National Statistical offices (NSOs) are the sources of wide ranges of socio-economic,
demographic and agricultural data and information that are used to monitor and evaluate
development programs and formulate policies. The data generated by NSOs is used as basis
for making decisions and also used to assess the extent and causes of poverty. Various
stakeholders such as researchers, the World Bank, the International Monetary Fund, the UN,
and various NGOs prepare and release research materials and annual reports using data and
information obtained from NSOs and line ministries. For example, Deneulin and Shahani
state that one of the intentions of the annual Human Development Report (HDR) prepared by
the UNDP is “to assess the quality of life of a population and be an advocacy tool for its
improvement with a political purpose of raising awareness and generating debate on public
issues and concerns which would otherwise not be on the political agenda”1. Based on the
different approaches to poverty, different sets of data and information are produced and used
for poverty measurement. Mostly, poverty is measured using data obtained from nationally
representative household surveys which focus on income and expenditure, ownership, access
to and use of some basic services. Another approach uses data on mental satisfaction; still
others assume poverty to be multi-dimensional and argue that income alone is not enough.
They view poverty as deprivation of basic capabilities due to high rates of mortality,
illiteracy, malnourishment, unemployment, ill health, lack of education and social exclusion,
etc2. The quality of data and information (such as integrity, methodological soundness,
accuracy and reliability, serviceability and accessibility) generated by data-producingagencies
therefore needs to be preserved and improved in order to obtain meaningful results
from the measurement of poverty in any of the approaches and to satisfy the growing data
quality demands of stakeholders. Loshin states that “strategic decisions based on
untrustworthy information are likely to result in poor decisions”3. This study focuses on the
role played by national statistical offices in poverty reduction in general. It examines the
various activities, players, interactions, and ICTs used at the various stages of the statistical process in the Ethiopian Central Statistical Agency (CSA) to generate poverty-related data
and information and how the quality of this data can be preserved and improved.
The purpose of this research is therefore to identify poverty related data quality problems
with respect to the IMF’s DQAF and assess where in the statistical process specific types of
ICTs can improve data quality. For this reason interpretive case study method with the
researcher as participant observer was adopted to study how poverty related data and
information is produced. It was found out that some of the data quality problems can be
addressed using appropriate ICTs with the availability of reliable power infrastructures.