Sri Lanka - Institut de statistique de l'Unesco

Out-of-School Children in Sri Lanka: Country Study
CHAPTER 2:
PROFILES OF EXCLUDED CHILDREN
Based on procedures defined in the CMF, this chapter uses household surveys and
administrative data sources to determine (i) how many children are out of school; (ii) which
children are out of school; and (iii) which children are at risk of exclusion.
2.1 Sources of data
Various sources of data were considered for this study. The last population census was not used,
as it was conducted in 2001 and it was felt that the data would not be sufficiently up to date. Data
from the 2011 census, which covered the whole country, are still being processed and analysed,
so results were not yet available for use in this study.
The report of the DCS’s Household Income and Expenditure Survey (HIES) 2009/10 was
published in August 2011 and provides relevant data on households, income, poverty, school
attendance and non-attendance. The HIES is a year-long sample survey, which is conducted in
12 consecutive monthly rounds, and an island-wide representative sample of equal size is
enumerated in each monthly round to capture seasonal and regional variations of income,
expenditure and consumption patterns. This data source has been used for comparison and
corroboration, wherever relevant, but is not the main source of data as the final report had not
been released when the study was begun. It must also be mentioned that the three districts of
Mannar, Kilinochchi and Mullaitivu in Northern Province were excluded from the HIES, as they
could not be reached during the 26 years of armed conflict.
The most recent and relevant data source, therefore, is the Demographic and Health Survey
(DHS) 2006/07 4 , which has data disaggregated by sex, residential sector and wealth quintile. The
sample for the DHS 2006/07 covered 18,000 children (weighted), with 50 percent males and 50
percent females. Data on the age of children has been adjusted by one year for this study, as the
DHS was conducted 9–10 months after the start of the school year. This follows the standard
practice used by UNICEF for analysis of its Multiple Indicator Cluster Survey (MICS)—when the
gap between the start of the academic year and the survey collection period is greater than six
months, age data are adjusted by one year in order to minimize errors in this regard. UIS also
adheres to this practice. Put simply, children were not likely to be the same age at the time of the
DHS interview as they were at the start of the school year up to 10 months earlier.
It must be noted that data were not collected from the five districts (Jaffna, Kilinochchi, Mannar,
Vavuniya and Mullaitivu) of the conflict-affected Northern Province, as data gatherers from the
DHS had no access to these districts at the time. Unfortunately, this has implications for the
results of this study, as figures will under-represent conflict-affected regions where it is known that
schooling has been heavily impacted. Therefore, it is important to bear in mind when analysing
these national figures that they are indicative only, and that levels of enrolment, attendance,
retention and achievement are probably lower and levels of non-enrolment and dropout are
probably higher. It is also argued that the conflict has differently impacted girls and boys, so
sex-disaggregated data may also be distorted. Disaggregation by wealth quintile and information
on child labour are also likely to under-represent the impact of the conflict on the education of
children from poor and vulnerable households.
4
It should be noted that datasets from the DHS 2006/07 are not available in the public domain. They were obtained for this study from the
Department of Census and Statistics. See Annex 1.
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