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PARIS21 Task Force On Statistical Capacity IMF Statistics Department May 21, 2001

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PARIS21. Task Force On Statistical Capacity. IMF Statistics Department May 21, 2001. Premise of the presentation. Measuring statistical capacity Equals Assessing data quality. Plan of the presentation. Background Description of the framework Current and potential uses of the framework - PowerPoint PPT Presentation

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Page 1: PARIS21

PARIS21

Task Force On Statistical Capacity

IMF Statistics Department

May 21, 2001

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2

Premise of the presentation

Measuring statistical capacity

Equals

Assessing data quality

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3

Plan of the presentation Background Description of the framework Current and potential uses of the

framework Concluding remarks

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BackgroundA framework: its uses dictate that it be:

Comprehensive Balanced between experts’ rigor and

generalists’ bird’s eye view Widely applicable:

Across various stages of statistical development Across the major datasets

Designed to give transparent results Arrived at by drawing on national statisticians’

best practices

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Dataset

(6-digit)

“Lite”Generic

(3-digit) Summary of

Results

DatasetSpecific

(5-digit)

NA

etc

.

BO

P GFS

etc

. etc

.

Framework suite of tools

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Dimensions of data quality                         

                    

Integrity

Methodological soundness

Accuracy and reliability aand Serviceability

Accessibility

Quality-of-the-Institution

Quality-of-the-product

 

 

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Structure of the frameworkA cascading structure Five dimensions (plus prerequisites) of quality

And for each dimension; Elements that can be used in assessing quality

And for each element; Indicators that are more concrete and detailed;

And for each indicator; Focal issues that are tailored to the dataset

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Structure of the framework (cont’d)The cascading structure—an example For serviceability, one of the five

dimensions: Four elements are identified as being useful

in assessing that dimension: relevance, timeliness and periodicity, consistency, and revision policy and practice

For consistency, three indicators are identified to provide detail and concreteness for that element: intertemporal, internal, and intersectoral consistency

For internal consistency, the focal issues in [dataset] are…

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Framework preview Purpose: serve as a diagnostic

preview or for a nonstatistician’s assessment

13 specific (three-digit) indicators were identified (in the handout):

Relatively nontechnical Relatively easy to get information

Formatted (in the handout) as a worksheet

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Framework summary Summary presentation of results

Purpose: for nonstatisticians—such as policy advisors and potential investors—after a full assessment based on the DQAF

For clarity and comparability (in handout): For each dataset, a one-page table At the two-digit level (21 elements)

On a 4-point scale, from “practice observed” to “practice not observed”

With an “n.A.” Column With a “comments” column

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Uses of the framework To guide IMF staff

In assessing data for IMF’s use in surveillance and operations;

In preparing ROSCs; and In designing technical assistance

To guide country efforts (including self-assessments) in strengthening statistical capacity

To guide data users—to complement the SDDS and GDDS

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Concluding remarks General reaction

Welcome initiative Fills important gap Is careful and thoughtful Provides basis for coherent and

practical way forward in a complex field