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Evaluating blended finance instruments and mechanisms
Approaches and methods
This paper provides an overview of how to evaluate different blended finance instruments
and mechanisms, including equity instruments, debt instruments, first loss capital,
guarantees and insurance, development impact bonds, performance-based grants, structured
funds and syndicated loans. It is structured along the most important and common questions
evaluators seek to answer, including how to measure the mobilisation of additional
financial resources, and assessing results. It provides a description of the most
appropriate methods and tools for answering these questions, highlighting their advantages
and disadvantages, and discusses their application.
Published on August 06, 2021
In series:OECD Development Co-operation Working Papersview more titles
There is a rich diversity of methods and tools available and used to evaluate blended finance instruments and mechanisms. However, the current practice of blended finance evaluation is unsystematised, fragmented and compartmentalised across instruments and mechanisms.
There is broad agreement among evaluators that analysing an intervention’s theory of change or investment thesis is the crucial first step in any evaluation. The intervention’s theory of change informs the selection of the most appropriate combination of research methods.
Most practitioners and many scholars recognise the value of selecting, integrating, and sequencing methods drawn from both the theory-based cluster of research tools and the counterfactual cluster in ways that respond to the evaluation’s terms of reference.
Stakeholder engagement throughout the evaluation process is essential to optimising insights and utilisation.
The confidentiality of information is a prominent challenge in collecting data on the performance of blended finance instruments and mechanisms, especially for front-end results. Strict privacy regulations in the banking and investment sectors often disallow the sharing or publication of certain types of data.