The Green Climate Fund (GCF) was launched in late 2013 and is set to play a key role in disbursing some of the $100 billion per year pledged to flow annually to developing countries by 2020 in support of climate action. A key question for the GCF Board concerns the rules for allocating its funds, as Benito Muller, Managing Director of Oxford Climate Policy, explains.

Resource allocation is a very tricky business, both technically and politically. However, it is by no means a new one. Considerable experience has been accumulated not only by other international funding institutions, but also in domestic contexts, and the GCF can draw lessons from this experience. During the past six months, I’ve worked with other analysts to pull together some of these lessons, and form recommendations for the GCF Board. Here is a summary of our findings and recommendations.

Numerous international and multilateral funding institutions are using a formula-based or ‘formulaic’ approach to country resource allocation. They are setting country funding ‘caps’ and ‘floors’: that is, minimum and maximum indicative amounts of funding a country can expect to receive during a funding period. With CDKN support, I have released a paper, Performance-based formulaic resource allocation − A cautionary tale, which looks at the Performance-Based Allocation (PBA) system of the World Bank International Development Association (IDA), probably the longest-serving, and certainly the most influential, methodology of its kind. The paper also assesses two of the World Bank’s ‘climate change progenies’: the Resource Allocation Framework  of the Global Environment Facility (GEF), and its successor, the System for Transparent Allocation of Resources (STAR). The experiences of these forerunners have yielded some important lessons for the GCF.

Lesson 1: Multiple funding objectives

The first lesson is about how to deal with different funding objectives. Most funds pursue different objectives, even within thematic funding windows. The Global Environment Facility’s current resource allocation methodology, STAR, has four objectives: first, to ensure global efficient use of the funds, ie, maximum global environmental benefits for the available money; second, to provide performance incentives; third, to satisfy the relevant capacity building needs; and, last but not least, to avoid being seen as inequitable because of a disproportional concentration of funding, which was a cause for the downfall of the earlier Resource Allocation Framework methodology.

STAR uses funding floors and ceilings to address its fourth objective: concerns around inequitable distribution. Its other objectives are addressed via a single, compound allocation formula: a first-order parameter is used to estimate potential global environmental benefits (first objective), and is modified by a performance factor (second objective) and a prosperity indicator (gross domestic product per capita), used as a proxy for estimating capacity building needs (third objective).

It comes as no surprise that the introduction of funding ceilings was found to limit the global efficiency with which funds were allocated, and so somewhat undermined STAR’s primary objective of delivering maximum environmental benefits. In light of this experience, my recommendation for the GCF is simple:

• Different objectives are best served through different funding envelopes (i.e., different ‘pots of money’). In other words, abandon the idea of a grand unified formula. What is needed is something rather more pragmatic: first determine a funding envelope for each of the objectives, and then allocate each of these envelopes in the most appropriate manner.

Lesson 2: Measures of funding need 

My analysis of the IDA’s Performance-Based Allocation demonstrated that the metric for determining a country’s poverty levels, which in turn determined a country’s funding need (or eligibility), was inappropriate. The IDA determined poverty by a measure of overall population size adapted by a per capita gross national income factor, whereas it would have been more appropriate to use the number of poor people as the base parameter.

The GEF’s Resource Allocation Framework (RAF) and System for Transparent Allocation of Resources (STAR) were also found to use an inappropriate funding need metric, namely the GEF Global Benefit Index. This allocates mitigation funding to countries with the aim of achieving maximum global benefit, ie, emissions reductions, for the available funding envelope. The analysis demonstrated that for certain objectives, an exogenous formulaic allocation may simply not be appropriate.  For allocations to provide best value for money, they are best decided endogenously through competitive financing tools such as the Quantity Performance Instruments (as discussed below).  The key recommendations to arise from this experience are therefore:

• Ensure that the ‘country funding needs’ to attain the objective in question can actually be estimated by way of an exogenous formula; and
• Ensure that the metric chosen is as direct as possible (try to avoid high-level proxy estimates).

Lesson 3: Some money for all eligible applicants

All these case studies confirmed that it is necessary to avoid the perception of inequity, should countries that are eligible to receive funding feel that they are left empty-handed (a lesson also drawn by a second study Lessons from fiscal transfer mechanisms, below). All three allocation systems have, or had, some funding floor. However, in the case of the GEF’s Resource Allocation Framework, this floor was not sufficient to avoid perceived inequity. That is why its successor followed the IDA’s Performance-Based Allocation system by introducing funding ceilings. These ceilings aimed to reduce the concentration of funding in few countries, but they also had the effect of reducing the cost effectiveness (efficiency) of the funding.

These equity demands – which can be interpreted as reflecting the principle of sovereign equality − could have been satisfied without compromising the efficiency objective in question by simply assigning to each of the objectives a separate funding envelope. By not mixing equity and efficiency with a single formula in a single envelope, it would have been possible, in particular, to defend more easily the idea that under a competitive distribution of funding, the outcome, no matter how concentrated, is fair – as  long as the competition was fair. This would not have impinged on the equity-based allocation, and the overall concentration of funding could have been managed by varying the relative sizes of the two envelopes. The recommendation in this context is thus:

• Ensure that equity considerations are adequately reflected. In particular avoid ‘empty eligible hands’, for example, by introducing appropriate funding floors.
• If there are funding objectives requiring (globally) efficient outcomes, then it is important that there is an explicit equity-based funding envelope that is distinct from the envelopes concerned with efficient outcomes.

Lesson 4: Adaptation funding needs

The next set of lessons for the GCF comes from experience with fiscal transfers from national to subnational governments. My paper on The Allocation of Adaptation Resources presents four short, illustrative country experiences – China, India, Switzerland, and the USA – chosen for the diversity in their underlying political systems and for the lessons to be learned. My analysis led to two recommendations that concern adaptation funding:

• Funding under an adaptation envelope should be allocated in proportion to funding needs, possibly with a prior division of eligible countries into categories with respect to their poverty intensity of gross domestic product (measured by the number of poor people per unit of GDP).
• Adaptation funding needs could be estimated in terms of vulnerability-adjusted numbers of people exposed to climate change impacts.

Lesson 5: QPP instruments as a competitive way to allocate resources

Finally, the GCF has a much to gain from scrutinising other funds’ experience with Quantity Performance Payments for mitigation funding. These could be used as part of enhanced direct access to the GCF. A paper by Samuel Fankhauser, and Maya Forstater and I looks into this experience in some depth: Quantity Performance Payment by Results. The paper describes in detail the main design options and issues regarding QPPs, in particular the issue of resource allocation and four core elements of QPP transactions: namely counterparty (vendor) selection, definition of results, price setting, and the setting of transaction quantities.

There are different ways in which these features can be determined, transaction by transaction. For example, counterparties and price could be determined competitively through auctions, or they could be set through negotiation on a first-come-first served basis, or by using a standard formula. Similarly, QPP transactions may be micro in structure (in other words, they could be structured as the aggregation of performance measured in smaller, decentralised activities, perhaps led by the private or third sector) or macro (rewarding performance measured at a national, sub-national, or sectoral level). The way in which these elements are determined fundamentally defines the nature of a QPP instrument. The GCF will have to develop a view on the design features that are most suitable for its purposes.

This paper considers some early experiments in using QPP instruments at a macro- and a micro-level. Examples of the former are the Norwegian International Forest Climate Initiative (NICFI), the Energy+ programme, and a scheme to reward accelerated transition pathways proposed by the Center for Global Development. The Global Energy Transfer Feed-in Tariffs (GET FiT) program and a proposal for a Clean Development Mechanism (CDM) Stabilization/Capacity Fund are examined as examples of QPP models involving micro-level results. We conclude that all these examples provide useful starting points, but none of them yet offers a fully operational approach to enhanced direct access.

The paper then carries out an evaluation of QPP instruments in the context of enhanced direct access, with respect to three key objectives of the GCF, namely, to promote a paradigm shift towards low-emission and climate-resilient development pathways, to achieve economic efficiency in directly securing emission reductions at cost, and to support equity in the distribution of resources.

• Based on this evaluation, the paper concludes that enhanced QPPs can be used in conformity with these objectives, provided they are used as a complement to other funding instruments.
• Finally, the paper puts forward two models − building on the example of the NICFI and the idea of a CDM Capacity Fund − as illustrations of how enhanced QPPs could be structured in the context of macro- or micro-level results.

Read the papers in full:

• Performance-based formulaic resource allocation − A cautionary tale
• The Allocation of (Adaptation) Resources
• Quantity Performance Payment by Results

Dr Benito Müller is Director, Energy and Climate Change, at the OIES, and Managing Director of Oxford Climate Policy.  Email: benito.mueller@philosophy.ox.ac.uk

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