Annex A. Statistical note

According to the WTO Task Force on Aid for Trade, projects and programmes are part of aid for trade if these activities have been identified as trade related development priorities in the partner country’s national development strategies. Furthermore, the WTO Task Force concluded that to measure aid for trade flows the following categories should be included:

Technical assistance for trade policy and regulations: for example, helping countries to develop trade strategies, negotiate trade agreements, and implement their outcomes;

Trade-related infrastructure: for example, building roads, ports, and telecommunications networks to connect domestic markets to the global economy;

Productive capacity building (including trade development): for example, supporting the private sector to exploit their comparative advantages and diversify their exports;

Trade-related adjustment: helping developing countries with the costs associated with trade liberalisation, such as tariff reductions, preference erosion, or declining terms of trade; and,

Other trade-related needs: if identified as trade-related development priorities in partner countries’ national development strategies.

The OECD DAC aid activity database (CRS) is recognised as the best available data source for tracking global aid-for-trade flows. The CRS was established in 1967 and collects information on official development assistance (ODA) and other official flows (OOF) to developing countries. It is the internationally recognised source of data on aid activities (geographical and sectoral breakdowns) and is widely used by governments, organisations and researchers active in the field of development. For the OECD, the CRS serves as a tool for monitoring specific policy issues, including aid for trade. The CRS enables the tracking of aid commitments and disbursements, and provides comparable data over time and across countries. The use of this existing database led to significant savings of time and resources to effectively track aid-for-trade flows. The policy and guidelines for CRS reporting are approved by DAC members as represented at the DAC Working Party on Statistics (WP-STAT). The OECD collects, collates and verifies the consistency of the data, and maintains the database.

It should be kept in mind that the CRS does not provide data that match exactly all of the above aid-for-trade categories. In fact, the CRS provides proxies under four headings:

Trade policy and regulations. In the CRS, five purpose codes are used to cover trade policy and regulations activities. These five sub-categories are: trade policy and administrative management; trade facilitation; regional trade agreements; multilateral trade negotiations; and trade education/training.

Economic infrastructure. Amounts relating to trade-related infrastructure are provided in the CRS by data under the heading “Economic Infrastructure and Services” and cover the sectors transport and storage, communications and energy generation and supply.

Building Productive capacity (BPC), including trade development. The CRS captures full data on all activities in the productive and services sectors, such as agriculture; industry; mineral resources and mining; business; and banking. Trade development activities are identified through the Trade Development policy marker and have been separately identified in the CRS data collection since 2007 flows. These activities are an “of which” of Building Productive Capacity and are scored as either principally or significantly contributing to trade development. However, at time of reporting, some donors may have difficulty in identifying aid activities that have a defined trade component. This may reflect upon the accuracy of these data and, as such, amounts shown under trade development can only at best be used as approximations.

Trade-related adjustment. Was introduced in the CRS as a separate data item in 2007 to track flows corresponding to trade-related adjustment. This category identifies contributions to developing country budgets to assist the implementation of trade reforms and adjustments to trade policy measures by other countries, and alleviate shortfalls in balance-of-payments due to changes in the world trading environment.

The CRS covers all ODA, but only those activities reported under the above four categories can be identified as aid for trade. It is not possible to distinguish activities in the context of ‘Other trade-related needs’. To estimate the volume of such ‘other’ activities, it would be necessary to examine aid projects in sectors other than those considered so far – for example in health and education – and indicate what share, if any, of these activities have an important trade component. A health programme, for instance, might permit increased trade from localities where the disease burden was previously a constraint on trade. Consequently, accurate monitoring of aid for trade would require comparison of the CRS data with providers and partner countries’ self-assessments of their aid for trade.

Most of the data shown in Annex B are sourced from the CRS. To view the full set of CRS data please visit:

The list of aid providers is split into DAC member countries, other bilateral donors and multilateral organisations. The full names of organisations are listed under the Acronyms section. Note that:

  1. Korea became a member of the DAC in 2010 and was joined in 2013 by the Czech Republic, Iceland, Poland, the Slovak Republic and Slovenia. Data shown in previous years for these countries may be partial.

  2. The Central American Bank for Economic Integration (CABEI/BCIE) provided its first-ever data to the CRS in 2021. Data on years prior to 2020 are unavailable.

  3. Data collected from the EIF, FAO, IMF, ITC UNESCAP, UNESCWA, UNIDO, WTO and Türkiye comprise specialised reporting as from 2007 on Aid for Trade flows and may not constitute the totality of their individual aid funding.

  4. The Inter-American Development Bank (IDB) changed its reporting methodology to the CRS as from 2009 flows.

  5. “Other multilateral donors” include small amounts from several multilateral agencies (GGGI, AITIC, Nordic Development Fund, UNPBF, UNICEF).

The DAC List of ODA Recipients represents all countries and territories eligible to receive official development assistance (ODA). These ODA-eligible recipients consist of low and middle income countries based on gross national income (GNI) per capita as published by the World Bank, with the exception of G8 members, EU members, and countries with a firm date for entry into the EU. The low-income countries include the Least Developed Countries (LDCs) as defined by the United Nations. Countries that graduated from the list of ODA recipient might be listed in Aid Recipients tables with no Aid for Trade flow reported after graduation. The DAC List of Aid Recipients by income group and region, as well as the full historic of graduations to and from the DAC List can be viewed at:

The list shown in Table A.11 represents major headings for channels of delivery in the CRS. The full list under each category (updated in 6 July 2016), is accessible at: The category “Other” represents channels of delivery such as: Universities, colleges, or other teaching institutions, research institutes or think-tanks.

As from 2010 the method used to calculate sector allocable aid has changed. In order to measure donors’ intention, the calculation is now based on types of aid. This allows the inclusion of unpredictable aid that has a specific policy. For example, humanitarian aid is unpredictable but allows practices targeting gender equality. Aid where the donor has no control on the spending has been removed such as sector budget support and core support to NGOs.

“..” denotes zero.

0.0 denotes amounts of less than USD 0.5 million.

0.0% denotes a percentage of less than 0.5%

The assignment of SDGs to CRS projects was conducted following the methodology laid out in Pincet Okabe and Pawelczyk (2019). An XGBoost algorithm trained on SDG-specific documents (definitions provided by the UN, classified projects and external PDF sources) yielded the predictions for individual projects in the CRS reporting system, based on their associated project descriptions.

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