Statistics in development cooperation - interventions to support statistics

This article is part of a set of background articles providing an outline of knowledge of international statistical cooperation between the European Union (EU) and developing countries, for non-statisticians needing to deal with statistics in development programmes and projects. The outline serves as an entry point and introduction to the much more detailed Eurostat publication 'Guide to statistics in European Commission development cooperation', downloadable in PDF format in English, French and Spanish (further down referred to as 'the Guide').

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Choosing the most adequate mode of intervention

Support to statistics can be given through any of the various types of instrument used in European Commission development cooperation but more specifically through:

Budget support programmes

These programmes typically have a capacity building component that can be mobilised to support the strengthening of statistical systems, either through project modality, technical assistance or pooled funding (Guide sections B.1.5.2, B.3.3.3, C.7.3.1.) See the Statistics explained article on Statistics in development cooperation - budget support for more details.

  • Comments: Local ownership, statistical activities are closely linked with the overall budget reform programme
  • Example: EDF10 budget support to Rwanda which includes support to statistics.

Projects focussed on statistics

They may address a specific weakness in statistical operations, technical capacities or production, analysis and dissemination of statistics or the functioning of the NSS as a whole (Guide sections C.7.3.1, C.7.4.1 and C.7.4.2)

  • Comments: Targeted on key statistical problems/issues; strenghten the National Statistical Institute as central producer of official statistics.
  • Example: Ethiopia – support to the business register.

Sector-Wide Action programmes

They are programme-based approaches applied to a particular sector, such as education, health or agriculture, which may contain a statistics element. There could also be a sector-wide programme for statistics which may or may not form part of a wider government or planning system reform. (Guide section C.7.3.1)

  • Comments: The statistical activities are embedded into the sector reform programme; Particular attention to be brought to the fact that they may be carried out by and for non-professional statisticians
  • Examples: Mozambique United Nations Development Assistance Framework 2007-2009, which includes a wide range of support to statistics at national, provincial and local level. EDF10 programme in Mauritania proposes general support to statistics reform as part of good governance.

Preparing the project

What to do?

Support to statistics may be offered in different ways:

Funding data collection and processing

  • Data collection: statistical operations (surveys, censuses, administrative data), standard questionnaires;
  • Data processing: up-to-date statistical software, development of standard tools for the processing of surveys, the automation of production of short-term indicators, archiving tools.

Building and strengthening capacities

  • Methodologies and practices (international standards and norms);
  • Organisation and functioning of the NSS: strategies, legal and institutional framework;
  • Training and human resources development;
  • Strategies and management (non-statistical types of support including potential technical advice in legislation, public administration, budget and external funds management, strategic planning, human resource management, communication).

Supporting data analysis and dissemination

  • Data analysis: statistical software, examples of analysis made in other countries;
  • Data dissemination: a GIS software, provision of standard tools for the dissemination of databases to general public, website designing tools.

Building statistical infrastructure

  • Provision of Geographical Information System (GIS) software to help in the design of a census, of a sample;
  • Provision of communication hardware and software for instance for the building and maintenance of registers (of enterprises, of administrations, of organisations) for contacts with data providers and users; ease of general access to internet, implementation of cost-effective methodologies.


Identification and feasibility

  • Guide sections C.8.1 and C.8.2
  • Guide Box 8.1: Terms of reference checklist for a statistics identification or pre-feasibility study
  • Guide Box 8.2: Elements for terms of reference of a design study for a statistical project

Analysis of the context

The analysis of the context (diagnostic of the NSS, identification of the main development issues for statistics, other interventions and coordination) is an important aspect of both the identification and the appraisal work (Guide sections B.1.3 and C.6.1).

Sources and related documentation for writing a statistical project

Statistics and the Project Cycle Management (PCM)

Overall objective – Project purpose

The purpose of any European Commission statistics intervention is to support the development partner to produce good quality statistics sustainably in order to inform decision-making. This statement is a model for any statistics action.

Specific objectives

All European Commission statistics actions in all regions of cooperation aim at one or more of the following three specific objectives:

  • Improve coverage and quality of statistical information (output);
  • Improve capacity to collect, produce, analyse and disseminate statistical information (capacity building);
  • Improve the use of statistical information (use).

For example, an action to support the adoption of international standards in a partner country might include specific objectives that cover both output and capacity-building.

For more information, see also the Guide sections C.7.1 and C.7.2

Expected results

At the operational objectives level, six common types of outputs can be identified, which together correspond to the range of statistics-related problems that a NSS may face:

  • Strengthen relationships with decision makers; medium term strategy developed to meet policy-oriented goals (strategy),
  • Strengthen legal and regulatory framework, inter-institutional relationships (framework),
  • Strengthen capacity to develop, produce and disseminate quality statistical information required to formulate, implement and monitor policies (capacity)
  • Develop the international comparability of statistics. In some cases this requires harmonisation with European standards (capacity / harmonisation)
  • Strengthen capacity of stakeholders to access, analyse and interpret statistical data (users)
  • Provide direct support to produce and disseminate specified statistics (production support). Direct support for data production and dissemination is usually given for population censuses and large-scale surveys, where external support is appropriate due to their cost.

Indicators and sources of verification

At the project purpose level, these should relate to publication of statistics and metadata both at country (or regional) level and through international data sources (Guide section C.7.2.). For statistics users, published analyses of statistics should be highlighted.

At the results level, indicators should relate to the application of the activity outputs. This is particularly important in capacity building activities. For example, in the case of training in statistics: what is the plan to apply the training received, for example in changing statistical nomenclature? To which extent have the students that participated in the training been employed to produce and disseminate official statistics?

Output level indicators are relatively straightforward, even for capacity building actions: training materials, attendance lists, trainer’s reports and student evaluations are examples.

For more information, see also:

See also the presentation in the Statistics explained article Statistics in the European Commission project cycle


Evaluation is a key aspect of the PCM. The general reference methodology for evaluation can be found in the section on evaluation methodology on the website of Directorate-general International Cooperation and Development.

Mid-term evaluation may help re-orient the objectives of the project during its implementation as a result of changes in methodologies, processing/production modes, data collection technology or in the demand from users.

Final (ex-post) evaluation may be very useful when the project is part of a larger medium term process of capacity strengthening, as it is often the case for statistics (Guide section C.8.4).


  • Do the project objectives aim at solving the problems identified in the provision of statistical information for the definition and monitoring of development (maybe sector) policies?
  • Are they consistent with the National Strategy for Development of Statistics (NSDS)?
  • In light of the experiences gained through implementation of the programme/project, has the initial analysis of the beneficiaries' needs (within and outside the national statistical system) been accurate?

The analysis of the relations between beneficiaries and of the institutional context will be verified in a similar way. The risks might be re-assessed.


  • Mid-term assessment: are the means committed adequate to achieve the expected results?
  • Are the means that have been committed (by the project and by the beneficiaries) comparable to those used in past similar operations (surveys having resulted in similar data or regarding similar domains)?
  • To which extent have the stakeholders committed to the monitoring process? How strong is their committment to align the monitoring process to the monitoring processes already in place in the implementing institution?
  • Did the project enable the institution to improve in this domain?


  • Sectoral statistics: are the expected data available? Are they of good quality (or has the quality improved?) according to the quality criteria?
  • Global statistical capacity building: to what extent have the results helped to implement the NSDS?


  • Sectoral statistics: what is the appraisal of the sector managers on the project impact?
  • Global statistical capacity building: how much impact did the project have on how the NSS as a whole performs its work?


  • Sectoral statistics: are the results of the project owned by the beneficiary institution? Does the beneficiary institution have the resources required to ensure future data production on a regular basis?
  • Global statistical capacity building: are the results sustainable in terms of NSS human, technical and financial inputs (budget, software and hardware, staff considering the expected turnover)?

For more information, see also:

  • Guide Box 8.3: Elements for terms of reference of an evaluation of a statistical project
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