Methodology and definitions

Humanitarian assistance is intended to save lives, alleviate suffering and maintain human dignity during and after human-made crises and disasters associated with natural hazards, as well as to prevent and strengthen preparedness for when such situations occur. Humanitarian assistance should be governed by the key humanitarian principles of humanity, impartiality, neutrality and independence. These are the fundamental principles of the international Red Cross and Red Crescent Movement, which are reaffirmed in UN General Assembly resolutions and enshrined in numerous humanitarian standards and guidelines.

In this report, when used in the context of financing data, international humanitarian assistance refers to the financial resources for humanitarian action spent outside the donor country. Our calculations of international humanitarian assistance are based on what donors and organisations report as such and do not include other types of financing to address the causes and impacts of crises, which we refer to as crisis-related financing.

There is no universal obligation or system for reporting expenditure on international, or indeed domestic, humanitarian assistance. The main reporting platforms for international humanitarian assistance are the Organisation for Economic Co-operation and Development (OECD) Development Assistance Committee (DAC) and the Financial Tracking Service (FTS) of the UN Office for the Coordination of Humanitarian Affairs (OCHA). Increasingly, data on humanitarian activities is also published according to the International Aid Transparency Initiative Standard. ^[1] OECD DAC members are obligated to report their humanitarian assistance to the DAC systems as part of their official development assistance (ODA), in accordance with definitions set out by the DAC. ^[2] Some other governments and most major multilateral organisations also voluntarily report to the DAC.

The FTS is open to all humanitarian donors and implementing agencies to voluntarily report contributions of internationally provided humanitarian assistance according to a set of inclusion criteria determined by the Inter-Agency Standing Committee. ^[3]

The analysis of international humanitarian assistance in the Global Humanitarian Assistance Report 2022 draws largely on data reported to the OECD DAC and the FTS. Between these sources, there is variation in inclusion criteria for humanitarian assistance, as well as volumes reported, so we aim to consistently explain and source the data that we use. Since the 2018 report, we have included humanitarian funding reported to FTS that has been provided by OECD DAC members as assistance to countries not eligible for ODA. We also use other sources to calculate international humanitarian assistance, including reports from UN agencies and non-governmental organisations (NGOs) on private humanitarian funding and data from the Central Emergency Response Fund on contributions from public donors; data sources and methodologies for these are also clearly marked and explained.

Our global estimate of humanitarian assistance provided in the form of cash and vouchers in 2021 is based on data collected from 27 organisations with support from the Cash Learning Partnership and supplemented with FTS data. The data will be analysed in greater detail in a forthcoming publication. ^[4] The methodology used for these estimates builds on one developed by Development Initiatives for research in 2016. For more information on this methodology and research, see Counting cash: tracking humanitarian expenditure on cash-based programming . ^[5]

We use ‘channels of delivery’ to describe the first level of organisations receiving funding for the delivery of humanitarian assistance – multilateral agencies, NGOs, the public sector and the international Red Cross and Red Crescent Movement – whether they deliver the assistance themselves or pass it on to partner organisations. Our data on channels of delivery in Figure 4.2 (Chapter 4) comes from the FTS. When referring to private donors’ channels of delivery in the report, we use our own dataset (see ‘Private funding’ ).

This data includes all ODA disbursements reported to the OECD DAC Creditor Reporting System (CRS) and marked with a relevant Rio marker by DAC members, multilateral organisations and other government donors that voluntarily report to the OECD DAC. The two Rio markers can be used to report the relevance of any ODA funding in terms of:

• Mitigation, where a project contributes to stabilising greenhouse gas concentrations in the atmosphere by promoting efforts to reduce or limit greenhouse gas emissions or enhance greenhouse gas sequestration
• Adaptation, where a project seeks to reduce the vulnerability of human or natural systems to current and/or expected impacts of climate change.

We include ODA marked as both principal and significant for both markers.

Country and region naming conventions used throughout this report are based on those used by the OECD DAC or the UN. Region naming conventions are based on those used by the OECD except the Middle East and North of Sahara regions, which have been combined. The conventions used do not reflect a political position of Development Initiatives.

For our analysis of crises by category, we apply thresholds to several indicators and cross-check with other data sources, notably ACAPS Crisis Overview. We use information from the Conflict Barometer 2021, of the Heidelberg Institute for International Conflict Research, to identify countries affected by conflict. For countries affected by disasters associated with natural and technical hazards, we use indicators in the INFORM Index for Risk Management and Centre for Research on the Epidemiology of Disasters Emergency Events Database (EM-DAT) data. And to identify displacement crises, we use data from the UN High Commissioner for Refugees (UNHCR), the Internal Displacement Monitoring Centre and the UN Relief and Works Agency for Palestine Refugees in the Near East (UNRWA).

Where appropriate in performing analyses of financial trends, we adjust for inflation by applying deflators in constant 2020 prices by source location of the funding. We use US$ gross domestic product deflators from the OECD DAC for DAC members and EU institutions and calculate these deflators from International Monetary Fund Economic Outlook April 2022 data for other countries. In the limited cases where data was missing from both of these sources, we estimate deflators based on the historical average real and nominal growth of gross domestic product based in US$. For financial flows that have a multilateral source, we deflate using the ODA-weighted average DAC deflator from the OECD. Consistent with our annual methodology, data in the Global Humanitarian Assistance Report 2021 was shown in constant 2019 prices, so totals may vary between reports.

We focus on three intersecting dimensions facing people in need in our analyses: climate vulnerability, socioeconomic fragility and conflict risk. We use country-level data for each of those dimensions.

We classify countries’ climate vulnerability using data from the Notre Dame Global Adaptation Initiative (ND-GAIN) vulnerability index. We identify people living in countries ranked in the top quintile of this index as having high climate vulnerability. People living in countries with no index data are assumed not to have high vulnerability.

The classification of socioeconomic fragility is based on the OECD States of Fragility framework 2020. Country-level socioeconomic fragility is calculated as the average of the framework’s first principal components of social, political and economic fragility dimensions. We identify people living in countries in the top quintile of this index as having high socioeconomic fragility. Countries with no index data are assumed not to have high fragility.

Our classification of high-intensity conflict risk uses information from the Conflict Barometer 2021 (of the Heidelberg Institute for International Conflict Research). Country-level conflict intensity is taken as the maximum of any sub-state, intra-state, and inter-state conflict intensity scores. People living in countries with a conflict score of 4+ (high-intensity, violent conflict) are identified as those with high-intensity conflict risk. People living in countries with no conflict data are assumed not to have high-intensity conflict risk.

For our analysis of ODA to disaster risk reduction (DRR) in 2020 in Figure 3.11 (Chapter 3) , we include the following funding flows as reported to the OECD DAC CRS:

• Funding reported with the purpose code 43060 ‘Disaster risk reduction’
• Funding reported with the value 2 under the ‘Disaster risk reduction’ marker, expressing DRR as principal objective of the associated activity
• Additional funding with DRR as principal objective as expressed by the project information reported to the CRS (this additional funding was identified by Development Initiatives through a search for DRR keywords in the project titles and descriptions of CRS entries; the output of the keyword search was then manually screened for relevance to DRR).

ODA in 2020 to the newly added ‘Covid-19 control’ purpose code that has also been marked as relevant to DRR has been excluded from this analysis, to focus on the risk reduction for natural hazards and to avoid conflating that with pandemic risk.

‘Earmarked’ funding comprises all non-core (‘other’) funding directed to multilateral organisations. Unearmarked funding may include softly earmarked contributions where this data was provided, for instance by region, to better reflect progress against the Grand Bargain commitment of providing more unearmarked and softly earmarked funding. Our definitions of different levels of earmarking used in our data collection reflect those in the annex of the Grand Bargain document. ^[6]

Our calculation of earmarking to nine UN agencies – the Food and Agriculture Organization, the International Organization for Migration (IOM), the UN International Children’s Emergency Fund (UNICEF), the UN Development Programme, UNHCR, UN OCHA, UNRWA, the World Food Programme (WFP) and the World Health Organization (WHO) – is primarily based on data provided directly to us by each agency based on its internal reporting or extracted from annual reports.

To convert original currency values into US$ values, we use exchange rates from the OECD DAC for currencies of DAC members, UN operational exchange rates for other currencies, and supplement with World Bank Development Economics Vice Presidency (DEC) alternative conversion factors where these are not available. The UN operational exchange rates are also used by UN OCHA FTS.

Our analysis of direct funding to local and national actors in Figures 4.3 , 4.4 and 4.5 (Chapter 4) uses data from FTS that we then ‘code’ according to a set of organisational categories. Figures 4.3 and 4.4 combine this FTS data with data available from country-based pooled funds on the funds’ direct and indirect funding to local and national actors, which uses the funds’ own classifications of recipients that might differ from the definitions below. For our own coding process, we use the following categories of local and national non-state actors and national and subnational state actors, as defined by the Inter-Agency Standing Committee Humanitarian Financing Task Team in its Localisation Marker Definitions Paper . ^[7]

• National NGOs/civil society organisations (CSOs): national NGOs/CSOs operating in the aid-recipient country in which they are headquartered, working in multiple subnational regions, and not affiliated to an international NGO. This category can also include national faith-based organisations.
• Local NGOs/CSOs: local NGOs/CSOs operating in a specific, geographically defined, subnational area of an aid-recipient country, without affiliation to an international NGO/CSO. This category can also include community-based organisations and local faith-based organisations.
• Red Cross/Red Crescent National Societies: national societies based in and operating within their own aid-recipient countries.
• Local and national private sector organisations: organisations run by private individuals or groups as a means of enterprise for profit, based in and operating within their own aid-recipient countries and not affiliated to an international private sector organisation.
• National governments: national government agencies, authorities, line ministries and state-owned institutions in aid-recipient countries, such as national disaster management agencies. This category can also include federal or regional government authorities.
• Local governments: subnational government entities in aid-recipient countries exercising some degree of devolved authority over a specifically defined geographic constituency, such as local/municipal authorities.

There are two other categories of first-level recipients featured in this analysis:

• Internationally affiliated NGOs: NGOs affiliated to an international NGO through interlinked financing, contracting, governance and/or decision-making systems. This category does not include local and national organisations that are part of networks, confederations or alliances wherein those organisations maintain independent fundraising and governance systems.
• Southern international NGOs: NGOs based in aid-recipient countries that are not OECD members, carrying out operations outside the aid-recipient country in which they are headquartered and not affiliated to an international NGO. The same organisation is classified as a national NGO/CSO when carrying out operations in the country in which it is headquartered.

Our dataset of gender-relevant international humanitarian assistance is based on a keyword search methodology applied to funding data reported to the UN FTS and consists of two major components.

• Gender-specific funding: funding that is reported to support gender-relevant humanitarian programming, with a key focus on addressing gender-related needs and advancing gender equality. This includes all funding reported under the Global Protection Cluster Gender-based Violence Area of Responsibility and other financial flows that reference gender-specific goals in the flow description, such as ‘women’s empowerment’ or ‘sexual and reproductive health’.
• Gender-mainstreamed funding: funding that references differing gender needs in programming, but where gender-related needs are not seen as the key focus.

For a more detailed account of our methodology, please see Appendix 1 in our separately published report, ‘Funding for gender-relevant humanitarian response’ . ^[8]

Our estimate of total international humanitarian assistance is the sum of that from private donors (see Figure 3.4, Chapter 3 ) and from government donors and EU institutions. Our calculation of international humanitarian assistance from government donors is the sum of:

• ‘official’ humanitarian assistance (OECD DAC donors)
• international humanitarian assistance from OECD DAC donors to countries not eligible for ODA from the FTS
• international humanitarian assistance from donors outside the OECD DAC using data from the FTS.

Our ‘official’ humanitarian assistance calculation comprises:

• the bilateral humanitarian expenditure of OECD DAC members, as reported to the OECD DAC database under Table 1
• the multilateral humanitarian assistance of OECD DAC members.

The multilateral humanitarian assistance of OECD DAC members consists of three elements.

• The unearmarked ODA contributions of DAC members to 10 key multilateral agencies engaged in humanitarian response: the Food and Agriculture Organization, IOM, the UN Development Programme, UNFPA, UNHCR, UN OCHA, UNICEF, UNRWA, WFP and WHO, as reported to the OECD DAC under Table 2a and the CRS. We do not include all ODA to the Food and Agriculture Organization, IOM, the UN Development Programme, UNFPA, UNICEF, WHO and WFP but apply a percentage to take into account that these agencies also have a ‘development’ mandate. These shares are calculated using data on humanitarian expenditure as a proportion of the total received directly from each multilateral agency.
• The ODA contributions of DAC members to some other multilateral organisations (beyond those already listed) that, although not primarily humanitarian-oriented, do report a level of humanitarian aid to OECD DAC Table 2a. We do not include all reported ODA to these multilateral organisations but just the humanitarian share of this.
• Contributions to the UN Central Emergency Response Fund that are not reported under DAC members’ bilateral humanitarian assistance. We take this data directly from the UN Central Emergency Response Fund website.

When we report on the official humanitarian assistance of individual OECD DAC countries that contribute to the EU budget, we include an imputed calculation of their humanitarian assistance channelled through the EU institutions, based on their ODA contributions to the EU institutions. We do not include this in our total international humanitarian assistance and response calculations, to avoid double counting.

Our estimate for official humanitarian assistance in 2021 is derived from preliminary DAC donor reporting on humanitarian aid grants.

Turkey is captured and shaded differently in Figures 3.1 and 3.2 (Chapter 3) because the humanitarian assistance that it voluntarily reports to the DAC largely comprises expenditure on hosting Syrian refugees within Turkey. We do not include Turkey’s spending on Syrian refugees in Turkey in our total international humanitarian assistance and response calculations elsewhere in the report, as these include only amounts directed internationally by donors.

In this year’s report, we use data from the FTS on volumes of international humanitarian assistance by recipient countries for 2021 data, which will become available in the OECD DAC CRS in December 2022 or later. FTS data was downloaded on 13 April 2022.

We drew estimates of people in need (PiN) from the UN OCHA Humanitarian Programme Cycle (HPC), supplemented by ACAPS. Our analysis for per-country PiN uses the maximum of HPC final-year estimates for country-level humanitarian response plans (HRPs), and ACAPS country year-maxima. To avoid double-counting, we do not include PiN as estimated by flash appeals (FAs) or regional response plans (RRPs) where a country-level HRP already exists.

For our analysis of PiN and people targeted for assistance by sector, we used HPC final-year estimates for country-level HRPs to ensure consistency and comparability. Sector-level data for Yemen 2020 HRP − which is missing from HPC − was drawn from the June−December update HRP documentation for this appeal.

Acute food insecurity classification data is from the Integrated Food Security Phase Classification. We classify people living in ‘crisis’, i.e. phase 3 level or higher, as being food insecure. Acute food insecurity numbers and phases are as reported or projected by the data year’s most comprehensive Integrated Food Security Phase Classification survey.

Survey coverage varies between years, with not all countries covered annually and some surveys limited to subnational areas. To capture a comprehensive total of people facing food insecurity, we select surveys from within two-year periods that cover the largest share of a country’s population. An exception to this is data for Yemen, where no comprehensive survey exists for the period 2019–2020 and so the figure reported is based on a 2018 survey.

Food insecurity severity is calculated based on an adapted Foster-Greer-Thorbecke (FGT; α=2) index that weights higher phases of food insecurity to produce a comparable index of severity.

We request financial information directly from humanitarian delivery agencies (including NGOs, multilateral agencies and the Red Cross and Red Crescent Movement) on their income and expenditure to create a standardised dataset. Where direct data collection is not possible, we use publicly available annual reports and audited accounts. For the most recent year, our dataset includes: ^[9]

• a large sample of NGOs that form part of representative NGO alliances and umbrella organisations such as Save the Children International, and several large international NGOs operating independently
• private contributions to IOM, UNHCR, UNICEF, UNRWA, WFP and WHO
• the International Federation of Red Cross and Red Crescent Societies and the International Committee of the Red Cross.

Our private funding calculation comprises an estimate of total private humanitarian income for all NGOs, and the private humanitarian income reported by six UN agencies, the International Federation of Red Cross and Red Crescent Societies and the International Committee of the Red Cross. To estimate the total private humanitarian income of NGOs globally, we calculate the annual proportion that the NGOs in our dataset represent of NGOs reporting to UN OCHA FTS. The total private humanitarian income reported to us by the NGOs in our dataset is then scaled up accordingly.

Data is collected annually, and new data for previous years may be added retrospectively. Due to limited data availability, detailed analysis covers the period 2016 to 2020.

Our 2021 private funding calculation is an estimate based on data on eight organisations that, combined, receive a large share of global private humanitarian funding year on year, pending data from our full dataset. These are: Médecins Sans Frontières, Plan International, Catholic Relief Services, the International Federation of Red Cross and Red Crescent Societies, the Danish Refugee Council, UNHCR, American Near East Refugee Air and World Relief. We calculate the average share that these eight organisations’ contributions represent in our private funding figure for the five previous years (50%, ranging between 47% and 52% over 2016–2020) and use this to scale up the private funding figure gathered from these eight organisations to arrive at an estimated total for 2021.

Our definition of protracted crisis countries includes countries with five or more consecutive years of UN-coordinated appeals, as of the year of analysis. The types of appeals and response plans used to determine this classification are outlined in ‘ UN-coordinated appeals ’.

We have chosen this approach to give an indication of the countries that have consistently, for a number of years, experienced humanitarian needs at a scale that requires an international humanitarian response. Those needs can be limited to specific geographical regions or populations (such as forcibly displaced people).

There may be minor discrepancies in some of the totals in our charts and infographics, and between those in the text, because of rounding.

We use this generic term to describe all humanitarian response plans and appeals wholly or jointly coordinated by UN OCHA or UNHCR, including strategic response plans, humanitarian response plans, flash appeals, joint response plans and regional refugee response plans. We use data from UN OCHA FTS and UNHCR for our financial analysis of UN-coordinated appeals.

Following an initial scoping exercise to identify mechanisms and channels of World Bank financing implemented in crisis contexts, seven instruments were selected based on their relevance for humanitarian actors, their volumes of funding and their accessibility of publicly available data. To ensure coherence, this selection was shared and discussed with relevant colleagues both within and external to the World Bank. The selected instruments do not provide an exhaustive overview of all World Bank financing in crisis contexts but aim to illustrate the main relevant tools currently operating in humanitarian settings.

The analysis is based on publicly available data from the World Bank Group. For the International Development Association (IDA), this includes: the IDA website, fiscal year 2021 country allocations, additions to IDA resources for IDA19 and IDA20, and mid-term operationalisation reviews, among others. For other mechanisms, sources include the Catastrophe Deferred Drawdown Option product note, the Global Risk Financing Facility website and annual report, the Global Concessional Financing Facility website, and the State and Peacebuilding Fund annual report.