KHM_2004_PETS_v01_M
Public Expenditure Tracking Survey in Education 2004
Name | Country code |
---|---|
Cambodia | KHM |
Public Expenditure Tracking Survey (PETS)
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).
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 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.
The scope of the study includes:
Topic | Vocabulary |
---|---|
Primary Education | World Bank |
Financial Management | World Bank |
7 provinces (Banteay Meanchey, Kampong Cham, Kampong Chhnang, Kampot, Kratie, Prey Veng and Sihanoukville).
Name |
---|
World Bank |
Cambodia Development Resource Institute (CDRI) |
Initial sample of 220 primary schools was randomly drawn from 12 provinces and 34 districts. The final sample included 200 schools in 7 provinces since some schools could not be accessed and a replacement could not be found.
Stratified random sample based on the 2002-2003 school census was used. Each province was weighted according to size (number of schools). Five early (receiving funding from 2000 and onwards) and seven late (receiving funding from 2001 and onwards) provinces were randomly chosen from the population of 24 provinces. Each of the 12 selected provinces (Banteay Meanchey, Battambang, Kampong Cham, Kampong Chhnang, Kampong Speu, Kampong Thom, Kampot, Phnom Penh, Ratanak Kiri, Siemreap, Svay Rieng, and Takeo) was then allotted a number of schools based on the proportion of schools in the province to the total number of schools in the selected sample of 12 provinces. To make the survey effort feasible, it was decided that 2 or 3 districts would be picked from each province (the final number depending on the total number of districts in the province). Similar to the draw of provinces, each district was weighted according to size (number of schools). Thereafter, 2 or 3 districts were randomly chosen from the population of districts within each province, yielding a total of 34 districts to be included in the final sample.
The second stage of the sampling was based on the Cambodian 2003-2004 household surveys (HSES). The HSES sampling frame consisted of 900 villages and 15,000 households. The sampling design involved stratification of the country into five geographical regions (Phnom Penh, Plain, Tonle Sap, Coastal, and Plateau and Mountain), dividing up each region into separate urban and rural strata. From each stratum, 4 independent sub-samples of villages were drawn, with the sample being allocated over the strata proportionately to the total number of households in the strata.
At the school level, questionnaires were administered to each school director. One teacher per grade was randomly selected from each school to interview. Three School Support Committee (SSC) members from each school and 6 parents per school were also randomly chosen to participate in the study.
The following survey instruments are available:
The core of the questionnaires for provincial treasuries, provincial education offices, district education offices and school directors focuses on resource flows (i.e., resources received from an upper tier of government and resources transferred to a lower tier of government), which allowed for some triangulation or cross checking of the data. The questionnaire for school directors also contained a variety of information on schools, teachers and students.
The teacher, School Support Committee (SSC) and parental questionnaires were designed to collect information on the degree of knowledge of and involvement in school matters (particularly PAP flows and use).
In addition, 20 Grade 4 students and 20 Grade 6 students were tested in numeracy and literacy skills; background socio-economic information was also collected from them.
Start | End |
---|---|
2004 | 2004 |
Name |
---|
Cambodia Development Resource Institute (CDRI) |
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 on all ten datasets can also be found in external resources.
Public use files
The use of this dataset must be acknowledged using a citation which would include:
Example:
World Bank and Cambodia Development Resource Institute (CDRI). Cambodia Public Expenditure Tracking Survey in Primary Education (PETS) 2004. Ref. KHM_2004_PETS_v01_M. Dataset downloaded from http://microdata.worldbank.org on [date].
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 | |
---|---|---|
Hooman Dabidian | World Bank | hdabidian@worldbank.org |
Cindy Audiguier | World Bank | caudiguier@worldbank.org |
DDI_KHM_2004_PETS_v01_M
Name | Affiliation | Role |
---|---|---|
Antonina Redko | DECDG, World Bank | DDI documentation |
2011-07-28
v01 (July 2011)
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