Transcript Presentation

Ian Castles Memorial Seminar
New York
23 February 2011
Addressing Data Discrepancies - What we
found and how we dealt with them
Francesca Grum [email protected]
United Nations Statistics Division
The issue of Data Discrepancies
between national and international data sets
• Role of Ian Castles in drawing attention to data quality
issues
• Discussed in several sessions of the UN Statistical
Commission (2000, 2001, 2005, 2006, yearly since 2008)
• Resulted in a ECOSOC resolution to Strengthening
Statistical Capacity in 2006
The issue of Data Discrepancies
between national and international data sets
• Countries’ concerns focused on the lack
of :
– Consultation with national statistical offices
– Transparency of data sources and
methodologies used
– Use of existing official statistics
UNSD assessment –
Investigating Data Discrepancies
• Assessing data discrepancies via country
missions and workshops :
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Since 2008 inventorying differences
20 MDG indicators/20 years (‘90-’09)
40 countries
Documenting/explaining reasons for differences
• In consultation with concerned NSOs and international
agencies
• For matching years/indicators, we found
discrepancies for around 50% of these instances
UNSD assessment –
Understanding Data Discrepancies
Based on 5 project countries
Reasons for differences
Percent
Example
Different data sources
25%
Indicator 5.2: International data from DHS + MICS;
Country data from administrative records
Different methodologies
22%
Indicator 1.1: World Bank adjusted data to account
for low survey coverage, Country did not
Data not collected or compiled
by NSO
22%
Indicator 6.9 : Tuberculosis
incidence/prevalence/death rates not available in
NSO
Different definitions
20%
Indicator 5.2: Different definitions of skilled
International
comparability
personnel
Different population estimates
7%
Indicator 2.1: International data used UNPD
estimates, country used NSO population estimates
More data available at country
level than at international level
5%
Indicator 1.1: Population below national poverty
line-Country has more recent data
Data sources
Country data
International data
Country and international data
40 countries
Features
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MDG indicators
Charts and tables
Discrepancies with explanations
Summary table
Download
UNSD approach to address data discrepancies
1. Consultation with national statistical offices
• Workshops with national and international statisticians
to review data gaps, identify causes and reconcile
inconsistencies
• Since 2008
• Covered more than 60 countries
2. Transparency of data sources and
methodologies used
• MDG Global database and website completely
redesigned to include metadata specifying sources
and methodologies for all data
UNSD approach to address data discrepancies
3. Use of existing official statistics
• Initiatives focusing on data transfer mechanisms to
improve data compilation at the country level and data
transferring to the international community
i. Adoption of SDMX for MDGs indicators within
IAEG members
ii. Ongoing projects to “Improve the Compilation and
Dissemination of National Development Indicators,
including MDGs”
UNSD Long term approach to address data
discrepancies
• Promoting use of national official statistics by
improving:
• Accessibility/searchability of data to facilitate easy
access to statistical information
• Dissemination/communication (reporting) of data to
increase the use/understanding of national statistics
among the widest audience possible
How
1. Implementing a country data platform, on the basis of
existing software, that centralizes country indicators agreed
by national data stakeholders
2. Linking country platforms to UNdata via SDMX protocol,
when possible
3. Improving metadata information provided to users (in
electronic + printed publications) - preparing metadata
handbooks for development indicators
In summary what UNSD is doing to address
data discrepancies
•
Different data sources
Workshops
•
Different methodologies
Extensive
metadata
•
Different definitions
Data not collected or
compiled by NSO
•
Improving
transparency
Projects
Improving
Coordination
within NSS
•
More data at country level
Projects
Improving data
Transfer nat/int
•
Different population estimates
For international
comparisons