DDI_EGY_2010_HIECS_v01_M Economic Research Forum Development Economics Data Group 2014-01 NADA Version 03 (June 2015). The original DDI (EGY_HIECS_2010_HD_V2.0) was downloaded from Economic Research Forum (ERF) Catalog (<http://www.erfdataportal.com/index.php/catalog>) on December 2014. Household Income, Expenditure, and Consumption Survey 2010 HIECS 2010 EGY_2010_HIECS_v01_M Central Agency For Public Mobilization & Statistics

Economic Research Forum and Central Agency For Public Mobilization & Statistics (CAPMAS)

(c) 2014, Economic Research Forum | (c) 2011, CAPMAS, Egypt NADA Arab Republic of Egypt Economic Research Forum (ERF) Income/Expenditure/Household Survey [hh/ies] The HIECS 2010/2011 is the tenth Household Income, Expenditure and Consumption Survey that was carried out in 2010/2011, among a long series of similar surveys that started back in 1955. Poverty Expenditure Income Infrastructure Education Labor Health The Household Income, Expenditure and Consumption Survey (HIECS) 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 measure average household and per-capita expenditure for various expenditure items along with socio-economic correlates. - To Measure the change in living standards and expenditure patterns and behavior for the individuals and households in the panel sample, previously surveyed in 2008/2009, for the first time during 12 months representing the survey period. - To define percentage distribution of expenditure for various items used in compiling consumer price indices which is considered important indicator for measuring inflation. - 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 define average 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. - 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 nutrition components and the levels of expenditure in both urban and rural areas. - To identify the value of expenditure for food according to its 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 equipments such as (cars, satellites, mobiles ,…etc) in urban and rural areas that enables measuring household wealth index. - To identify the percentage distribution of income earners according to some background variables such as housing conditions, size of household and characteristics of head of household. Egypt, Arab Rep. Covering a sample of urban and rural areas in all the governorates. - Household - Individual The survey covered a national sample of households and all individuals permanently residing in surveyed households. Sample survey data [ssd] - Household: Includes geographic, social, and economic characteristics of households, namely, household composition, dwelling characteristics, ownership of assets indicators, heads' and spouses' characteristics, annual household expenditure and income. - Individual: Includes demographic, migration, education, labor and health characteristics, as well as annual income for household members identified as earners. Moreover, fathers' and mothers' characteristics are generated for household members if possible. Central Agency For Public Mobilization & Statistics The sample of HIECS 2010/2011 is a self-weighted two-stage stratified cluster sample of around 26500 households. The main elements of the sampling design are described below. - Sample Size : It was deemed important to collect a smaller sample size (around 26.5 thousand households) compared to previous rounds due to the convergence in the time period over which the survey is conducted to be every two years instead of five years because of its importance. The sample was proportionally distributed on the governorate level between urban and rural areas, in order to make the sample representative even for small governorates. - Cluster size : The cluster size was decreased compared to older surveys since large cluster sizes previously used were found to be too large to yield accepted design effect estimates (DEFT). As a result, a cluster size of only 16 households was used (that was increased to 18 households in urban governorates and Giza, in addition to urban areas in Helwan and 6th of October, to account for anticipated non-response in those governorates: in view of past experience indicating that non-response may almost be nil in rural governorates). While the cluster size for the panel sample was 4 households. - Core Sample: The master sample of any household sample required to be pulled for the purpose of studying the properties of individuals and families. It is a large sample(1004800 household) that is distributed across urban and rural areas of all 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. Face-to-face [f2f] Three different questionnaires were used: 1- Expenditure and Consumption Questionnaire: This questionnaire comprises 14 tables in addition to identification and geographic data of household. 2- Diary Questionnaire (Assisting questionnaire): This questionnaire was prepared to help households record - on a daily basis- the quantity and value of food and beverages consumed during the reference period (15 days). 3- Income Questionnaire: This questionnaire consists of several tables; each designated to a specific income source. The survey period of the 2010-2011 HIECS extends over a 12 months period, starting from July 2010 and ending in June 2011. Households were observed for two continuous weeks only, to collect information on food expenditure. Data was collected using personal interview method for household in dwelling and it had been obtained from the head of household or wife or any eligible person in case of their absence. 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 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. The Statistical Package for Social Science (SPSS) was used to clean and harmonize the datasets. For the total sample, the response rate was 93.0% (91.2% in urban areas and 95.6% in rural areas). 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. Quality Control Procedures included: 1) Procedures implemented by the survey division a - 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. b - 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 fieldwork in all governorates (each 15 days) to solve any problem in the proper time. For the purpose of quality assurance, tables were generated for each survey round where internal consistency checks were performed to study the plausibility of consistency of data collected. 2) Procedures implemented by the quality control general division a - It was put into consideration during the survey implementation to assign the quality control general division a core role in controlling the quality of the fieldwork to ensure data accuracy and avoid any errors in suitable time, as well as taking all the necessary measures to guarantee that mistakes are not repeated, with the application of the principle of reward and punishment, and announce the results to all those working in the survey. b - 24 quality control rounds (2 rounds weekly) covering all governorates were implemented. A complete report on the results of each round was produced and distributed to all workers in the survey. The quality control procedures covered 73.2% of total kism/district in urban areas, 48.3% of rural districts, and 48% of total EAs of the new sample, where the percentage of inconsistencies did not exceed 2%. As for the panel sample, the quality control procedures covered 50.3% of total kism/district in urban areas, 16.9% of rural districts, and 14.2% of total EAs of the new sample, where the percentage of inconsistencies did not exceed 2.1%. To access the micro data, researchers are required to register on the ERF website and comply with the data access agreement. Economic Research Forum 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. Egypt Household Income, Expenditure and Consumption Survey (HIECS) 2010. Ref. EGY_HIECS_2010_v01_M. Dataset downloaded from [url] 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.