Labor Market Panel Survey, ELMPS 1998
Egypt, 1998
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Reference ID
EGY-CAPMAS-LMS-1998-V1.0
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Identification
Survey ID
EGY-CAPMAS-LMS-1998-V1.0
Title
Labor Market Panel Survey, ELMPS 1998
Country
| Name | Country code |
|---|---|
| Egypt | EGY |
Study type
Labor Force Survey [hh/lfs]
Series information
Economic Research Forum and Central Agency for Public Mobilization and Statistics , since established, conducted a series of Egypt Labor Market Panel Survey during the years 1988, 1998, 2006, 2012.
Abstract
In 1991, the Egyptian government initiated a major Economic Reform and Structural Adjustment Program (ERSAP). This reform included a stabilization component to eliminate external and external imbalances, a reform agenda for the trade and financial sectors and the exchange rate regime, and an ambitious privatization program. Until recently, however, little was known about the impact of this program on employment and earnings in the Egyptian labor market. Therefore ERF conducted The Egypt Labor Market survey with a nationally-representative household survey covering 5,000 households which aimed to assess the major changes in labor market conditions that occurred during the period from 1988 to 1998, a period of significant economic reform and structural adjustment.
This project investigated changes in the supply and demand for labor, including the extent to which the private sector has contributed to employment creation, and the groups that have benefited from employment growth. Trends in labor earnings and wages, in women’s and youth employment, and in child labor and schooling are analyzed and the role of the informal sector in employment creation is explored, as well as the extent to which the labor market itself has become more informal over the period.
This project investigated changes in the supply and demand for labor, including the extent to which the private sector has contributed to employment creation, and the groups that have benefited from employment growth. Trends in labor earnings and wages, in women’s and youth employment, and in child labor and schooling are analyzed and the role of the informal sector in employment creation is explored, as well as the extent to which the labor market itself has become more informal over the period.
Kind of data
Sample survey data [ssd]
Unit of analysis
individuals, households
Version
Version
V1.0: A cleaned and a harmonized version of the survey dataset, produced by the Economic Research Forum for dissemination.
Scope
Notes
The topics covered by the survey included:
(i) basic demographic and work characteristics, (ii) the characteristics of employment, unemployment, and underemployment, (iii) labor mobility, (iv) the family enterprise (to study the characteristics of informal sector employment), (v) women's work, and (vi) earnings. An additional module investigating the socio-economic status of the household. Moreover, the modules on the economic unit and earnings were significantly expanded to obtain more information on employment conditions and earnings of self-employed and other non-wage work in enterprises operated by the household.
(i) basic demographic and work characteristics, (ii) the characteristics of employment, unemployment, and underemployment, (iii) labor mobility, (iv) the family enterprise (to study the characteristics of informal sector employment), (v) women's work, and (vi) earnings. An additional module investigating the socio-economic status of the household. Moreover, the modules on the economic unit and earnings were significantly expanded to obtain more information on employment conditions and earnings of self-employed and other non-wage work in enterprises operated by the household.
Coverage
Geographic coverage
The sample was designed to provide estimates of the indicators at the national level, for urban and rural areas,and for all regions.
Universe
The survey covered a national sample of households and all individuals permanently residing in surveyed households.
Producers and sponsors
Primary investigators
| Name |
|---|
| Economic Research Forum |
Producers
| Name |
|---|
| Central Agency for Public Mobilization and Statistics |
Funding Agency/Sponsor
| Name |
|---|
| Ford Foundation |
| Economic Policy Initiative Consortium |
| World Bank |
Sampling
Sampling procedure
The process of sample extraction was primarily executed by CAPMAS staff in close coordination with the ERF team. The 5,000 household, which constitute the survey sample, were selected from a CAPMAS master sample prepared in 1995. The master sample consists of 750,000 households in 500 primary sampling units (PSUs) each consisting of 1500 households. Since the master sample is the basis for the survey sample, we find it necessary to start by explaining how the master sample was extracted in the first place.
Deviations from sample design
There was adeviation from sample design.
Regional variations show that the greatest incidence of closed households has been in Urban Upper Egypt, especially in Minia (16 cases) and Sohag (13 cases). It is difficult to account for the closure of these units. One explanation can be the escalating violence in this region in the past couple of year. The second region with high incidence of closed units has been the Alexandria and Suez Canal region. CAPMAS staff note that since many of the dwelling units, especially in Alexandria city, are used by residents of other governorates as summer resorts, these dwellings were closed at the time of the survey, which took place in October.
The sample had a very small rate of rejection cases. Only 23 cases, constituting 0.48% of the final sample size, consisted of total rejections to respond to the questionnaire.There were additional cases were the respondent refused to answer some parts of the questionnaire. As with most surveys, rejection cases are primarily in urban metropolitan areas, especially Cairo and Alexandria governorates.
While the majority of non-response cases are in urban areas, the majority of added households come from rural areas. This unintentional sampling bias towards rural areas can be corrected with the appropriate sampling weights.
Regional variations show that the greatest incidence of closed households has been in Urban Upper Egypt, especially in Minia (16 cases) and Sohag (13 cases). It is difficult to account for the closure of these units. One explanation can be the escalating violence in this region in the past couple of year. The second region with high incidence of closed units has been the Alexandria and Suez Canal region. CAPMAS staff note that since many of the dwelling units, especially in Alexandria city, are used by residents of other governorates as summer resorts, these dwellings were closed at the time of the survey, which took place in October.
The sample had a very small rate of rejection cases. Only 23 cases, constituting 0.48% of the final sample size, consisted of total rejections to respond to the questionnaire.There were additional cases were the respondent refused to answer some parts of the questionnaire. As with most surveys, rejection cases are primarily in urban metropolitan areas, especially Cairo and Alexandria governorates.
While the majority of non-response cases are in urban areas, the majority of added households come from rural areas. This unintentional sampling bias towards rural areas can be corrected with the appropriate sampling weights.
Response rates
The overall response rate for the ELMS 1998 was 96.5% of the designed sample. 4,816 households were actually interviewed, out of the 5,000 sampled households. Because the dwelling unit is the entry point for interviewers, when they encountered units housing more than one household, each household was interviewed separately.. This measure balances the missed cases with a number of added cases. 292 households of the initial sample were missed for a different number of reasons as will be noted shortly. Yet, 108 households were added to the sample due to dwelling units housing more than one household. . As a result, the number and percentage of missed cases were reduced to 186 cases (3.5%) instead of 292 cases (5.84%).
The major reason for non-response cases has been the closure of the dwelling unit at the time of the survey. Because interviewers were aware of the fact that their pay was based on the number of questionnaire completed, they tried their best to reach the residents of closed dwelling units. They would visit at different times of the day and would also ask neighbors on when the household members would be available. As a rsult, it is safe to assume that dwelling units marked as "closed" were actually not inhabited at the time of the survey. Many reasons can account for the existence of closed dwelling units. One major reason relates to CAPMAS master sample, the source of the survey sample, which dates back to 1995, three years before the date of the survey.
The major reason for non-response cases has been the closure of the dwelling unit at the time of the survey. Because interviewers were aware of the fact that their pay was based on the number of questionnaire completed, they tried their best to reach the residents of closed dwelling units. They would visit at different times of the day and would also ask neighbors on when the household members would be available. As a rsult, it is safe to assume that dwelling units marked as "closed" were actually not inhabited at the time of the survey. Many reasons can account for the existence of closed dwelling units. One major reason relates to CAPMAS master sample, the source of the survey sample, which dates back to 1995, three years before the date of the survey.
Weighting
The master sample was extracted through a two-stage process. The country is first divided into two strata: urban and rural. Each stratum is in turn divided into substrata representing each governorate. All the villages (in the case of rural strata) or shiyakhas (urban quarter, in the case of urban strata) in each substratum were listed and assigned a weight based on their population. The first stage consisted of choosing the villages and shiyakhas that would be represented in the sample based on the principal of probability proportional to size. This meant that a shiyakha or a village is possibly selected more than once if its size warrants that. The selected shiyakhas and villages are then divided into PSUs of approximately 1500 housing units each; then one or more PSUs are selected from each shiyakha or village. The selected PSUs were then re-listed in 1995 to enumerate all the households selected. the master sample contains 306 urban PSUs and 194 rural PSUs.
As for our survey sample, 200 PSUs were selected from the master sample. The desired number of PSUs in each substratum was selected from the number available in the master sample using a systematic interval. Cairo and Alexandria were deliberately over-sampled and rural areas under-sampled to increase the probability of obtaining women wage-workers in the private sector, which tend to be concentrated in Metropolitan areas. A self-weighted sample would have yielded too few of these individuals, which constitute an important target group for this study.
Twenty-five housing units were then randomly selected from the 1500 housing units listed in each of the selected PSUs. the expansion weight for each sampling stratum based on population estimates in June 1997.
Sample expansion factor will be updated based on the June 1998 estimates once they are available at CAPMAS.
As for our survey sample, 200 PSUs were selected from the master sample. The desired number of PSUs in each substratum was selected from the number available in the master sample using a systematic interval. Cairo and Alexandria were deliberately over-sampled and rural areas under-sampled to increase the probability of obtaining women wage-workers in the private sector, which tend to be concentrated in Metropolitan areas. A self-weighted sample would have yielded too few of these individuals, which constitute an important target group for this study.
Twenty-five housing units were then randomly selected from the 1500 housing units listed in each of the selected PSUs. the expansion weight for each sampling stratum based on population estimates in June 1997.
Sample expansion factor will be updated based on the June 1998 estimates once they are available at CAPMAS.
Survey instrument
Questionnaires
Includes three questionnaires:
1) the household questionnaire; 2) the individual questionnaire; 3) the family enterprise questionnaire. Each household should have at least one household questionnaire and one individual questionnaire. If any of the members of the household was self-employed or an employer, there has to be a family enterprise questionnaire for this household.
1) Data for the household questionnaire is collected from the head of the household. It includes the roster of members of the household, each individual's relationship to the head of the household, demographic characteristics of the household, access to public services, availability of durable goods and sources of income other than work for the household. This questionnaire serves as a springboard for interviewers to determine the individuals who should carry on with the subsequent questions in the individual questionnaire - those who are six years and older. Also, in this questionnaire each individual is assigned a person code (pn) that is used in the subsequent questionnaires as an identification code. The roaster for the household questionnaire allows space for 20 members of the household. In case the household had more than 20 members, as it happened in some rural areas, another copy of the questionnaire is used.
2) The individual questionnaire applies to individuals six years old and above. It includes modules on parents, education, detection of work during the reference week, unemployment, characteristics of employment during the reference three months, mobility and career history, and earnings. The latter applies to wage workers only. Data for this questionnaire are collected from the individual him/herself. Unless the research team fails to meet the individual personally after three visits, with prior appointment before each subsequent visit, data can be collected from another member of the household. For individuals less than 15 years old, data is collected from their parents or any adult household member in order to save these youngsters the interviewing process.
3) The family enterprise questionnaire applies to all individuals who are self-employed or employers (those who chose answers 2, 3 or 4 in questions number q1316 or 2122 at the individual questionnaire). Data for this questionnaire is collected from the individual responsible for the enterprise, unless interviewers fail to meet her/him after three trials as in the case of the individual questionnaire.
1) the household questionnaire; 2) the individual questionnaire; 3) the family enterprise questionnaire. Each household should have at least one household questionnaire and one individual questionnaire. If any of the members of the household was self-employed or an employer, there has to be a family enterprise questionnaire for this household.
1) Data for the household questionnaire is collected from the head of the household. It includes the roster of members of the household, each individual's relationship to the head of the household, demographic characteristics of the household, access to public services, availability of durable goods and sources of income other than work for the household. This questionnaire serves as a springboard for interviewers to determine the individuals who should carry on with the subsequent questions in the individual questionnaire - those who are six years and older. Also, in this questionnaire each individual is assigned a person code (pn) that is used in the subsequent questionnaires as an identification code. The roaster for the household questionnaire allows space for 20 members of the household. In case the household had more than 20 members, as it happened in some rural areas, another copy of the questionnaire is used.
2) The individual questionnaire applies to individuals six years old and above. It includes modules on parents, education, detection of work during the reference week, unemployment, characteristics of employment during the reference three months, mobility and career history, and earnings. The latter applies to wage workers only. Data for this questionnaire are collected from the individual him/herself. Unless the research team fails to meet the individual personally after three visits, with prior appointment before each subsequent visit, data can be collected from another member of the household. For individuals less than 15 years old, data is collected from their parents or any adult household member in order to save these youngsters the interviewing process.
3) The family enterprise questionnaire applies to all individuals who are self-employed or employers (those who chose answers 2, 3 or 4 in questions number q1316 or 2122 at the individual questionnaire). Data for this questionnaire is collected from the individual responsible for the enterprise, unless interviewers fail to meet her/him after three trials as in the case of the individual questionnaire.
Data collection
Dates of Data Collection
| Start | End |
|---|---|
| 1998-11-01 | 1998-12-20 |
Data Collectors
| Name |
|---|
| Central Agency for Public Mobilization and Statistics |
Notes on data collection
The field staff was trained from saturday October 17,1998 to Thursday October 29, 1998
Data processing
Cleaning operations
Raw Data
=======
The data collection phase was then followed by the data processing stage accomplished through the following procedures:
1- Data coding
This stage involved turning the text describing occupation, economic activity, educational attainment and geographic localities into numeric codes. Since one of the major objectives of this project was to compare data with the results of the 1988 labor survey, the research team decided to use the 1986 coding manuals for occupations and economic activities, despite the fact that CAPMAS has issued more recent coding manuals. However, for the coding of localities (administrative units) and educational attainment, the 1996 coding manuals were used, while making sure that the equivalent codes for 1986 be obtained.
2-Office checking
Office checkers had many tasks to do. First, they had to review the consistency of replies throughout the different sections of the questionnaires for each household. Second, they had to translate the options chosen under "other" according to the lists generated by the coding team. Third, they had to prepare the questionnaires for the data entry stage. This included adding -9 and ?? in places of missing data4, deleting replies that were not applicable and making sure that the person number is written on all pages of the individual questionnaires as well as project numbers in the family enterprise questionnaire. The last task for the office checking team was to provide a list of the total production of each field interviewer and reviewer by counting household questionnaires, number of individuals interviewed (six year old and above) and number of family enterprises for each reviewer and interviewer.
3-Data Entry
Data entry started before the end of the office checking stage. It lasted from February 16 till April 8, 1999 and took place at CAPMAS premises within the Statistics Department using the PCs and the LAN provided by ERF. This is not a regular arrangement since CAPMAS has a department for computer data processing. However, the arrangement proved to be significantly more efficient, specifically in comparison to the 1988 experience where the data processing stage took more than a year (Fergany, 1990:9).
4-Data Validation
The data validation process works as follows: First, the program produces lists of likely or mandatory errors in each questionnaire, identifying the question number and the individual person number (pn). The four supervisors, with consultation with the two reviewers, read the program message carefully and consult the questionnaire for data validation. One of two measures takes place: either change the data upon reviewing the questionnaire, or hand-write a note on the list that although there could be an inconsistency in the data provided, the case at hand is a unique case and hence data should remain as is. The reviewer and supervisor both sign their names on the program printout beside the message and the decision they reached. If changes need to be done, data entry clerks are given directions to input them.
During the data validation stage, the program pointed to discrepancies in the way occupations and economic activities were coded. As noted earlier, the ERF team decided to use the 1988 coding system to ensure comparability of data. However, the program pinpointed some inconsistent codes in relation to data in other parts of the questionnaire. The discrepant codes were mistakenly done according to the 1996 coding manual. As a result, two of CAPMAS specialists in coding were stationed at the data entry room to screen the coding for occupations and economic activities in all questionnaires. Moreover, CAPMAS programmers designed a program that would point out all coding for occupation and economic activity done using the 1996 coding system.
As a final data cleaning process, CAPMAS programmers re-applied the skip patterns and range rules to the data set at the end of the validation rules. The new program was designed to ensure that when some records were changed during the validation process, the new changes were in accordance with the rest of the information for the same record.
=======
The data collection phase was then followed by the data processing stage accomplished through the following procedures:
1- Data coding
This stage involved turning the text describing occupation, economic activity, educational attainment and geographic localities into numeric codes. Since one of the major objectives of this project was to compare data with the results of the 1988 labor survey, the research team decided to use the 1986 coding manuals for occupations and economic activities, despite the fact that CAPMAS has issued more recent coding manuals. However, for the coding of localities (administrative units) and educational attainment, the 1996 coding manuals were used, while making sure that the equivalent codes for 1986 be obtained.
2-Office checking
Office checkers had many tasks to do. First, they had to review the consistency of replies throughout the different sections of the questionnaires for each household. Second, they had to translate the options chosen under "other" according to the lists generated by the coding team. Third, they had to prepare the questionnaires for the data entry stage. This included adding -9 and ?? in places of missing data4, deleting replies that were not applicable and making sure that the person number is written on all pages of the individual questionnaires as well as project numbers in the family enterprise questionnaire. The last task for the office checking team was to provide a list of the total production of each field interviewer and reviewer by counting household questionnaires, number of individuals interviewed (six year old and above) and number of family enterprises for each reviewer and interviewer.
3-Data Entry
Data entry started before the end of the office checking stage. It lasted from February 16 till April 8, 1999 and took place at CAPMAS premises within the Statistics Department using the PCs and the LAN provided by ERF. This is not a regular arrangement since CAPMAS has a department for computer data processing. However, the arrangement proved to be significantly more efficient, specifically in comparison to the 1988 experience where the data processing stage took more than a year (Fergany, 1990:9).
4-Data Validation
The data validation process works as follows: First, the program produces lists of likely or mandatory errors in each questionnaire, identifying the question number and the individual person number (pn). The four supervisors, with consultation with the two reviewers, read the program message carefully and consult the questionnaire for data validation. One of two measures takes place: either change the data upon reviewing the questionnaire, or hand-write a note on the list that although there could be an inconsistency in the data provided, the case at hand is a unique case and hence data should remain as is. The reviewer and supervisor both sign their names on the program printout beside the message and the decision they reached. If changes need to be done, data entry clerks are given directions to input them.
During the data validation stage, the program pointed to discrepancies in the way occupations and economic activities were coded. As noted earlier, the ERF team decided to use the 1988 coding system to ensure comparability of data. However, the program pinpointed some inconsistent codes in relation to data in other parts of the questionnaire. The discrepant codes were mistakenly done according to the 1996 coding manual. As a result, two of CAPMAS specialists in coding were stationed at the data entry room to screen the coding for occupations and economic activities in all questionnaires. Moreover, CAPMAS programmers designed a program that would point out all coding for occupation and economic activity done using the 1996 coding system.
As a final data cleaning process, CAPMAS programmers re-applied the skip patterns and range rules to the data set at the end of the validation rules. The new program was designed to ensure that when some records were changed during the validation process, the new changes were in accordance with the rest of the information for the same record.
Data Access
Access authority
| Name | Affiliation | URL | |
|---|---|---|---|
| Economic Research Forum | (ERF) | www.erf.org.eg | erfdataportal@erf.org.eg |
Confidentiality
| Is signing of a confidentiality declaration required? | Confidentiality declaration text |
|---|---|
| yes |
To access the micro data, researchers are required to register on the ERF website and comply with the data access agreement. The data will be used only 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 requirement
The users should cite the Economic Research Forum as follows:
OAMDI, 2013. Labor Market Panel Surveys (LMPS), http://www.erf.org.eg/cms.php?id=erfdataportal. Version 1.0 of Licensed Data Files; ELMPS 1998. Egypt: Economic Research Forum (ERF).
OAMDI, 2013. Labor Market Panel Surveys (LMPS), http://www.erf.org.eg/cms.php?id=erfdataportal. Version 1.0 of Licensed Data Files; ELMPS 1998. Egypt: Economic Research Forum (ERF).
Disclaimer and copyrights
Disclaimer
The Economic Research Forum has 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) 1998, Economic Research Forum
Contacts
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| Economic Research Forum (ERF),21 Al-Sad Al-Aaly St., Dokki, Giza, Egypt | erfdataportal@erf.org.eg | www.erf.org.eg |
Metadata production
Document ID
EGY-CAPMAS-LMPS-1998-V1.0
Producers
| Name | Role |
|---|---|
| Economic Rerearch Forum | Documentation of the study |
Date of metadata production
2013-04-01
Metadata version
Version
version 1.0