The World Bank’s Framework for Statistical
Capacity Measurement: Strengths,
Weaknesses, and Options for Improvement
Floribert Ngaruko1
Abstract
Using the results-chain approach to capacity building and the PARIS21 framework, this paper discusses the use of statistical activities and outputs by the
World Bank to measure statistical capacity. The paper focuses on the strengths
and weaknesses of the World Bank’s approach, and explores options for improving the indicator that results from it. While international comparability and
cost effectiveness are the main strengths of the approach, the overemphasis that
it places on statistical activities and outputs to the detriment of characteristics
of statistical systems and data-producing agencies represents its main weakness,
which causes the indicator to capture performance instead of actual capacity.
To improve the World Bank approach would require refining the method of
aggregation of the ratings of various aspects of statistical capacity, activities and
outputs, and more critically, to take due account of statistical capacity utilization, which is the missing link in the World Bank approach between statistical
activities/outputs and statistical capacity.
Key Words: Statistical capacity indicator, Capacity building, Capacity utilization, PARIS21, Capacity building results-chain framework
Résumé
En recourant au cadre conceptuel de PARIS21 ainsi qu’à l’approche par la
chaîne des résultats aujourd’hui utilisée dans le renforcement des capacités, cet
article discute de l’utilisation par la Banque mondiale, des activités et de la
production statistiques pour mesurer les capacités des systèmes statistiques des
pays. L’article identifie les forces et les faiblesses de cette approche, et explore
les options pour améliorer l’indicateur qui en résulte. Si la comparabilité au
plan internationale et le faible coût sont les principaux atouts de l’approche,
sa focalisation sur les activités et la production statistiques au détriment des
caractéristiques des systèmes statistiques et des agences de production des données reste sa principale faiblesse, qui fait que l’indicateur reflète la performance
Coordinator of the ACBF Technical Advisory Panel and Network on National Statistics and Statistical Systems (STATNET); The African Capacity Building Foundation
(ACBF); ZB Life Towers; Cnr. Jason Moyo Ave / Sam Nujoma St.; Harare; Zimbabwe
([email protected]); (00-263) 4 702 931/2; 790 398/9; 700 208/10/14; 799
783/87; 799 810/12.
This paper does not necessarily reflect the views of the ACBF or STATNET.
1
164 African Statistical Journal, Volume 7, November
Le2008
Journal statistique africain, numéro 7, novembre 2008
The
149
The World Bank’s Framework for Statistical Capacity Measurement
Floribert Ngaruko
the
davantage
approach
queto
lescapacity
capacitésbuilding
à proprement
and align
parler.it Pour
to theaméliorer
paradigm
l’approche,
of resultsle
based
papier management.
suggère l’affinement
Thesedeefforts
la méthode
resulted
d’agrégation
in the framework
des indicateurs
knowndes
as difthe
“capacity
férentes composantes
building results-chain
des systèmes statistiques,
approach.” The
des activités
paper refers
et de to
la this
production
framework
statistiques,
in its attempt
et surtouttolacapture
prise enthecompte
very meaning
du degréofd’utilisation
statistical capacity.
des capacités
existantes qui est le chaînon manquant dans l’approche de la Banque mondiale, entre
et capacités
statistiques.
Second,
theactivités/production
paper relies on recent
developments
in terms of the measurement of statistical capacity at the international level. The formulation of
the
MotsWB’s
clés framework
: Indicateuralso
de capacités
took place
statistiques,
at a time Renforcement
when there was
des considercapacités,
able
Utilisation
momentum
des capacités,
to improve
PARIS21,
statistics,
Approche
statistical
du renforcement
capacity, and
desstatistical
capacités
capacity
par la chaîne
measurement
des résultats.
in developing countries. In November 1999, this
resulted in the launch of the PARIS21 Consortium, a global forum and
network aimed at promoting and facilitating statistical capacity building
and
use of statistics. It also led to the establishment of the PARIS21
1. better
iNtroductioN
Task Team, which in May 2001 was tasked with devising an approach to
statistical
capacity
building measurement.
Forrating
the purposes
this paper,
The World
Bank (henceforth
WB) has been
countriesofaround
the
the
PARIS21
against
which
the WB’s
apworld
for theirframework
statistical provides
capacity benchmarks
since 2004. The
WB’s
indicator
of staproach
to statistical
measurement
can be assessed.
tistical capacity
usescapacity
information
publicly available
to assess three aspects,
namely statistical practices, data collection activities, and statistics availThe
paper’s
reliance
on the
results
chain and
the
ability.
Recently,
the WB
has capacity
indicatedbuilding
its intention
to improve
its on
framePARIS21
approachescapacity
resonates
not only with
the specific
subject
matter
work for statistical
measurement
by shifting
toward
a new
apbut
alsofocusing
with the instrumental
role that institutional
the WB played
in the development
proach
on four dimensions:
framework,
statistical
2
of
these approaches.
Indeed,and
notdata
onlydissemination.
did it spearhead
the promotion of
methodology,
data sources,
the capacity building results chain approach but, in concert with the UN,
OECD,
IMF, of
andthis
thepaper
EC, the
also co-founded
the PARIS21
ConsorThe objective
is toWB
contribute
to this improvement
effort,
notium.
Moreover,
it was
also part
PARIS21
Team, and
assumed
tably by
proposing
an analysis
of of
thethe
strengths
andTask
weaknesses
of the
WB’s
3
the
PARIS21
Task Team’s
secretariat.
existing
approach
to statistical
capacity
measurement, and by exploring
some options for its enhancement. Specifically, the paper seeks to explore
the rationale
andPARIS21
modalitiesframework
of the WB’s
statistical
activities
and
Using
both the
anduse
theofcapacity
building
results
outputsapproach,
to measure
capacity,the
to determine
problems activities
that this
chain
thisstatistical
paper explores
WB’s use the
of statistical
poses,
and totodevise
some
options capacity.
as to howItthe
WB’s indicator
couldthat
be
and
outputs
measure
statistical
identifies
the problems
improved
better
captureinsights
actual statistical
this
poses,toand
provides
into how capacity.
the WB’s indicator could be
improved so as to better reflect statistical capacity.
The paper hypothesizes that the WB’s focus on statistical activities and
outputs to measure statistical capacity, to the detriment of aspects related
to statistical systems and data-producing agencies, results in the indicator
poorly reflecting actual statistical capacity. To support this hypothesis, the
3
The membership of the PARIS21 Task Team was as follows: the IMF, Chair (Ms. L.
paper
uses a two-pronged approach. First, the paper builds on the new
Laliberté, Chairperson, Mr. T. Morrison, Mr. J. Bové and Mr. S. Khawaja), the World
understanding
of, and
approachSecretariat,
to capacity
capacityand
enhancement.
Bank, Secretariat (Mrs.
M. Harrison,
Mr. and
M. Belkindas,
Mr. G. Eele),
Indeed,
the development
of the
measuring
statistical
the
UN Statistics
Division, UNSD
(Mr.WB’s
W. de framework
Vries), the UNfor
Economic
Commission
for
Latin
America
and the when
Caribbean,
UN ECLACefforts
(Ms. B. Carlson),
and the UN
capacity
occurred
international
were underway
toEconomic
revamp
Commission of Europe, UNECE (Mr. J-E. Chapron), and AFRISTAT (Mr. Lamine
Diop). The Consultants to the PARIS21 Task Team were Mr. D. Allen, Mr. T. Holt and
2
Mr.
Fantom
J. van Tongeren.
and Watanabe (2008).
150 African Statistical Journal, Volume 7, November
Le2008
Journal statistique
statistique africain,
africain, numéro
numéro 7,
7, novembre
novembre 2008
2008
166
The
Le
Journal
165
The World Bank’s Framework for Statistical Capacity Measurement
Floribert Ngaruko
the
davantage
approach
queto
lescapacity
capacitésbuilding
à proprement
and align
parler.it Pour
to theaméliorer
paradigm
l’approche,
of resultsle
based
papier management.
suggère l’affinement
Thesedeefforts
la méthode
resulted
d’agrégation
in the framework
des indicateurs
knowndes
as difthe
“capacity
férentes composantes
building results-chain
des systèmes statistiques,
approach.” The
des activités
paper refers
et de to
la this
production
framework
statistiques,
in its attempt
et surtouttolacapture
prise enthecompte
very meaning
du degréofd’utilisation
statistical capacity.
des capacités
existantes qui est le chaînon manquant dans l’approche de la Banque mondiale, entre
et capacités
statistiques.
Second,
theactivités/production
paper relies on recent
developments
in terms of the measurement of statistical capacity at the international level. The formulation of
the
MotsWB’s
clés framework
: Indicateuralso
de capacités
took place
statistiques,
at a time Renforcement
when there was
des considercapacités,
able
Utilisation
momentum
des capacités,
to improve
PARIS21,
statistics,
Approche
statistical
du renforcement
capacity, and
desstatistical
capacités
capacity
par la chaîne
measurement
des résultats.
in developing countries. In November 1999, this
resulted in the launch of the PARIS21 Consortium, a global forum and
network aimed at promoting and facilitating statistical capacity building
and
use of statistics. It also led to the establishment of the PARIS21
1. better
iNtroductioN
Task Team, which in May 2001 was tasked with devising an approach to
statistical
capacity
building measurement.
Forrating
the purposes
this paper,
The World
Bank (henceforth
WB) has been
countriesofaround
the
the
PARIS21
against
which
the WB’s
apworld
for theirframework
statistical provides
capacity benchmarks
since 2004. The
WB’s
indicator
of staproach
to statistical
measurement
can be assessed.
tistical capacity
usescapacity
information
publicly available
to assess three aspects,
namely statistical practices, data collection activities, and statistics availThe
paper’s
reliance
on the
results
chain and
the
ability.
Recently,
the WB
has capacity
indicatedbuilding
its intention
to improve
its on
framePARIS21
approachescapacity
resonates
not only with
the specific
subject
matter
work for statistical
measurement
by shifting
toward
a new
apbut
alsofocusing
with the instrumental
role that institutional
the WB played
in the development
proach
on four dimensions:
framework,
statistical
2
of
these approaches.
Indeed,and
notdata
onlydissemination.
did it spearhead
the promotion of
methodology,
data sources,
the capacity building results chain approach but, in concert with the UN,
OECD,
IMF, of
andthis
thepaper
EC, the
also co-founded
the PARIS21
ConsorThe objective
is toWB
contribute
to this improvement
effort,
notium.
Moreover,
it was
also part
PARIS21
Team, and
assumed
tably by
proposing
an analysis
of of
thethe
strengths
andTask
weaknesses
of the
WB’s
3
the
PARIS21
Task Team’s
secretariat.
existing
approach
to statistical
capacity
measurement, and by exploring
some options for its enhancement. Specifically, the paper seeks to explore
the rationale
andPARIS21
modalitiesframework
of the WB’s
statistical
activities
and
Using
both the
anduse
theofcapacity
building
results
outputsapproach,
to measure
capacity,the
to determine
thestatistical
problems activities
that this
chain
thisstatistical
paper explores
WB’s use of
poses,
and totodevise
some
options capacity.
as to howItthe
WB’s indicator
couldthat
be
and
outputs
measure
statistical
identifies
the problems
improved
better
captureinsights
actual statistical
this
poses,toand
provides
into how capacity.
the WB’s indicator could be
improved so as to better reflect statistical capacity.
The paper hypothesizes that the WB’s focus on statistical activities and
outputs to measure statistical capacity, to the detriment of aspects related
to statistical systems and data-producing agencies, results in the indicator
poorly reflecting actual statistical capacity. To support this hypothesis, the
3
The membership of the PARIS21 Task Team was as follows: the IMF, Chair (Ms. L.
paper
uses a two-pronged approach. First, the paper builds on the new
Laliberté, Chairperson, Mr. T. Morrison, Mr. J. Bové and Mr. S. Khawaja), the World
understanding
of, and
approachSecretariat,
to capacity
capacityand
enhancement.
Bank, Secretariat (Mrs.
M. Harrison,
Mr. and
M. Belkindas,
Mr. G. Eele),
Indeed,
the development
of the
measuring
statistical
the
UN Statistics
Division, UNSD
(Mr.WB’s
W. de framework
Vries), the UNfor
Economic
Commission
for
Latin
America
and the when
Caribbean,
UN ECLACefforts
(Ms. B. Carlson),
and the UN
capacity
occurred
international
were underway
toEconomic
revamp
Commission of Europe, UNECE (Mr. J-E. Chapron), and AFRISTAT (Mr. Lamine
Diop). The Consultants to the PARIS21 Task Team were Mr. D. Allen, Mr. T. Holt and
2
Mr.
Fantom
J. van Tongeren.
and Watanabe (2008).
151
166
The African Statistical Journal, Volume 7, November
Le2008
Journal statistique africain, numéro 7, novembre 2008
165
The World Bank’s Framework for Statistical Capacity Measurement
Floribert Ngaruko
The
the approach
rest of thetopaper
capacity
proceeds
building
as follows.
and align
Following
it to thethis
paradigm
introductory
of resultssection,
basedSection
management.
2 focuses
These
on the
efforts
characteristics
resulted in the
of the
framework
WB’s indicator
known of
as stathe
tistical
“capacity
capacity,
buildinganalyzes
results-chain
some approach.”
of its advantages
The paper
and refers
shortcomings,
to this frameand
presents
work in its
some
attempt
of thetoquestions
capture the
thatvery
it leaves
meaning
open.
ofSection
statistical
3 identifies
capacity. the
aspects of the statistical capacity results chain that this indicator captures,
and
discusses
an improvement
in developments
data aggregation
as a requirement
for
Second,
the paper
relies on recent
in terms
of the measurethe
indicatorcapacity
to betteratreflect
statistical capacity.
Section
4 focuses
mentWB’s
of statistical
the international
level. The
formulation
of
on
utilizationalso
as the
missing
link
in thewhen
WB’sthere
approach
between
the capacity
WB’s framework
took
place at
a time
was considerstatistical
capacitytoand
statistical
activities,
and as acapacity,
central factor
that has
able momentum
improve
statistics,
statistical
and statistical
to
be taken
into accountinfordeveloping
statistical activities
to consistently
capacity
measurement
countries.and
In outputs
November
1999, this
reflect
capacity.
5 concludes
the paper.
resultedstatistical
in the launch
of Section
the PARIS21
Consortium,
a global forum and
network aimed at promoting and facilitating statistical capacity building
and better use of statistics. It also led to the establishment of the PARIS21
2.
Task Team,
thewhich
frAmeWork
in May 2001 was tasked with devising an approach to
statistical capacity building measurement. For the purposes of this paper,
the PARIS21
framework
benchmarks
which
WB’s
apThe
WB’s framework
forprovides
measuring
statisticalagainst
capacity
usesthe
three
broad
proach to statistical
capacity
measurement
can
assessed.capacity: (i) stacomponents
to derive
a composite
indicator
ofbe
statistical
tistical practice, (ii) data collection, and (iii) statistics availability (see Annex
Statistical
practices
capturedbuilding
by 10 indicators
that and
referon
to the
The 1).
paper’s
reliance
on thearecapacity
results chain
base
year ofapproaches
national accounts;
(or with
not) of
balance
of payments
PARIS21
resonatesthe
notuse
only
thethe
specific
subject
matter
manual;
the status
of externalrole
debtthat
reporting;
baseinyear
of the Conbut also with
the instrumental
the WB the
played
the development
sumer
Index; the
index not
of industrial
availability of
of thesePrice
approaches.
Indeed,
only did itproduction;
spearhead the promotion
IMF’s
import/export
the government
finance
accounting
the capacity
building prices;
results chain
approach but,
in concert
with concept;
the UN,
the
frequency
of the
to UNESCO;
the frequency
OECD,
IMF, and
the enrollment
EC, the WBreporting
also co-founded
the PARIS21
Consorof
vaccine
reporting
to also
WHO;
thePARIS21
subscription
the IMF’s
Special
tium.
Moreover,
it was
partand
of the
Taskto
Team,
and assumed
3
Data
Dissemination
Standard.
As regards
data collection, five indicators
the PARIS21
Task Team’s
secretariat.
are used. These include: the periodicity of population censuses; the periodicity
agricultural
censuses;
the periodicity
poverty-related
Using of
both
the PARIS21
framework
and theofcapacity
building surveys
results
(IES,
etc.);this
thepaper
periodicity
of health-related
(DHS,activities
MICS,
chain LSMS,
approach,
explores
the WB’s use surveys
of statistical
priority
survey,
andstatistical
the completeness
registration
systems.that
As
and outputs
to etc.);
measure
capacity.of
It vital
identifies
the problems
for
cluster
statisticalinsights
indicator
availability,
this comprises
indicathisthe
poses,
andofprovides
into
how the WB’s
indicator10could
be
tors:
income
poverty,
child
malnutrition,
child mortality, immunization,
improved
so as
to better
reflect
statistical capacity.
HIV/AIDS, maternal health, gender equality, primary school completion,
access to water, and per capita GDP growth.
Within
each of the three clusters cited above, the various items are scored
3
The membership of the PARIS21 Task Team was as follows: the IMF, Chair (Ms. L.
on
the
same
scale and given equal weight. To obtain the overall score of
Laliberté, Chairperson, Mr. T. Morrison, Mr. J. Bové and Mr. S. Khawaja), the World
statistical
capacity,
three components’
scores
are givenandequal
weight
Bank, Secretariat (Mrs. the
M. Harrison,
Secretariat, Mr.
M. Belkindas,
Mr. G.
Eele),
(see
Annex
1).Division,
Such overall
then used
comparisons
among
the UN
Statistics
UNSDscores
(Mr. W.are
de Vries),
the UNfor
Economic
Commission
for
Latin America
the Caribbean,
UN ECLAC (Ms. B. Carlson), and the UN Economic
countries
andandover
time.
Commission of Europe, UNECE (Mr. J-E. Chapron), and AFRISTAT (Mr. Lamine
Diop). The Consultants to the PARIS21 Task Team were Mr. D. Allen, Mr. T. Holt and
Mr. J. van Tongeren.
152 African Statistical Journal, Volume 7, November
Le2008
Journal statistique
statistique africain,
africain, numéro
numéro 7,
7, novembre
novembre 2008
2008
The
166
Le
Journal
167
The World Bank’s Framework for Statistical Capacity Measurement
Floribert Ngaruko
Over
davantage
the past
que years,
les capacités
the indicator
à proprement
has revealed
parler. substantial
Pour améliorer
contrasts
l’approche,
among
le
the
papier
highest
suggère
and
l’affinement
lowest performers.
de la méthode
For example,
d’agrégation
Egypt
des achieved
indicateurs
a score
des difof
89
férentes
on acomposantes
zero-to-100des
scale
systèmes
in 2007,
statistiques,
against des
a score
activités
of only
et de17lafor
production
Liberia.
The
statistiques,
WB’s indicator
et surtoutalso
la prise
shows
en important
compte du changes
degré d’utilisation
over time.desFor
capacités
example,
existantes
the scores
qui estforle Nigeria
chaînonand
manquant
Rwandadans
rosel’approche
from 51 de
andla58
Banque
in 2006
monto
62
diale,
andentre
71 in
activités/production
2007, respectively,
et suggesting
capacités statistiques.
that these countries’ statistical
capacities had improved by 22% over a single year. Over the same period,
the
scores
Libya, Guinea-Bissau,
and the Central
African Republic
fell
Mots
clés for
: Indicateur
de capacités statistiques,
Renforcement
des capacités,
from
41, 37,
42 in 2006
down to
31, 29,du
andrenforcement
33 in 2007,des
pointing
to
Utilisation
desand
capacités,
PARIS21,
Approche
capacités
apar
decline
in statistical
capacity by 24%, 22%, and 21% in these countries,
la chaîne
des résultats.
respectively.
A
look at these scores for the three dimensions of statistical capacity
1. closeriNtroductioN
shows that variations over time are mostly due to changes in data collection
the Central
African Republic,
Bissau,countries
Libya, and
Nigeria.
The in
World
Bank (henceforth
WB) hasGuinea
been rating
around
the
The
suggest
that incapacity
these countries,
fromThe
2006
to 2007
the magniworldfigures
for their
statistical
since 2004.
WB’s
indicator
of statude
ofcapacity
change in
data
collection ranged
and 50%.
tistical
uses
information
publiclybetween
available40%
to assess
three aspects,
namely statistical practices, data collection activities, and statistics availAs
theseRecently,
figures illustrate,
the indicated
WB’s indicator
can result
in huge variations
ability.
the WB has
its intention
to improve
its frameover
periods. Given
themeasurement
time needed to
statistical
the
workshort
for statistical
capacity
bybuild
shifting
towardsystems,
a new apquestion
arises whether
indicator adequately
captures
statistical
capacproach focusing
on fourthedimensions:
institutional
framework,
statistical
ity.
Indeed, the
criticism
that the 2WB indicator obliges
methodology,
data
sources,has
andbeen
datamade
dissemination.
countries to continue to carry out statistical activities and produce outputs
at
regular
intervals
orderis to contribute
maintain high
scores,
as to do effort,
otherwise
The
objective
of thisinpaper
to this
improvement
no4
would
in significant
declines
their scores
statistical of
capacity.
tably byresult
proposing
an analysis
of theinstrengths
andofweaknesses
the WB’s
existing approach to statistical capacity measurement, and by exploring
somerelevance
options for
the paper
to explore
The
of its
theenhancement.
indicator has Specifically,
more specifically
beenseeks
questioned
by
the rationale
and
WB’sactual
use of
statistical
activities
and
national
studies
formodalities
its inabilityoftothe
reflect
statistical
capacity
changes
outputs
to For
measure
statistical
capacity,
to determine
thebeen
problems
that this
over
time.
example,
in Niger
since 2004,
there has
the enactment
poses,
and
somethe
options
as to how
WB’s indicator
could
be
of
a new
lawtoondevise
statistics;
establishment
of the
a National
Council of
Statisimproved
to better capture
actual
statistical
capacity.
tics;
the transformation
of the
former
Directorate
of Statistics and National
Accounts (DSCN) into the new and more dynamic National Institute of
The paperand
hypothesizes
that the of
WB’s
focus units
on statistical
activities into
and
Statistics;
the transformation
statistical
in core ministries
outputs to measure
statistical
capacity,
to the
detriment
of aspects
related
fully-fledged
Directorates.
Other
changes
include
improved
coordination
to statistical
systems andagencies;
data-producing
agencies,ofresults
in the indicator
among
data-producing
the formulation
the National
Statistipoorly
reflecting actual
statistical
capacity.
To support
this hypothesis,
the
cal
Development
Strategy
based on
the PARIS21
principles;
the provision
paper
uses a two-pronged
approach.
First, the paper
builds onstaff;
the new
of
a substantially
increased budget;
better-trained
and motivated
and
5
understanding
and approach
to capacity and capacity enhancement.
improved
work of,
conditions.
Indeed, the development of the WB’s framework for measuring statistical
capacity occurred when international efforts were underway to revamp
4
52
ACBF (2007).
Fantometand
Gafishi
al. Watanabe
(2008). (2008).
153
The African Statistical Journal, Volume 7, November
165
168
Le2008
Journal statistique africain, numéro 7, novembre 2008
The World Bank’s Framework for Statistical Capacity Measurement
Floribert Ngaruko
In
theview
approach
of all the
to capacity
above changes,
buildingitand
is apparent
align it that
to the
theparadigm
capacity of
of resultsNiger’s
statistical
based management.
system hasThese
been significantly
efforts resulted
strengthened.
in the framework
Gafishiknown
et al. (2008)
as the
argue
“capacity
thatbuilding
these changes
results-chain
have resulted
approach.”
in The
improved
paper data
referscollection
to this frameand
enhanced
work in itsindicator
attempt to
availability
capture the
to very
somemeaning
extent, as
ofwell
statistical
as in the
capacity.
National
Institute of Statistics enjoying a reputation as an emerging center of excellence.
authors
forcefully
stress theincontrast
the WB
Second,However,
the paperthe
relies
on recent
developments
terms ofwith
the measureindicator
scores, which
haveatbarely
changed overlevel.
the period
despite these
ment of statistical
capacity
the international
The formulation
of
improvements.
Accordingly,
theplace
authors
forwhen
further
investigation
into
the WB’s framework
also took
at acall
time
there
was consider6
the
for thistoapparent
ablereasons
momentum
improveparadox.
statistics,
statistical capacity, and statistical
capacity measurement in developing countries. In November 1999, this
resulted
in the launchthe
ofstrengths
the PARIS21
a global
and
To
fully comprehend
of theConsortium,
WB’s indicator
and theforum
problems
network
aimed
at promoting
and
facilitating
statisticalframework
capacity building
that
it poses,
it may
be useful to
look
at its underlying
and the
and better
of statistics. ItThe
alsoWB
led to
the establishment
of the PARIS21
context
of use
its development.
began
to use the approach
at a time
Task Team,
which ininitiative,
May 2001
with devising
to
when
the PARIS21
thewas
firsttasked
systematic
attempt an
at approach
the internastatistical
building
measurement.
For the purposes
thisalready
paper,
tional
levelcapacity
to develop
statistical
capacity building
indicators,ofhad
the PARIS21
benchmarks
against
which the
WB’s
approduced
its framework
framework provides
for measuring
statistical
capacity.
This
frameproachprovides
to statistical
capacity measurement
be assessed.
work
for comprehensive
reviews can
of national
statistical systems,
requiring detailed country visits. As has been pointed out by various comThe paper’sthe
reliance
onwith
the the
capacity
building
results
chainit is
and
on the
mentators,
problem
PARIS21
approach
is that
expensive
PARIS21
approaches resonates
only with
specific burden
subject on
matter
and
time-consuming.
Moreover,not
it imposes
anthe
additional
the
but also with the
instrumental
role that systems
the WB being
playedevaluated,
in the development
often-limited
capacity
of the statistical
especially
7
of low-income
these approaches.
Indeed,
did
spearhead
the promotion
of
in
countries.
It isnot
alsoonly
likely
toitresult
in idiosyncratic
descripthe capacity
building
results chain
approach difficult.
but, in concert with the UN,
tions
that render
international
comparisons
OECD, IMF, and the EC, the WB also co-founded the PARIS21 Consortium.WB
Moreover,
it was
also part more
of thelimited
PARIS21
Task Team,
and assumed
The
opted for
a different,
approach
to mitigate
these
the PARIS21 Task
secretariat.
shortcomings.
ThisTeam’s
approach
uses a 3smaller set of indicators (Annex 1),
for which the data are publicly available, and which allow for the capture
of
differences
in statistical
among
and over
time. In
this
Using
both the
PARIS21capacity
framework
andcountries
the capacity
building
results
context,
the WB’sthis
success
it hasuse
cost-effectively
ratchain approach,
paperis undeniable,
explores the asWB’s
of statistical been
activities
ing
forstatistical
144 countries
around
the world
2004.that
and statistical
outputs tocapacity
measure
capacity.
It identifies
thesince
problems
this poses, and provides insights into how the WB’s indicator could be
The
development
the WB’s
statistical capacity also occurred
improved
so as to of
better
reflectindicator
statisticalofcapacity.
at a time when the popularization of the results-based management approach lent support to the emergence of another new framework, known as
the “capacity building results chain framework” (Figure 1). This promotes
analysis
of cause and effect; clarifying the relationships among long-term
3
The membership of the PARIS21 Task Team was as follows: the IMF, Chair (Ms. L.
goals,
mid-term
outcomes, and immediate objectives, and the resources,
Laliberté, Chairperson, Mr. T. Morrison, Mr. J. Bové and Mr. S. Khawaja), the World
strategy,
and
actions
required
toSecretariat,
achieve them
a results-oriented
Bank, Secretariat (Mrs. M.
Harrison,
Mr. M.inBelkindas,
and Mr. G. manEele),
ner.
The
capacity
building
framework
also aims
to identify
the UN
Statistics
Division,
UNSDresults
(Mr. W.chain
de Vries),
the UN Economic
Commission
for
Latin America and the Caribbean, UN ECLAC (Ms. B. Carlson), and the UN Economic
Commission of Europe, UNECE (Mr. J-E. Chapron), and AFRISTAT (Mr. Lamine
6
Diop).
Gafishi
TheetConsultants
al. (2008: 13).
to the PARIS21 Task Team were Mr. D. Allen, Mr. T. Holt and
7
Mr.ACBF
J. van(2007).
Tongeren.
154African Statistical Journal, Volume 7, November
Le2008
Journal statistique
statistique africain,
africain, numéro
numéro 7,
7, novembre
novembre 2008
2008
The
166
Le
Journal
169
The World Bank’s Framework for Statistical Capacity Measurement
Floribert Ngaruko
davantage
Figure 1:queCapacity
les capacités
Building
à proprement
in theparler.key
Pourassumptions
améliorer l’approche,
and perle
papier
suggère l’affinement
de la méthode d’agrégation
formance
des indicators
indicateursfor
deseach
difResults-chain
Framework
férentes composantes des systèmes statistiques, desstage
activités
of the
et de
process;
la production
and to
r
impActS
statistiques,
et surtout la prise
en compte du degré
visualize
d’utilisation
the process
des capacités
in cone
existantes
qui est le chaînon manquant dans l’approche
text, by considering
de la Banquethemonexdiale, Sentre activités/production et capacités statistiques.
ternal factors that might influence outcomes.
u
outcomeS
Mots lclés : Indicateur de capacités statistiques, Renforcement des capacités,
Utilisation
des capacités, PARIS21, Approche du
In renforcement
such a framework,
des capacités
statist
par la chaîne des résultats.
tical capacity and statistical
S
outputS
capacity enhancement are
viewed as part of a chain going from statistical resources
1.
iNtroductioN
to activities, to outputs, to
ActiVitieS
(as statistical
inThe World Bank (henceforth WB) has been outcomes
rating countries
around the
come
to influence
world for their statistical capacity since 2004.dicators
The WB’s
indicator
of stapolicymaking
tistical capacity uses information publicly available
to assess and
threedevelopaspects,
ment
monitoring
and
evalnamely
statistical
practices,
data
collection
activities,
and
statistics
availr
iNputS
uation,tofor
example)
and
ability.e Recently, the
WB has indicated its intention
improve
its frameHUMAN RESOURCES;
finally
to
impact
(in
terms
work Sfor statistical capacity
measurement
by
shifting
toward
a
new
apFINANCING;
of
poverty
reduction
and
proach
focusing
on
four
dimensions:
institutional
framework,
statistical
o
EQUIPMENT AND
welfare2 improvement, for
methodology,
data sources,
and data dissemination.
u
FACILITIES;
instance).
r
SYSTEMS AND PRACTICES;
c
AND
The objective
of thisPROCESSES
paper is to
contribute to this improvement effort, noPARIS21 of the
initiative
tably eby proposing anPROCEDURES;
analysis of the strengthsThe
and weaknesses
WB’s
S approach to statistical
ETC.
followed this
Its
existing
capacity measurement,
and approach.
by exploring
stated
objective
to desome options for its enhancement. Specifically,
the paper
seekswas
to explore
demand-driven
the rationale and modalities of the WB’s usevelop
of statistical
activitiesstatisand
tical
capacity
indicators
as tools
to betoapplied
to specific
goals. The
apoutputs
to measure
statistical
capacity,
determine
the problems
that this
proach
aimed
to measure
the statistical
capacity
to meet
those could
goals, be
as
poses, and
to devise
some options
as to how
the WB’s
indicator
8
these
would
geared
toward
statistical
results
to meet users’ needs.
improved
to be
better
capture
actual
statistical
capacity.
{
The paper
hypothesizes
that the results-chain
WB’s focus on
statistical
and
Hence,
in the
light of the capacity
approach
and activities
the PARIS21
outputs to measure
statistical
to the detriment
related
framework,
and in view
of thecapacity,
aforementioned
variationsofinaspects
the scores
of
to statistical
systemsthe
andWB’s
data-producing
agencies,
in theThese
indicator
statistical
capacity,
approach poses
someresults
questions.
inpoorlythe
reflecting
actual statistical capacity. To support this hypothesis, the
clude
following:
paper uses a two-pronged approach. First, the paper builds on the new
understanding
of, and approach to capacity and capacity enhancement.
•
Canactualstatisticalcapacitybesovolatile,asillustratedbythecases
Indeed,
the development
of the Guinea-Bissau,
WB’s frameworkand
for the
measuring
of Nigeria,
Rwanda, Libya,
Centralstatistical
African
capacity
occurred when international efforts were underway to revamp
Republic?
82
PARIS21
Fantom and
Task
Watanabe
Team (2002a).
(2008).
155
170
The African Statistical Journal, Volume 7, November
Le2008
Journal statistique africain, numéro 7, novembre 2008
165
The World Bank’s Framework for Statistical Capacity Measurement
Floribert Ngaruko
•
theDoes
approach
the to
WB’s
capacity
statistical
building
capacity
and align
indicator
it to thecapture
paradigm
theofrelevant
resultsbased
dimensions
management.
of statistical
These efforts
capacity?
resulted in the framework known as the
•
“capacity
What–ifany–correctionsarerequiredfortheWB’sindicatortoreflect
building results-chain approach.” The paper refers to this framework
statistical
in its attempt
capacity
tomore
capture
consistently?
the very meaning of statistical capacity.
The
Second,
nextthe
sections
paper relies
attempt
on to
recent
address
developments
these issues.
in terms
However,
of the
first
measureit may
be
ment
useful
of statistical
to definecapacity
statisticalat capacity,
the international
and to look
level.
at The
the implications
formulation of
this
the WB’s
definition
framework
for the also
WB’stook
approach.
place at
This
a time
is thewhen
objective
thereofwas
theconsidernext section.
able momentum to improve statistics, statistical capacity, and statistical
capacity measurement in developing countries. In November 1999, this
resulted in the launch of the PARIS21 Consortium, a global forum and
networkcApAcity
aimed at promoting
facilitating statistical capacity building
3.
VerSuS and
performANce:
and better
use ofdoeS
statistics.
It also
lediNdicAtor
to the establishment
of the PARIS21
WhAt
the
WB’S
meASure?
Task Team, which in May 2001 was tasked with devising an approach to
statistical
capacity
building
For given
the purposes
this paper,
The
concept
of capacity
hasmeasurement.
frequently been
differentofdefinitions,
thedisparate
PARIS21motivations
framework provides
benchmarks
which the WB’s
as
and objectives
have against
led development
actorsapto
proach to
capacity aspects
measurement
can beFor
assessed.
choose
to statistical
address different
of capacity.
the purpose of this
paper, capacity is simply and generally viewed as the resources of a society
Theachieve
paper’ssocietal
reliance
on At
thethe
capacity
results or
chain
andcapacity
on the
to
goals.
level ofbuilding
an institution
agency,
PARIS21 approaches
not only with
the specific
subject matter
represents
the resourcesresonates
of that institution
to deliver
its mandate.
but also with the instrumental role that the WB played in the development
of these
approaches.
notsystems,
only didthe
it spearhead
promotionthat
of
In
the specific
case ofIndeed,
statistical
experiencethe
of countries
the capacity
building
resultsstatistical
chain approach
in concert
withstatistical
the UN,
have
successfully
enhanced
capacitybut,
shows
clearly that
9
OECD, IMF,
andrequires
the EC, focusing
the WB also
the PARIS21
capacity
building
on aco-founded
wide spectrum
of factors.ConsorThese
tium. Moreover,
it was also
part
of the PARIS21
Team, and
include
human resources
and
infrastructure
(suchTask
as buildings
andassumed
power,
3
the PARIS21
Task
among
others),
andTeam’s
other secretariat.
material resources.
Resources also include dataproducing agency staff and human resources management practices, such
as
hiring
andthefiring,
promotion,
rotation,
and building
career developUsing
both
PARIS21
framework
and training,
the capacity
results
ment.
chain 10approach, this paper explores the WB’s use of statistical activities
and outputs to measure statistical capacity. It identifies the problems that
this poses,also
andinclude
providesfinancing
insights and
intoitshow
the WB’s indicator
be
Resources
characteristics
– such ascould
its level,
improvedand
so as
to better
reflect largely
statistical
capacity.the flexibility and indesources,
stability
– which
determine
pendence of the statistical system, as well as related processes and procedures that determine the efficiency of the use of funds. Resources should
also include computing facilities, including the availability, maintenance,
and
updating of information technology infrastructure such as servers,
3
The membership of the PARIS21 Task Team was as follows: the IMF, Chair (Ms. L.
communication
network, and computers. Also falling under the rubric
Laliberté, Chairperson, Mr. T. Morrison, Mr. J. Bové and Mr. S. Khawaja), the World
“resources”
are
transportation
communication
systems
Bank, Secretariat (Mrs. M. Harrison,and
Secretariat,
Mr. M. Belkindas,
and equipment,
Mr. G. Eele),
the UN Statistics Division, UNSD (Mr. W. de Vries), the UN Economic Commission for
Latin America and the Caribbean, UN ECLAC (Ms. B. Carlson), and the UN Economic
Commission of Europe, UNECE (Mr. J-E. Chapron), and AFRISTAT (Mr. Lamine
9
Diop).
For example,
The Consultants
see Gafishi
to the
et al.
PARIS21
(2008) and
TaskKiregyera
Team were
(2006).
Mr. D. Allen, Mr. T. Holt and
10
Mr.PARIS21
J. van Tongeren.
Task Team (2002b).
156 African Statistical Journal, Volume 7, November
Le2008
Journal statistique
statistique africain,
africain, numéro
numéro 7,
7, novembre
novembre 2008
2008
The
166
Le
Journal
171
The World Bank’s Framework for Statistical Capacity Measurement
Floribert Ngaruko
inclusive
davantageofque
operational
les capacitéssupport,
à proprement
printing
parler.
equipment,
Pour améliorer
office supplies
l’approche,
and
le
11
sundries,
papier suggère
and l’affinement
other aspectsdeoflathe
méthode
office d’agrégation
environment.
des
indicateurs des différentes composantes des systèmes statistiques, des activités et de la production
statistiques,
surtoutstatistical
la prise en
compte and
du degré
d’utilisationframework
des capacités
Last
but notet least,
practices
the regulatory
of
existantes are
quikey
est resources
le chaînonofmanquant
dans
l’approche
de la processes
Banque monstatistics
a statistical
system.
Statistical
and
diale, entre activités/production
capacités
statistiques.
procedures
are resources as well,etto
the extent
that they determine access to
information, preserve confidentiality of individual data, ensure adequate
Mots clés : Indicateur
capacités statistiques,
Renforcement
des capacités,
coordination,
planning,demonitoring
and evaluation
of statistical
operaUtilisation
des capacités,
PARIS21, Approche
du activities,
renforcement
capacités
tions,
guarantee
the independence
of statistical
anddesensure
the
par la chaîne
des résultats.
accuracy,
reliability,
and accessibility of statistical data and metadata such
as information on underlying concepts, definitions, classifications, methodology, data sources, accuracy, etc.
1.
iNtroductioN
All this serves to confirm that the dynamics of statistical capacity – that is,
the
in the (henceforth
characteristics
of statistical
– are multifaceted.
Thechanges
World Bank
WB)
has been resources
rating countries
around the
Statistical
capacity
enhancement
increasing
the number
of
world for their
statistical
capacitymay
sinceconsist
2004.inThe
WB’s indicator
of stastaff
and
their skills
and/or altering
human
resources
management
practistical
capacity
uses information
publicly
available
to assess
three aspects,
tices
so that
a corepractices,
contingent
of collection
highly trained
staff can
retainedavailand
namely
statistical
data
activities,
andbestatistics
maintained
through
training.
changes
that
ability. Recently,
the regular
WB hasrecruitment
indicated itsand
intention
toOther
improve
its framemay
statisticalmeasurement
capacity building
include:toward a new apworkbeforconstrued
statisticalascapacity
by shifting
proach focusing on four dimensions: institutional framework, statistical
2
methodology,
data in
sources,
and data regulatory
dissemination.
•
improvements
the statistical
framework,
systems and
practices, and processes and procedures;
•
Thetheprovisionandupgradingofinfrastructuresuchasbuildings,inforobjective of this paper is to contribute to this improvement effort, nomation
technology
resources;
tably
by proposing
an analysis
of the strengths and weaknesses of the WB’s
•
improvementsinothermaterialresourcessuchas
existing
approach to statistical capacity measurement,transportationand
and by exploring
communication
equipment
and other
the to
office
ensome
options for itssystems
enhancement.
Specifically,
theaspects
paper of
seeks
explore
andmodalities of the WB’s use of statistical activities and
thevironment;
rationale and
•
theimprovementoffinancinganditscharacteristics.
outputs
to measure statistical capacity, to determine the problems that this
poses, and to devise some options as to how the WB’s indicator could be
In
light oftothe
capacity
building
results chain
framework discussed earimproved
better
capture
actual statistical
capacity.
lier, it appears that the WB’s indicator mostly captures statistical activities
and
that are outcomes
of statistical
resources
rather that
statistical
The outputs
paper hypothesizes
that the
WB’s focus
on statistical
activities
and
resources
se. Forstatistical
instance,capacity,
the 10 to
items
determine
the score
of
outputs toper
measure
the that
detriment
of aspects
related
statistical
indicator
clearly capture
outputs.
to statistical
systemsavailability
and data-producing
agencies,
resultsAs
in for
the statistical
indicator
activities,
they areactual
scattered
in thecapacity.
statistical
data collection
poorly reflecting
statistical
To practice
support and
this hypothesis,
the
clusters.
They
include population
censuses,
agricultural
censuses,
poverty
paper uses
a two-pronged
approach.
First, the
paper builds
on the
new
surveys,
and health
surveys.
Theytoalso
includeand
UNESCO
and
understanding
of, and
approach
capacity
capacity reporting,
enhancement.
setting
newdevelopment
base for national
the consumer
price index,
import
Indeed,athe
of theaccounts,
WB’s framework
for measuring
statistical
and
export
price indexes,
and industrialefforts
production
capacity
occurred
when international
were indexes.
underway to revamp
11
2
PARIS21
Fantom and
Task
Watanabe
Team (2002b).
(2008).
157
172
The African Statistical Journal, Volume 7, November
Le2008
Journal statistique africain, numéro 7, novembre 2008
165
The World Bank’s Framework for Statistical Capacity Measurement
Floribert Ngaruko
In
thefact,
approach
of thetototal
capacity
of 25building
items that
andthe
align
WB’s
it toindicator
the paradigm
encompasses,
of resultsas
many
based management.
as 19 items (accounting
These efforts
forresulted
nearly 77%
in theofframework
the overallknown
score) as
relate
the
to
“capacity
statistical
building
activities
results-chain
and outputs.
approach.”
Only sixThe
items
paper
(accounting
refers to this
forframeabout
23%
work of
in the
its attempt
overall score)
to capture
relatethe
to statistical
very meaning
capacity
of statistical
aspects. These
capacity.
are indicators of whether (or not) the UN considers the vital registration system
coverage
as complete;
thedevelopments
country has subscribed
Special
Second, the
paper relieswhether
on recent
in terms oftothethemeasureData
Standard;
national
and WHO/UNICEF
estimates of
ment Dissemination
of statistical capacity
at the
international
level. The formulation
the WB’s
national
immunization
coverage
area consistent;
finance
framework
also took
place at
time when government
there was consideraccounts
are consolidated;
thestatistics,
data used
for external
debt and
reporting
are
able momentum
to improve
statistical
capacity,
statistical
actual
or measurement
preliminary; and
the latest edition
of the
Balance of 1999,
Payments
capacity
in developing
countries.
In November
this
Manual
uselaunch
(see Annex
This demonstrates
thatathe
WB’sforum
indicator
resulted isininthe
of the1).PARIS21
Consortium,
global
and
of
statistical
capacity
is mostly and
driven
by statistical
activities
and outputs.
network
aimed
at promoting
facilitating
statistical
capacity
building
and better use of statistics. It also led to the establishment of the PARIS21
The
Taskfact
Team,
thatwhich
the WB’s
in May
indicator
2001iswas
largely
tasked
driven
withbydevising
statistical
anactivities
approachand
to
outputs
statisticaland
capacity
only marginally
building measurement.
by statistical For
resources
the purposes
means that
of this
it mostly
paper,
captures
the PARIS21
statistical
framework
performance
providesrather
benchmarks
than statistical
against which
capacity.
theSuch
WB’sperapformance
proach to statistical
is specifically
capacity
captured
measurement
quantitatively,
can be particularly
assessed. in terms of
frequency. As Annex 1 illustrates, the higher the frequency of statistical
activities
andreliance
outputs,onthethe
higher
the score.
As regards
fewand
items
The paper’s
capacity
building
results the
chain
on that
the
focus
on actual
capacity,
they mostly
reflect
the statistical
PARIS21
approaches
resonates
not only
withthe
theability
specificofsubject
matter
system
produce
quality statistical
outputs
andplayed
are at the
coredevelopment
of the Data
but alsotowith
the instrumental
role that
the WB
in the
Quality
has been the
developed
by the
of these Assessment
approaches. Framework
Indeed, not(DQAF)
only didthat
it spearhead
promotion
of
IMF.
the capacity building results chain approach but, in concert with the UN,
OECD, IMF, and the EC, the WB also co-founded the PARIS21 ConsorThe
tium.WB
Moreover,
indicator’s
it was
focus
also on
partperformance
of the PARIS21
rather
Task
than
Team,
capacity
and assumed
poses a
conceptual
the PARIS21
problem.
Task Team’s
While
secretariat.
capacity 3and performance are related – in the
sense that the latter is an outcome of the former – yet they are different, and
performance
indicators
cannot
be substituted
capacity
enhancement
Using both the
PARIS21
framework
and thefor
capacity
building
results
indicators.
As Mizrahi
argues,
the failure
to distinguish
betweenactivities
the two
chain approach,
this paper
explores
the WB’s
use of statistical
can
to inappropriate
policy. According
the author,
performand lead
outputs
to measure statistical
capacity. to
It identifies
theunlike
problems
that
ance
indicators,
indicatorsinsights
of capacity
enhancement
provide
this poses,
and provides
into and
howcapacity
the WB’s
indicator could
be
information
sustainability
by revealing
information on the extent of
improved so about
as to better
reflect statistical
capacity.
institutionalization or routinization of improvements to a system.12
This principle holds true not only for those cases where performance is
reflected
in quantitative terms; it is valid also in those cases where perform3
The membership of the PARIS21 Task Team was as follows: the IMF, Chair (Ms. L.
ance
is
captured
in qualitative terms. In this context, statistical capacity
Laliberté, Chairperson, Mr. T. Morrison, Mr. J. Bové and Mr. S. Khawaja), the World
measurement
has
approached
in a Mr.
different
way toandmere
statistiBank, Secretariat (Mrs.toM.beHarrison,
Secretariat,
M. Belkindas,
Mr. G.
Eele),
cal
quality
measurement.
As the
Team
forcefully
argued,fora
the UN
Statistics
Division, UNSD
(Mr.PARIS21
W. de Vries),Task
the UN
Economic
Commission
Latin America
and theentirely
Caribbean,
UN ECLAC
(Ms. B. Carlson),
andexternal
the UN Economic
statistical
output
financed
and executed
through
sources
Commission of Europe, UNECE (Mr. J-E. Chapron), and AFRISTAT (Mr. Lamine
Diop). The Consultants to the PARIS21 Task Team were Mr. D. Allen, Mr. T. Holt and
12
Mr.Mizrahi
J. van Tongeren.
(2003: 5).
158 African Statistical Journal, Volume 7, November
Le2008
Journal statistique
statistique africain,
africain, numéro
numéro 7,
7, novembre
novembre 2008
2008
The
166
Le
Journal
173
The World Bank’s Framework for Statistical Capacity Measurement
Floribert Ngaruko
may
davantage
be ofque
high
les quality,
capacitésyet
à proprement
be a poor parler.
measure
Pour
of améliorer
statisticall’approche,
capacity in
le
terms
papier of
suggère
domestic
l’affinement
expertise
de and
la méthode
sustainability.
d’agrégation
Accordingly,
des indicateurs
the PARIS21
des difTask
férentes
Team
composantes
emphasized
des systèmes
the needstatistiques,
for a sound
desstatistical
activités et
capacity
de la production
measurement
statistiques,
framework
et surtout
to take
la prise
account
en compte
of indicators
du degré
applicable
d’utilisation
to agencies
des capacités
(e.g.
central
existantesstatistical
qui est leagencies,
chaînon the
manquant
statistical
dans
units
l’approche
of central
de labanks
Banque
andmonline
13
ministries)
diale, entre that
activités/production
produce statistical
et capacités
outputs.statistiques.
Mots
clésways,
: Indicateur
de capacités
Renforcement
des capacités,
In
some
the weakness
of thestatistiques,
WB’s indicator
of statistical
capacity
Utilisation
destocapacités,
PARIS21,
Approchethe
du various
renforcement
capacités
is
partly due
its method
of aggregating
items des
it considers
parbe
la relevant
chaîne desdimensions
résultats. of statistical capacity. Indeed, minimizing the
to
relative weights of statistical activities and outputs would improve the indicator. The most straightforward and radical option would be to remove
1. items
iNtroductioN
the
related to activities and outputs from the indicator (or to apply a
zero weight to them), and to keep only the system- and agency-related aspects.
Such an
option
is particularly
since the
WB’s approach,
by
The World
Bank
(henceforth
WB) appealing
has been rating
countries
around the
indiscriminately
using inputs
and since
outputs
to measure
statistical
capacity,
world for their statistical
capacity
2004.
The WB’s
indicator
of staseems
double-count
a number publicly
of aspectsavailable
and to mix
up flows
tisticaltocapacity
uses information
to assess
three(periodic
aspects,
activities
and outputs)
and stocks
(improvements
that and
occurstatistics
once and
for
namely statistical
practices,
data collection
activities,
availall)
or performanceability.
Recently, the and
WBcapacity-related
has indicated itsaspects.
intention to improve its framework for statistical capacity measurement by shifting toward a new approach focusing
four dimensions:
institutional
framework, indicators
statistical
However,
despite on
its attraction,
the option
of totally eliminating
2
methodology,
dataoutputs
sources,from
and the
dataoverall
dissemination.
of
activities and
WB indicator
raises a serious
problem, which relates to the complexity of the relationship between inputs
and outputs
in statistical
relationship
is more
The objective
of this
paper is toprocesses.
contributeIndeed,
to this this
improvement
effort,
nocomplex
than suggested
by theofearlier
discussed
building
tably by proposing
an analysis
the strengths
andcapacity
weaknesses
of theresults
WB’s
chain
framework.
existing
approach to statistical capacity measurement, and by exploring
some options for its enhancement. Specifically, the paper seeks to explore
Statistical
activities
and outputs
be regarded
simply asactivities
an outcome
the rationale
and modalities
of cannot
the WB’s
use of statistical
and
of
statistical
resources,
as some
may also
serve as inputs
for downstream
outputs
to measure
statistical
capacity,
to determine
the problems
that this
activities
outputs.
For options
instance,as atonumber
resources
that form
poses, andand
to devise
some
how theofWB’s
indicator
couldthe
be
capacity
of a statistical
system
are required
to carry out household
improvedbase
to better
capture actual
statistical
capacity.
surveys to obtain survey data. These data are necessary to undertake further
produce statistical
such
a consumer
priceand
inThe work
paper to
hypothesizes
that theindicators,
WB’s focus
on as
statistical
activities
dex,
inequality
index,
and employment
amongofothers.
such
outputs
to measure
statistical
capacity, tostatistics,
the detriment
aspectsInrelated
atoprocess,
household
surveys
appear to beagencies,
the first-level
activity,
the
statistical
systems and
data-producing
results
in the while
indicator
calculation
of theactual
indicators
forms
the second-level
Between the
poorly reflecting
statistical
capacity.
To supportactivity.
this hypothesis,
two
thea survey
data as approach.
a first-levelFirst,
output.
The statistical
paperareuses
two-pronged
the paper
builds onindicators
the new
constitute
second-level
understanding
of, and outputs.
approach to capacity and capacity enhancement.
Indeed, the development of the WB’s framework for measuring statistical
capacity occurred when international efforts were underway to revamp
13
2
PARIS21
Fantom and
Task
Watanabe
Team (2002a:
(2008).
7).
159
174
The African Statistical Journal, Volume 7, November
Le2008
Journal statistique africain, numéro 7, novembre 2008
165
The World Bank’s Framework for Statistical Capacity Measurement
Floribert Ngaruko
Therefore
the approach
in actual
to capacity
statistical
building
processes,
and align
a number
it to of
the“intermediate”
paradigm of resultsactivities
based
and
management.
products canThese
be viewed
effortsasresulted
both outputs
in theand
framework
inputs, depending
known as the
on
the
“capacity
stage building
considered.
results-chain
The PARIS21
approach.”
Task Team
The paper
forcefully
refersacknowledged
to this framethe
workcomplexity
in its attempt
of this
to relationship
capture the very
between
meaning
inputs
of and
statistical
outputs
capacity.
in statistical processes. Not only did they view survey data as inputs for the production
of final
statistical
outputs.
They
also recognized
that statistical
activiSecond,
the paper
relies
on recent
developments
in terms
of the measureties
to the
maintenance
and development
basic
resources of
mentcontribute
of statistical
capacity
at the international
level. of
The
formulation
statistical
suchalso
as skills,
theyatallow
forwhen
such skills
beconsidercontinuthe WB’s systems
framework
took as
place
a time
there to
was
ously
in use.14 Thus,
able momentum
to improve
statistical
capacity,
and statistical
not only statistics,
can statistical
activities
and outputs
serve as
capacity measurement
developingactivities
countries.
November
1999,
thisa
resources
or inputs for in
downstream
andInoutputs;
there
is also
resulted in loop,
the launch
of statistical
the PARIS21
Consortium,
a global
forum
and
retroactive
whereby
activities
and outputs
impact
on basic
network aimed
at promoting
facilitating
capacity
building
statistical
capacity.
Such a loopand
makes
it even statistical
more difficult
to isolate
reand better
useresults,
of statistics.
It alsofrom
led tooutputs
the establishment
the PARIS21
sources
from
and inputs
in statisticalofprocesses.
Task Team, which in May 2001 was tasked with devising an approach to
statisticalcompelling
capacity building
measurement.
Foractivities
the purposes
of this paper,
Another
reason to
retain statistical
and outputs
in the
the PARIS21
framework
the WB’sbasic
apWB’s
indicator
is becauseprovides
they arebenchmarks
needed as against
proxies which
for statistical
proach to statistical
capacity
measurement
can to
be quantify.
assessed. The PARIS21
resources,
which would
otherwise
be difficult
Task Team suggests, for example, that crude measures of volume activities
The paper’s
relianceason
the capacity
building
results
chain and
on the
could
be considered
a proxy
for the mass
of general
statistical
expertise
of
15
approaches
resonates
notwords,
only with
the specific
subject matter
aPARIS21
data-producing
agency.
In other
although
some statistical
activibut also
with
instrumental
role that theof
WB
played in
the development
ties
are by
nothe
means
relevant dimensions
statistical
capacity,
they may
of these
approaches.
Indeed,
notrelationship
only did it spearhead
the promotion
of
serve
as proxies.
In light
of the
between statistical
resources
the capacity
results chainthe
approach
but,latter
in concert
the UN,
and
statisticalbuilding
activities/outputs,
use of the
may bewith
appropriate,
OECD, IMF,
the EC,
the WB also
co-founded
PARIS21 Consorespecially
as a and
number
of statistical
aspects
for whichthe
comparable
data extium.
Moreover, itrelate
was also
part of theactivities
PARIS21
Task
Team, more
and assumed
ist
internationally
to statistical
and
outputs,
than to
the PARIS21
Taskand
Team’s
secretariat.3 agencies.
statistical
systems
data-producing
In
conclusion,
may be useful
to highlight
the
Using
both theit PARIS21
framework
and the serious
capacitychallenge
buildingthat
results
use
statistical this
activities
outputs
WB approach.
chainof approach,
paperand
explores
therepresents
WB’s use to
of the
statistical
activities
As
section,
relying capacity.
on statistical
activities
outputsthat
to
andargued
outputsintothis
measure
statistical
It identifies
theand
problems
measure
statistical
capacity
causesinto
the how
indicator
to capture
performance
this poses,
and provides
insights
the WB’s
indicator
could be
rather
thansocapacity.
Yet,reflect
statistical
activities
and outputs need to be used
improved
as to better
statistical
capacity.
as proxies of genuine dimensions of statistical capacity that would otherwise not be accounted for. The greater the weight of such dimensions in
statistical capacity, the greater the weight that needs to be given to statistical
activities and outputs, hence the greater the distortion in the overall
3
The membership of the PARIS21 Task Team was as follows: the IMF, Chair (Ms. L.
indicator.
The next section argues that this problem may be mitigated by,
Laliberté, Chairperson, Mr. T. Morrison, Mr. J. Bové and Mr. S. Khawaja), the World
first,
a
better
understanding
of the
relationship
between
statistical
Bank, Secretariat
(Mrs. M. Harrison,
Secretariat,
Mr. M.
Belkindas,
and Mr. capacity
G. Eele),
the UN Statistics Division, UNSD (Mr. W. de Vries), the UN Economic Commission for
Latin America and the Caribbean, UN ECLAC (Ms. B. Carlson), and the UN Economic
Commission of Europe, UNECE (Mr. J-E. Chapron), and AFRISTAT (Mr. Lamine
14
Diop).
PARIS21
The Consultants
Task Team (2002b).
to the PARIS21 Task Team were Mr. D. Allen, Mr. T. Holt and
15
Mr.PARIS21
J. van Tongeren.
Task Team (2002b: 12).
160African Statistical Journal, Volume 7, November
Le2008
Journal statistique
statistique africain,
africain, numéro
numéro 7,
7, novembre
novembre 2008
2008
The
166
Le
Journal
175
The World Bank’s Framework for Statistical Capacity Measurement
Floribert Ngaruko
and
davantage
statistical
que activities
les capacités
and,
à proprement
second, by adequately
parler. Pouraccounting
améliorer l’approche,
for capacity
le
utilization.
papier suggère l’affinement de la méthode d’agrégation des indicateurs des différentes composantes des systèmes statistiques, des activités et de la production
statistiques, et surtout la prise en compte du degré d’utilisation des capacités
existantes
qui est lecApAcity
chaînon manquant
dans l’approche
la Banque mon4.
tAkiNg
utilizAtioN
iNtode
AccouNt
diale, entre activités/production et capacités statistiques.
In recent years, the development community has increasingly recognized
Motsinclés
: Indicateur
de capacités
statistiques,
Renforcement
desascapacités,
that
most
African countries,
capacity
is often
underutilized
a result
Utilisation
des capacités,
PARIS21,
Approche
du renforcement
deshave
capacités
of
the misallocation
of available
skills
and talents.
Some authors
even
par la chaîne
résultats. of circumstances, capacity is prevented from befound
that, indesa number
ing put to work.16 By and large, the literature points to incentives provided
by the prevailing public sector management system and governance factors
1. explain
iNtroductioN
to
the underutilization of capacity. As Obadan argues, when talents are misallocated, and recruitment and promotions based on personal
The World Bank
(henceforth
WB)
rating
countries
around
the
connections
and loyalties
rather
thanhasonbeen
merit,
existing
capacity
is likely
17
world
for their statistical
capacity since 2004. The WB’s indicator of stato
be underutilized.
tistical capacity uses information publicly available to assess three aspects,
namely statistical
practices,
collection
and
availCapacity
utilization
may varydata
across
time andactivities,
space, and
bestatistics
understood
in
ability. Recently,
the WB hasterms.
indicated
its intention
to improve
framequantitative
and qualitative
A society
may utilize
differentits
amounts
work
for statistical
capacity
measurement
by shifting
toward
a newvariapof
its capacity
at different
times,
just as different
societies
may utilize
proach
focusing
on four
dimensions:
institutional
framework,
statistical
able
amounts
of their
capacities
at a given
time. On the
other hand,
a soci2
methodology,
sources,
and data
ety
may utilizedata
the same
amount
of itsdissemination.
capacity but with
different efficiency
at different times; whereas different societies may utilize the same amount
of
capacity
butpaper
with is
different
efficiency
at aimprovement
given time. Thus,
Thetheir
objective
of this
to contribute
to this
effort, not
noonly
relationship
between
statistical
system’s
activities/outputs
and
tably isbythe
proposing
an analysis
ofathe
strengths
and weaknesses
of the WB’s
its
capacity
very complex,
as earlier
discussed,
but it is byand
no means
linear.
existing
approach
to statistical
capacity
measurement,
by exploring
This
by manySpecifically,
factors, which
different
rates
somerelationship
options for isitsaffected
enhancement.
the result
paper in
seeks
to explore
of
utilization
in different
circumstances.
thecapacity
rationale
and modalities
of the
WB’s use of statistical activities and
outputs to measure statistical capacity, to determine the problems that this
There
a growing
to consider
thatthe
a society’s
capacity to
utilize
poses, is
and
to deviseconsensus
some options
as to how
WB’s indicator
could
be
effectively
and
efficiently
capacity
is a keycapacity.
aspect of its capacity per se,
improved to
better
captureitsactual
statistical
and that the effort to increase the rate of utilization of its capacity should
18
be
as capacity that
enhancement
its own
Theconsidered
paper hypothesizes
the WB’s infocus
on right.
statistical
activities
and
This
means that
outputs to
measure could
statistical
capacity, toasthe
detriment
of aspects
capacity
utilization
be considered
a capacity
resource.
Yet, related
capacto statistical
and data-producing
resultsresides
in theinindicator
ity
utilizationsystems
is a particular
resource. Thisagencies,
particularity
the fact
poorly
reflecting
actual statistical
capacity.
To support
this hypothesis,
the
that
in specific
circumstances,
capacity
utilization
and overall
capacity may
paper uses
a two-pronged
approach.
First, the paper builds on the new
evolve
independently,
or even
in opposition.
understanding of, and approach to capacity and capacity enhancement.
Indeed, the development of the WB’s framework for measuring statistical
capacity occurred when international efforts were underway to revamp
16
17
18
2
Obadan (2007).
Ibid.
Obadan
Fantom and
(2005).
Watanabe (2008).
161
176
The African Statistical Journal, Volume 7, November
Le2008
Journal statistique africain, numéro 7, novembre 2008
165
The World Bank’s Framework for Statistical Capacity Measurement
Floribert Ngaruko
To
the illustrate,
approach let
to C,
capacity
A, andbuilding
U be statistical
and align
capacity,
it to thestatistical
paradigm
activity,
of resultsand
the
based
rate
management.
of utilizationThese
of theefforts
existing
resulted
statistical
in thecapacity
framework
C inknown
periodast, the
respectively.
“capacity building
One then
results-chain
can represent
approach.”
the relationship
The paper
among
refersthese
to this
variables
frameas
work
follows:
in its attempt to capture the very meaning of statistical capacity.
Second, the paper relies on recent
At = αC
developments
U
(1) in terms of the measuret t
ment of statistical capacity at the international level. The formulation of
thebeing
WB’sa framework
alsocaptures
took place
a time“productivity”
when there was
α
constant that
the at
average
of considerstatistical
able momentum
to (1)
improve
statistical
capacity,
andt, statistical
resources.
Equation
simplystatistics,
means that
at any point
of time
capacityismeasurement
in developing
November
1999,Takthis
activity
undertaken using
all or part countries.
of existing In
statistical
resources.
resulted
in the launch
of the
ing
the logarithm
and then
thePARIS21
differenceConsortium,
of equation a(1)global
yields:forum and
network aimed at promoting and facilitating statistical capacity building
and better use of statistics. ∆A
It also
led+to∆U
the establishment
of the PARIS21
= ∆C
(2)
Task Team, which in May 2001 was tasked with devising an approach to
statistical
capacity the
building
measurement.
purposes
of this
paper,
with
∆ indicating
percentage
change inFor
thethe
amount
of the
concerned
the PARIS21
framework
provides
benchmarks
whichasthe
WB’s apvariable
during
the period.
Equation
(2) can beagainst
rearranged
follows:
proach to statistical capacity measurement can be assessed.
∆C = ∆A – ∆U
(3)
The paper’s reliance on the capacity building results chain and on the
PARIS21
approaches
not only
withamount
the specific
subjectresourcmatter
As
Equation
(3) shows,resonates
a given change
in the
of statistical
butisalso
with
role thatthe
thechange
WB played
in the development
es
equal
to the
theinstrumental
difference between
in statistical
activity and
of these
approaches.
Indeed,
notamount
only did
spearhead
the promotion
of
the
change
in utilization
of this
of itstatistical
capacity,
all changes
the capacity
chainpoints.
approach
but,Equation
in concert
the UN,
expressed
in building
terms of results
percentage
Thus,
(3)with
implies
that
OECD,
IMF, and
the statistical
EC, the WB
also co-founded
the only
PARIS21
after
a period
of low
activity,
during which
part Consorof existtium.
Moreover,
it was also
of the PARIS21
Task Team,
and assumed
ing
statistical
resources
werepart
in effective
use, additional
statistical
activity
3
the PARIS21
Task Team’s
secretariat.
and
outputs could
be taken
up by mobilizing
latent capacity rather than
by acquiring fresh capacity. In such a situation, the increase in statistical
activity
wouldthe
be PARIS21
absorbed by
the increase
of utilization
existUsing both
framework
andin the rate
capacity
buildingofresults
ing
capacity
without
impact
on the
massofofstatistical
resourcesactivities
that the
chain
approach,
this any
paper
explores
theoverall
WB’s use
statistical
system
has at its
disposal.capacity. It identifies the problems that
and outputs
to measure
statistical
this poses, and provides insights into how the WB’s indicator could be
Equation
that if statistical
during a period,
improved (3)
so asalso
to means
better reflect
capacity.the change in the rate of
capacity utilization were higher than the change in the amount of statistical activities undertaken in that period, then statistical capacity would
have declined, not increased, during that period, even if the change in statistical
activity were positive. In fact, a given statistical activity growth rate
3
The membership of the PARIS21 Task Team was as follows: the IMF, Chair (Ms. L.
implies
a commensurate change in statistical capacity only if the rate of
Laliberté, Chairperson, Mr. T. Morrison, Mr. J. Bové and Mr. S. Khawaja), the World
capacity
utilization
constant
during
period. This
is what
the
Bank, Secretariat
(Mrs. remains
M. Harrison,
Secretariat,
Mr.that
M. Belkindas,
and Mr.
G. Eele),
WB
implicitly
assumes,UNSD
causing
to UN
relyEconomic
on a highly
restrictive
the UN
Statistics Division,
(Mr.its
W.approach
de Vries), the
Commission
for
Latinlargely
Americaunrealistic
and the Caribbean,
UN ECLAC (Ms. B. Carlson), and the UN Economic
and
assumption.
Commission of Europe, UNECE (Mr. J-E. Chapron), and AFRISTAT (Mr. Lamine
Diop). The Consultants to the PARIS21 Task Team were Mr. D. Allen, Mr. T. Holt and
Mr. J. van Tongeren.
162African Statistical Journal, Volume 7, November
Le2008
Journal statistique
statistique africain,
africain, numéro
numéro 7,
7, novembre
novembre 2008
2008
The
166
Le
Journal
177
The World Bank’s Framework for Statistical Capacity Measurement
Floribert Ngaruko
Indeed,
davantage
this
quecondition
les capacités
is likely
à proprement
to be metparler.
in two
Pour
particular
améliorer
circumstances,
l’approche, le
namely
papier suggère
situations
l’affinement
where existing
de la méthode
capacity
d’agrégation
is in full use
des and
indicateurs
where there
des difis
no
férentes
possibility
composantes
to further
des systèmes
increasestatistiques,
it, or where
deslatent
activités
capacity
et de la
exists
production
but no
actionable
statistiques, policy
et surtout
is available
la prise en
or possible
compte dutodegré
mobilize
d’utilisation
such unused
des capacités
capacity.
existantes
In such
quisituations,
est le chaînon
a given
manquant
percentage
dans
point
l’approche
increasedeinlathe
Banque
amount
monof
statistical
diale, entreactivities
activités/production
undertakenetwould
capacités
mean
statistiques.
a commensurate increase in
statistical capacity, since one would have, for example, to hire and train
new
equip them
with newstatistiques,
equipment Renforcement
to take up these
Motsstaff,
clés and
: Indicateur
de capacités
desadditional
capacités,
activities.
capacity
were Approche
not fully du
used,
and actionable
policy
UtilisationIfdesexisting
capacités,
PARIS21,
renforcement
des capacités
available
or possible
to mobilize (at least partially) the latent capacity, then
par la chaîne
des résultats.
additional activity would translate into the use of all or part of the unused
capacity, resulting in the new tasks being taken up without a commensurate
in statistical capacity.
1. increase
iNtroductioN
While
this suggests
that latentWB)
capacity
allows
for the
absorption
of the
The World
Bank (henceforth
has been
rating
countries
around
impact
of their
changes
in statistical
activity/outputs
on statistical
capacity,
is
world for
statistical
capacity
since 2004. The
WB’s indicator
of it
stanoteworthy
thatuses
in some
circumstances
could amplify
such
an impact.
tistical capacity
information
publiclyit available
to assess
three
aspects,
For
instance,
if thepractices,
volume ofdata
statistical
activities
and outputs
increases
at
namely
statistical
collection
activities,
and statistics
availaability.
given Recently,
rate during
period,
whileits
forintention
some reason
the rateits
of framecapacthea given
WB has
indicated
to improve
ity
utilization
is decreasing
the same period,
then toward
statistical
capacity
work
for statistical
capacityover
measurement
by shifting
a new
apwould
increased
at adimensions:
rate higher than
that of statistical
activity
and
proach have
focusing
on four
institutional
framework,
statistical
outputs.
methodology, data sources, and data dissemination.2
Equation
(3) suggests
that the
statistical capacity
The objective
of this paper
is torelationship
contribute between
to this improvement
effort, and
nostatistical
activities/outputs
spills
overstrengths
a third variable,
that is, capacity
utitably by proposing
an analysis
of the
and weaknesses
of the WB’s
lization.
aboveto
model
suggests
that there
is an identity
linking
changes
existing The
approach
statistical
capacity
measurement,
and
by exploring
in
theoptions
level of for
statistical
capacity in any
given country
withseeks
changes
in the
some
its enhancement.
Specifically,
the paper
to explore
level
of statistical
andofoutputs,
anduse
changes
in statistical
capacity
the rationale
andactivities
modalities
the WB’s
of statistical
activities
and
utilization.
The relationship
these
three variables
may be compared
outputs to measure
statisticalamong
capacity,
to determine
the problems
that this
to
that and
among
the angles
a triangle,
as the
among
them
poses,
to devise
someofoptions
as to
howinterdependency
the WB’s indicator
could
be
means
thattotobetter
derivecapture
reliably
the variation
any of the three variables, a
improved
actual
statisticalincapacity.
sufficient condition is to know variations in the other two variables.
The paper hypothesizes that the WB’s focus on statistical activities and
Thus,
“Capacity–Activity–Capacity
Triangle”
model
iloutputsthe
to measure
statistical capacity, to Utilization
the detriment
of aspects
related
lustrates
a relationship
between
statisticalagencies,
capacity results
and statistical
activity/
to statistical
systems and
data-producing
in the indicator
outputs
that is more
sophisticated
than theToone
assumed
the WB, and
poorly reflecting
actual
statistical capacity.
support
thisby
hypothesis,
the
which
implies
a mechanisticapproach.
and univocal
of changes
paper uses
a two-pronged
First,impact
the paper
builds in
onstatistical
the new
activities/outputs
The and
model
ratherenhancement.
suggests that
understanding of, on
andstatistical
approachcapacity.
to capacity
capacity
taking
utilizationofinto
every timefor
statistical
activities
and
Indeed,capacity
the development
theaccount
WB’s framework
measuring
statistical
outputs
used towhen
measure
statistical capacity
is crucial
if the WB’s
indicapacity are
occurred
international
efforts were
underway
to revamp
cator is to reliably capture actual statistical capacity. One interesting question
that this conclusion raises is how, as an improvement to the WB’s
2
Fantom and Watanabe (2008).
163
178
The African Statistical Journal, Volume 7, November
Le2008
Journal statistique africain, numéro 7, novembre 2008
165
The World Bank’s Framework for Statistical Capacity Measurement
Floribert Ngaruko
approach
the approach
to statistical
to capacity
capacity
building
measurement,
and align itaccounting
to the paradigm
for capacity
of resultsutilization
based management.
would compare
Thesewith
efforts
the resulted
earlier-mentioned
in the framework
need toknown
improve
as the
on
indicator
“capacity building
aggregation.
results-chain approach.” The paper refers to this framework in its attempt to capture the very meaning of statistical capacity.
One consequence of an improved method of score aggregation in the WB’s
approach
Second, the
would
paperberelies
a reduction
on recentindevelopments
the distortionincreated
terms of
by the
themeasureoveremphasis
ment of
onstatistical
statisticalcapacity
activitiesatand
theoutputs
international
to the detriment
level. The of
formulation
statistical caof
pacity.
the WB’s
Anframework
improved aggregation
also took place
method
at awould
time when
mean there
the WB’s
was approach
considergiving
able momentum
greater weight
to improve
to statistical
statistics,
resources
statistical
thancapacity,
to statistical
and statistical
activities
and
capacity
outputs,
measurement
leading toina reduction
developingincountries.
the distortion
In November
and to less1999,
volatility
this
in
resulted
the overall
in thescore
launch
of statistical
of the PARIS21
capacity.Consortium,
Furthermore,aitglobal
wouldforum
mean and
less
pressure
network on
aimed
countries
at promoting
to continue
and to
facilitating
carry outstatistical
statisticalcapacity
activitiesbuilding
and to
produce
and betterstatistical
use of statistics.
outputs Itatalso
regular
led tointervals
the establishment
in order toofmaintain
the PARIS21
high
scores,
Task Team,
as is the
which
caseinunder
May the
2001
current
was tasked
measurement
with devising
system.
an approach to
statistical capacity building measurement. For the purposes of this paper,
the PARIS21
framework
provides benchmarks
against
whichsolely
the WB’s
However,
none
of these problems
would totally
disappear
as a apreproach
to statistical
measurement
can be assessed.
sult
of an
improvedcapacity
aggregation
method. Indeed,
these problems cannot
disappear as long as statistical activities and outputs have to be used as
proxies
The paper’s
for those
reliance
aspects
onofthe
statistical
capacitycapacity
building
thatresults
wouldchain
not beand
accounted
on the
for
PARIS21
otherwise.
approaches
In circumstances
resonates not
where
only
such
with
aspects
the specific
represent
subject
a significant
matter
share
but also
of with
statistical
the instrumental
capacity, therole
problem
that the
of WB
volatility
played
would
in thebedevelopment
particularly
acute,
of thesesince
approaches.
scores ofIndeed,
statistical
notactivities
only didand
it spearhead
outputs would
the promotion
have to be
of
given
the capacity
relatively
building
greaterresults
weightchain
to account
approach
for but,
theseinaspects
concertadequately.
with the UN,
OECD, IMF, and the EC, the WB also co-founded the PARIS21 Consortium.
Moreover,
it was
also part
of the PARIS21
Taskwould
Team,likely
and assumed
In
contrast,
taking
capacity
utilization
into account
improve
3
PARIS21
Task Team’s
secretariat.
the WB’s
measurement
system
considerably.
This is borne out by the perspective that the “Capacity–Activity–Capacity Utilization Triangle” model
offers
address
the problem
of volatility.
thebuilding
apparentresults
volaUsing to
both
the PARIS21
framework
andSpecifically,
the capacity
tility
statisticalthis
capacity,
it results
WB’s
current approach,
chainofapproach,
paper asexplores
thefrom
WB’stheuse
of statistical
activities
is
largely
a consequence
of the neglect
of capacity
utilization,
since that
this
and
outputs
to measure statistical
capacity.
It identifies
the problems
approach
that variations
statistical
and outputs
imply
this poses,assumes
and provides
insights in
into
how theactivity
WB’s indicator
could
be
commensurate
in statistical
capacity.
improved so as variations
to better reflect
statistical
capacity.
A proportion of the changes in statistical activities may simply be absorbed
by changes in statistical capacity utilization, implying that variations in
statistical
activity/outputs do not mean commensurate variations in statis3
The membership of the PARIS21 Task Team was as follows: the IMF, Chair (Ms. L.
tical
capacity.
By the same token, countries would not have to continue to
Laliberté, Chairperson, Mr. T. Morrison, Mr. J. Bové and Mr. S. Khawaja), the World
carry
out
statistical
andSecretariat,
to produce
outputs
at G.
regular
Bank, Secretariat (Mrs. activities
M. Harrison,
Mr. statistical
M. Belkindas,
and Mr.
Eele),
intervals
to maintain
scores,
since
part the
or the
these activithe UN Statistics
Division,high
UNSD
(Mr. W.
de Vries),
UN totality
EconomicofCommission
for
Latinand
America
and the
Caribbean,
UN ECLAC
(Ms. existing
B. Carlson),
and the UN Economic
ties
outputs
could
be undertaken
using
capacity.
Commission of Europe, UNECE (Mr. J-E. Chapron), and AFRISTAT (Mr. Lamine
Diop). The Consultants to the PARIS21 Task Team were Mr. D. Allen, Mr. T. Holt and
Mr. J. van Tongeren.
164African Statistical Journal, Volume 7, November
Le2008
Journal statistique
statistique africain,
africain, numéro
numéro 7,
7, novembre
novembre 2008
2008
The
166
Le
Journal
179
The World Bank’s Framework for Statistical Capacity Measurement
Floribert Ngaruko
Thus,
davantage
the que
“Capacity–Activity–Capacity
les capacités à proprement parler.
Utilization
Pour améliorer
Triangle”l’approche,
model prole
vides
papiera suggère
plausible
l’affinement
explanation
de for
la méthode
the abnormally
d’agrégation
highdes
volatility
indicateurs
of statistical
des difcapacity
férentes composantes
as measureddesbysystèmes
the WB’s
statistiques,
indicator.desFurthermore,
activités et deitlaallows
production
for a
more
statistiques,
accurate
et surtout
envisioning
la prise
of en
thecompte
relationship
du degré
between
d’utilisation
statistical
des capacités
capacity
and
existantes
statistical
qui est
activities
le chaînon
andmanquant
outputs. In
dans
thisl’approche
model, capacity
de la Banque
utilization
monis
diale,
likeentre
a filter
activités/production
placed between et
statistical
capacitéscapacity
statistiques.
and statistical activities/
outputs to separate those variations in statistical activities/outputs that are
associated
changesdeincapacités
latent capacity,
from
those changes
that are
Mots clés :with
Indicateur
statistiques,
Renforcement
des capacités,
genuinely
withPARIS21,
variationsApproche
in actual du
statistical
capacity.
Utilisationassociated
des capacités,
renforcement
des capacités
par la chaîne des résultats.
Hence, whereas the WB’s indicator wrongly attributes the bulk of statistical activities and output variations to the change in statistical capacity systematically,
the “Capacity–Activity–Capacity Utilization Triangle” model
1.
iNtroductioN
makes up for this weakness. The model makes it clear that capacity utilization
the missing
link in the WB’s
approach
to statistical
capacity
measThe is
World
Bank (henceforth
WB) has
been rating
countries
around
the
urement,
statistical
capacity
and2004.
statistical
and outputs.
world for between
their statistical
capacity
since
The activities
WB’s indicator
of statistical capacity uses information publicly available to assess three aspects,
namely statistical practices, data collection activities, and statistics avail5.
ability. coNcluSioN
Recently, the WB has indicated its intention to improve its framework for statistical capacity measurement by shifting toward a new approach
focusingofon
dimensions:
institutional
framework,
statistical
The
objectives
thisfour
paper
were to explore
the rationale
and modalities
methodology,
data
and
data dissemination.
of
the WB’s use
of sources,
statistical
activities
and outputs2 to measure statistical
capacity, to identify the problems that this poses, and to devise some options
on how of
thethis
WB’s
indicator
could betoimproved
so as to better
The objective
paper
is to contribute
this improvement
effort,capnoture
statistical
Tothe
address
these
issues,
the paper
referred
tablyactual
by proposing
an capacity.
analysis of
strengths
and
weaknesses
of the
WB’s
to
the PARIS21
andcapacity
the capacity
building and
results
apexisting
approachframework
to statistical
measurement,
by chain
exploring
proach.
Choosing
to enhancement.
use these frameworks
was particularly
apposite,
given
some options
for its
Specifically,
the paper seeks
to explore
the paper’s
subject
matter andof
thethe
central
the WB played
in their
rationale
and modalities
WB’srole
usethat
of statistical
activities
and
emergence
and promotion.
outputs to measure
statistical capacity, to determine the problems that this
poses, and to devise some options as to how the WB’s indicator could be
The
paper to
identified
two major
shortcomings
in the WB’s approach, which
improved
better capture
actual
statistical capacity.
have resulted in its failure to adequately capture statistical capacity. These
are
its overreliance
on statistical
activities
andon
outputs
and (ii)
its neglect
The(i)paper
hypothesizes
that the WB’s
focus
statistical
activities
and
of
statistical
capacitystatistical
utilization.
These to
compel
a countryoftoaspects
carry out
staoutputs
to measure
capacity,
the detriment
related
tistical
activities
at regular
intervals in order
to maintain
they
to statistical
systems
and data-producing
agencies,
resultsa high
in thescore;
indicator
also
explain
why statistical
capacity,
as measured
by the this
WB’shypothesis,
indicator, appoorly
reflecting
actual statistical
capacity.
To support
the
pears
be highly
volatile. The
interactions
these
two on
factors
papertouses
a two-pronged
approach.
First,between
the paper
builds
the tend
new
to
aggravate theof,
bias
of approach
the WB’s indicator:
greater
the reliance
of the
understanding
and
to capacitythe
and
capacity
enhancement.
indicator
ondevelopment
statistical activities
and outputs,
the greater
the impact
of its
Indeed, the
of the WB’s
framework
for measuring
statistical
neglect
capacity when
utilization.
Conversely,
if the
WB’s
approach
capacityofoccurred
international
efforts
were
underway
toproperly
revamp
took capacity utilization into account, then the impact of its emphasis on
statistical
activities and outputs would be moderated.
2
Fantom and Watanabe (2008).
The African Statistical Journal, Volume 7, November
165
180
Le2008
Journal statistique africain, numéro 7, novembre 2008
The World Bank’s Framework for Statistical Capacity Measurement
Floribert Ngaruko
In
thethis
approach
paper, an
to capacity
effort hasbuilding
been made
andtoalign
identify
it to options
the paradigm
for an of
improved
resultsapproach.
based management.
It was argued
These
that
efforts
suchresulted
an approach
in theshould
framework
be consistent
known aswith
the
the
“capacity
PARIS21
building
framework
results-chain
and theapproach.”
capacity building
The paper
results
referschain
to this
approach
frameas
work
much
in its
as attempt
possible,towhile
capture
notthe
conflicting
very meaning
with cost-effectiveness
of statistical capacity.
and international comparability. The latter two factors were identified as the
bedrock
of the
WBrelies
indicator’s
success
to date, ininspite
highlighted
Second, the
paper
on recent
developments
termsofofitsthe
measureweaknesses.
ment of statistical capacity at the international level. The formulation of
the WB’s framework also took place at a time when there was considerAlthough
able momentum
removing
to activityimprove and
statistics,
output-related
statistical items
capacity,
fromand
thestatistical
WB indicator
capacitymight
measurement
initially appear
in developing
to be the
countries.
most appropriate
In November
solution
1999,
to this
the
problem,
resulted inthis
theoption
launchhasofbeen
the PARIS21
rejected forConsortium,
a number ofareasons.
global forum
One isand
the
difficulty
network aimed
in clearly
at promoting
distinguishing
andbetween
facilitating
inputs
statistical
and outputs
capacity
in statistical
building
processes.
and better Indeed,
use of statistics.
not onlyItdo
also
some
led activities
to the establishment
and outputsofserve
the PARIS21
as inputs
for
Taskdownstream
Team, which
activities
in May and
2001outputs,
was tasked
but with
theredevising
also exists
an aapproach
retroactive
to
loop
statistical
whereby
capacity
downstream
buildingactivities
measurement.
and outputs
For the
in purposes
turn affect
ofbasic
this paper,
statistical
the PARIS21
capacity. framework
Moreover, provides
the data benchmarks
available to measure
against which
statistical
the WB’s
capacity
apin
proach
a cost-effective
to statisticalmanner
capacityand
measurement
to allow for
caninternational
be assessed. comparability,
mostly relate to statistical activities and outputs, and only marginally to
actual
statistical
capacity.
The paper’s
reliance
on the capacity building results chain and on the
PARIS21 approaches resonates not only with the specific subject matter
Against
but also with
such the
a background,
instrumentalitrole
wasthat
argued
the WB
thatplayed
improvements
in the development
in the aggregation
of these approaches.
of various items
Indeed,
in not
the only
WB’sdid
indicator
it spearhead
methodology
the promotion
might be
of
athe
better
capacity
option
building
for anresults
improved
chain
measurement
approach but,
system.
in concert
Also, with
the paper
the UN,
argued
OECD,
thatIMF,
when
and
using
the EC,
scores
theofWB
statistical
also co-founded
activity and
theoutputs
PARIS21
to Consormeasure
statistical
tium. Moreover,
capacity,
it was
taking
alsodue
part account
of the PARIS21
of statistical
Task Team,
capacity
andutilization
assumed
would
the PARIS21
be helpful.
Task Team’s secretariat.3
These
wouldframework
have differing
however.
An improved
Using improvements
both the PARIS21
andimpacts,
the capacity
building
results
aggregation
method
thethe
distortion
caused
by the use
of the
chain approach,
thiswould
paper reduce
explores
WB’s use
of statistical
activities
volume
of statistical
activities
andcapacity.
outputsIttoidentifies
measurethe
statistical
capacand outputs
to measure
statistical
problems
that
ity.
into insights
account into
statistical
this However,
poses, andtaking
provides
how capacity
the WB’sutilization
indicator would
could albe
low
differentiation
in statistical
activities and
outputs between, on the one
improved
so as to better
reflect statistical
capacity.
hand, those associated with changes in actual statistical capacity and, on
the other, those likely to be absorbed by changes in mere capacity utilization. It is therefore recommended that the WB should work on improving
the
aggregation method, and more importantly, take into account capacity
3
The membership of the PARIS21 Task Team was as follows: the IMF, Chair (Ms. L.
utilization
in its approach, as the missing link between statistical activities
Laliberté, Chairperson, Mr. T. Morrison, Mr. J. Bové and Mr. S. Khawaja), the World
and
outputs
and
statistical
capacity.
Bank, Secretariat
(Mrs.
M. Harrison,
Secretariat, Mr. M. Belkindas, and Mr. G. Eele),
the UN Statistics Division, UNSD (Mr. W. de Vries), the UN Economic Commission for
Latin America and the Caribbean, UN ECLAC (Ms. B. Carlson), and the UN Economic
Commission of Europe, UNECE (Mr. J-E. Chapron), and AFRISTAT (Mr. Lamine
Diop). The Consultants to the PARIS21 Task Team were Mr. D. Allen, Mr. T. Holt and
Mr. J. van Tongeren.
166African Statistical Journal, Volume 7, November
Le2008
Journal statistique
statistique africain,
africain, numéro
numéro 7,
7, novembre
novembre 2008
2008
The
166
Le
Journal
181
The World Bank’s Framework for Statistical Capacity Measurement
Floribert Ngaruko
refereNceS
davantage que les capacités à proprement parler. Pour améliorer l’approche, le
papier suggère l’affinement de la méthode d’agrégation des indicateurs des différentes(2007),
composantes
des systèmes
statistiques,
des activités
et de laand
production
ACBF
Towards
Reforming
National Statistical
Agencies
Systems:
statistiques,
et surtout la Countries
prise en compte
du degréNational
d’utilisation
des capacités
A
Survey of Best-Practice
with Effective
Statistical
Systems
existantes
qui est Best-Practice
le chaînon manquant
dansBPS
l’approche
de la
Banque
in
Africa, ACBF
Study Series
01/2007.
Harare:
ThemonAfdiale, Capacity
entre activités/production
et capacités statistiques.
rican
Building Foundation.
Mots clésN.: Indicateur
de capacités
statistiques,
Renforcement
capacités,
Fantom,
and N. Watanabe
(2008),
“Improving
the WorlddesBank’s
DaUtilisation
des capacités,
PARIS21,
Approche
du renforcement
des 2,
capacités
tabase
of Statistical
Capacity,”
African
Statistical
Newsletter, vol.
no. 3,
par la
chaîne des résultats.
pp.
21-22.
Gafishi, P., I. MacAuslan, and C. Spanneut (2008), Evaluation de l’Appui
1. Renforcement
iNtroductioN
au
des Capacités Statistiques. Etude de Cas du Niger. Mimeo.
Niamey, Niger: Institut National de Statistique (INS).
The World Bank (henceforth WB) has been rating countries around the
world for their
statistical
capacity since
2004. The
WB’s indicator
staKiregyera,
B. (2006),
Strengthening
National
Statistical
Systems inofSubtistical capacity
uses information
publicly
available
to assessACBF
three Lessons
aspects,
Saharan
Africa –Some
Lessons from
Ugandan
Experience.
namelyHarare.
statistical practices, data collection activities, and statistics availNote,
ability. Recently, the WB has indicated its intention to improve its framework for E.
statistical
by shiftingReview
towardof athenew
apMizrahi,
(2003), capacity
Capacity measurement
Enhancement Indicators:
Literaproach
focusing
four dimensions:
institutional
framework,
statistical
ture.
World
Bankon
Institute
Evaluation Studies
No. EG03-72.
Washington,
methodology,
data
sources,
and data dissemination.2
DC:
The World
Bank
Institute.
Obadan,
M. (2005),
“Challenges
in the Building
Public Service
CapacThe objective
of this paper
is to contribute
to this of
improvement
effort,
noity
in by
Africa,”
ACBF
Paper
No. 5. Harare:
ACBF. of the WB’s
tably
proposing
anWorking
analysis of
the strengths
and weaknesses
existing approach to statistical capacity measurement, and by exploring
Obadan,
M. (2007),
“Capacity Utilization,
Retention,
andseeks
the Use
of Afsome options
for its enhancement.
Specifically,
the paper
to explore
rican
Diasporan
Challenges
the rationale
andCommunities
modalities of as
theDevelopment
WB’s use of Actors:
statistical
activities and
Opportunities.”
Paper
presented
at thetoSecond
Forum
Capacitythat
Buildoutputs to measure
statistical
capacity,
determine
theon
problems
this
ing,
Maputo
1-3 August.
poses,
and to(Mozambique),
devise some options
as to how the WB’s indicator could be
improved to better capture actual statistical capacity.
PARIS21 Task Team (2002a), The Framework for Determining Statistical
Capacity
Building
Indicators,
The paper
hypothesizes
thatApril.
the WB’s focus on statistical activities and
outputs to measure statistical capacity, to the detriment of aspects related
PARIS21
Task
Team and
(2002b),
Statistical Capacity
Indicators
Final
to statistical
systems
data-producing
agencies,Building
results in
the indicator
Report.
September.
poorly reflecting
actual statistical capacity. To support this hypothesis, the
paper uses a two-pronged approach. First, the paper builds on the new
understanding of, P.and
approach
to capacity
capacity
Wingfield-Digby,
(2008),
“Africa’s
STATS and
League
– Theenhancement.
Movers and
Indeed, 2006-2007,”
the development
of the
WB’s framework
for measuring
Shakers
African
Statistical
Newsletter, vol.
2, no. 1, pp.statistical
26-28.
capacity occurred when international efforts were underway to revamp
World Bank (2006), Statistical Capacity Improvement in IDA Countries –
Progress
Report. Washington DC: The World Bank, May 16.
2
Fantom and Watanabe (2008).
167
182
The African Statistical Journal, Volume 7, November
Le2008
Journal statistique africain, numéro 7, novembre 2008
165
The World Bank’s Framework for Statistical Capacity Measurement
Floribert Ngaruko
ANNex
the approach
1: compoNeNtS
to capacity building
of and
thealign
World
it to the
BANk’S
paradigm
iNdex
of resultsof
StAtiSticAl
based management.
cApAcity
These efforts resulted in the framework known as the
“capacity building results-chain approach.” The paper refers to this framework
in its attempt
to capture the very meaning of statistical capacity.
i. StAtiSticAl
prActice
indicators
1
0
max
Weight
Second,
paper
on last
recent
developments
terms of the
1. National the
accounts
base relies
Within
10 years
or annual chain inOtherwise
1 measure10
ment
year of statistical capacity
linking at the international level. The formulation of
the
WB’sof payments
framework also
took
placeManual,
at a time
there was
2. Balance
Balance
of Payments
the fifthwhen
Otherwise
1 consider10
able
momentum
to improve
statistics, statistical capacity, and statistical
manual
in use*
edition
capacity
measurement
in developing
November1 1999,10this
3. External debt
reporting
Actual
or preliminary countries. InOtherwise
resulted
status* in the launch of the PARIS21 Consortium, a global forum and
network
at promoting
facilitating
capacity
4. Consumeraimed
Price Index
Within last and
10 years
or annual chainstatistical
Otherwise
1 building
10
andbasebetter
year use of statistics.
linkingIt also led to the establishment of the PARIS21
Task
Team,
which in May
2001
was tasked
5. Industrial
production
Produced
and available
from IMFwith devising
Otherwise an approach
1
10 to
statistical
capacity building measurement. For the purposes of this paper,
index
the
PARIS21prices
framework
provides
benchmarks
which the
6. Import/export
Produced
and available
from IMF against
Otherwise
1 WB’s10approach
to
statistical
capacity
measurement
can
be
assessed.
7. Government finance
Consolidated central government
Otherwise
1
10
accounting concept*
accounts
The
paper’sreporting
reliance
on
theor capacity
building
chain and
on10the
8. Enrollment
to
Annual
missed reporting
only once results
Otherwise
1
PARIS21
not only with the specific subject matter
UNESCO approaches resonates
in the last 4 years
but
also reporting
with the
role that
themeasles
WB played
in the development
9. Vaccine
to instrumental
Nationally reported
data on
Otherwise
1
10
of WHO*
these approaches. Indeed,
not
only
did
it
spearhead
the promotion of
vaccine cover-age consistent with
the capacity building results
chain approach but, in concert with the UN,
WHO estimates
OECD,
IMF,Data
and
the EC,
the WB also co-foundedOtherwise
the PARIS21
10. IMF’s Special
DisSubscribed
1 Consor10
tium.
Moreover,
it was also part of the PARIS21 Task Team, and assumed
semination
Standard*
the PARIS21 Task Team’s secretariat.3
maximum total score: 100
ii. dAtA collectioN
Using both the PARIS21 framework and the capacity building results
indicators
1
max
Weight
chain approach,
this paper explores2 the WB’s
use of0 statistical
activities
1. Periodicity
of population
census statistical
≤ 10
years
Otherwise
2
10
and
outputs
to measure
capacity.
It identifies
the problems
that
2.
Periodicity
of
agricultural
census
≤
10
years
Otherwise
2
10
this poses, and provides insights into how the WB’s indicator could be
3. Periodicity of
surveys
≤ 3 years capacity.
≤ 5 years
Otherwise
2
10
improved
sopoverty
as torelated
better
reflect statistical
(IES, LSMS, etc.)
4. Periodicity of health related surveys
(DHS, MICS, Priority survey, etc)
≤ 3 years
5. Completeness of vital registration
Complete
The
membership of the PARIS21 Task Team
system*
≤ 5 years
Otherwise
2
10
Otherwise
2
10
was as follows: the IMF, Chair (Ms. L.
Laliberté, Chairperson, Mr. T. Morrison, Mr. J. Bové and Mr. S. Khawaja), the World
maximum total score: 100
Bank, Secretariat (Mrs. M. Harrison, Secretariat, Mr. M. Belkindas, and Mr. G. Eele),
the UN Statistics Division, UNSD (Mr. W. de Vries), the UN Economic Commission for
Latin America and the Caribbean, UN ECLAC (Ms. B. Carlson), and the UN Economic
/cont…
Commission of Europe, UNECE (Mr. J-E. Chapron), and AFRISTAT (Mr. Lamine
Diop). The Consultants to the PARIS21 Task Team were Mr. D. Allen, Mr. T. Holt and
Mr. J. van Tongeren.
3
168African Statistical Journal, Volume 7, November
Le2008
Journal statistique
statistique africain,
africain, numéro
numéro 7,
7, novembre
novembre 2008
2008
The
166
Le
Journal
183
The World Bank’s Framework for Statistical Capacity Measurement
Floribert Ngaruko
ANNex
davantage1:que
compoNeNtS
les capacités à proprement
of theparler.
World
Pour BANk’S
améliorer iNdex
l’approche,
of
le
StAtiSticAl
papier suggère l’affinement
cApAcity
de la(cont.)
méthode d’agrégation des indicateurs des différentes composantes des systèmes statistiques, des activités et de la production
statistiques,
etAVAilABility
surtout la prise en compte du degré d’utilisation des capacités
iii. StAtiSticS
existantes
qui
est
le chaînon
manquant
dans1 l’approche 0de la Banque
monindicators
3
2
max
Weight
diale,
entre
activités/production
et
capacités
statistiques.
1. Periodicity of income
≤ 3 years ≤ 5 years > 5 years
Otherwise
3
5
poverty indicator
Mots
clés of: child
Indicateur
Renforcement
des
2. Periodicity
mal- ≤ 3 de
yearscapacités
≤ 5 years statistiques,
> 5 years
Otherwise
3 capacités,
5
Utilisation
des capacités, PARIS21, Approche du renforcement des capacités
nutrition indicator
par
la chaîne
des résultats.
3. Periodicity
of child
National or inter- Otherwise
1
5
mortality indicator
1.4. Immunization
iNtroductioN
indicator
5. HIV/AIDS indicator
national estimates
available
Annual
Otherwise
1
5
National or inter-
Otherwise
1
5
The World Bank (henceforth WB) has
been
rating countries around the
national
estimates
world for their statistical capacity since
2004. The WB’s indicator of staavailable
tistical
capacity
uses ≤information
publicly
to assess three
aspects,
6. Periodicity
of maternal
3 years ≤ 5 years
> 5 yearsavailableOtherwise
3
5
namely
statistical practices, data collection activities, and statistics availhealth indicator
ability.
Recently,
has≤indicated
its intentionOtherwise
to improve3 its frame7. Periodicity
of gender the ≤WB
3 years
5 years > 5 years
5
equalityfor
in education
work
statistical capacity measurement by shifting toward a new apindicator focusing on four dimensions: institutional framework, statistical
proach
2
8. Primary completion
least one
Otherwise
1
5
methodology,
data sources, and data Atdissemination.
indicator
observation in the
last 5 years
contribute
to this
The objective of this paper is to
improvement effort, no9. Access
water indica- an analysis of the National
or interOtherwise
1 the WB’s
5
tably
bytoproposing
strengths
and weaknesses
of
tor
nationalmeasurement,
estimates
existing
approach to statistical capacity
and by exploring
available
some options for its enhancement. Specifically,
the paper seeks to explore
10.
Periodicity
of
GDP
Annual
≤
1.5
1.5 yearsuse of statistical
Otherwise activities
3
5and
the rationale and modalities of the >WB’s
growth
indicator
years
outputs to measure statistical capacity, to determine the problems that this
totalcould
score: 100
poses, and to devise some options as to how the WB’smaximum
indicator
be
improved to better capture actual statistical capacity.
Source: World Bank.
* Components not related to statistical activities and outputs.
The paper hypothesizes that the WB’s focus on statistical activities and
outputs to measure statistical capacity, to the detriment of aspects related
to statistical systems and data-producing agencies, results in the indicator
poorly reflecting actual statistical capacity. To support this hypothesis, the
paper uses a two-pronged approach. First, the paper builds on the new
understanding of, and approach to capacity and capacity enhancement.
Indeed, the development of the WB’s framework for measuring statistical
capacity occurred when international efforts were underway to revamp
2
Fantom and Watanabe (2008).
169
184
The African Statistical Journal, Volume 7, November
Le2008
Journal statistique africain, numéro 7, novembre 2008
165