This paper develops a draft framework for evaluating support to statistical capacity building in the context of
the Paris Declaration. This initial study is based on desk research (including a literature review and analyses of support to statistical capacity building in five low-income countries), and on field work from three low-income country case studies and two donor case studies. The study looks back over 15 years of support to establish lessons from past and current practices.
Following Paris Declaration principles is not the same thing as delivering relevant, efficient, effective, sustainable, and positive support to statistical capacity building. However it can contribute and the study shows that in most cases where Paris Declaration principles have been followed, the results of support to statistics have improved. Support delivered within larger programmes of predictable, coordinated support has been the most successful.
It seems that in comparison to other sectors, support to statis- tics has tended not to follow Paris Declaration principles. One reason for this is that official statistics are usually produced and used by a system composed of several different organisa- tions, and there are often no effective strategies to coordinate this system, which makes it difficult for donors to harmonise and align their support. In addition, since statistics has until recently been relatively neglected by donors, few donors have invested in permanent country experts in statistics or results to support the statistical ‘sector’.
Larger scale country based programmes, and particularly country-held common funds, seem more likely to meet the Paris Declaration principles. Results focussed governments were more likely to have statistical systems that were sup- ported in ways which largely met Paris Declaration principles. Although experience with country-held funds is not extensive, the available evidence suggests that country funds produce strong results when linked to highly policy-relevant plans; and
where the statistical producers are held accountable by a well- functioning governance body, which is in turn accountable to a government with a strong results focus.
It is increasingly common to deliver support through globally managed initiatives. Management at a global level makes these initiatives particularly difficult to administer in ways that meet Paris Declaration principles, because they are neither owned by individual countries nor well aligned to their sta- tistical priorities, institutions or procedures. This need not be detrimental to statistical capacity building in some contexts, but does indicate that a stronger representative presence is needed at country level when making decisions or managing support. In general, it appears that global initiatives are most effective at building sustainable statistical capacity when concerned with setting standards, providing tools or when decision-making is decentralised to maximise ownership by country-level statistical users and alignment to their needs. As DFID’s experience in Tanzania shows, the presence in country of a lead donor with expertise in statistics improved donors’ coordination of support to statistical capacity building.
Context for Statistics in Development
Statistics are used not only by citizens or governments, but also by the international and donor communities, among whom demand has been particularly strong in recent years(*).
(*) Weak home demand has been widely recognised as an inhibiting factor in build- ing capacity and it could be argued that international demand is much stronger than country demand.