Survey of Young People in Egypt, SYPE 2009
Egypt, 2009
Population Council
Identification
Survey ID Number
EGY_SYPE_2009_V1.6.2
Title
Survey of Young People in Egypt, SYPE 2009
Country
| Name | Country code |
|---|---|
| Egypt | Egy |
Study type
Young People in Egypt Survey
Series Information
The 2009 Survey of Young People in Egypt (SYPE) builds upon the ASCE survey from the previous decade, focusing on a larger age group: those aged 10 to 29. SYPE concentrates on the five key life transitions for youth: health, education, employment and livelihood, family formation, and civic participation.
Abstract
In every society, young people carry the promise of a better future. They are the building blocks of a country’s economy and society and its most essential human resource. In Egypt, young people are not only its most important capital but they also constitute the largest segment of the population. According to the 2006 census, approximately 40% of Egyptians are between the ages of 10 and 29. With the right investments, this youth bulge will represent a demographic opportunity that will positively shape the country’s future. Once Egypt’s young people reach working age, given a relatively low proportion of older and younger non-working populations to support, they will present a “demographic gift” of low economic dependency. However, the large size of this cohort places enormous pressures on social services and the labor market and creates a major challenge for development planning. Failures in these institutions could result in the social and economic marginalization of a large proportion of youth that will be unable to compete in an increasingly globalized economy, hence turning the “gift” to demographic “burden”.
Effective planning relies on high-quality research. The Population Council seeks to build the evidence base for better policies and programs with the view of generating research that makes a difference. Young people have been a primary focus for the Council for decades, directing research to determine their conditions and contexts, and providing evidence for decision-makers. In 1998, the Population Council published Transitions to Adulthood, a comprehensive profile of youth based on the Council’s 1997 Adolescence and Social Change in Egypt (ASCE) survey. The results of ASCE have been an important resource for programming for adolescents in Egypt.
Responding to the dearth of data on youth in Egypt, the Population Council conducted a comprehensive situation analysis of Egyptian adolescents and young people: the Survey of Young People in Egypt (SYPE), which covers a nationally representative sample of 15,029 young people aged 10-29.
The SYPE collected data on the five key life transitions of education, work, family formation; health, and civic and political participation. SYPE follows up to an earlier survey conducted by the Population Council in 1997, The Adolescence and Social Change in Egypt (ASCE) survey. With focus on young people aged 10 to 19, analysis of ASCE identified tobacco use, female circumcision, anemia, growth stunting and delayed sexual maturation, poor management of menstruation, and underutilization of health insurance as six priority issues for youth in Egypt. SYPE updates the results provided by the earlier survey and expands their scope.
Effective planning relies on high-quality research. The Population Council seeks to build the evidence base for better policies and programs with the view of generating research that makes a difference. Young people have been a primary focus for the Council for decades, directing research to determine their conditions and contexts, and providing evidence for decision-makers. In 1998, the Population Council published Transitions to Adulthood, a comprehensive profile of youth based on the Council’s 1997 Adolescence and Social Change in Egypt (ASCE) survey. The results of ASCE have been an important resource for programming for adolescents in Egypt.
Responding to the dearth of data on youth in Egypt, the Population Council conducted a comprehensive situation analysis of Egyptian adolescents and young people: the Survey of Young People in Egypt (SYPE), which covers a nationally representative sample of 15,029 young people aged 10-29.
The SYPE collected data on the five key life transitions of education, work, family formation; health, and civic and political participation. SYPE follows up to an earlier survey conducted by the Population Council in 1997, The Adolescence and Social Change in Egypt (ASCE) survey. With focus on young people aged 10 to 19, analysis of ASCE identified tobacco use, female circumcision, anemia, growth stunting and delayed sexual maturation, poor management of menstruation, and underutilization of health insurance as six priority issues for youth in Egypt. SYPE updates the results provided by the earlier survey and expands their scope.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
1- Households.
2- Youth aged (10-29) years.
2- Youth aged (10-29) years.
Version
Version Description
Version 1.6.2: A version of SYPE 2009 data prepared by the Population Council and the ERF for dissemination
Production
Date
2016-06
Scope
Notes
The topics covered by the survey included key life transitions for youth:
1- Health
2- Education
3- Employment and livelihood
4- International migration
5- Marriage and family formation
6- Social issues, values, and civic engagement
7- Time use
8- Attitudes toward gender roles
1- Health
2- Education
3- Employment and livelihood
4- International migration
5- Marriage and family formation
6- Social issues, values, and civic engagement
7- Time use
8- Attitudes toward gender roles
Topics
| Topic |
|---|
| Health |
| Education |
| Employment and livelihood |
| International migration |
| Marriage and family formation |
| Social issues, values & civic engagement |
| Time use |
| Attitudes toward gender roles |
Coverage
Geographic Coverage
The SYPE sample is nationally representative, covering all governorates in Egypt, including the five Frontier governorates. The SYPE sample is considered to be an innovative design, because it allows for a priori inclusion of slum areas within the urban sample.
Universe
The survey covered a national sample of households and selected youth aged 10-29.
Producers and sponsors
Primary investigators
| Name |
|---|
| Population Council |
Producers
| Name | Role |
|---|---|
| Information and Decision Support Center | Data collection and processing |
| National Center for Examinations and Educational Evaluation | Designing and pretesting the aptitude tests included in the survey too |
| Central Agency for Public Mobilization and Statistics | Sample-design expertise |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| Canadian International Development Agency | CIDA | Financial support |
| World Bank | WBG | Financial support |
| United Nations Population Fund | UNFPA | Financial support |
| United Nations Development Programme | UNDP | Financial support |
| United Nations Development Fund for Women | UNIFEM | Financial support |
| Embassy of the Netherlands | Financial support | |
| Swedish International Development Cooperation Agency | SIDA | Financial support |
| United Nations Children's Fund | UNICEF | Financial support |
Sampling
Sampling Procedure
Sample Design
==========
The sample of the Survey of Young People in Egypt 2009 (SYPE) was designed in such a way as to be representative at the national as well as regional levels. The sample size of approximately 17,000 young people between the ages of 10 and 29 was selected to provide estimates of key indicators related to adolescents and youth for the country as a whole and for four administrative regions (Urban governorates, Lower Egypt governorates, Upper Egypt governorates and the Frontier governorates), and, where relevant, for the urban and rural segments of these regions. These indicators include never enrollment rates, dropout rates, the incidence of child labor, and unemployment rates. Based on previous statistics about the incidence of young people in the relevant age and sex groups, we determined that a nationally-representative sample of 11,000 households would be sufficient. To obtain accurate estimates for the Frontier governorates, these governorates had to be oversampled. As a result, the SYPE is not a self-weighted sample and weights are needed to obtain the correct estimates.
Sample Frame
=========
The SYPE sample was designed as a multi-stage stratified cluster sample. The primary sampling units (PSUs) were selected from a CAPMAS master sample. The master sample is a stratified cluster sample that contains 2,400 PSUs, divided into 1,080 urban and 1,320 rural PSUs. These PSUs are drawn from a frame of enumeration areas (EAs) covering the entire country prepared by CAPMAS from the 2006 Population Census. Each EA is drawn up in such a way as to contain roughly 1500 dwelling units. The sample is stratified into governorates and each governorate is further stratified into urban and rural segments, where relevant. The distribution of PSUs across strata in the master sample reflects the distribution of the population so as to produce a self-weighted sample.
To achieve a fairly wide geographic dispersion in the SYPE sample and thus minimize the design effect, we set the number of households per cluster to 25. To obtain these 25 households, 25 dwelling units were systematically selected from the roughly 1500 listed in each EA. To get the sample size we needed, we set the number of required PSUs to 455, for a total sample size of 11,375 households. The distribution of PSUs across governorates and urban and rural areas in both the master sample and the SYPE sample are shown in (Table 1 in Appendix C of the final report available among the external resources). The final sample of households interviewed was made up of 11,372 households, which yielded a total of 15,029 young people aged 10-29.
The PSU's in the SYPE sample were drawn from the EA's in the master sample at a rate of roughly 19%-20%. With the exception of the Frontier Governorates and the Luxor administrative area, the sampling rate varies in a relatively narrow range from 14% to 27%. To get good representation from the sparsely populated Frontier Governorates, we increased the sampling rate significantly, in some cases retaining all the PSU's in the master sample. Weights will be derived at the level of the administrative region to account for these varying sampling rates.
Selecting the Urban Slums Sub-Sample
========================
One of the objectives of SYPE is to obtain separate estimates for young people living in urban slums (referred to in the final report chapters as informal urban areas). To make sure we had enough representation of urban slums, we used a study conducted by the Information and Decision Support Center of the Egyptian Cabinet of Ministers (IDSC) to classify urban PSU's in the CAPMAS master sample into slum and non-slum areas. Deciding how to allocate urban PSUs to slum and non-slum areas was not a straightforward exercise given the unreliability of the data on the population of the slum areas.
First, we had to make a decision on how to allocate the 212 urban PSUs to slum and non-slum PSUs. The most reasonable estimate of the share of slums in the urban population was close to 20%, leading us to allocate 44 of the 212 urban PSU's in the sample to slum areas. Second, we had to allocate these 44 slum PSUs to the various governorates. This allocation was done in such a way as to match as closely as possible, the distribution of the number of slum areas across governorates is shown in (Table 2 in Appendix C of the final report available among the external resources).
Ideally, we should have allocated slum PSUs across governorates according to each governorate's share of slum population rather than its share in the number of slum areas. However, given the unreliable information about the population of slum areas, it was impossible to do the allocation in terms of population. This allocation decision is likely to understate the true share of slums in governorates such as Cairo, Giza and Alexandria, where the size of slums is likely to be larger than average, and overstate slum populations in governorates like Damietta, Dakahlia and Sharkia where the size of slums is probably smaller than average. Without reliable data on slum populations, it is unfortunately not possible to use weights to correct for this possible bias in the geographic distribution of slums.
** More information on the sampling procedures is available in Appendix C in the English final report available among the external resources.
==========
The sample of the Survey of Young People in Egypt 2009 (SYPE) was designed in such a way as to be representative at the national as well as regional levels. The sample size of approximately 17,000 young people between the ages of 10 and 29 was selected to provide estimates of key indicators related to adolescents and youth for the country as a whole and for four administrative regions (Urban governorates, Lower Egypt governorates, Upper Egypt governorates and the Frontier governorates), and, where relevant, for the urban and rural segments of these regions. These indicators include never enrollment rates, dropout rates, the incidence of child labor, and unemployment rates. Based on previous statistics about the incidence of young people in the relevant age and sex groups, we determined that a nationally-representative sample of 11,000 households would be sufficient. To obtain accurate estimates for the Frontier governorates, these governorates had to be oversampled. As a result, the SYPE is not a self-weighted sample and weights are needed to obtain the correct estimates.
Sample Frame
=========
The SYPE sample was designed as a multi-stage stratified cluster sample. The primary sampling units (PSUs) were selected from a CAPMAS master sample. The master sample is a stratified cluster sample that contains 2,400 PSUs, divided into 1,080 urban and 1,320 rural PSUs. These PSUs are drawn from a frame of enumeration areas (EAs) covering the entire country prepared by CAPMAS from the 2006 Population Census. Each EA is drawn up in such a way as to contain roughly 1500 dwelling units. The sample is stratified into governorates and each governorate is further stratified into urban and rural segments, where relevant. The distribution of PSUs across strata in the master sample reflects the distribution of the population so as to produce a self-weighted sample.
To achieve a fairly wide geographic dispersion in the SYPE sample and thus minimize the design effect, we set the number of households per cluster to 25. To obtain these 25 households, 25 dwelling units were systematically selected from the roughly 1500 listed in each EA. To get the sample size we needed, we set the number of required PSUs to 455, for a total sample size of 11,375 households. The distribution of PSUs across governorates and urban and rural areas in both the master sample and the SYPE sample are shown in (Table 1 in Appendix C of the final report available among the external resources). The final sample of households interviewed was made up of 11,372 households, which yielded a total of 15,029 young people aged 10-29.
The PSU's in the SYPE sample were drawn from the EA's in the master sample at a rate of roughly 19%-20%. With the exception of the Frontier Governorates and the Luxor administrative area, the sampling rate varies in a relatively narrow range from 14% to 27%. To get good representation from the sparsely populated Frontier Governorates, we increased the sampling rate significantly, in some cases retaining all the PSU's in the master sample. Weights will be derived at the level of the administrative region to account for these varying sampling rates.
Selecting the Urban Slums Sub-Sample
========================
One of the objectives of SYPE is to obtain separate estimates for young people living in urban slums (referred to in the final report chapters as informal urban areas). To make sure we had enough representation of urban slums, we used a study conducted by the Information and Decision Support Center of the Egyptian Cabinet of Ministers (IDSC) to classify urban PSU's in the CAPMAS master sample into slum and non-slum areas. Deciding how to allocate urban PSUs to slum and non-slum areas was not a straightforward exercise given the unreliability of the data on the population of the slum areas.
First, we had to make a decision on how to allocate the 212 urban PSUs to slum and non-slum PSUs. The most reasonable estimate of the share of slums in the urban population was close to 20%, leading us to allocate 44 of the 212 urban PSU's in the sample to slum areas. Second, we had to allocate these 44 slum PSUs to the various governorates. This allocation was done in such a way as to match as closely as possible, the distribution of the number of slum areas across governorates is shown in (Table 2 in Appendix C of the final report available among the external resources).
Ideally, we should have allocated slum PSUs across governorates according to each governorate's share of slum population rather than its share in the number of slum areas. However, given the unreliable information about the population of slum areas, it was impossible to do the allocation in terms of population. This allocation decision is likely to understate the true share of slums in governorates such as Cairo, Giza and Alexandria, where the size of slums is likely to be larger than average, and overstate slum populations in governorates like Damietta, Dakahlia and Sharkia where the size of slums is probably smaller than average. Without reliable data on slum populations, it is unfortunately not possible to use weights to correct for this possible bias in the geographic distribution of slums.
** More information on the sampling procedures is available in Appendix C in the English final report available among the external resources.
Deviations from the Sample Design
Attrition was due to the individual's rejection or unavailability during the data collectors' visit or their subsequent two revisits to the same household.
Response Rate
A total of 16,061 young people were selected to be interviewed as part of this survey. Of this group, 15,029 young people were interviewed.
Weighting
Sampling Weights and Expansion Factors
=========================
Three sampling weights are included in the SYPE database:
(i) the household sampling weight,
(ii) the roster individual sampling weight, and
(iii) the interviewed individual sampling weight.
There are three corresponding expansion factors that expand the population to the projected population in mid-2009. It should be kept in mind, however, that both the weights and expansion factors are designed to reproduce the structure of the population as measured in the 2006 Population Census, since no information on changes in the structure of the population is available for the period from November 2006, when the census was taken, and mid-2009.
** More information on the sampling weights and expansion factor are available in Appendix C in the final English report available among the external resources.
- For data analysis purposes, the variable "EligW_adj_1_expan" should be used to weight the data.
=========================
Three sampling weights are included in the SYPE database:
(i) the household sampling weight,
(ii) the roster individual sampling weight, and
(iii) the interviewed individual sampling weight.
There are three corresponding expansion factors that expand the population to the projected population in mid-2009. It should be kept in mind, however, that both the weights and expansion factors are designed to reproduce the structure of the population as measured in the 2006 Population Census, since no information on changes in the structure of the population is available for the period from November 2006, when the census was taken, and mid-2009.
** More information on the sampling weights and expansion factor are available in Appendix C in the final English report available among the external resources.
- For data analysis purposes, the variable "EligW_adj_1_expan" should be used to weight the data.
Data Collection
Dates of Data Collection
| Start | End | Cycle |
|---|---|---|
| 2009 | 2009 | - |
Data Collection Mode
Face-to-face [f2f]
Data Collection Notes
Field-staff training was implemented by IDSC (the Information and Decision Support Center of the Egyptian Cabinet of Ministers) in close collaboration with the Population Council staff. Data collection was undertaken under the direct management of IDSC.
Data Collectors
| Name | Abbreviation |
|---|---|
| Information and Decision Support Center of the Egyptian Cabinet of Ministers | IDSC |
Questionnaires
Questionnaires
The survey instruments included three separate questionnaires:
1) A household-level questionnaire;
2) An individual questionnaire that was administered to eligible young people;
3) A community-level questionnaire, which aimed at providing a profile of the localities in which young people live.
1) A household-level questionnaire;
2) An individual questionnaire that was administered to eligible young people;
3) A community-level questionnaire, which aimed at providing a profile of the localities in which young people live.
Data Appraisal
Estimates of Sampling Error
SYPE estimates for sampling error estimation
============================
Sampling errors along with other precision estimates have been calculated for several key survey estimates. The chosen estimates are labor-force participation rate; unemployment rate; employment to population ratio; average number of hours worked during reference weak; average total monthly earnings for wage and salaried workers in the reference 3 months; proportion of wage workers; proportion working in agriculture; proportion working in industry; proportion working in services; proportion working in private sector; proportion of employers and self-employed workers; proportion of youth who dropped out of school; proportion aspiring to migrate; proportion who migrated and returned; average hours of school including homework and tutoring; average hours of inside/outside chores including care-giving; average hours of television; proportion of youth using internet; proportion of youth participating in voluntary work; proportion of youth participating in a group for social work; proportion of youth who voted in any election; proportion participating in sports club/youth center; proportion playing any kind of sport; proportion agreeing that educating boys is more important than educating girls; proportion agreeing that a woman has the right to ask for a divorce; proportion agreeing that a man is justified to beat his wife when she argues with him; disability incidence; prevalence of chronic health conditions (diabetes, heart problems, respiratory and kidney related diseases; proportion of smokers; proportion of youth who tried drugs; proportion of girls who have undergone FGM; proportion of married youth; proportion of married youth who live with their parents (extended families); ideal number of children for married people; ideal number of children for unmarried people; average age at marriage for males; average age at marriage for females; and proportion married before 18 for females.
In addition, precise estimates have been produced for the cross classifications of the above estimates with sex, location type (urban, rural, slum), region, age group, educational status and wealth index quintiles. The classifying variables were further broken down by sex so as to produce more detailed precision estimates for SYPE indicators. Nonetheless, these detailed estimates should be dealt with cautiously, especially when the sample size of some categories of the classifying variables is too small to produce reliable results. With the aim of avoiding this problem to some extent, whenever the sample size was found to be too small for some categories of the educational status (eight categories), a new educational status variable composed of only five categories was also used.
The calculated precision estimates are:
1- Sampling (Standard) Error;
2- Coefficient of Variation (CV);
3- 95% Confidence Interval; and
4- Design Effect (deff).
Following is the definition of each:
1- Sampling Error: is the measure of sampling variability which is the square root of the variance.
2- Coefficient of Variation: is the relative standard error. It is measured as a ratio of the sampling error of a given estimate to the value of this estimate. As a rule of thump, if CV exceeds 20% the reliability of the estimate is limited.
3- Confidence Interval: Using the sampling error, the Central Limit Theorem allows the construction of Confidence Interval of the parameter in question. Two-thirds of all possible samples with the same size and design would produce estimates within one sampling error, and 95% of all samples would produce estimates within 1.96 sampling errors.
4- Design Effect: is a measure of how much the present sampling design is worse than a Simple Random Sample (SRS) of the same size. It is the ratio of the variance of the present design to the variance of SRS of the same size.
Important Notes
===========
In a few cases the lower limit of the confidence interval is negative; this must be considered as being a zero. Whenever the upper limit of the confidence interval of a proportion exceeds one, this must be regarded as being 1.
Expectedly, the design effect (deff) should be greater than one, yet in some cases it was found to be less than one. Most probably this problem arises due to the presence of outliers and/or smaller sample size.
** More information on the sampling errors of key indicators of SYPE is available in Appendix B in the final English report available among the external resources.
============================
Sampling errors along with other precision estimates have been calculated for several key survey estimates. The chosen estimates are labor-force participation rate; unemployment rate; employment to population ratio; average number of hours worked during reference weak; average total monthly earnings for wage and salaried workers in the reference 3 months; proportion of wage workers; proportion working in agriculture; proportion working in industry; proportion working in services; proportion working in private sector; proportion of employers and self-employed workers; proportion of youth who dropped out of school; proportion aspiring to migrate; proportion who migrated and returned; average hours of school including homework and tutoring; average hours of inside/outside chores including care-giving; average hours of television; proportion of youth using internet; proportion of youth participating in voluntary work; proportion of youth participating in a group for social work; proportion of youth who voted in any election; proportion participating in sports club/youth center; proportion playing any kind of sport; proportion agreeing that educating boys is more important than educating girls; proportion agreeing that a woman has the right to ask for a divorce; proportion agreeing that a man is justified to beat his wife when she argues with him; disability incidence; prevalence of chronic health conditions (diabetes, heart problems, respiratory and kidney related diseases; proportion of smokers; proportion of youth who tried drugs; proportion of girls who have undergone FGM; proportion of married youth; proportion of married youth who live with their parents (extended families); ideal number of children for married people; ideal number of children for unmarried people; average age at marriage for males; average age at marriage for females; and proportion married before 18 for females.
In addition, precise estimates have been produced for the cross classifications of the above estimates with sex, location type (urban, rural, slum), region, age group, educational status and wealth index quintiles. The classifying variables were further broken down by sex so as to produce more detailed precision estimates for SYPE indicators. Nonetheless, these detailed estimates should be dealt with cautiously, especially when the sample size of some categories of the classifying variables is too small to produce reliable results. With the aim of avoiding this problem to some extent, whenever the sample size was found to be too small for some categories of the educational status (eight categories), a new educational status variable composed of only five categories was also used.
The calculated precision estimates are:
1- Sampling (Standard) Error;
2- Coefficient of Variation (CV);
3- 95% Confidence Interval; and
4- Design Effect (deff).
Following is the definition of each:
1- Sampling Error: is the measure of sampling variability which is the square root of the variance.
2- Coefficient of Variation: is the relative standard error. It is measured as a ratio of the sampling error of a given estimate to the value of this estimate. As a rule of thump, if CV exceeds 20% the reliability of the estimate is limited.
3- Confidence Interval: Using the sampling error, the Central Limit Theorem allows the construction of Confidence Interval of the parameter in question. Two-thirds of all possible samples with the same size and design would produce estimates within one sampling error, and 95% of all samples would produce estimates within 1.96 sampling errors.
4- Design Effect: is a measure of how much the present sampling design is worse than a Simple Random Sample (SRS) of the same size. It is the ratio of the variance of the present design to the variance of SRS of the same size.
Important Notes
===========
In a few cases the lower limit of the confidence interval is negative; this must be considered as being a zero. Whenever the upper limit of the confidence interval of a proportion exceeds one, this must be regarded as being 1.
Expectedly, the design effect (deff) should be greater than one, yet in some cases it was found to be less than one. Most probably this problem arises due to the presence of outliers and/or smaller sample size.
** More information on the sampling errors of key indicators of SYPE is available in Appendix B in the final English report available among the external resources.
Access policy
Access authority
| Name | Affiliation | |
|---|---|---|
| Economic Research Forum | Economic Research Forum (ERF) | erfdataportal@erf.org.eg |
Contacts
| Name | |
|---|---|
| Economic Research Forum (ERF) - 21 Al-Sad Al-Aaly St., Dokki, Giza, Egypt | erfdataportal@erf.org.eg |
Confidentiality
To access the micro-data, researchers are required to register on the ERF website and comply with the data access agreement.
The data should only be used for scholarly, research, or educational purposes.
Users are prohibited from using data acquired from the Economic Research Forum in the pursuit of any commercial or private ventures.
Access conditions
Licensed datasets, accessible under conditions.
Citation requirements
The users should cite the Population Council as the source of the data and the Economic Research Forum as the distributor as follows:
-----------------------------------------------------------------------------------------------------------------------------------------------------------------
Population Council, 2009.
Survey of Young People in Egypt dataset, SYPE 2009. [Computer file]. Cairo, Egypt: OAMDI; Economic Research Forum (distributor).
Acknowledgement must also be given to the Population Council's funders as follows:
----------------------------------------------------------------------------------------------------
Support for the Population Council's SYPE project was generously provided by the American people through the United States Agency for International Development, and by the Ford Foundation, Silatech, the University of Tennessee, and the UNFPA. The contents of this publication are the responsibility of the author/user and do not necessarily reflect the views of the Population Council or any of its donors.
-----------------------------------------------------------------------------------------------------------------------------------------------------------------
Population Council, 2009.
Survey of Young People in Egypt dataset, SYPE 2009. [Computer file]. Cairo, Egypt: OAMDI; Economic Research Forum (distributor).
Acknowledgement must also be given to the Population Council's funders as follows:
----------------------------------------------------------------------------------------------------
Support for the Population Council's SYPE project was generously provided by the American people through the United States Agency for International Development, and by the Ford Foundation, Silatech, the University of Tennessee, and the UNFPA. The contents of this publication are the responsibility of the author/user and do not necessarily reflect the views of the Population Council or any of its donors.
Disclaimer and copyrights
Disclaimer
The Economic Research Forum and the Population Council have granted the researcher access to relevant data following exhaustive efforts to protect the confidentiality of individual data. The researcher is solely responsible for any analysis or conclusions drawn from available data.
Copyright
(c) 2009, Population Council
Metadata production
DDI Document ID
EGY_SYPE_2009_V1.6.2
Producers
| Name | Abbreviation |
|---|---|
| Population Council | PC |
Date of Metadata Production
2009
DDI Document version
Version 1.6.2