An introduction to OECD-DAC data

Module Objectives:

  • Understand why you might use OECD-DAC data

  • Understand its strengths and weaknesses

  • Learn where to find it online

Prerequisites/before you get started:

  • Completed Introduction to Aid Data

Table of Contents:

  • Why are we looking at the OECD-DAC data?

  • What to expect from this data

  • Things to understand before diving into the data

  • Strengths of the OECD-DAC data

  • Where to find the data online

Introduction

As we mentioned in the Introduction to Aid Data, the OECD is a good source of development data. However, using it will be made much easier by understanding a few pieces of contextual information, thinking about its strengths and weaknesses, and of course, knowing where to actually find it online.

Why are we looking at the OECD-DAC data?

The DAC aid statistics are widely considered to be the “official” source of data on aid- in some cases, the data dates back to the 1960s.

Generally, the data included ranges from regional or national aggregates, to individual project level.

What to expect from this data?

Crucially, the data included here is on the money that flows out of donor countries, not necessarily the money that flows **into **low-income countries: as we’ve mentioned earlier, some of this money is spent in the donor countries themselves.

Also, as with all data on ‘aid’, or Official Development Assistance, remember that it is just a small part of a wider ecosystem of financial flows going into developing countries. In the case of the figures included here, they are also subject to the OECD’s definition of what they actually consider to be Official Development Assistance; ie.

  • Their main purpose must be the economic development or welfare of the developing country

  • The source must be “official” (eg. no informal financial flows like remittances or charitable contributions from individuals are included)

  • Must go to one of the countries which appear on a list of ‘Official Development Assistance’ recipients, agreed by the DAC.

  • It can be administered through grants or loans, but loans must be given at a more generous rate than usual loans – this can be done through either the recipient of the loan (the poorer country) having a longer time to pay the loan back, or having a lower interest rate. These kinds of loans are known as concessional loans.

The DAC database also includes:

  • OOF (Other official flows)

  • FDI (Foreign Direct Investment)

  • Some private flows

Things to understand before diving into the data

There are some structural and linguistic concepts it’s important to understand:

Commitment Disbursement
= written obligation or formal declaration of what will be paid or transferred
(ie. a promise of what donors will do)
= actual transfer of resources (money, or goods) to recipient country or agency
(ie. money has actually left the donor agency here)
Date of commitment = date that the written obligation/agreement is signed Date of disbursement:
for money: the point of payment by the official sector
for goods/resources: the date of transfer of ownership of the resources, or purchase of the goods

Special expenditures like humanitarian aid, where the date of disbursement = date of commitment are an exception

Bilateral aid Multilateral aid
Resources go from donor country directly to a low income country Resources go to a recipient institution which:
– works either fully or partly in development
– is an international agency – eg. United Nations agencies, the EU, international financial institutions, global multi-donor trust funds
Vertical Funds/Global Funds (e.g.
Global
Alliance for Vaccines and
Immunisation (GAVI))
Core contributions to UN, IFIs,
EU
Global multi-donor trust funds
Global Funds/Vertical Funds
Donor can specify how the funds should be spent (= earmarked funds) Recipient has complete freedom to decide how the funds are used (= unearmarked funds)
given through international organisations such as the World Bank rather than by one specific country

Strengths of the OECD-DAC data

Comprehensive: The data included here is fully comprehensive for what is defined as “Official Development Assistance”, and reporting to the database is mandatory for all 29 DAC member countries.

Less risk of double counting: Within the dataset itself, you don’t have to worry about double counting – ie. the same activity or event being counted more than once. This is a weakness of other aid datasets.

Validated/good quality: The data has been validated through the Development Cooperation Directorate, and via Peer Reviews (more information here)

Comparability: there are standard criteria (codes for sectors, types of aid, terms and conditions) – which are used universally, making the data comparable between donors, and over time

Historic: the data goes back as far as 1960 (in some cases; it’s not all complete)

Measuring against targets: the data is useful for measuring against commitment levels (eg. are donor countries meeting the 0.7% of GNI target?) – and, to a degree, sectoral targets, and geographical targets.

Weaknesses of the OECD-DAC data

Excludes much of the ‘aid bundle’: for example, remittances, charitable donations from the public, foreign investment, funds that don’t meet the ‘official’ definition of ODA – which means that the financial flows here are just a tiny portion of resources which are intended to reduce poverty in poor countries.

Slow to publish: full datasets are not published until December of the following year (although limited preliminary data is published in April)

Difficult to match up with money received: the data here is on money that flows out of donor countries, not necessarily the money that flows into** **low-income countries. There are multiple reasons why these two might not match up as lots of ODA is actually spent in the donor country (but still qualifies as ODA, if the economic welfare of a developing country is the ‘main’ aim). For example, some of it goes towards debt relief, or student costs in the donor country.

Difficult to match inputs with outcomes: as there are no economic/social indicators included here, it’s difficult to see whether projects had the desired outcomes – eg. increased spending on malaria prevention vs. a reduction in malaria prevalence

Not so useful for:

  • helping recipient countries manage their aid flows – for this, a dedicated Aid Management Platform is much more useful

  • tracking aid beyond recipient government level – what happened after it went to a specific government?

Where to find the data online

The OECD makes its data available in a number of ways: it can be slightly confusing to know where to go to get exactly what you’re looking for, so here is a quick guide to the various sites and sources.

Query Wizard for International Development Statistics

Where: http://stats.oecd.org/qwids/

What: A way of getting data by CSV, filtered by options that you can select on the initial screen. It provides 6 different options: by Donor, Recipient, Flow(s) (eg. type of financial flow, ODA, or OOF) Flow type (see glossary above), Sector and Time Period. It allows you to export what you get back in CSV, or send a ‘bookmarked link’ to others.

Strengths:

  • No understanding of the structure of the DAC data is required to use this.

  • Includes a page of Popular Queries — ie. other ways that people have used the site, and allows you to do the same thing.

  • 6 “dimensions” are included here, so lots of options to get exactly the data you want.

Weaknesses:

  • If we’re being picky, technically not all data within DAC is accessible via QWIDS- it’s actually only about 95% of the total.

  • Again, picky, but it doesn’t look very appealing:

image_0

Who is it useful for?

People investigating a specific section within the world of aid — for example, if you wanted to see how much money is going from donor X to recipient Y, over a certain time period, and get the data in CSV.

Further guidance:

A demo screencast by the makers of the site (caution: it starts automatically)

OECD.Stat

Where: http://stats.oecd.org/

What: The main repository for all DAC data. Start by selecting a dataset in the left hand menu (‘Data by theme’), then click on Customise → Selection to change what data is displayed, and reorganise its layout via Customise → Layout. using the option at the top of the table. You can download the data via Export → Excel or Export → CSV.

There are a lot of in-browser display options given; realistically though, very few people who actually want to work with the data are going to use the browser to manipulate it the data nor to create any visualisations from it, as it’s much easier to download the raw data and then work with it in another tool (Excel or Google Spreadsheets, for example.)

Strengths:

  • It contains, apparently, everything available in the DAC database, so, not just official development assistance flows, but data on a huge range of topics, from agriculture, to education, health, cities and transport.

Weaknesses:

  • In terms of Official Development Assistance, it doesn’t appear to be possible to filter the data by ‘recipient country’, just by donor, or sector; clearly (and naturally, given it is from the OECD) the data is structured with the donor country in mind.

  • No option to send a link to a specific dataset (ie. the URL doesn’t change)

  • Some options include very specific options labelled with acronyms, with no explanation of what they stand for (eg. data from the African Economic Outlook is classed by various indicators – PRB, PRMB, PRMS – the user has to look this up on a separate site to understand what these are)

Further Guidance

OECD.stat Web Browser User Guide

OECD iLibrary Statistics

Where: http://www.oecd-ilibrary.org/statistics

What: Offers access to OECD core data – rather than simply split across indicator datasets (eg. Agriculture, Education), here it is also arranged according to projects or reports that the OECD releases. For example, the data used for the OECD Economic Outlook report can be found here.

Once you’ve selected the dataset, it appears through the OECD.stat interface (as above), and can be downloaded, as above.

Strengths:

  • It’s good to have a single place to go to to get aggregated datasets – especially if they have been used to draw out potentially important conclusions, such as those from the OECD Economic Outlook report.

  • Includes a ‘search’ function, too.

Weaknesses:

  • As above, the data appears through the OECD.stat interface — while this might be good in some ways, it means that exporting the raw data directly requires another step.

OECD Aid Statistics

Where: http://www.oecd.org/dac/stats/data.htm

What: All OECD projects, sites and data that data that focuses on aid.

Strengths:

  • Includes links to specific datasets that might be useful to inspire further thought or exploration, via the International Development Statistics page though it is a little confusing to understand the difference between these datasets and the ones presented above.

  • Good to have one page with all data organised thematically

Weaknesses:

  • Slightly difficult to find, and to understand the differences between the various options offered

  • The data visualisations presented could do with a little work…

Further resources:

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