Page 408 - Contributed Paper Session (CPS) - Volume 4

CPS2460 Mustafa Dinc et al.
information from international agencies and country websites that were
produced by national statistical systems. The SPI framework helps countries
and development partners identify the strengths and weaknesses of national
statistical systems and areas of potential improvements. It could also provide
actionable guidance for national statistical systems in areas that may require
further and deeper assessment.

Key features of the SPI are:
• Uses only publicly accessible data
• Transparent methodology
• Easily replicable
• Provides a long-time series to track progress in performance
• Captures outcomes and supporting elements
• Reflects the SDGs.
• Facilitates at-a-glance comparisons on a global scale

SPI Methodology
Due to their complex and multi-dimensional nature socio-economic
phenomena cannot be measured by a single descriptive indicator. Instead,
generally a composite index method is utilized to measure and understand
such phenomena. In constructing a measure that is policy relevant it is helpful
to follow a series of basic steps.
The first step asks the question: what phenomenon is being measured? A
clear conception helps orient the process by which the measure is assembled
and will prove valuable in communicating its underlying meaning.
The second step asks: for what purpose or purposes is the index being
sought? Knowing how the index will be used can greatly affect subsequent
choices in its construction, and its eventual suitability. In particular, it will help
define the unit of analysis both for data gathering and reporting purposes.
The third step identifies a list of essential characteristics, or desiderata, that
the methodology should exhibit. This list of “pre-axioms” helps orient the
construction process and define what success means.
A fourth step identifies the conceptual space in which measurement is to
take place. If there are multiple conceptual dimensions, consideration must
also be given to the relative importance of each.
The fifth step selects the form of the variables to be used and the
aggregation method to be employed – how the variables are to be combined
into an overall measure.
The sixth step identifies a set of axioms that the resulting index should
satisfy to have the greatest practical utility. Axioms are not sterile
mathematical requirements, but rather contain the salient nuggets of policy
required of the index: which aspects of the data should be ignored, which
should be reflected, and helpful consistency requirements over subsets of

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