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Use of Census and Administrative Data in Monitoring of
Education Indicators – an international perspective
Said Ould Voffal
UNESCO Institute for Statistics
Kampala, May 2008
UNESCO Institute for
Statistics
• Mission: UIS is responsible for the collection, analysis and
dissemination of statistics; and to promote the use of
international statistics – source of internationally comparable data
Education Statistics
Science and
Literacy Statistics
International Data Repository
Technology
Culture and
Communication
Adult Education
Literacy Assessment and Monitoring Programme (LAMP)
Main users of UIS data
UNESCO
– Global Education Digest (UIS)
– EFA – Education For All annual report
– Women in Science
WORLD BANK – World Development Indicators
UNSD – Millennium Development Goals
UNDP – Human Development Report
UNICEF – State of the World’s Children
USAID
UNFPA
WHO
Researchers, companies and students
Most agencies request the information between January and
March of each year.
UIS - How does UIS Maintain
Internationally Comparable Statistics?
• Same data collection instruments for all countries
• Standardized definitions and formulas
• ISCED to classify programmes – and to maintain
international comparability of indicators e.g.
Ethiopia, Kenya, Malawi (8 grades nationally, but
6 grades internationally)
• Population estimates from the United Nations
Population Division for all countries
• Coverage – inclusion of all educational
institutions and groups in the data
Millennium Development Goals and
UIS Education Statistics and Indicators
Data collected from the annual UIS Education Statistics Survey Questionnaires are useful for
the production of relevant education indicators for the assessment of Millennium
Development Goals 2 and 3.
Millennium Development Goal
Education Statistics Indicators
2.1 : Net Enrollment Ratio in Primary
Education
2.2 : Survival Rate to last Grade in
Primary
2.3: Literacy rates of 15 – 24 year
olds
Background indicator: Primary gross
ACHIEVE UNIVERSAL PRIMARY
EDUCATION BY 2015 > Goal 2
completion rate
1
2
PROMOTE GENDER EQUALITY AND
EMPOWER WOMEN > Goal 3
1) Gender Parity Index in Primary
Education
MDG-EFA education indicators
• Education-related MDG indicators are a
subset of the EFA ones
 Improving data quality for EFA means
improving also quality for MDG
Raw data required for
calculating UIS-MDG indicators
• Enrolment by age/grade/gender for
primary education (ISCED 1) : Collected
by UIS from countries
• Data on repeaters by grade/gender for
primary education : collected by UIS from
countries
• Demographic data (provided by UNPD)
Data Source
• Mainly administrative data provided by countries
from their annual school census by Ministry of
education
• Literacy data collected by NSOs in censuses
• We collect raw data which we use to calculate
indicators: to maintain comparability in
methodology
UIS annual data collection
• UIS sends each questionnaires to all
all countries around the world
• UIS organizes trainings, workshop,
capacity buildings programmes on
education statistics and regional
represenation in all regions.
Indicator 2.1: total primary net
enrolment ratio
• Definition: number of children of primary
(ISCED 1) age enrolled either in primary or
lower secondary expressed as % of primary
school-age population.
• Sources of discrepancies between
international sources:
 Different definitions of primary education nationally
and internationally (eg : Ethiopia, Kenya and Malawi)
 Differences between population data used nationnally
and internationnally
 Coverage issues (like private education)
Quality issues for indicator 2.1
• Reliability problems of the age of children :
in many cases, ages are based on parent
declaration
• The date of reference for age is not always
the right one
Availability of administrative
data for calculating indicator 2.1
• Globally, indicator is calculated for 140
countries (around 67 %)
• For this group of countries: 14 countries
out of 19 (74%) have provided data each
year during the period for the year 20002006. Better than the World average!
Indicator 2.1
Provided AGE data are not published for:
Cameroon: Data by age not reliable
Liberia : no data provided between 2000-2005
Uganda : due to confirmed misreporting of AGE data at
the sub-national levels,
Sierra Leone : misreporting of age data at the subnational levels.
Indicator 2.2 : Survival rate to primary
last grade
• Definition
The proportion of pupils starting grade 1 who reach last
grade of primary education. Known as the Survival Rate
to last Grade of primary.
• Sources of discrepancies between global
and national figures:
 Country figures may differ from the international ones
because of differences between the national
education system and ISCED97. Also coverage data
(e.g :including adult education)
Indicator 2.2
• Problem of reliability of data on repeaters
due the fact that when repeaters change
school they may not be recorded as
repeaters.
Indicator 2.2: Data availability
1.
11 out of 19 countries (58%) have reported consistent
primary data by grade grade of Primary during 2000 – 2007.
2.
For countries such as Ghana, South Africa, Uganda, Zambia and
Kenya, it is observed that marked differences in repetition
by grade exist (especially at Grade 1 of Primary) over at least
6 years without feedback/validation from countries during the
country review process; and partial or missing data for the
same period.
3.
Missing data in the above countries is probably due to the
design of national data collection instruments, or
inconsistent reporting between years.
.
Main Data Quality Issues (by country –
primary education)
COUNTRY
MAIN DATA QUALITY ISSUES
Year of Most Recent Admin. Data
Botswana
Data coverage is comprehensive
2005
Ethiopia
Data coverage is comprehensive
2007
Ghana
Repetition by Grade
2007
Kenya
Repetition by Grade
2006
Lesotho
Data coverage is comprehensive
2006
Liberia
Post - Conflict Country
2006
Malawi
Quality of Age Data
2006
Mauritius
Data coverage is comprehensive
2006
Mozambique
Data coverage is comprehensive
2006
Namibia
Data coverage is comprehensive
2006
Sierra Leone
Post - Conflict Country
2007
South Africa
Quality of Age Data
2004
Swaziland
Data coverage is comprehensive
2005
Uganda
Quality of Age Data
2006
Tanzania
Data coverage is comprehensive
2007
Zambia
Quality of Age Data
2006
Zimbabwe
Inconsistent reporting to UIS
2006
What UIS is doing to improve the
Quality and Coverage of Data?
• Conducts annual country review process –
feedback of related education Statistics to MOE
national statisticians – 50% of countries respond
to the country review process.
• Conducts regional education statistics workshops
every two years to improve coverage, review
overall data quality, and complete data gaps
(Ghana, 2005) Tanzania (2007), South Africa
(2003)
• Conducts site visits to countries for specific data
quality assessment activities (Uganda, 2005)
Kenya and Tanzania (2004)
What UIS is doing to improve the
Quality and Coverage of Data?
• Engages UIS regional and statistical
advisors to follow-up on data gaps and
improve overall quality of data
disseminated by the UIS and related
Statistical Capacity building (based in
Sierra Leone, Ethiopia, Tanzania, Ghana
and Senegal)
• Continual research activities and
comparison of secondary sources of data
e.g. household surveys, MICS etc
• Continually improving methodology to
analyze data
The way forward………………..
•
•
UIS has selected an initial 9 priority
countries based on a data gap
analysis of 1999 – 2006 reported data,
and an assessment of data coverage
and quality for sub-Saharan Africa to
initialize a strategy to improve data
quality in Sub-Saharan Africa - these
include Gambia, Liberia, Malawi, Sierra
Leone, South Africa, Zimbabwe,
Uganda, Zambia, Nigeria
In collaboration with UIS regional
advisors, UNESCO Pole de Dakar and
Ministries of Education, the following
activities are envisaged:
Country
Activity
Partner
Malawi
RESEN activity
anticipated in
February - March
2009
Pole de Dakar
Nigeria
RESEN activities
anticipated in at
least 3 states in
2009
Pole de Dakar, MOE
Sierra Leone
Continual
improvement of
coverage of data
and private
institutions
UIS Regional
Advisor, MOE
South Africa
Country to consider
further analysis
of households
data to validate
data by age from
admin. Sur
Department of
Education
Uganda
Final rollout of UIS
EMIS tool to
promote
longitudinal
analysis of data March 2008
UIS Regional
Advisor, MOE