As of September 2024, Mumbai had the highest cost of living among other cities in the country, with an index value of ****. Gurgaon, a satellite city of Delhi and part of the National Capital Region (NCR) followed it with an index value of ****.  What is cost of living? The cost of living varies depending on geographical regions and factors that affect the cost of living in an area include housing, food, utilities, clothing, childcare, and fuel among others. The cost of living is calculated based on different measures such as the consumer price index (CPI), living cost indexes, and wage price index. CPI refers to the change in the value of consumer goods and services. The wage price index, on the other hand, measures the change in labor services prices due to market pressures. Lastly, the living cost indexes calculate the impact of changing costs on different households. The relationship between wages and costs determines affordability and shifts in the cost of living. Mumbai tops the list Mumbai usually tops the list of most expensive cities in India. As the financial and entertainment hub of the country, Mumbai offers wide opportunities and attracts talent from all over the country. It is the second-largest city in India and has one of the most expensive real estates in the world.

VITAL SIGNS INDICATOR Poverty (EQ5)

FULL MEASURE NAME The share of the population living in households that earn less than 200 percent of the federal poverty limit

LAST UPDATED December 2018

DESCRIPTION Poverty refers to the share of the population living in households that earn less than 200 percent of the federal poverty limit, which varies based on the number of individuals in a given household. It reflects the number of individuals who are economically struggling due to low household income levels.

DATA SOURCE U.S Census Bureau: Decennial Census http://www.nhgis.org (1980-1990) http://factfinder2.census.gov (2000)

U.S. Census Bureau: American Community Survey Form C17002 (2006-2017) http://api.census.gov

METHODOLOGY NOTES (across all datasets for this indicator) The U.S. Census Bureau defines a national poverty level (or household income) that varies by household size, number of children in a household, and age of householder. The national poverty level does not vary geographically even though cost of living is different across the United States. For the Bay Area, where cost of living is high and incomes are correspondingly high, an appropriate poverty level is 200% of poverty or twice the national poverty level, consistent with what was used for past equity work at MTC and ABAG. For comparison, however, both the national and 200% poverty levels are presented.

For Vital Signs, the poverty rate is defined as the number of people (including children) living below twice the poverty level divided by the number of people for whom poverty status is determined. Poverty rates do not include unrelated individuals below 15 years old or people who live in the following: institutionalized group quarters, college dormitories, military barracks, and situations without conventional housing. The household income definitions for poverty change each year to reflect inflation. The official poverty definition uses money income before taxes and does not include capital gains or noncash benefits (such as public housing, Medicaid, and food stamps). For the national poverty level definitions by year, see: https://www.census.gov/hhes/www/poverty/data/threshld/index.html For an explanation on how the Census Bureau measures poverty, see: https://www.census.gov/hhes/www/poverty/about/overview/measure.html

For the American Community Survey datasets, 1-year data was used for region, county, and metro areas whereas 5-year rolling average data was used for city and census tract.

To be consistent across metropolitan areas, the poverty definition for non-Bay Area metros is twice the national poverty level. Data were not adjusted for varying income and cost of living levels across the metropolitan areas.

In 2023, the U.S. Consumer Price Index was 309.42, and is projected to increase to 352.27 by 2029. The base period was 1982-84. The monthly CPI for all urban consumers in the U.S. can be accessed here. After a time of high inflation, the U.S. inflation rateis projected fall to two percent by 2027. United States Consumer Price Index ForecastIt is projected that the CPI will continue to rise year over year, reaching 325.6 in 2027. The Consumer Price Index of all urban consumers in previous years was lower, and has risen every year since 1992, except in 2009, when the CPI went from 215.30 in 2008 to 214.54 in 2009. The monthly unadjusted Consumer Price Index was 296.17 for the month of August in 2022. The U.S. CPI measures changes in the price of consumer goods and services purchased by households and is thought to reflect inflation in the U.S. as well as the health of the economy. The U.S. Bureau of Labor Statistics calculates the CPI and defines it as, "a measure of the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services." The BLS records the price of thousands of goods and services month by month. They consider goods and services within eight main categories: food and beverage, housing, apparel, transportation, medical care, recreation, education, and other goods and services. They aggregate the data collected in order to compare how much it would cost a consumer to buy the same market basket of goods and services within one month or one year compared with the previous month or year. Given that the CPI is used to calculate U.S. inflation, the CPI influences the annual adjustments of many financial institutions in the United States, both private and public. Wages, social security payments, and pensions are all affected by the CPI.

The Consumer Price Index (CPI) measures over time the prices of goods and services in major expenditure categories typically purchased by urban consumers. The expenditure categories include food, housing, apparel, transportation, and medical care. Essentially, the Index measures consumer purchasing power by comparing the cost of a fixed set of goods and services (called a market basket) in a specific month relative to the cost of the same market basket in an earlier reference period, designated as the base period. The CPI is calculated for two population groups: urban wage earners and clerical workers (CPI-W) and all urban consumers (CPI-U). The CPI-W population includes those urban families with clerical workers, sales workers, craft workers, operatives, service workers, or laborers in the family unit and is representative of the prices paid by about 40 percent of the United States population. The CPI-U population consists of all urban households (including professional and salaried workers, part-time workers, the self-employed, the unemployed, and retired persons) and is representative of the prices paid by about 80 percent of the United States population. Both populations specifically exclude persons in the military, in institutions, and all persons living outside of urban areas (such as farm families). National indexes for both populations are available for about 350 consumer items and groups of items. In addition, over 100 of the indexes have been adjusted for seasonality. The indexes are monthly with some beginning in 1913. Area indexes are available for 27 urban places. For each area, indexes are presented for about 65 items and groups. The area indexes are produced monthly for 5 areas, bimonthly for 10 areas, and semiannually for 12 urban areas. Regional indexes are available for four regions with about 95 items and groups per region. Beginning with January 1987, regional indexes are monthly, with some beginning as early as 1966. City-size indexes are available for four size classes with about 95 items and groups per class. Beginning with January 1987, these indexes are monthly and most begin in 1977. Regional and city-size indexes are available cross-classified by region and city-size class. For each of the 13 cross-classifications, about 60 items and groups are available. Beginning with January 1987, these indexes are monthly and most begin in 1977. Each index record includes a series identification code that specifies the sample (either all urban consumers or urban wage earners and clerical workers), seasonality (either seasonally adjusted or unadjusted), periodicity (either semiannual or regular), geographic area, index base period, and item number of the index. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR08166.v3. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future and includes additional years of data.

This statistic illustrates the monthly Consumer Price Index (CPI) for living room and dining room furniture in Italy from January 2018 to May 2024, where the year 2015 is 100. Inflation is measured through the construction of the Consumer Price Index, that measures changes in prices of a ‘basket’ of goods and services representative of households consumer expenditure in a specific year. Over the period under consideration, the CPI increased, reaching to 119.3 points in May 2024.

CPIH is the most comprehensive measure of inflation. It extends CPI to include a measure of the costs associated with owning, maintaining and living in one's own home, known as owner occupiers' housing costs (OOH), along with council tax. This dataset provides CPIH time series (2005 to latest published month), allowing users to customise their own selection, view or download.

The Consumer Price Index measures changes in the cost of selected food items over time like: * food purchased from stores * fresh or frozen beef * fresh or frozen pork * fresh or frozen chicken * dairy products and eggs * bakery products * fresh fruit * fresh vegetables * food purchased from restaurants

In 2023, Chiang Mai led among major cities in Thailand with the highest local purchasing power index score at **** points. This was followed by Bangkok with around ** index points.

VITAL SIGNS INDICATOR Poverty (EQ5)

FULL MEASURE NAME The share of the population living in households that earn less than 200 percent of the federal poverty limit

LAST UPDATED December 2018

DESCRIPTION Poverty refers to the share of the population living in households that earn less than 200 percent of the federal poverty limit, which varies based on the number of individuals in a given household. It reflects the number of individuals who are economically struggling due to low household income levels.

DATA SOURCE U.S Census Bureau: Decennial Census http://www.nhgis.org (1980-1990) http://factfinder2.census.gov (2000)

U.S. Census Bureau: American Community Survey Form C17002 (2006-2017) http://api.census.gov

METHODOLOGY NOTES (across all datasets for this indicator) The U.S. Census Bureau defines a national poverty level (or household income) that varies by household size, number of children in a household, and age of householder. The national poverty level does not vary geographically even though cost of living is different across the United States. For the Bay Area, where cost of living is high and incomes are correspondingly high, an appropriate poverty level is 200% of poverty or twice the national poverty level, consistent with what was used for past equity work at MTC and ABAG. For comparison, however, both the national and 200% poverty levels are presented.

For Vital Signs, the poverty rate is defined as the number of people (including children) living below twice the poverty level divided by the number of people for whom poverty status is determined. Poverty rates do not include unrelated individuals below 15 years old or people who live in the following: institutionalized group quarters, college dormitories, military barracks, and situations without conventional housing. The household income definitions for poverty change each year to reflect inflation. The official poverty definition uses money income before taxes and does not include capital gains or noncash benefits (such as public housing, Medicaid, and food stamps). For the national poverty level definitions by year, see: https://www.census.gov/hhes/www/poverty/data/threshld/index.html For an explanation on how the Census Bureau measures poverty, see: https://www.census.gov/hhes/www/poverty/about/overview/measure.html

For the American Community Survey datasets, 1-year data was used for region, county, and metro areas whereas 5-year rolling average data was used for city and census tract.

To be consistent across metropolitan areas, the poverty definition for non-Bay Area metros is twice the national poverty level. Data were not adjusted for varying income and cost of living levels across the metropolitan areas.

This is a historical measure for Strategic Direction 2023. For more data on Austin demographics please visit austintexas.gov/demographics. This measure answers the question of what number and percentage of residents are living below the federal poverty level, which means they meet certain thresholds set by a set of parameters and computation performed by the Census Bureau. Following the Office of Management and Budget's (OMB) Statistical Policy Directive 14, the Census Bureau uses a set of money income thresholds that vary by family size and composition to determine who is in poverty. If a family's total income is less than the family's threshold, then that family and every individual in it is considered in poverty. The official poverty thresholds do not vary geographically, but they are updated for inflation using the Consumer Price Index (CPI-U). The official poverty definition uses money income before taxes and does not include capital gains or noncash benefits (such as public housing, Medicaid, and food stamps). Data collected from the U.S. Census Bureau, American Communities Survey (1yr), Poverty Status in the Past 12 Months (Table S1701). American Communities Survey (ACS) is a survey with sampled statistics on the citywide level and is subject to a margin of error. ACS sample size and data quality measures can be found on the U.S. Census website in the Methodology section. View more details and insights related to this data set on the story page:https://data.austintexas.gov/stories/s/kgf9-tcgd

Abstract

The CPI is a current social and economic indicator constructed to measure changes over time in the general level of prices of consumer goods and services that households acquire, use, or pay for. The index measures changes in consumer prices over time by measuring the cost of purchasing a fixed basket of consumer goods and services of constant quality and similar characteristics. The products in the basket are selected to be representative of households' expenditure during a specific year. Such an index is called a fixed-basket price index. Changes in the index reflect the effects of price changes on the cost of achieving a constant standard of living.

The South African CPI has three equally important objectives: 1. To measure inflation in the economy so that macroeconomic policy is based on comprehensive and up-to-date price information. 2. To measure changes in the cost of living of South African households to promote equity in measures taken to adjust wages, grants, service agreements and contracts. 3. To provide a deflator for consumer expenditure in the national accounts and other economic data, to compute volume (as opposed to nominal) estimates.

In compiling the South African CPI, Stats SA largely follows the methodology guidelines in the 2020 Consumer Price Index Manual: Concepts and Methods published jointly by the International Monetary Fund, International Labour Organization, Statistical Office of the European Union, United Nations Economic Commission for Europe, Organisation for Economic Co-operation and Development, and World Bank.

Kind of data

Time-Series

In January 2025, the unadjusted consumer price index (CPI) of all items for urban consumers in the United States amounted to about 317.67. The data represents U.S. city averages. The base period was 1982-84=100. The CPI is defined by the United States Bureau of Labor Statistics as “a measure of the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services”. The annual consumer price index for urban consumers in the U.S. can be accessed here. Consumer Price Index The Consumer Price Index (CPI) began in 1919 under the Bureau of Labor Statistics and is published every month. The CPI for all urban consumers includes urban households in Metropolitan Statistical Areas and regions with over 2,500 inhabitants, as well as non-farm consumers living in rural regions. This index was established in 1978 and includes about 80 percent of the U.S. population. The monthly CPI of urban consumers in the United States increased from 292.3 in May 2022 to 304.13 in 2023. Inflation tends not to impact everyone equally for a variety of reasons, including geography - CPI often differs between regions, with a high of 287.49 in the Western region as of 2021. There are also disparities in inflation between income quartiles, in which inflation is generally felt more heavily by lower income households. The annual CPI in the United States has increased steadily over the past two decades, from 140.3 in 1992 to 292.56 in 2022. A forecast of the CPI expects this positive trend to continue, reaching 325.6 by 2027. As of March 2023, the CPI of the nation’s education had increased by 3.5 percent. Further, in the same month costs of recreation, rent, housing, medical care, and food and beverages, gasoline, and transportation increased. Comparatively, the CPI in Hong Kong reached 103.3 in 2022.

Consumer Price Index CPI in Kenya increased to 145.58 points in June from 144.88 points in May of 2025. This dataset provides the latest reported value for - Kenya Consumer Price Index (CPI) - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Survey for the calculation of the Active Ageing Index of the City of Madrid. OBJECTIVE OF THE STUDY: Know the result of certain indicators that allow to calculate the Active Ageing Index. The Active Ageing Index is an ideal tool both for comparison with other areas or cities and for its value in long-term longitudinal monitoring. Compare the potential of older people to have active and healthy aging. The index measures the independent standard of living of older people, their participation in paid work and social activities, as well as their ability to age actively. It is carried out for citizens over 55 years of age residing in the municipality of Madrid. It is part of the evaluation of the Madrid Plan Friendly with the Elderly, as an impact indicator. It consists of 22 indicators that are grouped into four dimensions: employment, social participation, independent and safe living, and capacity for healthy ageing.

Historical (real-time) releases of the measures of core inflation, with data from 1989 (not all combinations necessarily have data for all years). Data are presented for the current release and previous four releases. Users can select other releases that are of interest to them.

The underlying data are used to provide inputs for both the Vision indicator on the global population living in poverty as well as the Client Context indicator on the percentage of the population in FCV countries living in poverty. The Vision indicator measures the percentage of the population living on less than $6.85 a day in 2017 purchasing power parity (PPP) adjusted prices. Measures are based on internationally comparable poverty lines hold the real value of the poverty line constant across countries when making national and temporal comparisons. The threshold of $6.85 corresponds to the median poverty line for upper-middle-income countries.[1] _ [1] See Joliffe et al. (2022) for more details related to the assignment of poverty lines.

Structure: I) General information on the social indicator systemIa) Background II) The dimension of life: Housing I) General information on the social indicator system The time series of the European System of Social Indicators (EUSI) are´social indicators´ used to measure social welfare and social change. The conceptual framework builds on the theoretical discussion of welfare, quality of life and the goals of social development oriented towards them.The basis for defining these indicators is a concept of quality of life that encompasses different areas of life in society. Each area of life can be divided into several target areas. Target dimensions have been defined for the individual target areas, for each of which a set of social indicators (= time series, statistical measures) has been defined. The EUSI indicator time series combine objective living conditions (factual living conditions such as working conditions, income development) and subjective well-being (perceptions, assessments, evaluations) of the population.The time series starts in 1980 and end in 2013.They make it possible to understand social developments by reliable and, over time, comparable data between European countries.They are an important complement to national accounts indicators.EUSI indicators are part of an ongoing debate at European level on measuring welfare and quality of life, which has led to various initiatives by statistical offices in Europe. Ia) Background The social indicator system is the result of a discussion sparked off in the 1970s to measure a country´s prosperity development. Hans-Jürgen Krupp and Wolfgang Zapf initiated this discussion. Together they pointed out in 1972 in an expert opinion for the German Council of Economic Experts that the gross domestic product in particular and the parameters of national accounts (NA) in general are not sufficient to measure social welfare or ignore important aspects. (see:Krupp, H.-J. and Zapf, W. (1977), The role of alternative indicators of prosperity in assessing macroeconomic development. Council for Social and Economic Data, Working Paper No. 171, reprint of the report for the Council of Economic Experts of September 1972: 2011) They developed a multidimensional concept of quality of life in which, in addition to national accounts, the individual development possibilities and the possibilities perceived by individuals for satisfying their needs in different areas of life are also taken into account.The authors define the quality of life as ´the extent to which individuals perceive the satisfaction of their needs´ (1977, reprint: 2011, p. 4). Thus, the purely national economic concept of growth and prosperity is supplemented by categories of sociology and political science, in which ´quality of life is (represents) a positive objective against which efforts to measure and evaluate performance and deficits in the individual areas of life and for different social groups should be oriented´. (Krupp/Zapf, 1977, reprint: 2011, p. 5) In this way, the authors promote comprehensive social reporting that measures the achievement of welfare goals in society.The authors explain the concept of social indicators as follows: ´Social indicators are statistics that differ from usual statistics in several ways.They should measure performance, not the expenditure.They should primarily refer to the welfare of individuals and certain social groups, not to the activities of authorities; however, a whole range of aggregate sizes cannot be dispensed with.They should inform about change processes, i.e., be presented in the form of time series.They should be in a theoretical context, i.e., their causal relationship to the´indicator date´ should be as clear as possible. (… )Social indicators are statistics that often lie far outside the official survey programmes (...)´. (Krupp/ Zapf, 1977, p. 14) Compared to official government reporting, the system of social indicators represents independent reporting (cf. Krupp/Zapf 1977, p. 7) and also includes survey research in addition to official data. Based on the theoretical concept of quality of life, the structural parameters of the indicator system were defined. This means that the areas of life and the target and measurement dimensions belonging to them are operationalized. This initially results in a multidimensional structure with the following levels:1) The current ten areas of life are the highest level.They have published in histat under the topic ´SIMon: Social Indicators Monitor 1950-2013´.as individual studies.2) The second level is the target areas.Several target areas are assigned to each area of life. They appear as tables in the respective studies.3) The third level is the target dimensions (also called measurement dimensions). This is a subarea that is meaningful for the higher-level life area and for which data is collected for the corresponding target area. For example, a table on the´objective living conditions´ is offered for t...

Abstract

The main objectives of the 2018/19 NLSS are: i) to provide critical information for production of a wide range of socio-economic and demographic indicators, including for benchmarking and monitoring of SDGs; ii) to monitor progress in population’s welfare; iii) to provide statistical evidence and measure the impact on households of current and anticipated government policies. In addition, the 2018/19 NLSS could be utilized to improve other non-survey statistical information, e.g. to determine and calibrate the contribution of final consumption expenditures of households to GDP; to update the weights and determine the basket for the national Consumer Price Index (CPI); to improve the methodology and dissemination of micro-economic and welfare statistics in Nigeria.

The 2018/19 NLSS collected a comprehensive and diverse set of socio-economic and demographic data pertaining to the basic needs and conditions under which households live on a day to day basis. The 2018/19 NLSS questionnaire includes wide-ranging modules, covering demographic indicators, education, health, labour, expenditures on food and non-food goods, non-farm enterprises, household assets and durables, access to safety nets, housing conditions, economic shocks, exposure to crime and farm production indicators.

Geographic coverage

National coverage

Analysis unit

• Households
• Individuals
• Communities

Universe

The survey covered all de jure households excluding prisons, hospitals, military barracks, and school dormitories.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2018/19 NLSS sample is designed to provide representative estimates for the 36 states and the Federal Capital Territory (FCT), Abuja. By extension. The sample is also representative at the national and zonal levels. Although the sample is not explicitly stratified by urban and rural areas, it is possible to obtain urban and rural estimates from the NLSS data at the national level. At all stages, the relative proportion of urban and rural EAs as has been maintained.

Before designing the sample for the 2018/19 NLSS, the results from the 2009/10 HNLSS were analysed to extract the sampling properties (variance, design effect, etc.) and estimate the required sample size to reach a desired precision for poverty estimates in the 2018/19 NLSS.

EA SELECTION: The sampling frame for the 2018/19 NLSS was based on the national master sample developed by the NBS, referred to as the NISH2 (Nigeria Integrated Survey of Households 2). This master sample was based on the enumeration areas (EAs) defined for the 2006 Nigeria Census Housing and Population conducted by National Population Commission (NPopC). The NISH2 was developed by the NBS to use as a frame for surveys with state-level domains. NISH2 EAs were drawn from another master sample that NBS developed for surveys with LGA-level domains (referred to as the “LGA master sample”). The NISH2 contains 200 EAs per state composed of 20 replicates of 10 sample EAs for each state, selected systematically from the full LGA master sample. Since the 2018/19 NLSS required domains at the state-level, the NISH2 served as the sampling frame for the survey.

Since the NISH2 is composed of state-level replicates of 10 sample EAs, a total of 6 replicates were selected from the NISH2 for each state to provide a total sample of 60 EAs per state. The 6 replicates selected for the 2018/19 NLSS in each state were selected using random systematic sampling. This sampling procedure provides a similar distribution of the sample EAs within each state as if one systematic sample of 60 EAs had been selected directly from the census frame of EAs.

A fresh listing of households was conducted in the EAs selected for the 2018/19 NLSS. Throughout the course of the listing, 139 of the selected EAs (or about 6%) were not able to be listed by the field teams. The primary reason the teams were not able to conduct the listing in these EAs was due to security issues in the country. The fieldwork period of the 2018/19 NLSS saw events related to the insurgency in the north east of the country, clashes between farmers and herdsman, and roving groups of bandits. These events made it impossible for the interviewers to visit the EAs in the villages and areas affected by these conflict events. In addition to security issues, some EAs had been demolished or abandoned since the 2006 census was conducted. In order to not compromise the sample size and thus the statistical power of the estimates, it was decided to replace these 139 EAs. Additional EAs from the same state and sector were randomly selected from the remaining NISH2 EAs to replace each EA that could not be listed by the field teams. This necessary exclusion of conflict affected areas implies that the sample is representative of areas of Nigeria that were accessible during the 2018/19 NLSS fieldwork period. The sample will not reflect conditions in areas that were undergoing conflict at that time. This compromise was necessary to ensure the safety of interviewers.

HOUSEHOLD SELECTION: Following the listing, the 10 households to be interviewed were selected from the listed households. These households were selected systemically after sorting by the order in which the households were listed. This systematic sampling helped to ensure that the selected households were well dispersed across the EA and thereby limit the potential for clustering of the selected households within an EA.

Occasionally, interviewers would encounter selected households that were not able to be interviewed (e.g. due to migration, refusal, etc.). In order to preserve the sample size and statistical power, households that could not be interviewed were replaced with an additional randomly selected household from the EA. Replacement households had to be requested by the field teams on a case-by-case basis and the replacement household was sent by the CAPI managers from NBS headquarters. Interviewers were required to submit a record for each household that was replaced, and justification given for their replacement. These replaced households are included in the disseminated data. However, replacements were relatively rare with only 2% of sampled households not able to be interviewed and replaced.

Sampling deviation

Although a sample was initially drawn for Borno state, the ongoing insurgency in the state presented severe challenges in conducting the survey there. The situation in the state made it impossible for the field teams to reach large areas of the state without compromising their safety. Given this limitation it was clear that a representative sample for Borno was not possible. However, it was decided to proceed with conducting the survey in areas that the teams could access in order to collect some information on the parts of the state that were accessible.

The limited area that field staff could safely operate in in Borno necessitated an alternative sample selection process from the other states. The EA selection occurred in several stages. Initially, an attempt was made to limit the frame to selected LGAs that were considered accessible. However, after selection of the EAs from the identified LGAs, it was reported by the NBS listing teams that a large share of the selected EAs were not safe for them to visit. Therefore, an alternative approach was adopted that would better ensure the safety of the field team but compromise further the representativeness of the sample. First, the list of 788 EAs in the LGA master sample for Borno were reviewed by NBS staff in Borno and the EAs they deemed accessible were identified. The team identified 359 EAs (46%) that were accessible. These 359 EAs served as the frame for the Borno sample and 60 EAs were randomly selected from this frame. However, throughout the course of the NLSS fieldwork, additional insurgency related events occurred which resulted in 7 of the 60 EAs being inaccessible when they were to be visited. Unlike for the main sample, these EAs were not replaced. Therefore, 53 EAs were ultimately covered from the Borno sample. The listing and household selection process that followed was the same as for the rest of the states.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Two sets of questionnaires – household and community – were used to collect information in the NLSS2018/19. The Household Questionnaire was administered to all households in the sample. The Community Questionnaire was administered to the community to collect information on the socio-economic indicators of the enumeration areas where the sample households reside.

Household Questionnaire: The Household Questionnaire provides information on demographics; education; health; labour; food and non-food expenditure; household nonfarm income-generating activities; food security and shocks; safety nets; housing conditions; assets; information and communication technology; agriculture and land tenure; and other sources of household income.

Community Questionnaire: The Community Questionnaire solicits information on access to transported and infrastructure; community organizations; resource management; changes in the community; key events; community needs, actions and achievements; and local retail price information.

Cleaning operations

CAPI: The 2018/19 NLSS was conducted using the Survey Solutions Computer Assisted Person Interview (CAPI) platform. The Survey Solutions software was developed and maintained by the Development Economics Data Group (DECDG) at the World Bank. Each interviewer and supervisor was given a tablet

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

This measure answers the question of what number and percentage of residents are living below the federal poverty level, which means they meet certain threshold set by a set of parameters and computation performed by the Census Bureau. Following the Office of Management and Budget's (OMB) Statistical Policy Directive 14, the Census Bureau uses a set of money income thresholds that vary by family size and composition to determine who is in poverty. If a family's total income is less than the family's threshold, then that family and every individual in it is considered in poverty. The official poverty thresholds do not vary geographically, but they are updated for inflation using the Consumer Price Index (CPI-U). The official poverty definition uses money income before taxes and does not include capital gains or noncash benefits (such as public housing, Medicaid, and food stamps). Data collected from the U.S. Census Bureau, American Communities Survey (1yr), Poverty Status in the Past 12 Months (Table S1701). American Communities Survey (ACS) is a survey with sampled statistics on the citywide level and is subject to a margin of error. ACS sample size and data quality measures can be found on the U.S. Census website in the Methodology section.