Identifying and understanding the variables necessary for the analysis

The second step is to identify and understand all the variables which will be necessary for the estimation of averages per student� When doing so, it will be important to classify those variables (and in some cases merge them) so that they fit, as closely as possible, the NEA classification, since, ultimately, the data will need to be integrated with data on other sources of education funding (government and rest of the world)� This can be a challenge, since, often, the variables in the survey will not have been defined for this purpose, and the categories may be hard to match� When choosing how to treat the variables, a trade-off should be considered between the level of detail desired and the need for an acceptable sample size for each sub-group considered�

For example, there may be three types of private school in a country, which may be interesting to consider separately� However, if a sub-category is created for each, the number of observations may become too small to be valid� In such cases, it is advised to merge the three and create a new ‘private schools’ variable in the database before extracting the averages�

Having a printed questionnaire of the survey at hand can also be helpful� In fact, survey datasets do not have all the details necessary for data processing, while survey questionnaires usually include the coding definition of each variable and the corresponding question�

2.1 Type of expenditure

Each household survey will include a distinct list of questions on the type of education expenditure incurred by respondents, although they normally have some common features� To match the NEA classification and to prepare the data for eventual international comparison, the survey variables (questions asked) should, at a minimum, be grouped into the following two sub-groups:

1� Household payments to educational institutions,

which should include the following (which may or may not constitute additional categories, depending on survey questions, national interest, and consequent sample size in the sub-group):

i� tuition fees;

ii� other fees charged for educational services

(such as registration fees, laboratory fees, or examination fees);

iii� fees paid for ancillary services provided to

students by educational institutions, such as for board/student housing, meals, health services;

iv� contributions to PTAs, school-management

committees (SMCs), or any sort of ‘school fund’ or ‘parent contribution fund’ paid to the school�

2� Household payments for education goods and

services purchased outside educational institutions,

which are the ‘connected products’ as described in Chapter 2 of the NEA methodological guidelines� These include two main sub-groups:

a� Payments required for school attendance, for

example:

i� school uniforms and other required clothing;

ii� school books and teaching materials;

iii� other required purchases, such as athletic

equipment, materials for arts lessons, and so forth�

b� Payments not required for school attendance,

but nonetheless linked to participation in the

education programme, for example:

i� extra classes or private tuition linked to the

official curriculum;

ii� transport to and from school or canteen fees

where these services are not provided through educational institutions;

iii�additional books or computer or learning

software to be used at home in support of schooling�

The criteria used to decide whether or not the expenditure should be included under ‘education expenditure’ should be whether the expenditure would have been incurred if the individual did not attend school. If the answer is ‘yes’, it

should probably be excluded (if possible)� For example, extra music, arts, language or other leisure classes not linked to the official curriculum should be excluded�

Table 1 illustrates how the ‘type of expenditure’ variable

in three different surveys can be fitted into these common categories� In practice, it may be very difficult to match the categories exactly into the above definitions, as this is not how household questions are designed� Best efforts should, however, be made, using the available information� There are three things to note about the examples in Table 1:

1) The basket of goods included is not the same in all

three countries, illustrating problems of comparability� For example, there is no clear reference to food, meals, or canteen fees in the Viet Nam survey, as opposed to Nepal and Côte d’Ivoire�

2) Some items appear on their own in some surveys,

and as part of a broader ‘other’ group in others (e�g� transport)�

3) There are ‘other expenses’ categories, not very well

defined and including different groups of items�

q

Minimum/ common set of questions

Household expenditure

in educational institutions Household expenditure outside educational institutions ‘Other’categoriestoreassignorleave out

Goodsandservicesrequiredfor

schoolattendance Goodsandservicesnotrequiredforschoolattendance Uniforms

andother school clothing

Textbooksandschool

supplies Privatetutoring Canteenandtransporttoschool purchasedoutsideof institutions Othernot required (butlinked toschool attendance) Tuitionandotherfees Ancillary feespaid toinstitutions (canteen, board, transport) Nepal Tuition

fees Otherfees(exams admission, events,etc.) Uniforms Textbooks and supplies Private

tuition Transport Others(snacks, tea,etc.)

Viet Nam Tuition

fees Contributiontoschool construction fund Parents’ fund, class fund Uniforms Textbooks and reference books Other educational materials Extra classes linkedto curriculum Other education costs (transport, lodging, etc.) Côte

d’Ivoire Tuitionfees Inscriptionandother fees

SMC

orPTA Uniforms,sports andother clothing Books andother teaching materials Private tuition, repetition, extra courses Transport Food, canteen, lodging Contribu- tionsto extra- curricular activities Identity documents required forschool attendance Other school expenses

ANNEXES

2.2 Level of education

The survey variables related to the grade or level of education in which the individual is currently enrolled (often in another section of the questionnaire) should be identified and assigned or merged to match the NEA classification� This should reflect the way the national education system is organized in the country in which the household survey is conducted, as well as being easily relatable to an ISCED level (see the ‘Level of education’ section of Chapter 3 in the main NEA guide)� When the survey classification is by grade rather than level, relevant grades should be merged together to form a new category/variable in the database� For example, grades 1 to 6 may correspond to primary education in a given country�

2.3 Producing unit (type of educational institution)

With regard to level of education, the type of institution currently attended by the individual should be identified and assigned or merged to match the NEA classification of producing units� This may mean merging some survey variables, especially if it increases the sub-group sample size (or the number of observations by sub-category)� At a minimum, institutions should be separated between public and private�

2.4 Background characteristics

Background characteristics such as gender, location, and economic status are provided by most surveys and may be worth having alongside education expenditure variables for further analysis, even if they are not necessarily required for estimations or for the NEA�

STEP 3: Identifying the sample in the sub-group and the