIF countries (except Algeria and Libya.)

61. Since the evaluators were dependent upon CIF’s AU, MDB and national focal point staff for the initial identification of interviewees, there was a danger of confirmation bias in the interviewee selection. However, this was mitigated by the evaluation team who actively made efforts to consult more broadly, seeking out also alternative views. The initial list of interviewees was prepared with support from CIF’s AU, MDBs, and national focal point staff. Efforts were nevertheless made to mitigate confirmation bias through the identification of alternative interlocutors, whether other donors working in the same field, private sector (ten percent of interviewees) or civil society representatives (ten percent of interviewees.) Potential bias was also mitigated through the preparation and application of shared data collection tools across the evaluation and team through standard research protocols and related guidance. This included a shared interview guide that was developed in a collaborative manner, to ensure a shared understanding of key questions and streams of enquiry. These measures were installed to standardize data collection efforts and mitigate any established views among team members conducting interviews.

62. Regarding the analysis of data, the reliability of the analytical tools, such as the signals of transformation and the Transformational Change Rubric required clear understanding and uniform application across the work streams and the evaluation team for accurate documentation across cases. Transformational change dimension definitions relied upon the related work during Phase I, as well as regular discussion with CIF’s AU, across TCLP work streams and within the evaluation team. Likewise, the signals were clearly defined and categorized at inception, with regular review and quality control of evaluation inputs, such as the country reports and hypothesis reports employing them, by the deputy team leaders and team leader. The strength of signals was iteratively tested across the 15 countries explored in depth, through country reports, hypothesis reports and the summarization of signals data by country and CIF program across the dimensions of transformational change. Evaluation team members reviewed information, compared analysis, and deliberated conclusions through regular calls and key meetings. Findings were queried and challenged, with participation across the core team, as well as through five rounds of review by CIF’s AU, MDBs, and country focal points. The evaluation contributed to the transformational change definition identified during Phase I and developed and tested examples of signals as a part of the evaluation methodology. Nevertheless, further work on the definition of key concepts, whether relating to the dimensions of transformation, their relationships or specific early, interim and advanced signals is recommended.

63. The credibility of evidence and evaluative conclusions were reinforced iteratively, in cooperation also with CIF’s AU, MDBs, and country focal points. In order to facilitate the comparison of evidence and findings across the selected cases and broader CIF portfolio, the signals of transformation were assessed across the dimensions.


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Annex 3 TCLP Evaluation Key Informant Interviews

Total number of interviewees: 250

Multilateral Development Banks (MDBs): 105, from six MDBs

Percentage of women: 30%

Percentage of private sector representatives: 10%

Percentage of civil society representatives: 10%

# First Name Last Name Organization CIF Program Country

1. Yakoubou Mahaman Sani Ministry of Planning PPCR Niger

2. Saadou Bakoye Ministry of Planning PPCR Niger

3. Chaibou Dan Bakoye Ministry of Planning PPCR Niger

4. Dambagi Inoussa PACRC PPCR Niger

5. Yaye Manou PACRC PPCR Niger

6. Gousmane Moussa Secrétariat Exécutif CNEDD au Cabinet du Premier Ministre

PPCR Niger

7. Amadou Rouafi Doka Ministère de Développement Communautaire

PPCR Niger

8. Zakou Mayaki Moussa PDIPC et PROMOVARE PPCR Niger

9. Yahaya Nazoumou University of Niamey PPCR Niger

10. Seyni Ganda Private Sector PPCR Niger

11. Dan Adi Private Sector PPCR Niger

12. Ibrahim Baoua Souley Private Sector PPCR Niger

13. Youssouf Mohamed

Elmoctar Private Sector PPCR Niger

14. Ayouba Abdou Sani Jeunes Volontaires pour l’Environnement

PPCR Niger

15. Lawali Malam Karami National Platform of NGOs for Climate Change

PPCR Niger

16. Nacibe Chemor CONAFOR FIP Mexico

17. Berenice Hernandez CONAFOR FIP Mexico

18. Jorge Fernández Medina

CONAFOR FIP Mexico

19. Mario Antonio Mosqueda Vazquez

CONAFOR FIP Mexico


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20. José Antonio Ávila Mendez

CONAFOR FIP Mexico

21. Julio Cesar Bueno Talamantes

CONAFOR FIP Mexico

22. Francisco Javier Anazattee Garera

CONAFOR FIP Mexico

23. Karime Chavez Rocha CONAFOR FIP Mexico 24. Ifrain Mohedor Garcia CONAFOR FIP Mexico

25. Germanico Galicia Garcia CONAFOR FIP Mexico

26. Roberto Bautista CONAFOR Oaxaca FIP Mexico

27. Manuel Aldrete Terrazas DGM FIP Mexico

28. Alvaro Yañez Finance (SHCP) FIP Mexico

29. Camila Zepeda Finance (SHCP) FIP Mexico

30. Hector Peña FND FIP Mexico

31. Eduardo Juárez FINDECA FIP Mexico

32. Joan Lagos FINDECA FIP Mexico

33. Gustavo Sanchez Red Mocaf FIP Mexico

34. Juan Labougle Conservation International

FIP Mexico

35. Sergio Madrid Mexican Civil Council for Sustainable Forestry

FIP Mexico

36. Jesus Manuel Aldrete Terrazas Corporate Consortium of Producers and Exporters in Forestry, SC DE, R.L

FIP Mexico

37. Israel Santiago Garcia Community Forestry Enterprise

FIP Mexico

38. Juan Manuel Frausto FMCN (Fondo Mexicano para la Conservación de la Naturaleza)

FIP Mexico

39. Edgar Gonzalez Rainforest Alliance FIP Mexico

40. Jorge Calderon Rubisco FIP Mexico

41. Juergen Blaser Co-chair FIP Expert Group

FIP Mexico

42. David Kaimowitz Ford Foundation FIP Mexico

43. Ken Creighton Wood Hole Research Center

FIP Mexico

44. Kenneth Adrasko Senior Methodology Specialist, World Bank

FIP Mexico

45. Marjory-Anne Bromhead Natural Resources and Climate Change Adviser

FIP Mexico

46. Gerhard Dieterle ITTO FIP Mexico

47. Jaime Severino CONAFOR FIP Mexico

48. Elizabeth Robberechts IDB CTF Mexico

49. Maria Tapia IDB CTF Mexico


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50. Leticia Riquelme Inter-American Development Bank (IADB) Mexico

CTF Mexico

51. Abel Lopez Dodero World Bank CTF Mexico

52. Guillermo Hernández González

World Bank CTF Mexico

53. Ernesto Infante Barbosa Sociedad Hipotecaria Federal

CTF Mexico

54. Claudia Castillo Aguilar Sociedad Hipotecaria Federal

CTF Mexico

55. Andrea Hernández Espinoza

Sociedad Hipotecaria Federal

CTF Mexico

56. Diana Avalos Gil Sociedad Hipotecaria Federal

CTF Mexico

57. Arturo Gochicoa Nacional Financiera (NAFIN)

CTF Mexico

58. Ivan Cornejo Villalba Nacional Financiera (NAFIN)

CTF Mexico

59. Sandra Romero Osorio BANOBRAS CTF Mexico

60. Uriel Cervantes Gonzalez

BANOBRAS CTF Mexico

61. Fernando Ramones Fernández

SENER CTF Mexico

62. Luis Alfonso Munozcano SENER CTF Mexico

63. Samuel Reyes ECON SOLUCIONES ENERGÉTICAS INTEGRALES

CTF Mexico

64. Fernando Torres VEOLUS CTF Mexico

65. Adrian Fernandez Iniciativa Climatica CTF Mexico

66. Jorge Villarreal Iniciativa Climatica CTF Mexico

67. Bernardo Baranda ITDP Mexico CTF Mexico

68. Pushkar Manandhar ADB SREP Nepal

69. Arun Rana ADB PPCR Nepal

70. Bhakta Mani Sitola ADB PPCR Nepal

71. Harsh Vivek IFC PPCR Nepal

72. Akira Dhakwa IFC PPCR Nepal

73. Santosh Pandey IFC PPCR Nepal

74. Subodh Adhikari World Bank SREP Nepal

75. Avani Mani Dixit World Bank PPCR Nepal

76. Ram Prasad Mainali Ministry of Finance PPCR Nepal

77. Akhanda Sharma Ministry of Forest and Environment

PPCR; MCCRMD

Nepal

78. Shib Nandan Prasad

Shah Ministry of Agriculture, Land Management and Cooperatives

PPCR Nepal


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79. Shyam Kishor Shah Ministry of Agriculture, Land Management and Cooperatives

PPCR Nepal

80. Nawa Raj Dhakal Alternative Energy Promotion Center (AEPC)

SREP Nepal

81. Mukesh Ghimire Alternative Energy Promotion Center (AEPC)

SREP Nepal

82. Sushim Man Amatya Alternative Energy Promotion Center (AEPC)

SREP Nepal

83. Sushut Dhakal Alternative Energy Promotion Center (AEPC)

SREP Nepal

84. Rishi Ram Sharma Ministry of Forest and Environment

PPCR Nepal

85. Saraju Baidhya Ministry of Forest and Environment

PPCR Nepal

86. Ram Singh Thapa Ministry of Forest and Environment

PPCR Nepal

87. Raju Sapkota Ministry of Forest and Environment

PPCR Nepal

88. Abhishek Adhikary National Electricity Agency

SREP Nepal

89. Akhileshwar Karna Ministry of Forest and Environment

PPCR Nepal

90. Krishna Prasad Devkota Nepal Micro Hydropower Developers' Association

SREP Nepal

91. Cow farmer Cow farmer Cow farmer SREP Nepal

92. Manoj Khadka DFID SREP Nepal

93. Vijaya Singh UNDP SREP Nepal

94. Shanti Karanjit UNDP SREP Nepal

95. Sautish Gautum UNDP SREP Nepal

96. Erik Holmqvist Nordic Development Fund

PPCR Nepal

97. Local biogas developer

Local biogas developer

Local biogas developer SREP Nepal

98. Milan Kumar Joshi Practical Action SREP Nepal

99. Bala Ram Shrestha Biogas Sector Partnership Nepal

SREP Nepal

100. Prakash Lamichhane Biogas Sector Partnership Nepal

SREP Nepal


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101. Dibya Gurung Women Organization for Change in Agriculture and Natural Resource Management (WOCAN)

SREP/PPCR Nepal

102. Birkha Bahadur Shahi Federation of Community Forestry Users, Nepal (FECOFUN)

PPCR Nepal

103. Anjana Shakya Independent Consultant PPCR Nepal

104. Gyanesh Bajracharya Independent Consultant; formerly International Centre for Environmental Management (ICEM)

All Nepal

105. Nabina Shrestha Independent Consultant; formerly International Centre for Environmental Management (ICEM)

All Nepal

106. Vishnu Prasad Pandey International Water Management Institute (IWMI)

PPCR Nepal

107. Sanita Bdaubanjar International Water Management Institute (IWMI)

PPCR Nepal

108. Nadia Taobane World Bank CTF Morocco

109. Adama Moussa African Development Bank (AfDB)

CTF Morocco

110. Manaf Touati World Bank Group CTF Morocco

111. Riccardo Ambrosini International Finance Corporation

CTF Morocco

112. Jonathan Walters World Bank CTF Morocco

113. Abdelkrim El Amrani Ministry of General Affairs and Governance

CTF Morocco

114. Rachid El Kissi Ministry of General Affairs and Governance

CTF Morocco

115. Mohamed Oumed Ministry of Energy, Mines and Sustainable Development

CTF Morocco

116. Boubker Chatre Ministry of Energy, Mines and Sustainable Development

CTF Morocco

117. Belaine Fadoua Ministry of Energy, Mines and Sustainable Development

CTF Morocco

118. Laabdaoui Aicha Ministry of Energy, Mines and Sustainable Development

CTF Morocco


32

119. Badr El Fadili Ministry of Industry, Commerce, Investment and Statistics

CTF Morocco

120. Nassima Sami Ministry of Industry, Commerce, Investment and Statistics

CTF Morocco

121. Mohamed Zahidi ONEE CTF Morocco

122.

Aatef ONEE CTF Morocco

123. Loumia Mellouki Felali ONEE CTF Morocco

124. Mohamed Sahri MASEN CTF Morocco

125. Noureddine Hany SIE CTF Morocco

126. Meriem Bali SIE CTF Morocco

127. Said Mouline AMEE CTF Morocco

128. Rachid El Mrabet IRESEN CTF Morocco

129. Karim Zriouel IRESEN CTF Morocco

130. Amine Berrada Sounni Nareva Holding CTF Morocco

131. Tahra Al Abaddan Attijari wafabank CTF Morocco

132. Laila Mikou CDG Capital CTF Morocco

133. Amal El Malouani Credit Agricole CTF Morocco

134. Sarah Bellahsen Credit Agricole CTF Morocco

135. Khalid Semmaoui Amisole CTF Morocco

136. Katharina Bohme KfW CTF Morocco

137. Ian Berryman Bloomberg CTF Morocco

138. Carlos Alberto Jacome

Montenegro IADB SREP Honduras

139. Andrey Shlyakhtenko IFC SREP Honduras

140. Jose Manuel Gonzalez Mi Ambiente SREP Honduras

141. Diana Solis Pas Sub-secretaria de Energia Renovable y Electricidad

SREP Honduras

142. Alejandro Aplicano Ministry of Finance; Honduras

SREP Honduras

143. Mario Bonilla Barrientos

Ministry of Finance; Honduras

SREP Honduras

144. Elvis Rodas Flores Ministry of Natural Resources and Environment; Honduras

SREP Honduras

145. Nelson Ulloa Ministry of Energy, Natural Resources, Environment and Mines; Honduras

SREP Honduras


33

146. Leonardo Valladares Matute

Ministry of Finance; Honduras

SREP Honduras

147. Karla Aguilar SREP Honduras

148. Manuel Davila Banco Atlantida SREP Honduras

149. Elsia Paz AHER SREP Honduras

150. Abram Riera APRODERDH SREP Honduras

151. Andres Carbajal Soluz Honduras SREP Honduras

152. Richard Hansen Soluz Honduras SREP Honduras

153. Liliana Bendana Executive Director Honduran Association of Small Producers of Renewable Energy (AHPPER)

SREP Honduras

154. Jorge Chi Ham Fundación Vida http://fundacionvida.org

SREP Honduras

155. Julio Cárcamo Fundación Vida http://fundacionvida.org

SREP Honduras

156. Jorge Cárcamo Fundación Vida http://fundacionvida.org

SREP Honduras

157. Gareth Phillips African Development Bank (AfDB)

158. Leandro Azevedo African Development Bank (AfDB)

159. Matthew Harris African Development Bank (AfDB)

160. Christian Ellermann ADB

161. Ancha Srinivasan ADB

162. Cristina Santiago ADB

163. Xianfu Lu ADB

164. Nathan Rive ADB

165. Preety Bhandari ADB

166. Charles Rodgers ADB

167. Jay Roop ADB

168. Sonomi Tanaka ADB

169. Samuel Tumiwa ADB

170. Jan-Willem van de Ven ERBD

171. Ryan Alexander ERBD

172. Nurgul Esenamanova ERBD

173. Marialena Vyzaki ERBD

174. Craig Davies ERBD

175. Andreas Biermann ERBD

176. Rachel Robboy IDB CTF

177. Claudio Alatorre IDB CTF

178. Gloria Visconti IDB


34

179. Gerard Alleng IDB

180. Maria Netto IDB

181. Paloma Marcos IDB

182. Fernando de Olloqui IDB

183. Gregory Watson IDB

184. Gmelina Ramirez-Ramirez

Inter-American Development Bank (IADB)

CTF

185. Andrey Shlyakhtenko IFC

186. Joyita Mukharjee IFC

187. Jussi Tapio Lehmusvaara

IFC

188. Monyl Toga Makang World Bank

189. Meerim Shakirova World Bank

190. Raul Alfaro-Pelico World Bank

191. Kazi Ahmed World Bank

192. John Roome World Bank

193. Margaret Arnold World Bank

194. Inka Schomer World Bank

195. Angela Armstrong World Bank

196. Katharina Siegmann World Bank

197. Ian Gray World Bank

198. Madhavi Pillai World Bank

199. Rohit Khanna World Bank

200. Chandrasekar Govindarajalu World Bank

201. Joonkyung Seong World Bank

202. Leesle Hong World Bank

203. Almudena Mateos Merino World Bank SREP Armenia

204. Dahlia Lotayef World Bank PPCR Niger

205. Ruben Gevorgyan Armenia Renewable Resources and Energy Efficiency (R2E2) Fund

SREP Armenia

206. Tamara Babayan Independent Expert; Energy Saving Foundation

SREP Armenia

207. Joan Miquel Carrillo Cortada IDB Invest CTF Chile

208. Mijal Brady Ministry of Energy; Chile CTF Chile

209. Romina Tan Nicaretta Canadian Climate Fund (C2F)

CTF Chile

210. Lehome Johnson Improving Climate Data and Information Management Project

PPCR Jamaica

211. Winsome Townsend Adaptation Program and Financing Mechanism

PPCR Jamaica


35

212. Keiko Ashida Tao World Bank PPCR Jamaica

213. Gerard Alleng Inter-American Development Bank

PPCR Jamaica

214. Le-Anne Roper PIOJ PPCR Jamaica

215. Nadine Brown PIOJ PPCR Jamaica

216. Leandro Azevedo AfDB SREP Kenya

217. Alemayehu Wubeshet Zegeye

AfDB SREP Kenya

218. Rodney Sultani Ministry of Energy; Kenya

SREP Kenya

219. Isidro Jose Fote Ministry for Land, Environment and Rural Development

PPCR Mozambique

220. Takhmina Akhmedova Committee for Environment Protection under the Government of Tajikistan

PPCR Tajikistan

221. Zafar Makhmudov Committee for Environment Protection under the Government of Tajikistan

PPCR Tajikistan

222. Tristan Knowles ADB CTF Thailand

223. Haruhisa Ohtsuka IFC CTF Thailand

224. Nintira Abhisinha Bangchak Petroleum Public Company Limited

CTF Thailand

225. Anna Maria Kawimbe Chunga

Pilot Programme for Climate Resilience

PPCR Zambia

226. Carol Mwape Zulu Pilot Programme for Climate Resilience

PPCR Zambia

227. Catherine Mwewa Lishomwa

Ministry of National Development Planning

PPCR Zambia

228. Mahmuda Begum Ministry of Finance PPCR Bangladesh

229. Shamshur Khan Ministry of Environment and Forests

PPCR Bangladesh

230. Kenta Usui World Bank SREP Ethiopia

231. Raihan Elahi World Bank SREP Ethiopia

232. Epiphanius Farai Kanonda AfDB CTF South Africa

233. Penny Herbst Africa GreenCo CTF South Africa

234. Chris Ahlfeldt Blue Horizon Energy Consulting Services

CTF South Africa

235. Sandeep Kohli World Bank SREP Maldives

236. Abhijeet Khanna

SREP Maldives

237. Joan Carillo IADB CTF Chile

238. Jean Tagiitumalii Viliamu Ministry of Finance PPCR Samoa

mailto:Haruhisa%20Ohtsuka%20%[email protected]


36

239. Trelson Mapp Ministry of Finance PPCR St Vincent and the Grenadines

240. Mafalda Duarte Head of Climate Investment Funds

All All

241. Andrea Kutter Senior Program Coordinator

PPCR/FIP All

242. Rachel Allen Senior Program Coordinator

PPCR All

243. Lorie Rufo Climate Change Specialist

PPCR All

244. Zhihong Zhang Senior Program Coordinator

CTF/SREP All

245. Ian Gray Senior Program Coordinator

FIP All

246. Chris Head Private Sector Specialist All All

247. Rafael Ben Energy Specialist SREP All

248. Abishek Bhaskar Energy Specialist CTF All

249. Ines Angulo Forest Specialist FIP All

250. Anne Kuriakose Senior Social Development Specialist, Gender

All All

Evaluation of Transformational Change in the CIF - Annex 4

37

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38

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http://pubdocs.worldbank.org/en/583711531832587993/4114-XFIPDG214A-Mozambique-Project-Document.pdf

http://documents.worldbank.org/curated/en/792001512392701402/Mini-grids-in-Kenya-a-case-study-of-a-market-at-a-turning-point

http://documents.worldbank.org/curated/en/792001512392701402/Mini-grids-in-Kenya-a-case-study-of-a-market-at-a-turning-point

http://documents.worldbank.org/curated/en/374901487522968695/pdf/Mozambique-Forest-Investment-Project-PAD-02152017.pdf

http://documents.worldbank.org/curated/en/374901487522968695/pdf/Mozambique-Forest-Investment-Project-PAD-02152017.pdf

http://documents.worldbank.org/curated/en/933391513842174278/pdf/122180-ESMAP-PUBLIC-MyanmarProgressMiniGridsWeb.pdf

http://documents.worldbank.org/curated/en/933391513842174278/pdf/122180-ESMAP-PUBLIC-MyanmarProgressMiniGridsWeb.pdf


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World Bank. (2017c). The Story of the Forest Investment Program – Taking Root in International Climate Finance and Branching Out to Sustainable Development (Draft).

World Bank. (2018a). International Development Association Project Paper for the Zambia Strengthening Climate Resilience (PPCR Phase II).

World Bank. (2018b). Nepal: SREP Extended Biogas Project, Mid-term Review Aide Memoire.

World Bank. (2018c). Total Greenhouse Gas Emissions (kt of CO2 equivalent). [online] Available at: https://data.worldbank.org/indicator/EN.ATM.GHGT.KT.CE?contextual=default&end=2012&locations=BF-1W&name_desc=false&start=2012&view=bar

World Bank, Climate Investment Funds (CIF). (2018). A Case Study of the Brazil Forest Investment Program.

World Bank, Sustainable Energy for All (SE4ALL) database. World Bank, International Energy Agency, Energy Sector Management Assistance Program.

World Bank, FAO and IFAD. (2015). Gender in Climate-Smart Agriculture: Module 18 for Gender in Agriculture Sourcebook.

World Economic Forum. Fostering Effective Energy Transition. Available at: http://www3.weforum.org/docs/WEF_Fostering_Effective_Energy_Transition_report_2018.pdf

World Resources Institute (WRI). (2008). Correcting the World’s Greatest Market Failure: Climate Change and the Multilateral Development Banks. Available at: http://www.wri.org/sites/default/files/pdf/correcting_the_worlds_greatest_market_failure.pdf

Wesoff, E. and Lacey, S. (2017). Solar Costs are Hitting Jaw Dropping Lows In Every Region of the World. [online] Green Tech Media. Available at: https://www.greentechmedia.com/articles/read/solar-costs-are-hitting-jaw-dropping-lows-in-every-region-of-the-world#gs.UVyPkB4

World Resources Institute (WRI). (2017). DRC Improved Forested Landscape Management Project.

Wright, H., Hawkins, J., Orozco, D., and Mabey, N. (2018). Banking on Reform: Aligning Development Banks with the Paris Climate Agreement. [online] E3G. Available at: https://www.e3g.org/library/banking-on-reform-aligning-development-banks-with-paris-climate-agreement

Yaron g., Gregorowski R., Vogel, I., Villanueva, P., and Dorgan, A. (2015). CDKN End of Year 5 Evaluation 2014. Itad.

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https://data.worldbank.org/indicator/EN.ATM.GHGT.KT.CE?contextual=default&end=2012&locations=BF-1W&name_desc=false&start=2012&view=bar

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https://evaluationcanada.ca/system/files/cjpe-entries/30-1-108.pdf


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Annex 5 Additional Examples of Contributions to Transformational Change in the Energy Sector

This annex includes supplemental information and examples relevant to assessments of CIF’s (CTF’s and SREP’s) contributions to transformational change progress in the energy sector.

7.1 Context

The global context for low-carbon energy in 2008, when CIF was founded, looked quite different

than it does now. First, deployment of utility-scale renewable energy technologies in developing

countries was very limited in 2008. For example, many CIF countries—including Chile, Honduras,

Kazakhstan, Mexico, Morocco, and South Africa—had no (or few) utility-scale wind or solar PV

systems.22 Second, technology costs and investment risks for renewable energy technologies were

high compared with fossil fuel energy sources, particularly in “frontier” developing country contexts

where technologies had not been demonstrated to work and utility-scale projects had not tested

policy frameworks.23 Third, CTF and SREP countries were just beginning to make national

commitments to reduce GHG emissions and expand deployment of renewable energy, and few

countries had national policy frameworks in place to support renewable energy deployment.24 The

early years of CIF coincided with an expanding number of developing countries making such

commitments.25 The national policy frameworks that existed around 2010—such as the renewable

energy self-generation provisions in Mexico—had generally not been tested in ways that

demonstrated their ability to deliver predictable outcomes.26

Globally, large-scale investments in renewable energy technologies—notably, wind and solar PV—

have rapidly driven down technology costs and fueled global competition and investment in projects

in emerging markets. Renewable energy has entered a virtuous cycle of falling costs, increasing

deployment, and further accelerating technological progress and economies of scale. The global

levelized costs of electricity from wind, solar PV, and CSP sources have fallen dramatically over the

past decade.27 Three main cost reduction drivers have emerged for renewable power: technology

improvements; competitive procurement policy frameworks; and a large base of experienced,

internationally-active project developers.28 Globally, public finance in overall investment in clean

energy assets has been ceding its share to private finance, although public finance still comprises a

greater share of clean energy asset development costs for lower-income countries. Collective MDB

investment in clean energy has grown substantially since CIF was launched, although individual MDB

investments vary year to year, based on project pipelines and other factors.29

Developing countries have expanded national commitments to GHG emissions reduction and

renewable energy deployment while pursuing national policy reforms—sometimes supported or

tested by CIF investments—that encourage renewable energy. More ambitious national targets for

decarbonizing the power sector—including country commitments through the UNFCCC process—have

bolstered political will to capitalize on falling renewable energy technology costs in ways that also

22 IRENA 2010, 2018. 23 IEA 2017, IRENA 2018. 24 IRENA 2018. 25 RISE 2018. 26 IRENA 2018, BNEF 2019. 27 IRENA 2018, BNEF 2019. 28 IRENA 2018. BNEF 2019. 29 IRENA 2018, BNEF 2019.


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support energy access (particularly for SREP countries), energy security, and national economic

development and employment goals.30 Many countries have pursued policy reforms to accelerate

renewable energy investment. For example, the number of countries promoting renewable energy

through direct policy support has tripled from at least 48 in 2004, to at least 147 in 2018.31

While many middle-income countries targeted by CTF have energy access rates near 100 percent,

most lower-income countries targeted by SREP have substantially lower energy access rates, despite

progress in recent decades. The number of people without access to electricity has fallen over the last

15 years, from 1.7 billion people in 2000 to 1.1 billion in 2016.32 Since 2012, more than 100 million

people per year have gained electricity access—an acceleration from the rate of 62 million people per

year seen between 2000 and 2012. While most of this access over the last five years has been through

new grid connections, mostly with fossil fuel power generation, renewable energy has started to gain

momentum in addressing energy access needs, including through off-grid and mini-grid systems, and

this shift is expected to accelerate.33

7.2 Changes in renewable energy deployment: CIF implementation

Evaluation team analyses of IRENA data indicate that deployment of renewable energy capacity has

increased in nearly all CTF and SREP countries since CIF’s inception. Evaluation case study analyses

indicate that CIF has contributed to these increases—some modest and some more substantial—in all

five CTF countries analyzed in more depth (Chile, Mexico, Morocco, Thailand, and Turkey), and in all

four SREP countries analyzed in depth (Armenia, Honduras, Kenya, and Nepal). This section provides

additional information on, and examples of, renewable energy deployment in selected CIF countries.

7.3 CTF

CTF investment has directly contributed to the deployment of 7 GW of installed renewable energy generation capacity.34 Examination of the CTF portfolio indicates that CIF investments in and contributions to renewable energy deployment have focused on a range of renewable energy technologies, including solar PV, thermal solar (CSP), wind energy, and geothermal power, with some attention to hydropower. Figures 1 and 2 show the increases in solar PV and wind energy capacity in selected CTF countries since 2008. It is important to note that not all capacity increases in these figures are directly related to CTF investments. However, case study analyses of CTF investments in Chile, Mexico, Morocco, South Africa, Thailand, and Turkey indicate that CTF investments have played meaningful roles in advancing systemic changes that have supported the broader scaling of renewable energy resources reflected in these figures.

30 RISE Database 2018, Carbon Brief Country Climate Commitment Tracking Database 2015; IRENA 2014. 31 IRENA 2018. 32 IEA 2017. 33 IEA 2017. 34 Draft CTF Semi-Annual Operational Report (CTF ORR), November 2018, 16.


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Figure 7: Solar PV energy capacity (in MW) for selected CTF countries with available data for all years shown. Source: Evaluation team analysis of IRENA data

Figure 8: Wind energy capacity (in MW) for selected CTF countries with available data for all years shown. Source: Evaluation team analysis of IRENA data

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Examples of renewable energy deployment across CTF countries include the following:

• Thailand (CTF). Over the past decade, Thailand installed more solar power capacity (3 GW)

than all ten other Association of Southeast Asian Nations (ASEAN) nations combined.

• Morocco (CTF). In Morocco, all stakeholders consulted agreed that the country will almost

certainly meet its overall stated renewable energy target of 6,000 MW by 2020, including solar

(2,000 MW) and wind (2,000 MW). CTF is responsible for co-financing a significant proportion

of this new capacity, alongside MDB and government finance. By the end of 2018, Morocco

will have 887 MW of solar power capacity in operation, 1,207 MW of wind power, and in

excess of 1,700 MW of hydro power plants.

• Turkey (CTF). In Turkey, CTF investment has supported the addition of at least 1,385 MW of

new renewable energy capacity.35

7.4 SREP

Examination of the SREP portfolio suggests that most CIF investments in and contributions to renewable energy deployment have focused on solar PV (including solar PV and hybrid mini-grids) and geothermal power, with some modest attention to biomass and hydropower. Figures 3 and 4 show the increases in solar PV and wind energy capacity in selected SREP countries since 2008. It is important to note that not all capacity increases are directly related to SREP investments. However, case study analyses of SREP investments in Armenia, Honduras, Kenya, Maldives, and Nepal indicate that SREP investment have played meaningful roles in advancing systemic changes that have supported the broader scaling of renewable energy resources reflected in these figures.

Figure 9: Solar PV energy capacity (in MW) for selected SREP countries with available data for all years shown. Source: Evaluation team analysis of IRENA data

35 Climate Investment Funds. (2017). CTF Results Report. p. 34-35.


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Figure 10: Wind energy capacity (in MW) for selected SREP countries with available data for all years shown. Source: Evaluation team analysis of IRENA data

Examples of renewable energy deployment across SREP countries include the following:

• Armenia. In Armenia (SREP), in the small-scale renewable energy project pipeline, by October

2016, 11 licenses had been awarded under the feed-in tariff program for solar projects (under

1 MW), with construction on several beginning in 2017.

• Honduras (SREP and DPSP). In Honduras, the market for solar energy has grown significantly

during the time in which CIF resources have been deployed. CTF support to the Choluteca and

Pacifico projects in Honduras were part of a broader mobilization of financing to develop

competitively priced renewable generation capacity. These projects were part of a suite of

early-mover grid-scale solar PV projects in Honduras that collectively represented the largest

solar production in Central America at the time.

• Nepal. In December 2017, Nepal inaugurated its first wind-solar hybrid power system in

Chisapani, Hariharpugadhi. Progress to date on the SREP-supported South Asia Sub-regional

Economic Cooperation Power System Expansion Project (ADB) includes awarding contracts for

five mini hydro sub-projects for a total of 1,400 kW. Procurement is ongoing for another two

sub-projects, with a cumulative size of 1,200 kW. Three wind-solar mini-grid projects (totaling

90 kW) have been completed, and construction continues on another three totaling 245 kW.

Overall, the project aims to develop 500 kW via wind-solar mini-grid sub-projects.

0

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https://www.spotlightnepal.com/2017/12/12/nepals-largest-wind-solar-hybrid-power-system-switched/


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7.5 Stages of renewable energy technology deployment

Different CIF countries are at different stages of technology deployment for specific low-carbon technologies, such as wind, solar PV, CSP, and geothermal energy. Box 1 discusses these different stages. Box 2 provides country examples illustrating CTF support for deployment along this curve.

Box 1: CIF INVESTMENTS ACROSS THE TECHNOLOGY DEPLOYMENT CURVE

The evaluation found that CTF investments in clean technology have made productive contributions at different phases of the deployment curve (see illustration below), particularly during the early ‘initiation’ phase and the ‘market take-off’ phase. These phases are discussed below, and evidence outlining CTF contributions to country progress along the curve is summarized in Box 2.

Initiation phase. CTF has invested in multiple renewable energy projects that are among the first commercial-scale deployments of wind, solar PV, CSP, and geothermal energy technologies within a country or region (see Box 6 in the main report). Case study evidence indicates that these early projects typically require substantial concessional finance to address higher capital costs compared with conventional alternatives, as well as high risk premiums due to: (1) technology performance risks linked with deploying technologies in new country contexts; and (2) uncertainties around new policy, regulatory, and contracting frameworks and how they will affect project costs and future payment streams, among other factors. Experience in the five CTF countries examined shows that these early projects demonstrate the viability of technologies in the new market context and lower the perceived risks and costs by testing policy, regulatory, contracting, and payment frameworks.

Market take-off phase. CTF investments have also supported renewable energy projects during the ‘market take-off phase’, often through financing facilities that help support the development of larger portfolios of projects in ways that build market momentum, enable continued reductions in costs and risk premiums, and build capacity among key institutions (e.g., national development banks, regulatory agencies) and the private sector (e.g., commercial investors, project developers). Policy mechanisms such as competitive bidding auctions which prioritize renewable energy generation resources have helped accelerate this take-off phase in countries such as Chile, Mexico, and South Africa. Complementary CTF and MDB investments in transmission infrastructure have also proven important to open new areas to project development.

Consolidation phase. Over time, as the market for a technology develops and the technology becomes more cost-competitive (compared with alternative sources), the need for concessional finance typically wanes and national development banks, commercial banks, and/or private sector investors have played more significant roles in new renewable energy project financing. For example, in Mexico, CTF supported wind energy projects during the initiation and market take-off phases; however, the market has moved sufficiently towards the consolidation phase to eliminate the need for concessional finance during the three rounds of competitive power auctions since the 2015 Energy Reform. In Chile, the country’s CTF Investment Plan envisioned investments in multiple utility-scale solar PV projects; while CTF supported one 73 MW project, private investment flooded the market and rapidly moved the market toward the consolidation phase (supported by auctions for power contracts and by PV merchant plants) and eliminated the need for subsequent concessional financing for solar PV projects in Chile.

Sources: Evaluation country case studies; BNEF 2019; World Bank 2018; IEA 2015.


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Box 2: CTF CONTRIBUTIONS TO COUNTRY-LEVEL MOVEMENT ALONG THE DEPLOYMENT CURVE

The table below summarizes key evidence collected by the evaluation and other recent studies of how CTF has contributed to technology deployment during both the initiation and market take-off phases for selected CTF countries.

Country Initiation phase contributions Market take-off phase contributions Chile (solar PV)

Chile’s CTF Investment Plan envisioned supporting multiple large solar PV plants. CTF supported the 73 MW Maria Elena solar PV project (CTF $16M, operational in 2014), the fourth PV plant commissioned in Chile larger than 50 MW in capacity and the first ‘merchant’ PV plant without long-term power contracts.

The Chilean power market moved rapidly into the take-off phase, as private investment flooded in to develop solar PV projects, eliminating the need for concessional finance for solar PV. In 2018, there are 95 grid-connected PV projects on line in Chile, including 20 that are 50 MW or larger. Two stakeholders indicated that CIF and MDB commitment to the Chilean solar PV market signalled through the CIF Investment Plan helped assure private investors that the Chilean solar PV market was primed for investment.

Mexico (wind)

CTF co-financed two of the first large-scale wind farms in Mexico: Eurus (250 MW, with $30M from CTF) and La Ventosa (67.5 MW, with $15M from CTF). Stakeholders reported strong demonstration effects and reductions in perceived risks/costs.

CTF supported the Renewable Energy Financing Facility at NAFIN development bank, co-financing five wind projects which helped build sector momentum, reduce project development costs, and shape 2015 energy policy reforms. CTF projects laid the groundwork for growing rounds of commercially-financed wind projects through recent power auctions.

Morocco (wind)

Morocco’s wind energy sector received initiation-phase investment (more than $600M) prior to CTF involvement in the sector. CTF wind energy investment came in during the market take-off phase.

CTF provided $95M of concessional financing to five projects (more than 850 MW) under the One Wind Energy Plan. Additionally, the CTF awarded $10.7M of concessional financing to the Khalladi wind farm in 2015. While this sum is small in the Moroccan context, Khalladi set the precedent for future project finance deals under the Law 13-09 framework. Morocco has a strong pipeline of wind projects under development until 2020.

Thailand (solar PV, wind)

Thailand’s wind and solar PV markets had moved beyond the initiation phase when CTF involvement began, although substantial financing barriers to scaling remained (which CTF sought to address).

CTF has invested a total of $51 million in 10 PV projects, with a total capacity of 134 MW, and $34 million in two wind projects, with a total capacity of 87.5 MW, representing 5% and 10% of each technology's overall capacity there, respectively. CTF played an important role in addressing financing barriers to further scaling of wind and solar PV energy. BNEF estimates that new utility-scale PV financed on commercial terms stands to undercut new combined-cycle gas turbine plants by 2019 and coal-fired power plants by 2020.

CTF role in bringing emerging technologies up the deployment curve

As certain low-carbon technologies move up the deployment curve and can be more fully supported by public and private sector market actors, opportunities can arise through new low-carbon technologies. For example, CTF and SREP are supporting multiple countries with initiation phase development of CSP and geothermal energy technologies. While CSP and geothermal are not as cost-competitive as solar PV, wind, or fossil fuel alternatives in some countries, they can address baseload power and grid stabilization needs that may not be fully appreciated in existing policy and market contexts. Many MDB and country government interviewees indicated that power storage technologies are important emergent technologies that would benefit from initiationphase investment by CTF or other climate finance mechanisms.

Sources: Evaluation country case studies; BNEF 2019.


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7.6 Examples of follow-on investment in the energy sector

The evaluation team found evidence of follow-on investment (or signals of interest from private investors or developers) in all CTF and SREP countries analyzed in detail. Examples of follow-on investment or investor interest are summarized below.

CTF

• Chile. Chile has attracted a cumulative $11.4 billion in investment in large-scale renewable

energy projects since 2010.36 CTF engagement in Chile has catalyzed private sector investment

in solar PV, geothermal, and CSP energy. For example, CTF financing for the 73 MW Maria

Elena solar PV project played an important demonstration and risk mitigation role in catalyzing

subsequent investment in utility-scale solar PV projects in Chile (see Figure 5 for information

on solar PV investment trends in Chile).37

Figure 5: Chile disclosed new build PV investments by investor type

Source: BNEF 2018

• Thailand. In Thailand, the market for solar PV and wind power has changed such that the need

for concessional finance for projects has declined, and commercial banks are more open to

financing renewable energy projects. This may be on account of the overall changes in the

solar PV and wind markets (decreased technology costs, familiarity with renewable energy

financing and paybacks, etc.), as well as the demonstration value of individual blended finance

projects in Thailand. The Thai energy market appears to have shifted in important ways and is

approaching a tipping point where costs for new solar/wind power plant development

compare favorably to those for new fossil fuel plant development. (It will be longer for the

36 BNEF 2019. 37 BNEF 2019.

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second tipping point to materialize, whereby the levelized cost of electricity is the same). The

Subyai wind project represented an extension of and a follow-on project to the Theppana

wind project (7.5 MW). The success of the Theppana project gave investors the confidence to

proceed with the larger Subyai project (81 MW), which used a similar financing structure. Also,

in Thailand, after the initial projects supported by CTF and IFC, the Solar Power Company

Group (SPCG) went on to develop over 250 MW of solar generating capacity by 2014 and

planned to expand to other countries, such as Myanmar. SPCG has attracted over $800 million

in investment and has become the largest solar provider in Thailand.

• Mexico. In Mexico, three rounds of competitive auctions following energy reform in 2014

have seen numerous solar PV and wind energy projects proposed and selected for long-term

power purchase agreements that do not include concessional finance. Interviewees widely

asserted that moving forward, solar PV and wind energy projects in Mexico will not require

concessional finance.

• Morocco. In Morocco, the government renewable energy agency is looking to expand

regionally to support renewable energy deployment in ten other countries. Recognizing that

each country has its own market structure and resource profile, government representatives

acknowledge that the Moroccan institutional and finance model will have to be adapted, and

MDB representatives point to a need for additional capacity building for the agency to act as a

project developer outside of Morocco.

• Turkey. Over the past few years, private investment through the country’s feed-in tariff

program associated with Turkey’s Wind Energy Renewable Energy Resource Area (YEKA)

project has increased, driving down wind energy costs to record levels.38

• South Africa. In South Africa, co-financing through the Sustainable Energy Acceleration

Program has supported CSP projects through the REIPPPP competitive auction framework.

This has helped set price signals and build investor confidence. In subsequent rounds of the

REIPPPP, additional development finance partners, including local development banks, have

supported CSP projects and the costs for CSP projects have dropped.

SREP

• Armenia. In Armenia, there has been increased developer interest after the government

released its first ever reverse-auction tender for a 55 MW solar park in Masrik in April 2017.

Several interviewees noted they have observed increased private sector interest in future

utility-scale solar PV and wind energy projects.

• Ethiopia. In Ethiopia, where SREP has focused on improving the enabling environment for

geothermal energy development, there are signs of substantial private sector interest, as the

Government of Ethiopia signed 25-year power purchase agreements in December 2017 with

Reykjavik Geothermal for two US$2 billion geothermal plants, with a capacity of 500 MW

each.

• Honduras. In Honduras (SREP and DPSP), financing from local institutions is occurring, both at

the large project level and through micro-credit mechanisms. Banco Atlántida currently has

approximately US$280 million invested in renewable energy projects and is planning to

increase this investment to US$350 million within the next few years, although there are

substantial challenges to subsequent development of utility-scale renewable energy projects

in the country.

38 Daily Sabah 2017. World record bid for YEKA tender expected to lower electricity generation costs in Turkey. Accessed at

https://www.dailysabah.com/energy/2017/08/07/world-record-bid-for-yeka-tender-expected-to-lower-electricity-generation-costs-in-turkey




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• Nepal. Evaluation interviews indicate that there has been significant private sector interest in

Nepal regarding the issue of a tender release for utility-scale solar in which REP will finance

the viability gap between costs of production and the power purchase agreement price.

However, mini-grids face a range of barriers, including commercial banks’ perceptions of

major risks in terms of the capacity of communities to manage the projects and marginal

economic opportunities to support the capacity of the system. Ultimately, partial risk

guarantees were offered—on top of subsidy—to bring demonstration projects to financial

closure.

7.7 Examples of intermediation in the energy sector supported by CIF

As discussed in the evaluation report, CTF and SREP investment has supported a range of projects that

engage financial and/or supply chain intermediaries to develop new business models for deploying

low-carbon energy technologies. Selected examples include the following:

• Mexico (CTF) Green Bonds Initiative. In Mexico, a CIF-supported IDB private sector project is

working with energy service companies (ESCOs) to develop an innovative green bond financing

mechanism for energy efficiency and small renewable energy projects.39 While the project has

suffered delays due in part to low electricity prices that undermine energy efficiency project

revenues, the project is now supporting a new business model based on project finance

revenue streams. Securitization of the green bonds allows ESCOs to attract investments from

new sources, including institutional and impact investors, and IDB is working to replicate the

model in other Latin American countries.

• Mexico (CTF) Renewable Energy Financing. In Mexico, CTF investments supported NAFIN, a

national development bank, to grow a staff of more than 20 experts in renewable energy

financing and to develop a blended finance facility that supported seven utility-scale

renewable energy projects.

• Honduras (SREP) Cookstoves Project. In Honduras (SREP), CIF investments have focused on

improving market conditions for new business models for deploying clean cookstoves. The CIF-

supported project established a national clean cookstove quality standard; fostered

coordination among value chain stakeholders; reinvigorated local cookstove manufacturing;

created knowledge products on business models, gender, and legal frameworks; and delivered

over 10,000 cookstoves from 2014 to 2017.

7.8 The important role of country context and enabling conditions

Country context and enabling conditions play a vital role in determining whether and the extent to

which large-scale investments are successful and contribute toward transformational chance. The

evaluation team found a range of examples that support this finding, including the following:

• Even with large-scale concessional finance, potential geothermal and CSP energy projects

often face price barriers, which means they are not able to compete effectively against other

energy sources, including solar PV and wind energy. Market structures do not always value the

baseload (non-intermittent) benefits that geothermal and CSP can provide. In larger power

markets, the early focus is often on the integration of lower-cost intermittent renewable

energy sources, such as solar PV and wind energy.

• In Mexico, for example, several stakeholders indicated that the rapid fall in solar and wind

prices (reflected in winning bids for long-term power auctions) would slow the commercial

39 IDB 2015.


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development of geothermal, with projects now at least a decade away. In Morocco, CSP

projects are approximately four times the cost of the latest wind round issued, with the

government uncertain as to whether future expansions of CSP capacity will be included in the

2020–30 power plan. In Armenia, one geothermal developer sought a guaranteed tariff

payment of 10 c/kWh even after subsidized exploration and drilling support, more than

double the price of a recent utility-scale solar PV project. The value of renewable dispatchable

power becomes a driver when penetration of wind and solar PV issues begin to affect grid

performance and raise issues of new baseload or grid enhancement. These issues are

enhanced where concessional support is removed, and the costs of finance increase after a

series of demonstration rounds.

Evaluation of Transformational Change in the Climate ...

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