Page 412 - Contributed Paper Session (CPS) - Volume 4

CPS2460 Mustafa Dinc et al.
being measured; they should be publicly available. The aggregation method
should be selected with rigor in mind, including the axioms or properties that
the method satisfies. At the same time, it should aim for simplicity to maximize
general understanding and impact.
In the domain of statistical capacity, a variable is typically derived from a
simple “yes-no” question concerning a normative guideline that a country’s
NSS should meet. Each of these “yes-no” questions generate a dichotomous
variable having a 0-1 representation, where 1 means that the underlying test
or target has been successfully achieved, while 0 indicates it has not.
The indicator selection process is guided by conventions of international
agencies, expert opinions on statistical performance and the principles of
SDGs. However, given the cost and time constraints and the accuracy concerns
of assessment, trade-offs have to be made to build an actionable, cost-
effective and internationally comparable index.
One such trade-off is the equal weighting of each dimension and
individual indicator, even though some of them may be more important than
others or countries may assign higher priority to some than others. The equal
weighting selection may be, to some extent subjective, partly failing to address
the relative importance of the dimensions and indicators. This could be
checked by simulations that will show the sensitivity of SPI scores and rankings
in relation to alternative weights.
When variables are dichotomous (or can be dichotomized), a
measurement approach called a “counting method” is applicable and, indeed,
has become standard for many types of measurement exercises. This method
is used here to aggregate the scores of four dimensions into an overall SPI
score and to create the composite index. Hence:
Total SPI Score =(MSC+CS+DPO+AKI)/4
Each of the four dimensions has a scale of 1-100 and are aggregated into
a total score which also ranges from 1 to 100.

4. Conclusions
This SPI could be the first step before more resource-intensive country-
specific assessments to inform multi-year improvement plans. The SPI
framework is also flexible enough to allow for future revisions as the global
data landscape evolves. For example, it is possible to incorporate new
indicators such as whether an NSO uses cloud computing to store their data
or implements household panel surveys in the relevant dimensions without
creating major changes to the total scores. The SPI may also be relevant to the
construction of other indexes in related areas, such as tracking the global SDGs
or child development. Since the SPI will be produced every year, it will provide
time series data for monitoring the progress over time.

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