Public Expenditure Tracking Survey in Education 2002
Uganda, 2002
Created on
Feb 14, 2018
Last modified
Feb 14, 2018
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Identification
Survey ID Number
UGA_2002_PETS_v01_M
Title
Public Expenditure Tracking Survey in Education 2002
Country
| Name | Country code |
|---|---|
| Uganda | UGA |
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
The 1996 Uganda public expenditure tracking survey revealed that schools received only 20 cents on average of every dollar allocated to them by the central government. As the evidence of local officials’ diversion of funds intended for schools became known, the central government began to publish newspaper accounts of monthly transfers of these capitation grants to local governments (districts). The main newspapers used were the The New Vision (and its local language editions) and The Monitor. In 1997 the Ministry of Education proposed extending the information campaign to all school communities. Primary schools (and district administration headquarters) were required to post notices on actual receipts of funds for all to see. In this two-part campaign, information on entitlements transferred by the central government was made available through newspapers, while information on what each school actually received was posted at schools to inform parents.
In 2002, researchers conducted a follow-up expenditure tracking survey to study the effects of improved access to public information as a tool to reduce diversion and corruption.
This research replicated the 1996 survey, measuring the difference between the capitation grants disbursed by the central government and the resources actually received by the schools. In addition, it collected data on access to information and the means to acquire information on the grant program and other variables that may influence the bargaining position of individual schools.
The 2002 sample covered 218 public primary schools from 16 districts.
In 2002, researchers conducted a follow-up expenditure tracking survey to study the effects of improved access to public information as a tool to reduce diversion and corruption.
This research replicated the 1996 survey, measuring the difference between the capitation grants disbursed by the central government and the resources actually received by the schools. In addition, it collected data on access to information and the means to acquire information on the grant program and other variables that may influence the bargaining position of individual schools.
The 2002 sample covered 218 public primary schools from 16 districts.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
- Public Primary Schools
Version
Version Description
v01 - Final, edited dataset.
Documented here is the final, cleaned dataset 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 is the final, cleaned dataset 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:
- General information about a school, organization and supervision, support from government, school income/receipts, UPE capitation grants, knowledge test for head teachers, total value of in-kind support.
- General information about a school, organization and supervision, support from government, school income/receipts, UPE capitation grants, knowledge test for head teachers, total value of in-kind support.
Topics
| Topic | Vocabulary |
|---|---|
| Primary Education | World Bank |
Coverage
Geographic Coverage
16 districts: Arua, Moyo (Northwest); Apac, Gulu (North); Soroti, Kapchorwa (Northeast); Jinja, Kamuli, Pallisa (East); Kampala, Mukono, Mubende (Central); Bushenyi, Kabale (Southwest); and Kabarole, Hoima (West).
Producers and sponsors
Primary investigators
| Name |
|---|
| World Bank |
| Economic Policy Research Centre (EPRC) |
Producers
| Name |
|---|
| International Development Consultants Ltd |
Sampling
Sampling Procedure
The original, 1996 sample consisted of 250 schools, randomly drawn from 18 districts. The selected districts were: Arua, Moyo (Northwest); Apac, Gulu (North); Soroti, Moroto, Kapchorwa (Northeast); Jinja, Kamuli, Pallisa (East); Kampala, Mukono, Mubende (Central); Bushenyi, Kabale (Southwest); and Kabarole, Hoima, Bundibugyo (West).
To ensure that the sample had broad regional coverage (Northwest, North, Northeast, East, Central, Southwest and West) and that it was representative of the population of schools in the selected districts, schools were selected using a stratified random sample. For each region two or three districts were drawn with a probability proportional to the number of schools in the district, and in each district 10-20 schools were visited, depending on the number of schools in the districts.
Not all schools in the original sample could be re-surveyed in 2002 because of security concerns. Two districts (Moroto and Bundibugyo) were dropped, reducing the sample by 20 schools. One district (Gulu) experienced a major insurgency during the data collection phase, and an additional 11 schools had to be dropped. And one school in the original sample had closed, resulting in a final sample of 218 schools.
To ensure that the sample had broad regional coverage (Northwest, North, Northeast, East, Central, Southwest and West) and that it was representative of the population of schools in the selected districts, schools were selected using a stratified random sample. For each region two or three districts were drawn with a probability proportional to the number of schools in the district, and in each district 10-20 schools were visited, depending on the number of schools in the districts.
Not all schools in the original sample could be re-surveyed in 2002 because of security concerns. Two districts (Moroto and Bundibugyo) were dropped, reducing the sample by 20 schools. One district (Gulu) experienced a major insurgency during the data collection phase, and an additional 11 schools had to be dropped. And one school in the original sample had closed, resulting in a final sample of 218 schools.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2002 | 2002 |
Data Collection Mode
Face-to-face [f2f]
Data Collection Notes
The school-specific measure of grant diversion is grants received (by school j in year t) as a share of grants disbursed by the central government to that school. A school’s entitlement is based on the number of students in grades P1- P3 and P4 - P7. In 1995 the grant formula allocated 2,500 Ugandan shillings (USh) a year for each student in grades P1- P3 and 4,000 USh for each student in grades P4 - P7.
In 2001 the amounts were 5,000 USh for grades P1- P3 and 8,100 USh for grades P4 - P7. Records from the Ministry of Finance indicate that this rule was followed unless districts did not submit the required quarterly documentation, in which case funds could be delayed or withheld in the following months.
These records show that in fiscal 2000-01, 93 percent of the approved funds were released, although some districts received significantly less (for example, the central government withheld 49 percent of the funds to Kyenjojo and 25 percent to Kayunga, both newly established districts). The actual amounts disbursed by the central government were confirmed by the public expenditure
tracking survey at the district level. To adjust for the withholding effect in deriving the diversion measure, a school’s entitlement was scaled down by the share of funds actually released by the center to the district.
In 2001 the amounts were 5,000 USh for grades P1- P3 and 8,100 USh for grades P4 - P7. Records from the Ministry of Finance indicate that this rule was followed unless districts did not submit the required quarterly documentation, in which case funds could be delayed or withheld in the following months.
These records show that in fiscal 2000-01, 93 percent of the approved funds were released, although some districts received significantly less (for example, the central government withheld 49 percent of the funds to Kyenjojo and 25 percent to Kayunga, both newly established districts). The actual amounts disbursed by the central government were confirmed by the public expenditure
tracking survey at the district level. To adjust for the withholding effect in deriving the diversion measure, a school’s entitlement was scaled down by the share of funds actually released by the center to the district.
Questionnaires
Questionnaires
The following survey instrument is available:
- School Head Teacher Questionnaire.
The 2002 survey collected detailed information on receipt of funds and school enrollment and administered a knowledge test to head teachers.
- School Head Teacher Questionnaire.
The 2002 survey collected detailed information on receipt of funds and school enrollment and administered a knowledge test to head teachers.
Data Processing
Data Editing
Detailed information about data editing procedures is available in "Data Cleaning Guide for PETS/QSDS Surveys" in external resources.
The STATA cleaning do-file and data quality report can also be found in external resources.
The STATA cleaning do-file and data quality report 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, Economic Policy Research Centre (EPRC), Uganda. Public Expenditure Tracking Survey in Education (PETS) 2002. Ref. UGA_2002_PETS_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, Economic Policy Research Centre (EPRC), Uganda. Public Expenditure Tracking Survey in Education (PETS) 2002. Ref. UGA_2002_PETS_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_UGA_2002_PETS_v01_M
Producers
| Name | Affiliation | Role |
|---|---|---|
| Antonina Redko | DECDG, World Bank | DDI documentation |
Date of Metadata Production
2011-08-16
DDI Document version
v01 (August, 2011)