The social welfare benefits in Sweden aims to help people in need to reach a reasonable standard of living through monthly monetary benefits. The average monthly benefits increased from 2013 until 2021, but fell somewhat in 2022. In 2022, the average amount paid out per month was 9,135 Swedish kronor. In 2021, the total expenses of social welfare benefits were at almost 12 billion Swedish kronor.

Decreasing number of recipients

In 2021, around 340,000 individuals received social welfare benefits in Sweden. The number of recipients has decreased steadily since 2015, even though the total amount has increased.

 More common to receive benefits for households with children

The most common type of household receiving benefits were single woman households with children. Almost 14 percent of all single-woman households with children received social welfare benefits in 2021, and eight percent of all households consisting of single men with children received benefits. In general, the share of receiving households was higher for the ones with children than those without.

Since 2015, the number of recipients of social welfare in Sweden has decreased steadily. Whereas more than 415,000 people received social welfare in Sweden in 2015, it had sunk below 300,000 in 2022. However, even though the total number of recipients has decreased, the value of the total benefits has increased since 2017.

To help people reach a reasonable standard of living

The social welfare benefits in Sweden are administered by the National Board of Health and Welfare (Socialstyrelsen in Swedish). The aim of the benefits is to help people in need to reach a reasonable standard of living through monthly benefits. The amount of the average monthly payment was around 9,100 Swedish kronor in 2022.

 Benefits in foreign and Swedish households

Looking at households with Swedish-born and foreign-born citizens, the most common group of recipients was Swedish-born single men living without children. However, when looking at couples with children, far more foreign-born citizens received social benefits.

The Stephanie Tubbs Jones Child Welfare Services Program provides grants to States and Indian tribes for programs directed toward the goal of keeping families together. They include preventive intervention so that, if possible, children will not have to be removed from their homes. If this is not possible, children are placed in foster care and reunification services are available to encourage the return of children who have been removed from their families. Services are available to children and their families without regard to income.

These funds are a small but integral part of State social service systems for families who need assistance in order to stay together. These funds, often combined with State and local government, as well as private funds, are directed to accomplish the following purposes:

States can use a portion of their funds (no more than their 2005 expenditure level) for foster care maintenance payments, adoption assistance and day care related to employment or training for employment. States must limit expenditures for administrative costs 10 percent or less of their expenditures under this program.

Each state receives a base amount of $70,000. Additional funds are distributed in proportion to the state's population of children under age 21 multiplied by the complement of the state's average per capita income. The state match requirement is 25 percent. Funding is approximately $282,000,000 for FY 2008.

Metadata-only record linking to the original dataset. Open original dataset below.

The Global Welfare Dataset (GLOW) is a cross-national panel dataset that aims at facilitating comparative social policy research on the Global North and Global South. The database includes 381 variables on 61 countries from years between 1989 and 2015. The database has four main categories of data: welfare, development, economy and politics.The data is the result of an original data compilation assembled by using information from several international and domestic sources. Missing data was supplemented by domestic sources where available. We sourced data primarily from these international databases:Atlas of Social Protection Indicators of Resilience and Equity – ASPIRE (World Bank)Government Finance Statistics (International Monetary Fund)Social Expenditure Database – SOCX (Organisation for Economic Co-operation and Development)Social Protection Statistics – ESPROSS (Eurostat)Social Security Inquiry (International Labour Organization)Social Security Programs Throughout the World (Social Security Administration)Statistics on Income and Living Conditions – EU-SILC (European Union)World Development Indicators (World Bank)However, much of the welfare data from these sources are not compatible between all country cases. We conducted an extensive review of the compatibility of the data and computed compatible figures where possible. Since the heart of this database is the provision of social assistance across a global sample, we applied the ASPIRE methodology in order to build comparable indicators across European and Emerging Market economies. Specifically, we constructed indicators of average per capita transfers and coverage rates for social assistance programs for all the country cases not included in the World Bank’s ASPIRE dataset (Austria, Belgium, Bulgaria, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Luxembourg, Netherlands, Norway, Poland, Portugal, Romania, Slovak Republic, Slovenia, Spain, Sweden, Switzerland, and United Kingdom.)For details, please see:https://glow.ku.edu.tr/about

Besides a survey of those seeking help (clients) with Caritas, conducted orally by a Caritas worker, there was also a form to be filled out by the Caritas worker, who due to problem and file knowledge could refer to the client interviewed. The data in both parts of the survey are assigned to each other.

Abstract

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 50% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE CENTRAL AGENCY FOR PUBLIC MOBILIZATION AND STATISTICS (CAPMAS)

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 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.

The survey 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.

Compared to previous surveys, the current survey experienced certain peculiarities, among which : 1- The total sample of the current survey (26.5 thousand households) is divided into two sections: a- A new sample of 16.5 thousand households. This sample was used to study the geographic differences between urban governorates, urban and rural areas, and frontier governorates as well as other discrepancies related to households characteristics and household size, head of the household's education status, ....... etc. b- A panel sample with 2008/2009 survey data of around 10 thousand households was selected to accurately study the changes that may have occurred in the households' living standards over the period between the two surveys and over time in the future since CAPMAS will continue to collect panel data for HIECS in the coming years. 2- The number of enumeration area segments is reduced from 2526 in the previous survey to 1000 segments for the new sample, with decreasing the number of households selected from each segment to be (16/18) households instead of (19/20) in the previous survey. 3- Some additional questions that showed to be important based on previous surveys results, were added, such as: a- Collect the expenditure data on education and health on the person level and not on the household level to enable assessing the real level of average expenditure on those services based on the number of beneficiaries. b- The extent of health services provided to monitor the level of services available in the Egyptian society. c- Smoking patterns and behaviors (tobacco types- consumption level- quantities purchased and their values). d- Counting the number of household members younger than 18 years of age registered in ration cards. e- Add more details to social security pensions data (for adults, children, scholarships, families of civilian martyrs due to military actions) to match new systems of social security. f- Duration of usage and current value of durable goods aiming at estimating the service cost of personal consumption, as in the case of imputed rents. 4- Quality control procedures especially for fieldwork, are increased, 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.

The raw survey data provided by the Statistical Agency were cleaned and harmonized by the Economic Research Forum, in the context of a major project that started in 2009. During which extensive efforts have been exerted to acquire, clean, harmonize, preserve and disseminate micro data of existing household surveys in several Arab countries.

Geographic coverage

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

Analysis unit

1- Household/family. 2- Individual/person.

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 50% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE CENTRAL AGENCY FOR PUBLIC MOBILIZATION AND STATISTICS (CAPMAS)

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 in the following.

1- Sample Size
It has been 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 has been proportionally distributed on the governorate level between urban and rural areas, in order to make the sample representative even for small governorates. Thus, a sample of about 26500 households has been considered, and was distributed between urban and rural with the percentages of 47.1 % and 52.9, respectively. This sample is divided into two parts: a- A new sample of 16.5 thousand households selected from main enumeration areas. b- A panel sample with 2008/2009 survey data of around 10 thousand households.

2- Cluster size
The cluster size in the previous survey has been 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, it has been decided to use a cluster size of only 16 households (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.

3- Core Sample The core sample is 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 and distributed on urban and rural areas of all governorates. It is a representative sample for the individual characteristics of the Egyptian society. This sample was implemented in January 2010 and its size reached more than 1 million household (1004800 household) selected from 5024 enumeration areas distributed on all governorates (urban/rural) proportionally with the sample size (the enumeration area size is around 200 households). The core sample is the sampling frame from which the samples for the surveys conducted by CAPMAS are pulled, such as the Labor Force Surveys, Income, Expenditure And Consumption Survey, Household Urban Migration Survey, ...etc, in addition to other samples that may be required for outsources. New Households Sample 1000 sample areas were selected across

In May 2025, 2.8 billion U.S. dollars were paid out in unemployment benefits in the United States. This is a decrease from April 2025, when 3.2 billion U.S. dollars were paid in unemployment benefits. The large figures seen in 2020 are largely due to the impact of the coronavirus pandemic. Welfare in the U.S. Unemployment benefits first started in 1935 during the Great Depression as a part of President Franklin D. Roosevelt’s New Deal. The Social Security Act of 1935 ensured that Americans would not fall deeper into poverty. The United States was the only developed nation in the world at the time that did not offer any welfare benefits. This program created unemployment benefits, Medicare and Medicaid, and maternal and child welfare. The only major welfare program that the United States currently lacks is a paid maternity leave policy. Currently, the United States only offers 12 unpaid weeks of leave, under certain circumstances. However, the number of people without health insurance in the United States has greatly decreased since 2010. Unemployment benefits Current unemployment benefits in the United States vary from state to state due to unemployment being funded by both the state and the federal government. The average duration of people collecting unemployment benefits in the United States has fluctuated since January 2020, from as little as 4.55 weeks to as many as 50.32 weeks. The unemployment rate varies by ethnicity, gender, and education levels. For example, those aged 16 to 24 have faced the highest unemployment rates since 1990 during the pandemic. In February 2023, the Las Vegas-Henderson-Paradise, NV metropolitan area had the highest unemployment rate in the United States.

For the financial year 2024, the funding is granted as a technical lump sum in accordance with Section 29 of the NRW Budget Act. All local public youth welfare institutions will receive 50% of the subject-related lump sum granted in 2019 as a permanent base amount. The remaining funds of €6,045,985 will be paid to the local public youth welfare institutions according to the number of children under the age of three in the SGB II benefit receipt in the respective youth welfare district in relation to the nationwide total number of children under the age of three in the SGB II benefit receipt (source: Federal Employment Agency; Annual average 2021, as at: April 2022), taking into account that each local public youth welfare institution receives a minimum amount of 12,500 euros in the distribution of the total budget. The database for the distribution of funds according to the number of children receiving SGB II benefits in the respective youth welfare district in relation to the country-wide total number of children under three years of age receiving SGB II benefits has been updated every three years since 2020.

For the 2023 financial year, the funding for benefits under Section 3(4) of the Act on Cooperation and Information in Child Protection is granted as a specialist lump sum in accordance with Section 29 of the NRW Budget Act. All local public youth welfare institutions will receive 50% of the subject-related lump sum granted in 2019 as a permanent base amount. The remaining funds of €6,038,340 will be distributed to the local public youth welfare institutions according to the number of children under the age of three in the SGB II benefit receipt in the respective youth welfare district in relation to the nationwide total number of children under the age of three in the SGB II benefit receipt (annual average 2021), taking into account that in the distribution of the total funds each local public youth welfare institution receives a minimum amount of €12,500. The database for the distribution of funds according to the number of children receiving SGB II benefits in the respective youth welfare district in relation to the country-wide total number of children under three years of age receiving SGB II benefits has been updated every three years since 2020.

This data is a detailed compilation of statistics on pharmaceutical expenses paid by the Korea Workers' Compensation and Welfare Service (KCOMWEL) as part of the Industrial Accident Compensation Insurance (IACI) medical benefits, by branch office, as of the fourth quarter of 2012. Key fields include branch name, number of pharmaceutical expense claims and amounts, number of beneficiaries who actually received payments, final number of payments and amounts, and average pharmaceutical expenses per patient (the average amount paid per patient). These statistics provide crucial foundational data for analyzing regional characteristics and payment patterns of IACCI pharmaceutical expense expenditures. The ratio of payments to claims allows for assessing the efficiency of pharmaceutical expense review and payment management. By analyzing the difference in average pharmaceutical expenses per person relative to the number of beneficiaries by branch, the data can indirectly infer the severity of illness and medication usage patterns of patients with industrial accidents in each region. Policymakers and financial management departments can leverage this data to identify specific regions or branches with excessive pharmaceutical expenditures and analyze regional pharmaceutical expense claim trends to focus on developing measures to improve the soundness and efficiency of pharmaceutical expenditures. Ultimately, these are key statistics that contribute to preventing insurance financial leaks and securing financial stability while providing the necessary medicines to industrial accident patients.

Abstract

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 50% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE CENTRAL AGENCY FOR PUBLIC MOBILIZATION AND STATISTICS (CAPMAS)

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 First Survey that covered all the country governorates was carried out in 1958/1959 followed by a long series of similar surveys . The current survey, HIECS 2012/2013, is the eleventh in this long series.

Starting 2008/2009, Household Income, Expenditure and Consumption Surveys were conducted each two years instead of five years. this would enable better tracking of the rapid changes in the level of the living standards of the Egyptian households.

CAPMAS started in 2010/2011 to follow a panel sample of around 40% of the total household sample size. The current survey is the second one to follow a panel sample. This procedure will provide the necessary data to extract accurate indicators on the status of the society. The CAPMAS also is pleased to disseminate the results of this survey to policy makers, researchers and scholarly to help in policy making and conducting development related researches and studies

The survey 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.

• To provide a time series of the most important data related to dominant standard of living from economic and social perspective. This will enable conducting comparisons based on the results of these time series. In addition to, the possibility of performing geographical comparisons.

Compared to previous surveys, the current survey experienced certain peculiarities, among which :

1- The total sample of the current survey (24.9 thousand households) is divided into two sections:

a- A new sample of 16.1 thousand households. This sample was used to study the geographic differences between urban governorates, urban and rural areas, and frontier governorates as well as other discrepancies related to households characteristics and household size, head of the household's education status, ....... etc.

b- A panel sample of 2008/2009 survey data of around 8.8 thousand households was selected to accurately study the changes that may have occurred in the households' living standards over the period between the two surveys and over time in the future since CAPMAS will continue to collect panel data for HIECS in the coming years.

2- Some additional questions that showed to be important based on previous surveys results, were added to the survey questionnaire, such as:

a- The extent of health services provided to monitor the level of services available in the Egyptian society. By collecting information on the in-kind transfers, the household received during the year; in order to monitor the assistance the household received from different sources government, association,..etc.

b- Identifying the main outlet of fabrics, clothes and footwear to determine the level of living standards of the household.

3- Quality control procedures especially for fieldwork are increased, 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.

The raw survey data provided by the Statistical Agency were cleaned and harmonized by the Economic Research Forum, in the context of a major project that started in 2009. During which extensive efforts have been exerted to acquire, clean, harmonize, preserve and disseminate micro data of existing household surveys in several Arab countries.

Geographic coverage

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

Analysis unit

1- Household/family. 2- Individual/person.

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 50% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE CENTRAL AGENCY FOR PUBLIC MOBILIZATION AND STATISTICS (CAPMAS)

The sample of HIECS 2012/2013 is a self-weighted two-stage stratified cluster sample, of around 24.9 households. The main elements of the sampling design are described in the following.

1- Sample Size The sample has been proportionally distributed on the governorate level between urban and rural areas, in order to make the sample representative even for small governorates. Thus, a sample of about 24863 households has been considered, and was distributed between urban and rural with the percentages of 45.4 % and 54.6, respectively. This sample is divided into two parts: a- A new sample of 16094 households selected from main enumeration areas. b- A panel sample of 8769 households (selected from HIECS 2010/2011 and the preceding survey in 2008/2009).

2- Cluster size The cluster size in the previous survey has been 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, it has been decided to use a cluster size of only 8 households (In HIECS 2011/2012 a cluster size of 16 households was used). While the cluster size for the panel sample was 4 households.

3- Core Sample The core sample is 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 and distributed on urban and rural areas of all governorates. It is a representative sample for the individual characteristics of the Egyptian society. This sample was implemented in January 2012 and its size reached more than 1 million household (1004800 household) selected from 5024 enumeration areas distributed on all governorates (urban/rural) proportionally with the sample size (the enumeration area size is around 200 households). The core sample is the sampling frame from which the samples for the surveys conducted by CAPMAS are pulled, such as the Labor Force Surveys, Income, Expenditure And Consumption Survey, Household Urban Migration Survey, ...etc, in addition to other samples that may be required for outsources.

New Households Sample 1000 sample areas were selected across all governorates (urban/rural) using a proportional technique with the sample size. The number

An average of around 3.95 million people in Germany who are capable of working and around 1.45 million who are not, were receiving citizen's income as of 2025.

[Kiva.org][1] is an online crowdfunding platform to extend financial services to poor and financially excluded people around the world. Kiva lenders have provided over $1 billion dollars in loans to over 2 million people. In order to set investment priorities, help inform lenders, and understand their target communities, knowing the level of poverty of each borrower is critical. However, this requires inference based on a limited set of information for each borrower.

In Kaggle Datasets' inaugural [Data Science for Good][2] challenge, Kiva is inviting the Kaggle community to help them build more localized models to estimate the poverty levels of residents in the regions where Kiva has active loans. Unlike traditional machine learning competitions with rigid evaluation criteria, participants will develop their own creative approaches to addressing the objective. Instead of making a prediction file as in a supervised machine learning problem, submissions in this challenge will take the form of Python and/or R data analyses using Kernels, Kaggle's hosted Jupyter Notebooks-based workbench.

Kiva has provided a dataset of loans issued over the last two years, and participants are invited to use this data as well as source external public datasets to help Kiva build models for assessing borrower welfare levels. Participants will write kernels on this dataset to submit as solutions to this objective and five winners will be selected by Kiva judges at the close of the event. In addition, awards will be made to encourage public code and data sharing. With a stronger understanding of their borrowers and their poverty levels, Kiva will be able to better assess and maximize the impact of their work.

The sections that follow describe in more detail how to participate, win, and use available resources to make a contribution towards helping Kiva better understand and help entrepreneurs around the world.

Problem Statement

For the locations in which Kiva has active loans, your objective is to pair Kiva's data with additional data sources to estimate the welfare level of borrowers in specific regions, based on shared economic and demographic characteristics.

A good solution would connect the features of each loan or product to one of several poverty mapping datasets, which indicate the average level of welfare in a region on as granular a level as possible. Many datasets indicate the poverty rate in a given area, with varying levels of granularity. Kiva would like to be able to disaggregate these regional averages by gender, sector, or borrowing behavior in order to estimate a Kiva borrower’s level of welfare using all of the relevant information about them. Strong submissions will attempt to map vaguely described locations to more accurate geocodes.

Kernels submitted will be evaluated based on the following criteria:

1. Localization - How well does a submission account for highly localized borrower situations? Leveraging a variety of external datasets and successfully building them into a single submission will be crucial.

2. Execution - Submissions should be efficiently built and clearly explained so that Kiva’s team can readily employ them in their impact calculations.

3. Ingenuity - While there are many best practices to learn from in the field, there is no one way of using data to assess welfare levels. It’s a challenging, nuanced field and participants should experiment with new methods and diverse datasets.

How to Participate and [Make a Submission »][3]

To be considered a participant in the Kiva Crowdfunding Data Science for Good Event, there are a few requirements:

1. [Everyone must register and accept the rules by filling out this form][10] (you'll need to be logged into your Kaggle account to view the form). This ensures you're a participant and also means you'll receive update emails from us about key deadlines and announcements throughout the event.
2. To submit a kernel for consideration in the main prize track, make sure it's public and [submit it here][11] (you'll need to be logged into your Kaggle account to view the form). [Read more details here][4].
3. To submit a kernel or dataset for consideration in the secondary prize track, all you need to do is make sure it's public and be a registered participant before the deadline.

[Prizes and Eligibility »][5]

There is a total prize pool of $30,000 split into two tracks:

• Main prize track for the primary event objective: accurate and localized analyses or methods for assessing poverty levels. ($14,000; five winners total)
• Upvoted kernels and popular datasets to encourage public sharing of code and data ($16,000; 12 winners total)

Main Prize Track

Kiva will award $14,000 in total prizes to five winning authors who submit public kernels effectively tackling the objective by the deadline...

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 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. The survey 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.

Compared to previous surveys, the current survey experienced certain peculiarities, among which :

1- The total sample of the current survey (26.5 thousand households) is divided into two sections:

a- A new sample of 16.5 thousand households. This sample was used to study the geographic differences between urban governorates, urban and rural areas, and frontier governorates as well as other discrepancies related to households characteristics and household size, head of the household's education status, etc.

b- A panel sample with 2008/2009 survey data of around 10 thousand households was selected to accurately study the changes that may have occurred in the households' living standards over the period between the two surveys and over time in the future since CAPMAS will continue to collect panel data for HIECS in the coming years.

2- The number of enumeration area segments is reduced from 2526 in the previous survey to 1000 segments for the new sample, with decreasing the number of households selected from each segment to be (16/18) households instead of (19/20) in the previous survey.

3- Some additional questions that showed to be important based on previous surveys results, were added, such as:

a- Collect the expenditure data on education and health on the person level and not on the household level to enable assessing the real level of average expenditure on those services based on the number of beneficiaries.

b- The extent of health services provided to monitor the level of services available in the Egyptian society.

c- Smoking patterns and behaviors (tobacco types- consumption level- quantities purchased and their values).

d- Counting the number of household members younger than 18 years of age registered in ration cards.

e- Add more details to social security pensions data (for adults, children, scholarships, families of civilian martyrs due to military actions) to match new systems of social security.

f- Duration of usage and current value of durable goods aiming at estimating the service cost of personal consumption, as in the case of imputed rents.

4- Quality control procedures especially for fieldwork, are increased, 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. The raw survey data provided by the Statistical Office was cleaned and harmonized by the Economic Research Forum, in the context of a major research project to develop and expand knowledge on equity and inequality in the Arab region. The main focus of the project is to measure the magnitude and direction of change in inequality and to understand the complex contributing social, political and economic forces influencing its levels. However, the measurement and analysis of the magnitude and direction of change in this inequality cannot be consistently carried out without harmonized and comparable micro-level data on income and expenditures. Therefore, one important component of this research project is securing and harmonizing household surveys from as many countries in the region as possible, adhering to international statistics on household living standards distribution. Once the dataset has been compiled, the Economic Research Forum makes it available, subject to confidentiality agreements, to all researchers and institutions concerned with data collection and issues of inequality. Data is a public good, in the interest of the region, and it is consistent with the Economic Research Forum's mandate to make micro data available, aiding regional research on this important topic.

Geographic coverage

National

Analysis unit

1- Household/family

2- Individual/Person

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

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 in the following:

1- Sample Size It has been 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 has been proportionally distributed on the governorate level between urban and rural areas, in order to make the sample representative even for small governorates. Thus, a sample of about 26500 households has been considered, and was distributed between urban and rural with the percentages of 47.1 % and 52.9, respectively. This sample is divided into two parts: a- A new sample of 16.5 thousand households selected from main enumeration areas. b- A panel sample with 2008/2009 survey data of around 10 thousand households.

2- Cluster size The cluster size in the previous survey has been 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, it has been decided to use a cluster size of only 16 households (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.

3- Core Sample The core sample is 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 and distributed on urban and rural areas of all governorates. It is a representative sample for the individual characteristics of the Egyptian society. This sample was implemented in January 2010 and its size reached more than 1 million household (1004800 household) selected from 5024 enumeration areas distributed on all governorates (urban/rural) proportionally with the sample size (the enumeration area

The increasing proportion of older people in the population is creating a continuously growing demand for care services. Over the past five years, this trend has led to average revenue growth of 0.5% per year. This comparatively moderate growth is mainly due to the effects of the coronavirus pandemic. In the initial phase of the pandemic, a significant proportion of fatal cases were among residents of inpatient care facilities. During this time, many of those affected and their relatives only decided to move into a nursing or retirement home when necessary, which temporarily slowed the growth of the sector. After the end of the pandemic, the number of moves from home to inpatient care increased again, which also had a positive impact on sector turnover. The development of energy prices, inflation and rising staff costs have placed an additional burden on the sector. As the care insurance funds only partially refinanced these cost increases, the earnings situation deteriorated in 2022 and 2023. Delayed cost reimbursements and falling capacity utilisation due to the increasing shortage of nursing staff put many care facilities under economic pressure in 2023. As a result, the number of insolvencies increased.Revenue growth of 1.7% is expected for 2025, which means that the market volume is likely to reach 65.9 billion euros. At the same time, high payment arrears from social welfare offices and protracted payment processes by local social welfare organisations are causing a tense liquidity situation in the facilities. In order to ensure their economic stability, many operators are passing on most of the rising costs to the residents. As a result, own contributions are likely to continue to rise despite current surcharges for capping and a planned dynamisation of benefit rates. More and more people in need of care are likely to be dependent on social assistance in the future, as they will no longer be able to cover the growing co-payments themselves. Despite these challenges, individual market participants are achieving high profit margins in some cases, which is increasing the interest of private equity investors in this sector. The demographic change that will continue in the coming years will both increase the demand for care services and make it even more difficult to find qualified staff. As a result, the sector's capacities will probably not be able to grow at the same pace as demand due to legal requirements. The efficient use of financial and human resources will therefore become more important. Innovative technologies could make an important contribution to relieving the burden on care staff and ensuring the care of those in need. Average revenue growth of 3.8% per year is expected to be achieved in the period up to 2030, meaning that the market volume of the care sector is likely to increase to 79.4 billion euros.

Abstract

The 2003 Core Welfare Indicators Questionnaire (CWIQ) Survey is a nationwide sample survey, designed to provide indicators for monitoring poverty and living standards in the country, at national, regional and district levels. It is a district-based probability sample that covered a total of 49,003 households nationwide, with 405 households drawn from each district, except for the metropolitan areas, which had samples of households as follows: Accra, 2,430; Kumasi, 11,620; and Shama-Ahanta East, 1,215; as well as the Tema Municipal Area, 810.

Key Findings were as follows:

Adult Literacy

About 50 per cent of the population aged 15 years can read and write (53.4 per cent), an increase of about 10 per cent over the rate recorded in the 1997 CWIQ Survey. Males have a higher literacy rate than females, 65.8 per cent compared to 42.3 per cent. There is a 30 percentage point gap between urban and rural literacy rates (69.6 per cent and 39.8 per cent respectively). Females are more disadvantaged in rural areas where the literacy rate is less than 30 per cent compared urban areas where the rate is more than 50 per cent. The female literacy rates are also lower than the male rates in both urban and rural areas of the country.

Youth Literacy

Among the youth, i.e., the population aged 15 - 24 years, the proportion that can read and write increased only slightly from 64.1 per cent in 1997 to 68.7 per cent in 2003. The female youth made some modest gains in their literacy levels, which increased by 10 per cent, while that of males increased by only 4 per cent over the five-year period. The literacy rate for urban youth (81.7 per cent) is considerably higher than that of the rural youth (56.4 per cent). The rural poor have however remained disadvantaged, with just a third of its females and less than half of its males being able to read and write.

Net Enrolment

Seven in 10 children aged 6 to 11 years are enrolled in primary school, for girls as for boys. The differences between the enrolment rates for girls and boys at the national level, and in the rural and urban areas are marginal. The biggest gender gap is 2.4 percentage points among the urban poor, with boys having the edge. Substantially fewer children progress from primary to secondary level. Of the children aged 12 to 17 years, only about 4 in 10, are enrolled in secondary school, and the gender disparity in 1997 has reversed. Overall, enrolment at the secondary level declined marginally, from 40.0 percent in 1997 to 38.1 per cent in 2003. The rate however declined appreciably for males (from 43.6 to 37.9 per cent) but increased slightly for females (from 36.4 to 38.4 per cent) over the five year period. There are substantial differences between the urban and rural areas (50.5 per cent compared to 28.7 per cent), and between the poor in urban and rural areas (40.3 per cent compared to 15.2 per cent).

Access to School

A high proportion of primary school children (85.4 per cent) have a primary school within 30 minutes of their home, compared to only 43.3 per cent, for secondary schools. Access to a primary school is substantially high for all four subgroups - rural versus urban and rural poor versus urban poor. The rural poor have the lowest access rate (72.7 per cent), with 93.4 percent of the urban poor reporting access. In contrast, about 62.6 per cent of secondary level students in urban areas, but only 28.8 per cent of their counterparts in rural areas have a secondary school within 30 minutes of their home. The corresponding proportions for the urban and rural poor are 55.1 and 12.9 per cent, respectively.

Satisfaction with Education

About two-thirds (68.0 per cent) of all primary school children report being satisfied with the school they attend while a higher proportion (75.0 per cent) of the secondary school students report being satisfied with their school. However, primary pupils and secondary students in rural areas, especially the rural poor, are less satisfied with their schools than their counterparts in the urban areas.

Access to Health Facilities.

The time required to reach a health facility could affect the chances of survival of sick people, especially in emergency situations. Yet, only 57.6 per cent of the population live within 30 minutes of a health facility. This is however a significant improvement over the 1997 average of 37.2 per cent. More than three quarters (78.5 per cent) of urban households have good access to health facilities compared to 42.3 per cent of the rural households. The urban poor have an access rate (72.7 per cent) below the average rate for all urban areas (78.5 percent); while the rural poor is more disadvantaged, relative to their counterparts - in all rural areas and the urban poor. Only 27 per cent of the rural poor live within 30 minutes of a health facility.

Adequacy of Health Services

About 18 per cent of the population reported having been sick or injured in the four-week period preceding the survey, and there has been little change in the situation since 1997 (18.6 percent). In general, only 18.4 per cent of the people consult a health practitioner. Nearly eight out of ten (78.6 per cent) persons who use health services are satisfied with the services they receive, a considerable improvement over the 1997 rate of 57 per cent. The level of satisfaction with the medical services show very little variation across groups. Equal proportions of rural and urban users of the health services are satisfied, and a slightly lower percentage of the rural than urban poor users of these facilities are satisfied.

Prenatal Care

About nine in ten women (93.4 per cent) aged 12-49 years who had live births within 12 months of the survey, received prenatal care. The urban and rural poor have lower participation in prenatal care than their counterparts. The proportion of these women who received prenatal care is 95.9 per cent for the urban poor, and 97.3 per cent for all urban areas. Similarly, the rural poor have lower participation in prenatal care than all rural areas; 86.5 per cent compared to 91.2 percent, respectively.

Births Assisted by Trained Health Professionals

About half of the children aged under five years, were delivered with the assistance of a trained health professional (doctors, nurses and midwifes) in 2003 (51.8 per cent), an increase over the proportion in 1997 (44.7 per cent). The involvement of trained professionals in birth deliveries is more than twice as high in the urban areas (83.3 per cent), than in the rural areas (34.7 per cent). The rate of professionally assisted births is extremely low among the rural poor, for whom the corresponding proportion is only 17.3 per cent compared to that for the urban poor, almost four times as high.

Child Nutritional Status

Of the three anthropometric indicators of malnutrition (stunting, wasting and underweight), stunting is the most prevalent among the children aged 0-4 years. Nearly one-third (32.4 percent) of the children under the age of five years are stunted (short for their age) compared to 15.5 per cent for wasted (underweight for age for height) and 25.8 per cent for underweight (underweight for their height for age). Stunting is higher in rural children (33.6 per cent) than in urban children (30.0 per cent), while children of the poor in both rural and urban areas are worse off relative to the national average. However, the urban rates for both wasting and underweight are considerably higher than the rural rates, and the urban rates are higher than the national average, while the rural rates are lower. While the level of underweight barely changed over the five year period, (26.0 per cent, in 1997), the rates of stunting and wasting have worsened, and in the case of wasting, it is more than double the 1997 rate (6.5 per cent).

Availability of Employment

The proportion of the population aged 15 years and older who are unemployed averaged 5.4 percent, a slight increase over the 1997 figure (4.6 per cent). The proportion for urban areas (7.6 per cent) is about twice that of rural areas (3.5 per cent). The underemployment rate stood at 13.6 per cent, with the rural rate being 14.9 per cent, and urban, 12.1 per cent.

Meeting Food Needs

More than a tenth (12.8 per cent) of the households report having problems to meet their basic food needs. However, this problem is more prevalent among the rural poor. The proportion of rural households that have difficulty meeting their basic food needs is slightly higher (13.8 per cent) than for urban areas (11.6 per cent).

Access to Water

More than 90 per cent of households are within 30 minutes of their source of drinking water, compared to 82.1 per cent recorded in 1997. Both the rural and urban households record an access level of over 90 per cent. The rural poor have a lower access rate of 83.1 per cent, compared to 94.9 per cent for the urban poor.

Improved Water Source

The quality of drinking water is of great importance to the health of every individual. A higher percentage of households obtain their drinking water from improved water sources- pipe water in the dwelling, outdoor tap, borehole, and protected well-(74.1 per cent), compared to the 1997 figure of 65.2 per cent. Urban households record a higher percentage than rural households (87.3 per cent and 63.0 per cent, respectively), with over 20 percentage points difference.

Safe Sanitation

Safe sanitation, defined as the use of flush toilet, covered pit latrine and VIP/KVIP, is available to 55 per cent of households. Although this represents an improvement over the 1997 rate of 45.8 per cent, safe sanitation is more of an urban (80.9 per cent) than rural phenomenon (33.1 per cent). Safe sanitation facilities are even scarcer among the rural poor, with only 9.2 per cent of their households with these facilities. Moreover, the proportion of urban poor households with safe sanitation (66.9 per cent), is

Abstract

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.

Geographic coverage

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

Analysis unit

• Household
• Individual

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

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.

Mode of data collection

Face-to-face [f2f]

Research instrument

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.

Cleaning operations

The Statistical Package for Social Science (SPSS) was used to clean and harmonize the datasets.

Response rate

For the total sample, the response rate was 93.0% (91.2% in urban areas and 95.6% in rural areas).

Sampling error estimates

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

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%.

Abstract

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 50% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE CENTRAL AGENCY FOR PUBLIC MOBILIZATION AND STATISTICS (CAPMAS)

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 First Survey that covered all the country governorates was carried out in 1958/1959 followed by a long series of similar surveys. The current survey, HIECS 2021/2022, is the Thirteenth in this long series. Starting 2008/2009, Household Income, Expenditure and Consumption Surveys were conducted each two years instead of five years. this would enable better tracking of the rapid changes in the level of the living standards of the Egyptian households.

The CAPMAS also is pleased to disseminate the results of this survey to policy makers, researchers and scholarly to help in policy making and conducting development related researches and studies

The survey 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.

• To provide a time series of the most important data related to dominant standard of living from economic and social perspective. This will enable conducting comparisons based on the results of these time series. In addition to, the possibility of performing geographical comparisons.

The raw survey data provided by the Statistical Agency were cleaned and harmonized by the Economic Research Forum, in the context of a major project that started in 2009. During which extensive efforts have been exerted to acquire, clean, harmonize, preserve and disseminate micro data of existing household surveys in several Arab countries.

Geographic coverage

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

Analysis unit

1- Household/family. 2- Individual/person.

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample of HIECS 2021/2022 is a self-weighted two-stage stratified cluster sample. The main elements of the sampling design are described in the following.

1- Sample Size The sample size is around 27 thousand households. It was distributed between urban and rural with the percentages around 46% and 54%, respectively.

2- Cluster size The cluster size is 20 households in all governorates.

3- Sample allocation in different governorates

The sample was distributed on urban/rural areas in different governorates proportionally with the household size A sample size of a minimum of 1000 households was allocated to each governorate to ensure accuracy of poverty indicators. Therefore, the sample size was increased in Port-Said, Suez, Ismailiya, kafr el-Sheikh, Damietta, Bani Suef, Fayoum, Qena, Luxor and Aswan, by compensation from other governorates where the sample size exceeds a 1000 households. All Frontier governorates were considered as one governorate.

4- Core Sample The core sample is 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 and distributed on urban and rural areas of all governorates. It is a representative sample for the individual characteristics of the Egyptian society. This sample was implemented in January 2010 and its size reached more than 1 million household selected from 5024 enumeration areas distributed on all governorates (urban/rural) proportionally with the sample size (the enumeration area size is around 200 households). The core sample is the sampling frame from which the samples for the surveys conducted by CAPMAS are pulled, such as the Labor Force Surveys, Income, Expenditure And Consumption Survey, Household Urban Migration Survey, ...etc, in addition to other samples that may be required for outsources.

A more detailed description of the different sampling stages and allocation of sample across governorates is provided in the Methodology document available among external resources in Arabic.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three different questionnaires have been designed as following:

1- Expenditure and Consumption Questionnaire. 2- Assisting questionnaire. 3- Income Questionnaire.

In designing the questionnaires of expenditure, consumption and income, we were taking into our consideration the following: - Using the recent concepts and definitions of International Labor Organization approved in the International Convention of Labor Statisticians held in Geneva, 2003. - Using the recent Classification of Individual Consumption According to Purpose (COICOP). - Using more than one approach of expenditure measurement to serve many purposes of the survey.

A brief description of each questionnaire is given next:

----> 1- Expenditure and Consumption Questionnaire This questionnaire comprises 14 tables in addition to identification and geographic data of household on the cover page. The questionnaire is divided into two main sections.

Section one: Household schedule and other information, it includes: - Demographic characteristics and basic data for all household individuals consisting of 25 questions for every person. - Members of household who are currently working abroad. - The household ration card. - The main outlets that provide food and beverage. - Domestic and foreign tourism. - The housing conditions including 16 questions. - Household ownership of means of transportation, communication and domestic appliances. - Date of purchase, status at purchase, purchase value and current imputed value of the household possessed appliances and means of transportation. - The Duration since the household was established - The main outlet that provides fabrics, clothes and footwear. -This section includes some questions which help to define the social and economic level of households which in turn, help interviewers to check the plausibility of expenditure, consumption and income data.

Section two: Expenditure and consumption data It includes 14 tables as follows: 1- The quantity and value of food and beverages