Presentation on theme: "2A. Counting and Locating Constructing a sampling frame Wednesday 1 st October."— Presentation transcript:
2A. Counting and Locating Constructing a sampling frame Wednesday 1 st October
Basic Demographics Fifteen year olds are a very small proportion of total population Average number of households to be visited to find one 15 year old = 10 (except Senegal) Average density of 15 year olds per square kilometre = <2 (except 3 in Guatemala) DHS estimates of same order of magnitude, except for Cambodia, Tanzania and Zambia
Low Birth Registration and Age Heaping In LA countries birth registration are above 90% (judged to be complete registration) Among other countries, low in Tanzania (16%) and Zambia (14%) Demographers have shown that both caregivers and respondents tend to give ages to nearest 5 or 10 years to interviewer The most pronounced deviations are at age 10 for Cambodia, Tanzania and Zambia and age 20 for Senegal. The effect at age 15 is small but should be considered at analysis stage
Current Definitions of Out of School CREATE defined 6 zones of exclusion from Primary and Lower Secondary UIS and UNICEF defined 5 Dimensions of Exclusion based on age rather than grade Neither approach addresses problem of defining current status vis-à-vis school Both CREATE and UIS/UNICEF are based on rights of children to a basic education and so are ‘school based’ in sense that school defines whether or not child is registered is enrolled and currently attending sufficiently to be counting as not having dropped out
Survey Definitions Current questions in DHS and MICS surveys leave judgement as to whether 15 year old is currently attending to the respondent themselves Obviously subjective and contextual questionnaire needs to robe more deeply within constraints of questionnaire length Also surveys responses are not based on actual current attendance but on whether or not the 15 year old has attended school at some time in the year
Alternative Education Programme Need to decide how to treat Accelerated Learning Programmes including NGO-provided NFE programmes and some apprenticeships How should religious education be treated How can contextual questionnaire be detailed and comprehensive so as to capture the whole range of NFE and religious education within the time constraints
Age 15TotalUrbanRural Brazil Cambodia Ecuador Guatemala Senegal Tanzania Zambia In school: variation across countries Source: UNESCO, EFA GMR
By grade Below Above 10 Brazil Cambodia Ecuador Guatemala Senegal Tanzania Zambia In school by grade: variation across countries Source: UNESCO, EFA GMR
Out of school: Never been to school Incomplete primary Complete primary or higher Brazil63163 Cambodia747 Ecuador9883 Guatemala Senegal70265 Tanzania Zambia Out of school variation across countries Source: UNESCO, EFA GMR
Groups omitted or systematically under-represented in survey data Sampling Frames based on sometimes very out-of-date censuses Household surveys exclude, by design: the homeless those in institutions: – hospitals, prisons, refugee camps the mobile: – Nomads, pastoralists, travellers.
Groups Omitted or Systematically Uncounted in Survey Data (B) In practice, they tend to exclude those in fragile, disjointed households, those in urban slums and those in insecure areas – This will also be a problem for in-school assessment Those six categories constitute a pretty good ostensive definition of the poorest of the poor There are two other groups of adults and children who may be ‘hidden’ in households: Those who are illegally resident Those who suffer discrimination e.g. disabled
Approach to Counting To complement the approach of a standard household survey, we need to search actively for marginalised or vulnerable groups likely to include OOS 15 year olds Given unknown errors in age-specific population & unreliability of enrolment data, we cannot count OOS numbers by subtraction of enrolment figures form population figures Most marginalised will be found among (isolated) rural poor and informal settlements
Using household surveys to count and locate OOS 15 year olds Estimates can be made of percentages likely to be missing from sampling frames of standard household surveys in rural and urban areas This can be combined with assumptions about how additional numbers would be divided between out-of-school groups
Difficulties in counting OOS 15 year olds Several data sources, e.g.: International administrative routine data with issues of coverage, accuracy, timeliness Standardised Household Surveys, with problems of coverage of marginalised groups Used standardised household surveys because they are comparable
Questions for discussion What is our cohort? year olds? What is an out of school 15 year old? Is our picture correct? Where are out-of-school 15 year olds? How do we construct the sample frame? What is an appropriate ambition for PISA-D?