Public Expenditure Tracking Survey in Education 2007
Madagascar had low school enrollment rates: only 60% of the urban children and 12% of the rural children completed primary school (World Bank, 2002). To improve the enrollment and completion rates as well as the quality of education, Madagascar government had substantially increased investments in the education sector. It committed itself to the Education For All (EFA) initiative and started to fully subsidize the tuition fees through the so-called "caisse ecole," and to provide school kits for all students in public primary schools. The Government also raised the districts' budgets for school material and started distributing free textbooks to schools.
This study investigated the different resource flows in the financing of the public primary education sector in Madagascar.
The survey was conducted in two rounds. The first round was carried out in October-November 2006 and the second round in April-May 2007. The study was implemented using stratified random sampling. Data from more than 200 schools in 28 districts was analyzed.
Public Expenditure Tracking Survey among Madagascar health care facilities and workers was conducted at the same time with PETS in Education.
Kind of data
Sample survey data [ssd]
v01 - Final, edited datasets.
Documented here are final, cleaned datasets prepared by the World Bank based on raw datasets provided by the study researchers.
The description of the difference between raw and edited datasets is taken from "Data Cleaning Guide for PETS/QSDS Surveys" (p.10):
"Each country set includes two data files. The first file, the "raw" data file, presents the data as collected and entered by the survey teams. While field teams do conduct very high-level coherence tests with regards to responses collected, the data contained therein has generally not been thoroughly checked for internal coherence across questions, variable outliers and other such involved data cleaning procedures.
Finally, independently of the values presented in the questionnaires, missing values are replaced across all "final" data sets to ensure consistency across countries. Following industry best practices, negative 3-digit integers are used in order to ensure there is no confusion between missing values and valid data points. "
"Data Cleaning Guide for PETS/QSDS Surveys" is available in external resources.
Provinces: Antananarivo, Fianarantsoa, Toamasina, Mahajanga, Toliara and Antsiranana.
Ministere de L’education Nationale et de la Recherche Scientifique
The study was conducted using stratified random sampling.
The stratified sample was set up in such a way to be representative at the national level. Madagascar has 22 regions and 111 districts, and at least one district was visited in each region. Two districts were selected in the six largest regions. Hence, 28 districts were visited in total. The selected districts were obtained through random selection, giving greater (less) weight to districts with more (less) public primary schools within the district. In each district, three communes were randomly selected, giving greater weight to the communes with more schools. Within each commune, three public primary schools were randomly selected. By ranking schools from large to small and ensuring that a school was picked out of each tercile, a representative sample of school sizes was chosen.
In order to track different resource flows from the decentralized district facility levels to the schools, surveys were organized at district and school levels. At the local level, the directors of the education facility as well as teachers were interviewed independently. To ensure compatibility, the surveys at district and school levels were held at the same time.
In total, 252 schools were visited. Due to closure of some schools during either the first or the second round (or both rounds), researchers ended up with reliable panel data on 229 schools. Finally, it is noteworthy that the second round of data collection faced greater challenges to collect the data and therefore results were less robust for the second round. (For example, researchers faced mismatching codes for some schools and health centers as well as personnel codes between both rounds; there were a lot of blank entries on school equipment and other line items in the second round, and there were more cases where collected information on certain budgets did not add up to the total of those budgets as reported by the enumerators in the second round).
Overall, in the province of Antananarivo 54 schools were visited, 63 schools were visited in Fianarantsoa, 36 - in Toamasina, 45 - in Mahajanga, 36 - in Toliara and 18 - in Antsiranana.
Dates of collection
Mode of data collection
The following survey instruments are available:
- Enquête Au Niveau Des Établissements Scolaires, Enquete Cisco;
- Enquête Au Niveau Des Établissements Scolaires, Enquete Directeur Ecole, Visite 1er Jour;
- Enquête Au Niveau Des Établissements Scolaires, Enquete Directeur Ecole, Visite 2ème Jour;
- Enquête Au Niveau Des Établissements Scolaires, Enquete Enseignant.
Detailed information about data editing procedures is available in "Data Cleaning Guide for PETS/QSDS Surveys" in external resources.
STATA cleaning do-files and data quality reports can also be found in external resources.
Public use file
The use of this dataset must be acknowledged using a citation which would include:
- the identification of the Primary Investigator (including country name)
- the full title of the survey and its acronym (when available), and the year(s) of implementation
- the survey reference number
- the source and date of download (for datasets disseminated on-line)
World Bank, UNICEF, Ministere de L’education Nationale et de la Recherche Scientifique. Public Expenditure Tracking Survey in Education, Second Round (PETSEr2) 2007. Ref. MDG_2007_PETSEr2_v01_M. Dataset downloaded from http://microdata.worldbank.org on [date].
Disclaimer and copyrights
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.