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Humanitarian aid: data and descriptive statistics
The Financial Tracking Service (FTS) database is a global database managed by the UN Office for the Coordination of Humanitarian Affairs (OCHA). FTS reports global humanitarian aid flows to emergencies and natural disasters. It records all reported international humanitarian aid contributions including bilateral and multilateral aid, NGOs, the Red Cross/Red Crescent Movement, private (personal of from a private entity) or confessional donations. Humanitarian aid is often seen as an intervention to help people who are victims of a natural disaster or conflict. However humanitarian aid is also sent to a country for which international assistance is needed to save lives even in the absence of disasters or conflict, during a lasting crisis. The Humanitarian aid must meet according to UN OCHA the following criteria:
Part of reconstruction projects can be included in humanitarian aid rather than in deve-lopment aid. FTS focuses on humanitarian funding flows. Data does not include government’s expenditure on crises within its own borders, government’s expenditure on refugees within its own borders, concessional finance and soft loans. This definition of humanitarian aid is precise and differs slightly from the OECD definition of emergency and humanitarian aid which is less precise: humanitarian action are actions saving lives, alleviating suffering and maintaining hu-man dignity during and in the aftermath of crises.
Nevertheless there is no major difference in the magnitude of aid and its evolution between FTS and OECD when focusing on donors that are in both databases and aid devoted to disaster response. Comparing FTS data with Development Assistance Committee (DAC) data, Fink & Redaelli (2011) find only minor differences between both databases, which show that FTS has The FTS data includes humanitarian aid from 2000 to 2014. 5 FTS covers humanitarian response plans (HRPs) and refugee response plans (RRPs), developed by the UN, after major humanitarian crises whose funding requirements are well defined. Response plans represent half of total humanitarian aid. FTS also includes humanitarian aid which is not linked to response plans and is provided by different type of donors.
FTS differentiates three types of flows: paid contribution (54 percent), committed funding (45 percent) and uncommitted pledges (1 percent). A pledge is a non-binding announcement of an intended contribution by the donor. A pledge could lead to zero formal contracts if it does not turn in commitments. A paid contribution is the payment or transfer of funds or in-kind goods from the donor to an implementing agency: it would correspond to a disbursement in the case of official development aid. A commitment is the creation of a contractual obligation re-garding funding between the donor and the implementing agency. Once a commitment is made implementing agencies can begin spending. Thus commitments result on actual projects before showing up as a paid contribution.
It is important to know whether there could be double-counting of implementation of com-mitment and paid contribution. As each humanitarian project is uniquely defined in the FTS database, I can check whether a commitment is followed one year of after by a paid contribu-tion. It is not the case. Hence it corresponds to two distinct flows of humanitarian aid and both should be taken into account. 6 In this paper I focus on paid contributions and commitments.
Another argument goes in favor to include both paid contribution and commitments. There is no statistical difference on the start date of projects or on the length of the project. 7 The only difference is on who reports the flow. Donors are more likely to reports paid contribution while implementing agencies are more likely to report commitments.
The FTS data has many advantages compared to the OECD data on emergency and huma-nitarian aid. First the FTS database provides information on more donors that DAC donors.
Fragmentation of humanitarian aid
In this section I describe the two different measures of fragmentation used in the literature. For simplicity I will always refer to donors but the indicator could be computed for implemen-ting agencies.
The simplest indicator is the number of donors (N). It refers quite directly to the OECD definition of aid fragmentation: “Fragmentation occurs when there are too many donors giving too little aid to too many countries. » The underlying assumption is that a high number of do-nors will make donor coordination more difficult and thus aid less effective, irrespective to the distribution of aid among donors. For instance a recipient with a donor allocating 90 percent of total aid and nine donors allocating the remaining amount is perceived as fragmented as a recipient with 10 donors each allocating 10 percent of total aid. This indicator does not take into account the possible existence of a leading donor that allocates the main share of aid to a recipient. If focuses on marginal donors that provide only little financial support while adding to the overall number of humanitarian partners and, arguably, to the needs of coordination.
The second indicator is based on an indicator used to measure the degree of competition in an industry: the concentration ratio CRm. It is the percentage of aid share provided by the largest m donors to a recipient country m CRm = X sordi i=1.
with sordi the share of the iest largest donor. Concentration indicators focus on the existence of few dominant donors In this paper I will look at CR3 which is the share of aid provided by the three largest donors (IAs). In order to compare this indicator with the first one, I define my second fragmentation indicator as 1 − CR3. Hence an increase in the value of the indicator means an increase in fragmentation.
The two indicators reflect different dimensions of fragmentation by putting emphasis on the high or the low end of the distribution: 1 − CR3 value the existence of top donors. It is relevant if the transaction costs of a marginal donor are small. In that case, the multiplication of donors does not lead to large increases in transactions costs and thus what really matters is the presence (or absence) of leading donors able to coordinate humanitarian aid. N values the existence of small donors at the low tail of the distribution. They are relevant if there are (increasing) and large transaction costs of dealing with a new donor in that case the multiplication of donors induces large costs compared to the benefit of having a new donor bringing humanitarian aid.
Donor and implementing agency fragmentation
On average 12.33 donors allocates humanitarian aid to a recipient country (table 2.5). In the case of a disaster as could be expected the average number of donors is increasing with the severity of the disaster – measured by the number of people affected. Indeed needs are higher and disaster are publicized. Fragmentation is higher when the UN launches a humanitarian appeal attracting 24.39 donors instead of 5.9 on average in the other case. However in that case, the UN is in charge of the coordination of donors (and implementing agencies). Hence an increase in the number of actors in this situation does not necessarily imply negative outcomes.
The structure of aid players, seen with the concentration ratio, seems less fragmented. 36.73 percent of humanitarian aid on average is given by three donors and thus does not appear to be fragmented at all given the indicator (table 2.5). The lower level of fragmentation in the struc-ture of aid is explained by the United States and the European Union who allocate large share of total humanitarian aid but also by Switzerland – who is often the only donor in recipient countries. The average fragmentation is about 0.17 which is a moderate level of fragmentation – it increases to 0.25 when I exclude recipients with less than three donors. Hence it seems that humanitarian aid is mostly funded by some large donors but that there are multiple donors allocating marginal amounts of humanitarian aid.
Table 2.5 also shows different patterns across regions. Donor fragmentation seems to be larger in Asia and Africa and lowest in the Pacific region. The table presents the results for America with and without Haiti in 2010: it affects the average number of donors while the concentration ratio remains similar. Indeed the earthquake leads to an unprecedented number of donors, especially American private donors.
However there is a large heterogeneity among recipient countries (table 2.6). 17 percent of recipient country-year has received humanitarian aid from only one donor. Those countries are mostly small islands and intermediate income-level countries. In that case, United States (13 percent), the European Union (18 percent) and Switzerland (18 percent) are the most likely donors. 41 percent of recipient countries have less than 5 donors which is quite low. Only 1.4 percent of countries have more than 50 donors.
Delegating aid and its fragmentation: potential consequences
A donor has the choice to delegate her humanitarian project to an implementing agency, to implement herself the project or to ask the recipient country to do so. As already mentioned the delegation to an implementing agency is the common choice in humanitarian aid. 22 The question is why delegating takes place.
Another question relates to the number of agencies through which humanitarian aid projects are delegated. Costs induced by fragmentation are often highlighted. Does the potential negative consequences of fragmentation offset the expected positive impact of delegation? Indeed while it is intuitively plausible that a growing number of intervening partners raises transaction costs and represents a burden on developing countries’ administrative capacities, it is theoretically much less clear whether these effects must necessarily outweigh potentially positive effects of delegation on aid effectiveness.
Positive impacts of delegation and fragmentation on aid efficiency
Delegations relies upon the division of labor and gains from specialization. Rather than performing the humanitarian project, the donor (the principal) delegates to a specialized imple-menting agency (the agent) with the expertise, time, ability and resources to perform the project.
Humanitarian aid requires specific expertise and knowledge that favors delegation. Imple-menting agencies have plausible comparative advantages in specific sectors, countries or to reach some sub-groups of the population. For instance de-mining activities require expertise that do-nors often do not have. They may also be involved in the country for a long time and thus have a specific expertise of the recipient context: 13 percent of projects are implemented by domestic IAs and 22 percent by IAs with more than 10 years of experience in the given country. A catholic-oriented implementing agency and a Muslim-oriented agency are more likely not to reach the same beneficiaries. It is particularly important in conflict crisis to insure that both sides of the conflict receive equal treatment. Hence implementing agencies are not necessary substitutes but could be complement.
Second implementing agencies can have the resources to perform the project because they pool together aid from different donors. In addition it allows some economy of scale that could be beneficial for humanitarian aid efficiency: entry fixed costs are for instance paid only once. Annen & Knack (2015) proposes a model that explains why it could be optimal for donors with very different motives to delegate development aid implementation to the same (multilateral) agency even if the agency is not specialized. They show that the multilateral agency is more able to increase aid selectivity (which is more likely to be efficient) than donors.
Table of contents :
1 Does Food Aid Disrupt Local Food Market? Evidence from Rural Ethiopia
1.1 Introduction
1.2 Context
1.2.1 Food aid in Ethiopia
1.2.2 Related studies on Ethiopia
1.3 Data and descriptive statistics
1.4 Empirical specification
1.4.1 On production
1.4.2 On sales and purchases
1.5 Results and analysis
1.5.1 On production
1.5.2 On sales and purchases
1.5.3 Robustness checks
1.6 Conclusion
1.7 Figures and tables
1.8 Appendix
2 Donors Versus Implementing Agencies: Who Fragments Humanitarian Aid?
2.1 Introduction
2.2 Humanitarian aid: data and descriptive statistics
2.2.1 Data
2.2.2 Descriptive statistics
2.3 Fragmentation of humanitarian aid
2.3.1 Indicators of aid fragmentation
2.3.2 Donor and implementing agency fragmentation
2.4 Delegating aid and its fragmentation: potential consequences
2.4.1 Positive impacts of delegation and fragmentation on aid efficiency
2.4.2 Negative impacts of delegation and fragmentation on aid efficiency
2.5 Three case studies of implementing agency fragmentation
2.5.1 Haiti 2010: the burden of fragmentation
2.5.2 Pakistan 2010: a useful fragmentation
2.5.3 Sudan 2010: the leading role of the UN
2.6 Conclusion
2.7 Figures and tables
3 To Give or Not to Give? How Do Donors React to European Food Aid Allocation?
3.1 Introduction
3.2 Empirical strategy
3.2.1 Specification
3.2.2 Instrumental strategy
3.2.3 Potential concerns
3.3 Data and descriptive statistics
3.3.1 Food aid statistics
3.3.2 Controls
3.4 Empirical results
3.4.1 Baseline results
3.4.2 Bilateral reactions
3.4.3 Placebo tests and robustness checks
3.5 A donor typology
3.5.1 Setting
3.5.2 Reaction function
3.5.3 Typology
3.6 Conclusion
3.7 Figures and tables
3.8 Appendix
General Conclusion
Bibliographie
