Expenditure and Service Delivery Survey in Education 2002
Zambia, 2002
Get MicrodataIdentification
ZMB_2002_ESDS_v01_M
Expenditure and Service Delivery Survey in Education 2002
| Name | Country code |
|---|---|
| Zambia | ZMB |
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).
Documented here are datasets covering schools, Provincial Education Offices (PEO) and District Education Offices (DEO).
Education expenditures in Zambia (apart from teacher salaries) are distributed through an administrative hierarchy consisting of PEOs and DEOs. The survey data contain a detailed tracking of resources allocated by the government through this hierarchy to schools. Approaches of public expenditure tracking surveys (PETS) and quantitative service delivery surveys (QSDS) are integrated in this study.
The study was carried out by the Government of Zambia and the World Bank. It covered 184 primary (grades 1-7) and basic (grades 1-9) schools, 33 DEOs and four PEOs in four provinces: Lusaka, Copperbelt, Northern, and Eastern.
Sample survey data [ssd]
- District Education Offices;
- Provincial Education Offices;
- Schools;
- Teachers;
- Head-Teachers;
- Students.
Version
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.
Scope
The scope of the study includes:
-
District Education Offices (DEO): demographics of DEO, characteristics of DEO, decision process, shortages and requests, school visits, complaints, meetings with PEO/Ministry of Education representatives, funding, expenditures in the last month, receipts by schools.
-
Provincial Education Offices (PEO): demographics of PEO, characteristics of PEO, decision process, shortages and requests, school visits, complaints, meetings with Ministry of Education representatives, funding, expenditures in the last month, receipts by district and by schools.
-
Schools: characteristics of schools (type, special programs, number of students, alternative schools), characteristics of students (ethnic groups, where do children come from), facilities, school location, enrolment, grade repetition, dropouts, reasons for dropouts, school finances and sources of support, payment of fees, external funding, educational materials, and use of funds.
-
Head-Teachers: demographics, characteristics of head-teachers, remuneration of head-teachers, teacher absenteeism and turnover, students' attendance, DEO/PEO contacts and visits, Parent-Teacher Association (PTA) activities and fees, decision process, shortages and requests.
-
Teachers: demographics, characteristics of teachers, remuneration of teachers, and classroom facilities.
| Topic | Vocabulary |
|---|---|
| Primary Education | World Bank |
| Secondary Education | World Bank |
Coverage
Lusaka, Copperbelt, Northern, and Eastern provinces.
Producers and sponsors
| Name |
|---|
| Government of the Republic of Zambia |
| World Bank |
| Name |
|---|
| UK Department for International Development |
Sampling
A random sample stratified on the basis of urban and rural locations included 184 schools in 33 districts. The schools surveyed were chosen from a frame of primary (grades 1-7) and basic (grades 1-9) schools in four Zambian provinces: Lusaka, Copperbelt, Northern, and Eastern. The choice of these four provinces was dictated primarily by the variation in educational attainments, regional incomes, and administrative structures. Specifically, Lusaka and Copperbelt are the two richest provinces in Zambia, with high enrollment rates, and Northern and Eastern provinces are the poorest, with enrollment rates only marginally better than the worst performing Central province.
Since this study is linked to 2001 National Assessment Survey (NAS), the choice of schools in the sample was restricted by the sampling methodology of the NAS. The NAS sampling was based on a probability-proportional to size methodology. For this study, researchers surveyed about half the schools covered in NAS 2001. For details on sampling methodology, please refer to "Zambia ESDS 2002 Sampling Note " in external resources.
Survey instrument
The following survey instruments are available:
- District Education Office Questionnaire (Part I)
- District Education Office Questionnaire (Part II)
- Provincial Education Office Questionnaire (Part I)
- Provincial Education Office Questionnaire (Part II)
- General School Questionnaire
- Teacher Roster Card
- Head-Teacher Questionnaire
- Teacher Questionnaire, Grades I-VI
- Head-Teacher Matching Roster
- Pupil Matching Roster.
The Teacher Questionnaire was designed to examine two sorts of inputs that may impact on the performance of a teacher: first are the teacher-inputs such as demographic and educational characteristics and second are institutional inputs (primarily teacher salaries). The teacher questionnaire thus focuses on obtaining a basic demographic and educational profile of the teacher, and then moves on to asking about salary and allowances, as well as delays in the receipt of payments.
The Head-Teacher Questionnaire starts with the same sections as the teacher questionnaire. Several additional sections then probe the characteristics of teachers, pupils, parents (through the PTA section) and the administrative structure (through the Relationship with DEO/PEO sections). Finally the head-teacher questionnaire also contains a section on decisions and shortages, where we try to understand the nature of the financial constraints that schools are operating under.
The General School Questionnaire has a three-fold purpose. First, researchers believed that school infrastructure and location themselves may be important for learning achievement; the first few sections of this questionnaire thus systematically ask about the availability and condition of infrastructure in the school. Second, the questionnaire examines the characteristics of the student population in the school such as the overall profile of attendance and grade-repetition. Finally, the questionnaire links to the DEO/PEO questionnaire to complete the Public Expenditure Tracking exercise. To enable researchers to track the flow of resources, the questionnaire then asks about the receipt of resources from other levels of the administration such as the DEO and the PEO's offices.
The District Education Office and Provincial Education Office Questionnaires like the General School and the Head-Teacher Questionnaires, are designed to address two different components of the survey. Part II is concerned with the tracking of public expenditure-how much do the DEO and PEO offices receive? What are the primary expenses in these offices? Part I is similar in form to the head-teacher questionnaire, and asks about the demographic and educational characteristics of the DEO/PEO, before moving on to examine the views of the DEO on their relationship with schools (through visits and inspections) and the overall educational administration.
Head-Teacher Matching Roster and Pupil Matching Roster were designed to match students, who were tested in math and English and other subjects in 2001 and 2002, with teachers, and to carefully identify the changes that could have potentially affected students during the last year. The datasets documented here do not include test scores.
Data collection
| Start | End |
|---|---|
| 2002-05 | 2002-06 |
It is necessary to distinguish between provinces with and without district education boards. Although districts receive money directly from the government, both for rule-based and discretionary allocations, all money for discretionary allocations is first transferred to the concerned province, and from there moves onward to the district. For this reason, provinces with district education boards are referred to as decentralized provinces and those without district education boards are referred to as centralized provinces. In the study sample there are two of each: Lusaka and
Copperbelt provinces are decentralized and Northern and Eastern province are centralized.
Data processing
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.
Data Access
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 online).
Example:
Government of the Republic of Zambia and World Bank. Expenditure and Service Delivery Survey in Education (ESDS) 2002. Ref. ZMB_2002_ESDS_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.
Contacts
| Name | Affiliation | |
|---|---|---|
| Hooman Dabidian | World Bank | hdabidian@worldbank.org |
| Cindy Audiguier | World Bank | caudiguier@worldbank.org |
Metadata production
DDI_ZMB_2002_ESDS_v01_M
| Name | Affiliation | Role |
|---|---|---|
| Antonina Redko | DECDG, World Bank | DDI documentation |
2011-09-06
Metadata version
v01 (September, 2011)