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1. Introductory questions about DAC Statistics
1.1 What is Official Development Assistance (ODA) and how is it measured?
Official Development Assistance (ODA) is the term used by Development Assistance Committee (DAC) members to refer to what most people would call aid. To be counted as ODA, public money must be given outright or loaned on concessional (non-commercial) terms, and be used to support the welfare or development of developing countries.
1.2 Who reports data on their development cooperation to the OECD?
The DAC publishes a list of countries and organisations that report aid and development related financial flows to it. The list encompasses DAC members, countries that are not members, and multilateral organisations plus the Bill and Melinda Gates Foundation.
Two charts available to view ODA in USD and as per cent of GNI:
The first, for the latest year available.
The second, long term trends since 1960.
2. Donors and flows
2.1 What are the differences between multilateral agencies and NGOs?
The simplest distinction is that multilateral agencies, such as the many agencies of the United Nations, are governed, by representatives of governments. Non-Governmental Organisations (NGOs), on the other hand, do not have government representatives directly involved in their governance, which consists of individuals acting in their private capacity.
2.2 What are the differences between bilateral, multilateral and Bi/Multi aid?
Bilateral aid represents flows from official (government) sources directly to official sources in the recipient country.
Multilateral aid represents core contributions from official (government) sources to multilateral agencies where it is then used to fund the multilateral agencies’ own programmes.
In some cases, a donor can contract with a multilateral agency to deliver a programme or project on its behalf in a recipient country. Such cases are typically counted as bilateral flows and are often referred to as Bi/Multi.
2.3. What are the differences between multilateral ODA and multilateral outflows and why are multilateral outflows captured in DAC statistics?
The term multilateral Official Development Assistance (ODA) is a measure, from the donor perspective, that represents flows from a government to multilateral organisations. These are also referred to as core contributions as the donor country would typically not specify which projects and programmes are to be funded. Core funds are also used to meet the overheads of multilateral agencies. Multilateral agencies may also receive funds from other sources, such as the general public or from other private donors.
Outflows from multilateral organisations typically represent project and programme spending. Multilateral outflows are measured and published by the DAC, not only a means of tracking and providing transparency around spending, but also to allow for analyses leading to better policy and targeting of such spending.
2.4 How is double counting avoided with regard to money flowing into, then out of, multilateral agencies from donor countries?
Double counting is avoided by being clear about what is being measured. Donors report the following flows to the DAC:
Bilateral ODA to recipient countries
Multilateral ODA - core contributions to multilateral organisations
Earmarked ODA channelled through multilateral organisations (Bi/Multi) to a specific recipient (the multilateral organisation is contracted to deliver a specific project)
Other Official Flows
Private flows originating in the donor country
These flows are added together (total official and private flows) represent the total donor effort.
Calculating receipts by recipient country
Multilateral organisations report their outflows to the DAC, including details of the recipients such as the country or region. When it comes to calculating the total receipts for a recipient country, the total donor effort is used except donor’s core contributions to multilateral agencies. Instead, data recorded on outflows from multilateral organisations to a recipient country is added to bilateral flows to find the total receipts for a given recipient country and so avoid double counting.
The advantage of this method is that information on flows to recipient countries is much more accurate and detailed.
2.5 What is the difference between core (pooled) and non-core contributions to multilateral agencies?
Official Development Assistance (ODA) to multilateral development organisations from donor countries or institutions that is pooled and used to meet an agency’s running and programme costs, in a way that means that it loses its identity and becomes an integral part of the recipient institution’s financial assets. Non-core funding can include instances where the donor specifies how the money is to be spent.
2.6 How are loans repayments (principal) and interest treated?
The repayment of the principal of the loan is netted off against gross Official Development Assistance (ODA) flows as these repayments are made. This means that when the loan has been fully repaid, the effect on total net flows over the life of the loan is zero. Flow data does not include repayments of interest.
3. Statistical terms and reporting issues
3.1 Where do I find definitions of all the technical terms related to statistical reporting e.g. commitment versus disbursement, constant versus current amounts etc.?
3.2 What is the difference between gross and net ODA?
Gross ODA is the amount that a donor actually spends in a given year. This figure becomes net once repayments of the principal on loans made in prior years (but not interest) are taken into account, as well as offsetting entries for forgiven debt and any recoveries made on grants.
In some cases, repayments exceed gross amounts, which is why net figures sometimes appear as negative values.
3.3 What is the difference between preliminary and final data for a given year?
Preliminary data for aid (ODA) are reported each April for the preceding calendar year. These are published at a high level that just shows the aggregate data for different types of spending. The data are not broken down by recipient country or to the level of individual projects. Detailed, final, data are released in December.
Country Programmable Aid (CPA) is the portion of ODA donors programme for individual countries, and over which partner countries could have a significant say. CPA is much closer than ODA to capturing the flows of aid that goes to the partner country, and has been proven in several studies to be a good proxy of aid recorded at country level.
3.5 What is the difference between a commitment and a disbursement?
Commitments measure donors’ intentions and permit monitoring of the targeting of resources to specific purposes and recipient countries. They fluctuate as aid policies change, and reflect how donors’ political commitments translate into action. They thus give an indication about future flows.
Disbursements show actual payments in each year. They show the realisation of donors’ intentions and the implementation of their policies. They are required to examine the contribution of donors’ actions in development achievements. They better describe aid flows from a recipient’s point of view.
Analysing the relation between commitments and disbursements can provide useful insights on aid delivery. Commitments are often multi-year and subsequent disbursements spread over several years. In DAC statistical reporting systems, commitments, even if multi-year, are recorded in whole in the year they are signed (the use of moving averages in statistical presentations smoothes the resulting fluctuations). Subsequent disbursements of an earlier commitment are recorded annually, in the years they are transferred from donors to recipients. An increase in aid allocations over time is thus visible in disbursements data only with a few years’ time lag. Consequently, disbursements in one year cannot be directly compared to commitments in the same year, as disbursements may relate to commitments originally recorded in different years.
3.6 Where can I find technical information such as code lists, sector and flow classification, counting in-donor refugee costs, grant element calculation, deflators, bilateral and multilateral outflows, imputation calculations and how Country Programmable Aid is calculated?
There are two main data updates each year. In April, high level (aggregated) figures are published on total aid given by donor countries for the previous calendar year. In December, these figures are updated with detail on how the money was allocated by recipient country, sector (health, education, etc), geographical region and by income group (Least Developed, Upper Middle Income, etc). In December, detail is also available right down to individual project level. In addition to these two main updates, partial database updates occur in June and September each year.
4.2 What is the difference between OECD.Stat and QWIDS?
These are two gateways to the same aid and development related data. OECD.Stat is the OECD’s data warehouse. It contains datasets from across the OECD, including those relating to aid and development which can be found under Themes/Development. QWIDS is a query tool for datasets relating to aid and development. QWIDS is easy to use and automatically selects the best dataset from which to extract data based on the search terms you select.
4.3 What is the difference between the DAC and CRS datasets?
The Development Assistance Committee (DAC) Secretariat collects data using two different questionnaires. These are known as the DAC and Creditor Reporting System (CRS) questionnaires. The main differences are that the DAC questionnaire focuses on high level data, while the CRS questionnaire focuses on detail, right down to the individual project level.
In principle, data from both questionnaire should match but, for historical data, discrepancies can arise from:
Coverage gaps, especially for earlier years – not all donors provided data compatible with the level of detail required for the CRS;
Different bases being used – e.g. it may be that for some entries, aggregate data were reported as commitments, whereas activity level (CRS) reporting may reflect actual disbursements.
The DAC Secretariat has now published a single, converged, set of reporting directives applicable to both questionnaires which enables aggregates to be compiled from activity (CRS) level data so such problems should no longer arise.
You can search individual data sets from the DAC and CRS datasets in OECD.Stat, look under Themes/Development then select a dataset. Or you can use the QWIDS tool to have data extracted automatically from the most appropriate dataset based on your search terms.
4.4 If there are two reporting systems, are there two, different, sets of data?
The Development Assistance Committee (DAC) aggregate statistics consist of an annual questionnaire that collects high level information by theme (types of aid, types of flows, country, sector and tying status). The Creditor Reporting System consists of a reporting template that collects detailed level information at the level of an individual aid activity. As the two systems are in the process of being converged, the detailed project level data (aid activities) can be used to produce the DAC aggregates.
4.5 What do the results such as ‘..’ and ‘-‘ and ‘0’ mean?
The symbols used and their meanings are:
1. For datasets viewed in OECD.Stat and using QWIDS:
() Secretariat estimate in whole or in part 0 or 0.00 Nil or negligible n.a Not applicable p provisional
2. When viewing data from the Total Flows by donor (ODA+OOF+Private) [DAC1] dataset in OECD.Stat or using QWIDS:
Viewing the latest year for which data is otherwise available:
.. Data not available (in a particular field)
Viewing early years’ data:
3. Additional symbols applicable to the Development Cooperation Report:
- Nil or not applicable .. Data not available
4.6 I see negative disbursement figures when I run a data query – what does this mean?
When calculating net ODA, loan repayments are recorded as negative and deducted from ODA and loans. In some cases loan repayments are higher than new ODA and net ODA will show as a negative number.
4.7 Help! I am having technical problems and cannot access the data, can you help?
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4.8 Where can I find the Creditor Reporting System (CRS) data before 1995?
Creditor Reporting System (CRS) data on commitments from 1995 and disbursements from 2002 are made available for viewing in OECD.Stat and via QWIDS.
Earlier commitment and disbursement data is available for download, but there are gaps in the coverage for some donors and years yet this data is still useful for some analytical purposes such as ODA loans.
4.9 How do I download CRS data, including on disbursements prior to 2002 and commitments prior to 1995?
Go to the CRS dataset in OECD.Stat. Then use the Export drop-down menu above the data and select Related files. Click on the file name that you would like to download and a dialogue box will open at the bottom of the screen with options for what you can do with the file. All CRS text files can be converted to either Excel 2007 or a later version (you need to use the vertical bar ‘|’ as delimiter and none as text qualifier) or any other software which enables the download of files with more than 65,000 rows.
The bulk files enable data users to carry out multi-faceted analysis by filtering different categories such as donor, recipient, purpose and channel.
A text search on the project descriptions provides the data users with further information on the relevant activities, although text search results would be dependent on the quality of the descriptive information provided by donors.
4.10 What are policy markers and what is the best means to review and analyse marker data?
Markers are applied to project level data across a number of sectors to help the international community track its perfomance relating to a number of international agrements to take action in certain areas. Marker data is available for Gender Equality and the Environment:
The Environment (including the Rio Conventions)
Climate change adaptation
Climate change mitigation
Given that all funding is primarily recorded by sector, it is not appropriate to view marker data as additonal spending, nor can different sets of marker data be added togehter, such as climate change mitigation, and climate change adaptation, as this might lead to double counting of projects that support both outcomes.