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Household Income, Expenditure, and Consumption Survey 2008

Egypt, Arab Rep., 2008 - 2009
Reference ID
EGY_2008_HIECS_v01_M
Producer(s)
Central Agency for Public Mobilization & Statistics
Metadata
DDI/XML JSON
Created on
Mar 13, 2015
Last modified
Mar 29, 2019
Page views
45263
Downloads
1052
  • Study Description
  • Data Dictionary
  • Downloads
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  • Related Publications
  • Identification
  • Version
  • Scope
  • Coverage
  • Producers and sponsors
  • Sampling
  • Survey instrument
  • Data collection
  • Data processing
  • Data appraisal
  • Data Access
  • Disclaimer and copyrights
  • Contacts
  • Metadata production
  • Identification

    Survey ID number

    EGY_2008_HIECS_v01_M

    Title

    Household Income, Expenditure, and Consumption Survey 2008

    Country
    Name Country code
    Egypt, Arab Rep. EGY
    Study type

    Income/Expenditure/Household Survey [hh/ies]

    Series Information

    This series of Egypt Household, Income, Expenditure, and Consumption Surveys (HIECS) was started in 1955. Ten subsequent surveys have been conducted since then in the following years: 1958, 1964, 1974, 1981, 1990, 1995, 1999, 2004, 2008, and 2010.

    Abstract

    The Household Income, Expenditure and Consumption Survey (HIECS) is of great importance among other household surveys conducted by statistical agencies in various countries around the world. This survey provides a large amount of data to rely on in measuring the living standards of households and individuals, as well as establishing databases that serve in measuring poverty, designing social assistance programs, and providing necessary weights to compile consumer price indices, considered to be an important indicator to assess inflation.

    The survey's main objectives are:

    • To identify expenditure levels and patterns of population as well as socio- economic and demographic differentials.
    • To estimate the quantities, values of commodities and services consumed by households during the survey period to determine the levels of consumption and estimate the current demand which is important to predict future demands.
    • To measure mean household and per-capita expenditure for various expenditure items along with socio-economic correlates.
    • To define percentage distribution of expenditure for various items used in compiling consumer price indices which is considered important indicator for measuring inflation.
    • To define mean household and per-capita income from different sources.
    • To provide data necessary to measure standard of living for households and individuals. Poverty analysis and setting up a basis for social welfare assistance are highly dependent on the results of this survey.
    • To provide essential data to measure elasticity which reflects the percentage change in expenditure for various commodity and service groups against the percentage change in total expenditure for the purpose of predicting the levels of expenditure and consumption for different commodity and service items in urban and rural areas.
    • To provide data essential for comparing change in expenditure against change in income to measure income elasticity of expenditure.
    • To study the relationships between demographic, geographical, housing characteristics of households and their income and expenditure for commodities and services.
    • To provide data necessary for national accounts especially in compiling inputs and outputs tables.
    • To identify consumers behavior changes among socio-economic groups in urban and rural areas.
    • To identify per capita food consumption and its main components of calories, proteins and fats according to its sources and the levels of expenditure in both urban and rural areas.
    • To identify the value of expenditure for food according to sources, either from household production or not, in addition to household expenditure for non-food commodities and services.
    • To identify distribution of households according to the possession of some appliances and equipment such as (cars, satellites, mobiles ...) in urban and rural areas.
    • To identify the percentage distribution of income recipients according to some background variables such as housing conditions, size of household and characteristics of head of household.
    Kind of Data

    Sample survey data [ssd]

    Unit of Analysis
    • Household/families
    • Individuals

    Version

    Version Date

    2013-03

    Scope

    Notes
    • Household: geographic, social, and economic characteristics of households

    • Individual: demographic, education, labor and health characteristics, as well as annual income for household members identified as earners.

    Topics
    Topic Vocabulary
    Poverty ERF
    Expenditure ERF
    Income ERF
    Infrastructure ERF
    Education ERF
    Labor ERF
    Health ERF

    Coverage

    Geographic Coverage

    Covering a sample of urban and rural areas in all the governorates.

    Universe

    The survey covered a national sample of households and all individuals permanently residing in surveyed households.

    Producers and sponsors

    Primary investigators
    Name Affiliation
    Central Agency for Public Mobilization & Statistics Egypt, Arab Rep.
    Producers
    Name
    Economic Research Forum
    Funding Agency/Sponsor
    Name Role
    Arab Republic of Egypt Funded the study

    Sampling

    Sampling Procedure

    The 2008/2009 HIECS is a two-stage stratified cluster sample, approximately self-weighted, of nearly 48000 household in urban and rural areas. The main elements of the sampling design are described below.

    • Sample Size: It has been deemed important to retain the same sample size of the previous two HIECS rounds. Thus, a sample of about 48000 households has been considered. The justification of maintaining the sample size at this level is to have estimates with levels of precision similar to those of the previous two rounds: therefore trend analysis with the previous two surveys will not be distorted by substantial changes in sampling errors from round to another. In addition, this relatively large national sample implies proportional samples of reasonable sizes for smaller governorates. Nonetheless, oversampling has been introduced to raise the sample size of small governorates to about 1000 households. As a result, reasonably precise estimates could be extracted for those governorates. The oversampling has resulted in a slight increase in the national sample to 48658 households.

    • Cluster size: An important lesson learned from the previous two HIECS rounds is that the cluster size applied in both surveys is found to be too large to yield an accepted design effect estimates. The cluster size was 40 households in the 2004-2005 round, descending from 80 households in the 1999-2000 round. The estimates of the design effect (deft) for most survey measures of the latest round were extraordinary large. As a result, the cluster size was decreased to only 19 households (20 households in urban governorates to account for anticipated non-response in those governorate. In view of past experience non-response is almost nil in rural governorates).

    A more detailed description of the different sampling stages and allocation of sample across governorates is provided in the Methodology document that is provided as an external resources in both Arabic and English.

    Response Rate

    For the total sample, the response rate was 96.3% (93.95% in urban areas and 98.4% in rural areas).

    Weighting

    In order for the sample estimates for the HIECS to be representative of the population, it is necessary to multiply the data by a sampling weight, or expansion factor. The basic weight for each sample household would be equal to the inverse of its probability of selection (calculated by multiplying the probabilities at each sampling stage). The HIECS sample is approximately self weighting at national level and strictly self-weighting at the governorate level, it should be easy to attach a weight to each sample household record in the computer files, and the tabulation programs can weight the data automatically. The sampling probabilities at each stage of selection will be maintained in an Excel spreadsheet so that the overall probability and corresponding weight can be calculated for each sample cluster.

    The procedures for calculating the weights and variances are described in details in the methodology technical document attached to the documentation materials published in both Arabic and English.

    Survey instrument

    Questionnaires

    Three different questionnaires were used:
    1- Expenditure and consumption questionnaire
    2- Diary questionnaire for expenditure and consumption
    3- Income questionnaire

    Data collection

    Dates of Data Collection
    Start End
    2008-04-01 2009-03-30
    Data Collectors
    Name Affiliation
    Central Agency For Public Mobilization & Statistics Egypt, Arab Rep.
    Supervision

    Supervisors were responsible for financial and technical aspects of all the survey stages especially:

    • Selecting interviewers (females) and editors (males) and send the list of their names to the administration of survey
    • Attending the central training in Cairo
    • Training the interviewers on field work
    Data Collection Notes

    The survey period of the 2008-2009 HIECS extended over 12 month-period, starting from April 2008 and ending in March 2009. Households were observed for two continuous weeks only, to collect information on food expenditure, instead of one month as was followed in the previous rounds of the HIECS. The observation period was shortened in this HIECS round to lighten the respondent burden and thus encourage more cooperation.

    Data processing

    Data Editing

    Harmonized Data

    • The Statistical Package for Social Science (SPSS) is used to clean and harmonize the datasets.
    • The harmonization process starts with cleaning all raw data files received from the Statistical Office.
    • Cleaned data files are then all merged to produce one data file on the individual level containing all variables subject to harmonization.
    • A country-specific program is generated for each dataset to generate/compute/recode/rename/format/label harmonized variables.
    • A post-harmonization cleaning process is run on the data.
    • Harmonized data is saved on the household as well as the individual level, in SPSS and converted to STATA format.

    Data appraisal

    Estimates of Sampling Error

    The sampling error of major survey estimates has been derived using the Ultimate Cluster Method as applied in the CENVAR Module of the Integrated Microcomputer Processing System (IMPS) Package. In addition to the estimate of sampling error, the output includes estimates of coefficient of variation, design effect (DEFF) and 95% confidence intervals.

    Data Appraisal

    The precision of survey results depends to a large extent on how the survey has been prepared for. As such, it was deemed crucial to exert much effort and to take necessary actions towards rigorous preparation for the present survey. The preparatory activities, extended over 3 months, included forming Technical Committee. The Committee has set up the general framework of survey implementation such as:

    1- Applying the recent international recommendations of different concepts and definitions of income and expenditure considering maintaining the consistency with the previous surveys in order to compare and study the changes in pertinent indicators.

    2- Evaluating the quality of data in all different Implementation stages to avoid or minimize errors to the lowest extent possible through:

    • Implementing field editing after finishing data collection for households in governorates to avoid any errors in suitable time.
    • Setting up a program for the Survey Technical Committee Members and survey staff for visiting field work in all governorates (each 15 days) to solve any problem in the proper time.
    • Re-interviewing a sample of households by Quality Control Department and examining the differences with the original responses.
    • For the purpose of quality assurance, tables were generated for each survey round where internal consistency checks were performed to study the plausibility of mean household expenditure on major expenditure commodity groups and its variability over major geographic regions.

    Data Access

    Citation requirements

    Use of the dataset must be acknowledged using a citation which would include:

    • the Identification of the Primary Investigator
    • the title of the survey (including country, acronym and year of implementation)
    • the survey reference number
    • the source and date of download

    Example:
    Central Agency for Public Mobilization & Statistics and Economic Research Forum. Egypt Household Income, Expenditure and Consumption Survey (HIECS) 2008. Ref. EGY_2008_HIECS_v01_M. Dataset downloaded from [url] 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.

    Copyright

    (c) 2013, Economic Research Forum | (c) 2009, CAPMAS

    Contacts

    Contacts
    Name Email URL
    Economic Research Forum (ERF) erfdataportal@erf.org.eg www.erf.org.eg

    Metadata production

    DDI Document ID

    DDI_EGY_2008_HIECS_v01_M

    Producers
    Name Affiliation Role
    Economic Research Forum Cleaning and Harmonizing raw data received from the Statistical Office
    Development Economics Data Group The World Bank Revision of the DDI
    Date of Metadata Production

    2013-03

    Metadata version

    DDI Document version

    Version 02 (May 2015). The original DDI (EGY_HIECS_2008_HD_V2.0) was downloaded from Economic Research Forum (ERF) Catalog (http://www.erfdataportal.com/index.php/catalog) on December 2014.

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