United States US: GDP: Growth: Household Final Consumption Expenditure per Capita data was reported at 1.981 % in 2016. This records a decrease from the previous number of 2.862 % for 2015. United States US: GDP: Growth: Household Final Consumption Expenditure per Capita data is updated yearly, averaging 2.181 % from Dec 1971 (Median) to 2016, with 46 observations. The data reached an all-time high of 5.003 % in 1972 and a record low of -2.460 % in 2009. United States US: GDP: Growth: Household Final Consumption Expenditure per Capita data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Gross Domestic Product: Annual Growth Rate. Annual percentage growth of household final consumption expenditure per capita, which is calculated using household final consumption expenditure in constant 2010 prices and World Bank population estimates. Household final consumption expenditure (private consumption) is the market value of all goods and services, including durable products (such as cars, washing machines, and home computers), purchased by households. It excludes purchases of dwellings but includes imputed rent for owner-occupied dwellings. It also includes payments and fees to governments to obtain permits and licenses. Here, household consumption expenditure includes the expenditures of nonprofit institutions serving households, even when reported separately by the country.; ; World Bank national accounts data, and OECD National Accounts data files.; Weighted Average;

The average for 2023 based on 46 countries was 36.77 billion U.S. dollars. The highest value was in Egypt: 327 billion U.S. dollars and the lowest value was in the Comoros: 1.35 billion U.S. dollars. The indicator is available from 1960 to 2023. Below is a chart for all countries where data are available.

This dataset contains the load curves of various household appliances with a fine resolution (1 second) collected during 2020 over a period of one month using connected sockets installed in 13 households. ### Description of data #### 1. Information about connected sockets The file ‘smart_plug_devices.csv’ contains information about the 46 connected sockets that allowed power consumption readings. The file contains the following columns: | Column | Comments | | — | — - | | id | Id of the socket | | first_ts | Date of the first measure available| | last_ts |Date of the latest measure available| | available_duration | Total duration of measurements available (number of days)| | plug_name | Name of device connected to the socket| | appliance_category | Category of device connected to the socket| | how | Possible comments on the connected device| | files_names | Associated csv filename| | power_max | Maximum registered power (W)| The possible categories of the column ‘appliance_category’ based on the column ‘plug_name’ are as follows: — Multimedia = [computer, 3D_printer, internet_router, laptop, phone_charger, printer, screen, tv, sound_system] — Kitchen = [boiler, coffee, freezer, fridge, micro_wave_oven] — washing = [dishwasher, dryer, washing_machine] — Cooling = [air_conditioner, fan] — Other = [air_purify, dehumidifier, radiator, solar_panel, vacuum] #### 2. Data collected The file ‘data_smart_plugs.zip’ contains the ‘data’ folder in which there are 46 csv files corresponding to each row of the file ‘smart_plug_devices.csv’ (see previous section). File names can be found in the ‘files_names’ column of the file ‘smart_plug_devices.csv’ and are constructed as follows: ‘_.csv’ Each file contains the following columns: | Column | Comments | | — | — - | | timestamp | Date and time of measurement | | power | Power (W)| ## Contact For any questions or requests regarding this dataset, please contact research@ecoco2.com.

Japan JP: GDP: Growth: Household Final Consumption Expenditure per Capita data was reported at 0.176 % in 2016. This records an increase from the previous number of 0.074 % for 2015. Japan JP: GDP: Growth: Household Final Consumption Expenditure per Capita data is updated yearly, averaging 1.928 % from Dec 1971 (Median) to 2016, with 46 observations. The data reached an all-time high of 7.897 % in 1973 and a record low of -1.976 % in 1974. Japan JP: GDP: Growth: Household Final Consumption Expenditure per Capita data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Japan – Table JP.World Bank.WDI: Gross Domestic Product: Annual Growth Rate. Annual percentage growth of household final consumption expenditure per capita, which is calculated using household final consumption expenditure in constant 2010 prices and World Bank population estimates. Household final consumption expenditure (private consumption) is the market value of all goods and services, including durable products (such as cars, washing machines, and home computers), purchased by households. It excludes purchases of dwellings but includes imputed rent for owner-occupied dwellings. It also includes payments and fees to governments to obtain permits and licenses. Here, household consumption expenditure includes the expenditures of nonprofit institutions serving households, even when reported separately by the country.; ; World Bank national accounts data, and OECD National Accounts data files.; Weighted average;

These tables outline changes in the energy consumption and other characteristics of major household appliances shipped in Canada between 1990 and 2014.

Abstract

The energy statistics program has implemented many rounds of the Household Energy Survey during 1999-2011.

Because of the importance of the household sector and due to its large contribution to energy consumption in the Palestinian Territory, PCBS decided to conduct a special Household Energy Survey to cover energy indicators in the household sector. To achieve this, a questionnaire was attached to the Labor Force Survey.

This survey aimed to provide data on energy consumption in the household sector and to provide data on energy consumption behavior and patterns in the society by type of energy.

The survey presents data on energy indicators pertaining to households in the Palestinian Territory. This includes statistical data on electricity and other fuel consumption by households covering type of fuel for different activities (cooking, baking, heating, lighting, and water heating).

Geographic coverage

Geographic Coverage

Analysis unit

households

Universe

The target population was all Palestinian households living in the Palestinian Territory.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Frame The sample is a two-stage stratified cluster random sample.

Target Population: The target population was all Palestinian households whom are living in the Palestinian territory.

Sampling Frame: The sample of this survey is a part of the main sample of Labor Force Survey (LFS) which implemented periodically every quarter by PCBS since 1995, so this survey implement every quarter in the year (distributed over 13 weeks), the survey attached with the LFS in the first quarter of 2011, and the sample contain of 6 weeks from the eighth week to the thirteen week from the round 60 of labor force. The sample is two stage stratified cluster sample with two stages, first stage we selected a systematic random sample of 211 enumeration areas for the semi round, then in the second stage we select a random area sample of average 16 households from each enumeration area selected in the first stage.

Sampling Design: The sample of this survey is a sub-sample of the Labor Force Survey (LFS) sample, which has been conducted periodically since September 1995. The sample of LFS is distributed over 13 weeks. The sample of the survey occupies six weeks of the first quarter of 2011 within implementing LFS.

Stratification by number of households: In designing the sample of the LFS, three levels of stratification by number of households were made: Stratification by number of households: Stratification by place of residence which comprises: (a) Urban (b) Rural (c) Refugee camps Stratification by locality size.

Sample Unit: In the first stage, the sampling units are the enumeration areas (clusters) from the master sample. In the second stage, the sampling units are households.

Analysis Unit: The unit of analysis is the household.

Sample Size: The sample size is comprised of (3,313) Palestinian households in the West Bank and Gaza Strip, where this sample was distributed according to locality type (urban, rural and refugee camps).

Mode of data collection

Face-to-face [f2f]

Research instrument

The design of the questionnaire for the Household Energy Survey was based on the experiences of similar countries as well as on international standards and recommendations for the most important indicators, taking into account the special situation of the Palestinian Territory.

Cleaning operations

he data processing stage consisted of the following operations: Editing and coding before data entry: All questionnaires were edited and coded in the office using the same instructions adopted for editing in the field.

Data entry: At this stage, data was entered into the computer using a data entry template developed in Access. The data entry program was prepared to satisfy a number of requirements such as: · To prevent the duplication of the questionnaires during data entry. · To apply integrity and consistency checks of entered data. · To handle errors in user friendly manner. · The ability to transfer captured data to another format for data analysis using statistical analysis software such as SPSS.

Response rate

The survey sample consists of about 3313 households of which 3029 households completed the interview; whereas 1950 households from the West Bank and 1079 households in Gaza Strip. Weights were modified to account for non-response rate. The response rate in the West Bank reached 95. % while in the Gaza Strip it reached 98%.

Non-response cases

No of cases non-response cases
3029 Household completed 22 Traveling households
19 Unit does not exist 56 No one at home
22 Refused to cooperate
139 Vacant Housing unit 1 No available information
25 Other
3313 Total sample size

Sampling error estimates

It includes many aspects of the survey, mainly statistical errors due to the sample, and non statistical errors referring to the workers and tools of the survey. It includes also the response rates in the survey and their effect on the assumptions. This section includes:

Sampling Errors These types of errors evolved as a result of studying a part of the population and not all of it. Because this is a sampled survey, the data will be affected by sampling errors due to using a sample and not the whole frame of the population. Differences appear compared to the actual values that could be obtained through a census. For this survey, variance calculations were made for average household consumption and total consumption for the different types of energy in the Palestinian Territory.

The results of gasoline, wood, charcoal and olive cake suffer from a high variance. This problem should be taken into consideration when dealing with the average household consumption of these types of fuel, keeping in mind that there are no problems in publishing the data at the geographical level (North of the West Bank, Middle of the West Bank, South of the West Bank and Gaza Strip). However, publishing data at the governorate level is not possible due to the high variance, especially for wood, charcoal and olive cake. The variances for the main indicators of this survey are as follows:

95% Confidence Interval C.V % Standard Error Estimate Variable
Upper Lower Value Unit
99.9 99.5 0.001 0.1 99.8 % Main Electricity Source 66.2 61.2 0.020 1.3 63.7 % Use of Solar Heaters
98.5 97.5 0.003 0.2 98.1 % Use of LPG
273 259 0.013 3.44 266 KWh Average Electricity Consumption 264 191 0.081 18.47 228 Kg Average wood Consumption
50.5 41.8 0.047 2.19 46 Liter Average Gasoline Consumption

Non Sampling Errors These errors are due to non-response cases as well as the implementation of surveys. In this survey, these errors emerged because of (a) the special situation of the questionnaire itself, where some parts depend partially on estimation, (b) diversity of sources (e.g., the interviewers, respondents, editors, coders, data entry operator, etc).

The sources of these errors can be summarized as: Some of the households were not in their houses and the interviewers could not meet them. Some of the households did not give attention to the questions in questionnaire.
Some errors occurred due to the way the questions were asked by interviewers. Misunderstanding of the questions by the respondents. Answering the questions related to consumption by making estimations.

Data appraisal

The data of the survey is comparable geographically and over time by comparing the data between different geographical areas to data of previous surveys and census 2007.

GOLSPIE (Government On-Line Sustainability Performance Information Exchange) is the online platform for disclosure on the sustainability performance of the Scottish Government Estate Automatic Meter Readings provide utilities consumption readings every 30 minutes and will allow patterns of use to be identified on an individual building basis Data for 4 government buildings in Glasgow for electricity/gas consumption on a half-hourly and daily basis is accessed from the GOLSPIE database using SPARQL queries. Note that the queries only return the top 1000 records and to obtain more use the 'OFFSET' instruction Data provided dynamically through a query covering the period from 2013-01-01 to the current date. Licence: None highlanderhousedailyelectricity-sparql.txt - https://dataservices.open.glasgow.gov.uk/Download/Organisation/728522f0-86da-48c6-8f75-1649934eb8a4/Dataset/36c4af33-02a1-4f78-903f-f7d6018cdf38/File/6bdb10e8-987a-4150-b7b5-2f1e433ab6ef/Version/77c5e7ff-13c0-4b8e-abf6-8048741f471d Highlander House location data .html - https://dataservices.open.glasgow.gov.uk/Download/Organisation/728522f0-86da-48c6-8f75-1649934eb8a4/Dataset/36c4af33-02a1-4f78-903f-f7d6018cdf38/File/e462ed60-59aa-4678-95dc-35f4cbb27bab/Version/28186d53-34fc-46ac-a6fc-b34be7094021

Based on a survey conducted in 2023, most respondents with no electricity meter paid between 1,000 and 5,000 Nigerian naira (1.31 U.S. dollars and 6.54 U.S. dollars). Around 57 percent of the respondents spent within this pay band for electricity monthly via estimated or direct billing. Comparably, individuals with a post-paid meter (47 percent) and prepaid meter (46 percent) also paid from 1,000 to 5,000 Nigerian naira per month. Furthermore, only two percent of the respondents with post-paid meters reported paying over 51,000 Nigerian naira (66.67 U.S. dollars).

A single member household uses an average of 54 cubic meters of water annually in the United Kingdom. This figure almost doubled when there were two members per household and increased to approximately 191 cubic meters within a household of five. In terms of daily use, a single person household used an estimated 149 liters per day, with water usage amounting to 276 liters per day when two people lived at home. Baths consume the most water There are many household appliances that use water, such as dishwashers, washing machines or toilets, and each uses varying amounts. However, it is baths that use the largest quantity. On average, a bath consumes 80 liters of water per use. In comparison, a shower uses 46 liters per use. Household water bills The average household water bill in the UK differs from company to company. In 2018, customers of water supply and sewerage utility Wessex Water paid on average 245 British pounds for their water bill. This was the most expensive in the UK. Water bills were on average cheapest for customers of Southern Water, at an estimated 158 British pounds. Southern Water covers areas of East Kent, Sussex, Hampshire and the Isle of Wight.

United States US: GDP: Growth: Final Consumption Expenditure: Household data was reported at 2.733 % in 2016. This records a decrease from the previous number of 3.642 % for 2015. United States US: GDP: Growth: Final Consumption Expenditure: Household data is updated yearly, averaging 3.254 % from Dec 1971 (Median) to 2016, with 46 observations. The data reached an all-time high of 6.133 % in 1972 and a record low of -1.601 % in 2009. United States US: GDP: Growth: Final Consumption Expenditure: Household data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Gross Domestic Product: Annual Growth Rate. Annual percentage growth of household final consumption expenditure based on constant local currency. Aggregates are based on constant 2010 U.S. dollars. Household final consumption expenditure (formerly private consumption) is the market value of all goods and services, including durable products (such as cars, washing machines, and home computers), purchased by households. It excludes purchases of dwellings but includes imputed rent for owner-occupied dwellings. It also includes payments and fees to governments to obtain permits and licenses. Here, household consumption expenditure includes the expenditures of nonprofit institutions serving households, even when reported separately by the country.; ; World Bank national accounts data, and OECD National Accounts data files.; Weighted average;

Residential Construction: Number of Households: Original, Residential Construction: Number of Households: Five-year Moving Average, Residential Construction: Number of Households: Net Increase, Residential Construction: Average Space of Housing Units, Residential Construction: Net Increase of Total Space of Housing Units, Residential Construction: Renewal & Repair of Residential Houses: Number of Units, Residential Construction: Renewal & Repair of Residential Houses: Total Space, Residential Construction: Total Space Destroyed by Fire, Residential Construction: Total Space of Residential Construction, Non-residential Building Construction: Commercial, Non-residential Building Construction: Industrial, Non-residential Building Construction: Government, Non-residential Building Construction: Total, Roundwood Inputs per Unit of Space: Residential, Roundwood Inputs per Unit of Space: Non-residential, Total Volume of Roundwood: Residential, Total Volume of Roundwood: Non-residential, Total Volume of Roundwood: Total

Cuba CU: GDP: % of GDP: Final Consumption Expenditure: Household data was reported at 55.724 % in 2015. This records an increase from the previous number of 55.088 % for 2014. Cuba CU: GDP: % of GDP: Final Consumption Expenditure: Household data is updated yearly, averaging 54.411 % from Dec 1970 (Median) to 2015, with 46 observations. The data reached an all-time high of 71.097 % in 1995 and a record low of 48.096 % in 2009. Cuba CU: GDP: % of GDP: Final Consumption Expenditure: Household data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Cuba – Table CU.World Bank.WDI: Gross Domestic Product: Share of GDP. Household final consumption expenditure (formerly private consumption) is the market value of all goods and services, including durable products (such as cars, washing machines, and home computers), purchased by households. It excludes purchases of dwellings but includes imputed rent for owner-occupied dwellings. It also includes payments and fees to governments to obtain permits and licenses. Here, household consumption expenditure includes the expenditures of nonprofit institutions serving households, even when reported separately by the country. This item also includes any statistical discrepancy in the use of resources relative to the supply of resources.; ; World Bank national accounts data, and OECD National Accounts data files.; Weighted Average;

In 2022, the average household consumption expenditure in current prices on cookers in Denmark increased by 46 Danish Kroner per household (+11.53 percent) since 2021. With 445 Danish Kroner per household, the average household consumption expenditure thereby reached their highest value in the observed period. Find more statistics on cookers in Denmark with key insights such as Average household expenditure on yoghurt and Average household expenditure on food processors.

GDP: by Expenditure: Final Consumption Expenditure: Household: Beijing data was reported at 1,671.120 RMB bn in 2023. This records an increase from the previous number of 1,542.510 RMB bn for 2022. GDP: by Expenditure: Final Consumption Expenditure: Household: Beijing data is updated yearly, averaging 135.310 RMB bn from Dec 1978 (Median) to 2023, with 46 observations. The data reached an all-time high of 1,671.120 RMB bn in 2023 and a record low of 2.860 RMB bn in 1978. GDP: by Expenditure: Final Consumption Expenditure: Household: Beijing data remains active status in CEIC and is reported by Beijing Municipal Bureau of Statistics. The data is categorized under China Premium Database’s National Accounts – Table CN.AEZ: Gross Domestic Product: Prefecture Level City: Expenditure: Final Consumption Expenditure: Household.

In 2025, ** percent of survey respondents in the United States stated that they drank coffee within the last day. About ** percent of U.S. respondents had drunk espresso-based beverages instead. Coffee brands in the U.S. In 2020, Folgers produced over ************* U.S. dollars’ worth of sales in the United States, making it the leading brand of regular ground coffee by a significant margin. Total sales numbers generated by private coffee labels amounted to some *** million U.S. dollars. Folgers Coffee was first introduced in 1850, and by 2020, had the largest ground coffee market share in the United States. The coffee giant was followed by other well-known brands, such as Maxwell House, Starbucks, and Dunkin’ Donuts. Arabica vs. Robusta In the commercial coffee industry, there are two main types of coffee species: Arabica and Robusta. Coffee beans of the Arabica variety are slightly larger, produce a smooth and aromatic taste, and are the most commonly produced coffee bean variety: in 2023/24, just over ** million bags (60 kilograms each) of Arabica coffee were produced worldwide. Robusta beans are generally smaller and rounder, cheaper to cultivate, and taste quite bitter. Just over ** million bags of this coffee type were produced during the same marketing year.

The number of households is presented in brackets.

Luxembourg LU: GDP: Growth: Final Consumption Expenditure: Household: Include Discrepancy data was reported at 2.674 % in 2016. This records a decrease from the previous number of 3.722 % for 2015. Luxembourg LU: GDP: Growth: Final Consumption Expenditure: Household: Include Discrepancy data is updated yearly, averaging 2.633 % from Dec 1971 (Median) to 2016, with 46 observations. The data reached an all-time high of 7.907 % in 1991 and a record low of -8.550 % in 1995. Luxembourg LU: GDP: Growth: Final Consumption Expenditure: Household: Include Discrepancy data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Luxembourg – Table LU.World Bank.WDI: Gross Domestic Product: Annual Growth Rate. Annual percentage growth of household final consumption expenditure is based on constant local currency. Aggregates are based on constant 2010 U.S. dollars. Household final consumption expenditure (formerly private consumption) is the market value of all goods and services, including durable products (such as cars, washing machines, and home computers), purchased by households. It excludes purchases of dwellings but includes imputed rent for owner-occupied dwellings. It also includes payments and fees to governments to obtain permits and licenses. Here, household consumption expenditure includes the expenditures of nonprofit institutions serving households, even when reported separately by the country. This item also includes any statistical discrepancy in the use of resources relative to the supply of resources.; ; World Bank national accounts data, and OECD National Accounts data files.; Weighted Average;

ABS experimental estimates of household rainwater tank water consumption (gigalites) in 2013-2014. For more information please see http://www.abs.gov.au/AUSSTATS/abs@.nsf/Previousproducts/4610.0Main …Show full descriptionABS experimental estimates of household rainwater tank water consumption (gigalites) in 2013-2014. For more information please see http://www.abs.gov.au/AUSSTATS/abs@.nsf/Previousproducts/4610.0Main Features12013-14?opendocument&tabname=Summary&prodno=4610.0&issue=2013-14&num=&view= Figure BLT45 in Built environment theme. https://soe.environment.gov.au/theme/built-environment/topic/2016/urban-environmental-efficiency-water-efficiency#built-environment-figure-BLT45

Abstract

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 100% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE NATIONAL INSTITUTE OF STATISTICS - TUNISIA (INS)

The National Survey on Household Budget, Consumption, and Standard of Living, 2005 is a quinquennial survey. It is the eighth survey of its kind that was carried out by the National Institute of Statistics (INS) in Tunisia. The seven previous surveys were conducted in 1968, 1975, 1980, 1985, 1990, 1995 and 2000, concurrently with the preparatory work for the Tunisian development plans. The 2005 survey was conducted as part of the preparation work for the Tenth Development Plan (2007-2011). Its expected findings would allow assessing the progress made in the improvements of the living level & conditions of the population.

The survey aims at providing detailed information on the procurement of goods and services for consumption (food consumption as well as household access to community services of health and education). And its data was collected from direct observation of household consumption to allow for having the necessary elements to assess the situation & changes in the living standards & conditions of the households.

Thus, the 2005 survey tackles three major areas of study: 1 - Household expenditure and acquisitions during the survey period 2 - Food consumption and nutritional status of households. 3 - Household access to community services of health and education.

The objectives of the survey are: a- Identifying levels of expenditure on the household level: The survey aims to assess the levels of household expenditure .The total expenditure of the household, is not only an indicator of income, but it is also a quantitative assessment of the standard of living index.

b- Income distribution: Due to the absence of data on income distribution, the mass distribution of expenditure between the different categories of the population constitutes a first outline for the income distribution in the country.

c- Investigating the structure of expenditure: Detailed information collected on expenditures per product used to establish the structures of the household expenditure as well as the budget coefficients according to different levels of classifications of goods in the nomenclature of goods and services. These factors coefficients are particularly useful for revision and development of the weights of the Consumer Prices Index (CPI). It should also be noted that the change in expenditure structure is an indicator of the evolution of living standards.

d- Analysis of household demand: Household behavior in terms of product demand is synthesized by the coefficients of income elasticity which, according to the model of consumption retained and under the assumptions of the growth of income and population, allows predicting future household demand.

e- Resources-use balance in the national accounts: The results related to the consumption by product are necessary elements for the development of balanced resource-use of products in the frame of national accounts.

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 all urban, small and medium towns and rural areas.

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 100% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE NATIONAL INSTITUTE OF STATISTICS - TUNISIA (INS)

Sampling method

The National Survey on Household Budget, Consumption and Standard of Living, 2005 has focused initially on a sample of 13,392 households representing 0.61% of total households in the country (61 surveyed household for every 10,000 household) . This sample is distributed across 1116 districts covering all the country governorates, cities, urban and rural areas. The sample was also equally divided on the months of the survey year to take the seasonal changes in household expenditure into account.

These households were drawn using a two stages stratified random sampling in each governorate. The sampling frame follows that of the general Census of Population and Housing in 2004.

Stratification criteria: The sampling frame is stratified by two geographical criteria: namely the governorate and the living area. The latter is stratified as follows: large municipalities, medium and small towns, major cities and the rest of the non-municipal areas. These stratification criteria (governorate, habitat and size of municipalities) represent the differentiation variable of lifestyles households. Strata used are as follows:

Stratum of large cities (stratum 1): the municipalities of the city of Tunis and its suburbs, the city of Bizerte and its suburbs, the city of Sousse and its suburbs, the city of Kairouan and its suburbs, the city Sfax and its suburbs, and the general Gabes. Thus, this stratum is formed of large urban centers corresponding to municipalities with more than 100.000 inhabitants and neighboring municipalities.

Stratum of other cities (stratum 2): This is all small and medium sized cities other than those classified in the stratum of large cities.

Stratum of the main cities (stratum 3): These are non-municipal urban areas classified as major cities during the general census of population and housing 2004 (with a population of more than 70 households).a city is considered a main city if the number of its inhabitants exceeds 400 during the census of 2004.

Stratum dispersed outside communes (stratum 4): These are areas of land located outside the main towns and cities. Households in these areas live in houses scattered or grouped in small towns.

This strata classification is closely related to the levels of household income and lifestyle.

Survey type:

The sampling frame is divided on the level of each governorate according to strata previously defined. It was set, at the level of each stratum, to make a two-stage random sampling for the selection of the household survey sample. This drawing process allows to breakdown the sample into clusters of 12 households relatively little distant from each other, thereby facilitating the conduct of the survey at the time of the information collection in the field

In the first stage: a sample of primary units is drawn in proportion to their size in number of households as they were identified. Taking into consideration that the primary units correspond to the districts that have been defined in the census of the population and these geographic areas contain on average 70 households.

In the second stage: in each sampled district, 12 households are selected according to the following method: The households in each sampled district are classified primarily according to the number of employed persons in the household. Within each category of classified households, households are also classified according to the number of persons in each household. A systematic sampling is then performed to select 12 sampled households per primary unit (sampled district). For each sampled district, another 12 households are drawn according to the same previously illustrated criteria. These households serve as a substitutive sample so that in case the interviewer failed to get in contact with the originally selected household (due to long absence- change of place of residence) , after coordinating with the supervisor, this household can be replaced by one from the substitutive sample. For this purpose, two lists of the names of head of households were developed (original list, substitutive list) that the survey is supposed to cover.

Distribution of districts and households sampled by governorates

Uganda UG: GDP: Final Consumption Expenditure: Household data was reported at 68,908,112.177 UGX mn in 2017. This records an increase from the previous number of 63,846,509.688 UGX mn for 2016. Uganda UG: GDP: Final Consumption Expenditure: Household data is updated yearly, averaging 4,023,505.000 UGX mn from Jun 1960 (Median) to 2017, with 46 observations. The data reached an all-time high of 68,908,112.177 UGX mn in 2017 and a record low of 30.250 UGX mn in 1960. Uganda UG: GDP: Final Consumption Expenditure: Household data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Uganda – Table UG.World Bank.WDI: Gross Domestic Product: Nominal. Household final consumption expenditure (formerly private consumption) is the market value of all goods and services, including durable products (such as cars, washing machines, and home computers), purchased by households. It excludes purchases of dwellings but includes imputed rent for owner-occupied dwellings. It also includes payments and fees to governments to obtain permits and licenses. Here, household consumption expenditure includes the expenditures of nonprofit institutions serving households, even when reported separately by the country. Data are in current local currency.; ; World Bank national accounts data, and OECD National Accounts data files.; ;