Public Expenditure Tracking Survey in Education 2006
Madagascar, 2006
Created on
Apr 25, 2019
Last modified
Apr 25, 2019
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Identification
Survey ID Number
MDG_2006_PETSEr1_v01_M
Title
Public Expenditure Tracking Survey in Education 2006
Subtitle
First Round
Country
| Name | Country code |
|---|---|
| Madagascar | MDG |
Study type
Public Expenditure Tracking Survey (PETS)
Series Information
A Public Expenditure Tracking Survey (PETS) is a diagnostic tool used to study the flow of public funds from the center to service providers. It has successfully been applied in many countries around the world where public accounting systems function poorly or provide unreliable information. The PETS has proven to be a useful tool to identify and quantify the leakage of funds. The PETS has also served as an analytical tool for understanding the causes underlying problems, so that informed policies can be developed. Finally, PETS results have successfully been used to improve transparency and accountability by supporting "power of information" campaigns.
PETS are often combined with Quantitative Service Delivery Surveys (QSDS) in order to obtain a more complete picture of the efficiency and equity of a public allocation system, activities at the provider level, as well as various agents involved in the process of service delivery.
While most of PETS and QSDS have been conducted in the health and education sectors, a few have also covered other sectors, such as justice, Early Childhood Programs, water, agriculture, and rural roads.
In the past decade, about 40 PETS and QSDS have been implemented in about 30 countries. While a large majority of these surveys have been conducted in Africa, which currently accounts for 66 percent of the total number of studies, PETS/QSDS have been implemented in all six regions of the World Bank (East Asia and Pacific, Europe and Central Asia, Latin America and Caribbean, Middle East and North Africa, South Asia and Sub-Saharan Africa).
PETS are often combined with Quantitative Service Delivery Surveys (QSDS) in order to obtain a more complete picture of the efficiency and equity of a public allocation system, activities at the provider level, as well as various agents involved in the process of service delivery.
While most of PETS and QSDS have been conducted in the health and education sectors, a few have also covered other sectors, such as justice, Early Childhood Programs, water, agriculture, and rural roads.
In the past decade, about 40 PETS and QSDS have been implemented in about 30 countries. While a large majority of these surveys have been conducted in Africa, which currently accounts for 66 percent of the total number of studies, PETS/QSDS have been implemented in all six regions of the World Bank (East Asia and Pacific, Europe and Central Asia, Latin America and Caribbean, Middle East and North Africa, South Asia and Sub-Saharan Africa).
Abstract
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.
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]
Unit of Analysis
- Cisco (Circonscription Scolaire/District Education Facility);
- Schools;
- School Principals;
- Teachers.
- Schools;
- School Principals;
- Teachers.
Version
Version Description
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.
The second file, the "final" data file, has been reviewed in order to ensure consistency both within and across single observations. While the sanctity of data is paramount, such that no changes are made if it cannot be asserted that the edited value is closer to the "true" value than the previous entry, data edits are introduced into the final data set. The list of edits applied are listed in the available Stata 10 © do-file associated with each data set. Furthermore, each do-file includes other tests that were applied to the data set. In addition, basic statistical analysis is applied to variables in order to identify potential statistical outliers. Outlier values that cannot be explained are replaced by missing values in the "final" data set; these changes are reported both in the do-file and in the Data Quality Report.
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.
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.
The second file, the "final" data file, has been reviewed in order to ensure consistency both within and across single observations. While the sanctity of data is paramount, such that no changes are made if it cannot be asserted that the edited value is closer to the "true" value than the previous entry, data edits are introduced into the final data set. The list of edits applied are listed in the available Stata 10 © do-file associated with each data set. Furthermore, each do-file includes other tests that were applied to the data set. In addition, basic statistical analysis is applied to variables in order to identify potential statistical outliers. Outlier values that cannot be explained are replaced by missing values in the "final" data set; these changes are reported both in the do-file and in the Data Quality Report.
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.
Scope
Notes
The scope of the study includes:
Tuition fees (caisse école), school kits, school equipment, parents-teachers association (FRAM), teachers' salaries, teacher characteristics, director characteristics, school characteristics, commune characteristics, Cisco (Circonscription Scolaire/District Education Facility), allocation of government teachers, monitoring and inspection.
Tuition fees (caisse école), school kits, school equipment, parents-teachers association (FRAM), teachers' salaries, teacher characteristics, director characteristics, school characteristics, commune characteristics, Cisco (Circonscription Scolaire/District Education Facility), allocation of government teachers, monitoring and inspection.
Topics
| Topic | Vocabulary |
|---|---|
| Primary Education | World Bank |
Coverage
Geographic Coverage
Provinces: Antananarivo, Fianarantsoa, Toamasina, Mahajanga, Toliara and Antsiranana.
Producers and sponsors
Primary investigators
| Name |
|---|
| World Bank |
| UNICEF |
| Ministere de L’education Nationale et de la Recherche Scientifique |
Sampling
Sampling Procedure
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 the First Round, 252 schools were visited. Six percent of the visited schools were closed at the time of the survey and researchers ended up with reliable data on 238 schools.
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.
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 the First Round, 252 schools were visited. Six percent of the visited schools were closed at the time of the survey and researchers ended up with reliable data on 238 schools.
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.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2006-10 | 2006-11 |
Data Collection Mode
Face-to-face [f2f]
Questionnaires
Questionnaires
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.
- 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.
Data Processing
Data Editing
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.
STATA cleaning do-files and data quality reports can also be found in external resources.
Access policy
Contacts
| Name | Affiliation | |
|---|---|---|
| Hooman Dabidian | World Bank | hdabidian@worldbank.org |
| Cindy Audiguier | World Bank | caudiguier@worldbank.org |
Access conditions
Public use file
Citation requirements
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 online).
Example:
World Bank, UNICEF, Ministere de L’education Nationale et de la Recherche Scientifique. Public Expenditure Tracking Survey in Education, First Round (PETSEr1) 2006. Ref. MDG_2006_PETSEr1_v01_M. Dataset downloaded from http://microdata.worldbank.org on [date].
- 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 online).
Example:
World Bank, UNICEF, Ministere de L’education Nationale et de la Recherche Scientifique. Public Expenditure Tracking Survey in Education, First Round (PETSEr1) 2006. Ref. MDG_2006_PETSEr1_v01_M. Dataset downloaded from http://microdata.worldbank.org on [date].
Disclaimer and copyrights
Disclaimer
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.
Metadata production
DDI Document ID
DDI_MDG_2006_PETSEr1_v01_M
Producers
| Name | Affiliation | Role |
|---|---|---|
| Antonina Redko | DECDG, World Bank | DDI documentation |
Date of Metadata Production
2011-08-04
DDI Document version
v01 (August, 2011)