NAM_2003_PETSE_v01_M
PETS - QSDS in Education 2003
Name | Country code |
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Namibia | NAM |
Public Expenditure Tracking Survey (PETS)/Quantitative Service Delivery Survey (QSDS)
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).
After gaining independence in 1990, Namibia prioritized spending on social sectors such as education and health in order to address poverty and disparity in access to quality education and health care. The education and health sectors have received the highest budget allocations over the last three decades.
In order to understand effectiveness of budget expenditures in health and education sectors, the Namibian government decided to implement Public Expenditure Tracking Survey combined with Quantitative Service Delivery Survey in 2003. PETS methodology has been employed to evaluate the distribution and use of financial resources at the national, sub-national and frontline service provider levels. The QSDS goes beyond tracing of funds and tries to explore the determinants of poor service delivery.
The guiding hypothesis for the survey was an assumption that actual service delivery is much worse than budgetary allocations would imply, because public funds do not reach the intended facilities as expected. As the result outcomes cannot improve. To verify this hypothesis, a sample of schools and health facilities in seven of Namibia's thirteen regions was randomly selected. Questionnaires were developed to collect information from different levels within the education sector on the use of financial and human resources, and the availability of materials and equipment.
Documented here is the survey conducted in Namibia education sector. One hundred and thirteen public and private primary and secondary schools were surveyed. Extensive interviews were carried out with officials in regional offices, with school inspectors, principals, teachers, students and school board members.
Sample survey data [ssd]
Topic | Vocabulary |
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Education | World Bank |
Primary Education | World Bank |
Hardap, Kavango, Khomas, Kunene, Omaheke, Omusati and Oshana regions
Name |
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World Bank |
Ministry of Basic Education, Culture and Sport |
Name |
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Ministry of Finance |
National Planning Commission Secretariat |
Office of the Prime Minister |
Office of the Auditor General |
Name |
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World Bank |
A convenient sample of seven of Namibia's thirteen administrative regions was chosen for the survey. Hardap, Kavango, Khomas, Kunene, Omaheke, Omusati and Oshana regions were selected.
Once the regions were chosen, a representative sample of schools was randomly selected. The number of schools in each of the regions varied significantly. There were some 330 schools - primary, combined and secondary schools - in the Kavango region compared to 42 schools in the Omaheke region. In the larger regions, researchers selected between 7% and 10% of schools while in the smaller regions about 20%. Investigators did not distinguish between primary, combined and secondary schools but selected a random sample of the total number of schools.
A slightly different approach was chosen for the Khomas region where enumerators selected only schools in Windhoek: five schools of the central city and ten schools in the former townships of Khomasdal and Katutura.
In total, 109 public and seven private schools were randomly chosen for the survey.
Investigators covered 113 out of the sample of 116 schools and 23 of the 27 school inspectors.
Questionnaires were designed for a Ministry of Basic Education, Culture and Sport representative, directors of regional education offices, school inspectors, school principals or alternatively heads of department, teachers, students (head boy or head girl) and school board members who are not employed by the school (representing parents on school boards).
A pilot survey covering six schools (three in Windhoek, two in Okahandja and one in Groot-Aub for each sector) was carried out to test the questionnaires. The pilot survey did not indicate any major problem with the questionnaires. After a last round of discussions internally as well as with the Ministry of Basic Education, Culture and Sport, questionnaires were finalised.
Start | End |
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2003 | 2003 |
Name |
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Namibian Economic Policy Research Unit |
The project members were divided into five teams. Four teams started gathering data from Kavango region in 28 July 2003. One team remained in the Khomas region.
Each team consisted of one Namibian Economic Policy Research Unit (NEPRU) staff member and one or two enumerators. After being trained at NEPRU, enumerators received one-day refresher instructions when they joined the teams in the field. For interviewing school board members, the knowledge of local languages was essential.
One of the major challenges enumerators encountered during the survey - besides locating schools in remote areas - was the poor communication infrastructure. For instance, of the 26 schools sampled in Kavango region, only three had a telephone and a fax machine (one being a private school), another three had a telephone but no fax machine, while the rest had none. However, even schools and other institutions that had phones and fax machines often could not be contacted because the equipment was not working or in some areas, the telephone wires were stolen because of the copper content. Thus, except for the Windhoek region, schools and health facilities were usually not informed survey team visits and were not prepared. Subsequently, enumerators spent much more time at the facilities than planned to collect all the data and information needed. In addition, meetings with school board members had to be arranged ad hoc. This was hardly a problem in rural areas but it posed a challenge in Windhoek where parents are often employed and not readily available. Parents in Hardap region often work on commercial farms far away from schools and were therefore not available for interviews either.
Furthermore, records at service providers were generally poor or did not exist at all. Investigators had to count desks, chairs, textbooks and even ask students about drop-outs and repeaters. Researchers had to find innovative ways to extract pieces of information on financial matters because of the lack of records. Order forms for text books and stationery were not kept at schools, except for few schools that filed copies of them. Delivery notes for textbooks and other materials were also rarely available. That made it very difficult to compare what schools had ordered with what they actually received or what they should have received.
In many instances, team members had to return to the same institution more than once to collect missing information.
Public use file
The use of this survey must be acknowledged using a citation which would include:
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.
Name | Affiliation | |
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Hooman Dabidian | World Bank | hdabidian@worldbank.org |
Cindy Audiguier | World Bank | caudiguier@worldbank.org |
DDI_NAM_2003_PETSE_v01_M
Name | Affiliation | Role |
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Antonina Redko | DECDG, World Bank | DDI documentation |
2011-10-05
v01 (October 2011)