The table 2004 (Part 2) Economic Development Survey is part of the dataset Economic Development Survey, available at https://stanford.redivis.com/datasets/62h7-ac4qhzm2p. It contains 726 rows across 166 variables.

The Annual Survey of Manufactures (ASM) provides key intercensal measures of manufacturing activity, products, and location for the public and private sectors. The ASM provides the best current measure of current U.S. manufacturing industry outputs, inputs, and operating status, and is the primary basis for updates of the Longitudinal Research Database (LRD). Census Bureau staff and academic researchers with sworn agent status use the LRD for micro data analysis.

This data is about Economic Survey National Income for the period 1950-2020. Data from Ministry of Finance, India.Follow datasource.kapsarc.org for timely data to advance energy economics research.

Abstract

A comprehensive and detailed statistical database of any economic activity is a prerequisite for planning and policy making and this applies to economic activities that play a major role in most modern world economies.

The Palestinian Central Bureau of Statistics is pleased to issue the twenty-second volume of the Economic Survey of Palestine, including statistical tables of findings. This edition presents the findings of the surveys conducted for 2016 as the reference year and covers most of the economic activities operating in Palestine since 1994. Economic surveys of various fields constitute the basic foundations for the compilation of National Accounts for Palestine

Geographic coverage

Palestine

Analysis unit

Enterprises

Universe

The twenty second round of the economic survey series was conducted based on the Establishments Census of 2012 as a sampling frame. The economic surveys series covered activities in accordance with ISIC-4 (fifth digits).

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample of the economic surveys series was One-Stage Stratified Systematic Random Sample in which enterprises were divided into two types: the first type covered overall enterprises taken comprehensively, the second type covered enterprises selected in a systematic random way in which the enterprise constituted the sampling unit. Three levels of strata were used to draw up an efficient representative sample: 1. The frame was divided into two geographical locations: the West Bank excluding that part of Jerusalem governorate which was forcefully annexed by Israel following its occupation of the West Bank in 1967, and the Gaza Strip. 2. Strata were created based on the fourth digit of ISIC-4, excluding services sector based on the second in which every activity presents an actual stratum. 3. Within each stratum, new strata were created according to employment size.

According to services sector profit and non-profit enterprises are taking into consideration as a forth level.

The sample size in Palestine (excludes that part of Jerusalem governorate which was forcefully annexed by Israel following its occupation of the West Bank in 1967) in 2016 was 9,491 enterprises out of 143,140 enterprises comprising the survey sampling frame.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

All of the economic surveys series used the same questionnaire, with a few different characteristics for each survey. The design of the 2016 questionnaire takes into account the major economic variables pertaining to the sector examined and the needs to be met to compile the National Accounts for Palestine. The questionnaire included these variables: 1. The employed persons in enterprise and compensation of these employees. 2. Value of output from the main activity and secondary activity. 3. Production inputs of goods and services. 4. Payments and transfers. 5. Taxes on production. 6. Assets and capital formation.

Cleaning operations

·A specialized field work team with a background in economics was selected and trained theoretically and practically on the surveys' questionnaire. ·The main field work team was selected based on skills acquired from the training course. ·Project management received a daily report on the progress and response rates. ·Programs were designed to check and extract data through the web by project management and field work supervisors. ·A refreshment training course was conducted during the stage of data collection to reinforce the main points made during the training, and to answer questions by field workers about issues they faced in the field. ·Field visits were conducted from the project management team to check and progress of work for all governorates in the West Bank and Gaza Strip. ·Editing: PC-Tablets were used in collecting data in the West Bank and Gaza Strip, the sample was loaded onto the tablets and automated rules applied to the program. ·Coding: After finishing editing process, the completed questionnaires are subject to coding process to be prepared to the data entry process. ·Creation of a data entry program prior to the collection of data to ensure this would be ready in advance. ·A set of validation rules were applied to the program to check the consistency of data. · The efficiency of the program was pre-tested by entering several questionnaires including incorrect information and checking its efficiency in capturing the incorrect information

Response rate

Response rate:93.3%..

Sampling error estimates

Sampling Errors Data of this survey affected by sampling errors due to use of the sample and. Therefore, certain differences were expected in comparison with the real values obtained through censuses. Variance were calculated for the most important indicators as shown in tables below. Dissemination of results at the national level did not pose a problem, but there was high variance in some variables.

Non Sampling Error These types of errors could appear on one or on all of the survey stages that include data collection and data entry; they related to, respondents, fieldworkers, and data entry personnel. To avoid errors and mitigate their impact, a number of procedures were applied to enhance the accuracy of the data through a process of data collection from the field and data processing.

Abstract

A comprehensive and detailed statistical database of any economic activity is a prerequisite for planning and policy making and this applies to economic activities that play a major role in most modern world economies.

The Palestinian Central Bureau of Statistics is pleased to issue the Economic Survey of Palestine, including statistical tables of findings. This edition presents the findings of the surveys conducted for 2019 as the reference year and covers most of the economic activities operating in Palestine since 1994. Economic surveys of various fields constitute the basic foundations for the compilation of National Accounts for Palestine

Geographic coverage

Palestine

Analysis unit

Enterprises

Universe

The economic survey series was conducted based on the Establishments Census of 2019 as a sampling frame. The economic surveys series covered activities in accordance with ISIC-4 (fifth digits).

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample is One-Stage Stratified Systematic Random Sample (without replacement).

Sample Strata Three levels are used to divide the population into strata: 1. Region (North of the West Bank in addition to Jericho Governorate, Ramallah and Al-Bireh Governorate, Jerusalem Governorate, Bethlehem Governorate, Hebron Governorate, Gaza Strip) 2. Strata were created based on the fourth digit of ISIC-4, excluding services sector based on the second in which every activity presents an actual stratum. 3. Enterprise size (small, medium, large) by number of employees.

13,974 enterprises were reached of which 10,602 enterprises responded on financial questions (baseline of economic indicators)

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

All of the economic surveys series used the same questionnaire, with a few different characteristics for each survey. The design of the 2019 questionnaire takes into account the major economic variables pertaining to the sector examined and the needs to be met to compile the National Accounts for Palestine. The questionnaire included these variables: 1. The employed persons in enterprise and compensation of these employees. 2. Value of output from the main activity and secondary activity. 3. Production inputs of goods and services.

Cleaning operations

Data processing went through several phases since the beginning of the preparation of data collection on 21/06/2020 until the end of the fieldwork on 30/11/2020. This process included the following phases:

1. Programming Phase The data collection application was prepared by the IT staff at PCBS.

IT staff tested the application with the project director and all comments and updates were implemented, skips between questions, and some verification rules were also tested, a final version of the application was provided on time.

1. Training Phase All materials were prepared and included in the training manual on the requirements of data processing during fieldwork. The training halls were well prepared and contained microphones and a Wi-Fi. Training for Gaza Strip was carried out separately.

2. Verification Phase All verifications and consistency checks were applied to PC-Tablet applications. An error message pops up when entering a wrong value and some error messages show up in red for sensitive questions. The project coordinator tested the application by entering pilot questionnaires. In addition, there was a pretest by project director before collecting the data.

3. Other Data Processing Issues

· PC-Tablets: In general, PC-tablets were user friendly and familiar. During training, every interviewer was trained on a PC-tablet for their own use

· Data Collection Application (Survey Solution): The application was well designed and had a user friendly interface. Nevertheless, a programmer needed to be available when an error occurred by any of the supervisors and interviewers.

· Internet Connection (Wi-Fi): During the training, internet connection was available for trainers and trainees. During fieldwork, 81 SIM cards with internet connection were provided for each PC-tablet by Jawwal Company during data collection process.

· Administration Website: The website was friendly designed and easy to use, as it shows totals of completed questionnaire by interviewers.

Supervisors were supplied by PCBS with four PC-tablets operating on Windows operations system to review and follow up on the data and to fill the sections they were responsible for.

Response rate

Response rate:84.0%.

Sampling error estimates

Sampling Errors Data of this survey were affected by sampling errors due to use of the sample. Variance was calculated for the most important indicators, accordingly, it is possible to disseminate the results at regional level.

Non Sampling Error These types of errors could appear on one or on all of the survey stages that include data collection and data entry; they related to, respondents, fieldworkers, and data entry personnel. To avoid errors and mitigate their impact, a number of procedures were applied to enhance the accuracy of the data through a process of data collection from the field and data processing.

Data contains information on variable and fixed costs about small scale fishermen

The project will produce a valuation function that depends on factors related to Steller sea lion (SSL) protection measures, and may include some combination of the expected aggregate size of the population and improvements to the ESA listing status resulting from protection measures, cost of the protection measures, and effects of protection measures on local economies, fishery participants, and consumer fish prices. This function can be used to identify non-consumptive use values for SSLs and how these values are affected by protection measures, thereby providing valuable information to policy makers.

LIVES is an initiative designed by the International Livestock Research Institute (ILRI), the International Water Management Institute (IWMI) and their national partners to build upon the success of the Canadian International Development Agency-funded project, Improving Productivity and Market Success of Smallholders in Ethiopia (IPMS). This dataset contains the household baseline Socio-economic survey.

This statistic shows the Economic Confidence Index, created by Gallup, on a monthly basis for the ongoing year. The survey is conducted doing weekly telephone interviews among approx. 2,499 adults in the U.S. The graph shows the results for the first update each month to depict an annual trend. The Index is computed by adding the percentage of Americans rating current economic conditions to the percentage saying the economy is (getting better minus getting worse), and then dividing that sum by 2. The Index has a value between null and +100. In December 2017, the U.S. Economic Confidence Index stood at 8.

Saudi Arabia Economic Survey of Establishments: EE: ow Accommodation data was reported at 11,590,334.000 SAR th in 2017. This records an increase from the previous number of 9,699,194.000 SAR th for 2016. Saudi Arabia Economic Survey of Establishments: EE: ow Accommodation data is updated yearly, averaging 10,205,131.000 SAR th from Dec 1995 (Median) to 2017, with 20 observations. The data reached an all-time high of 27,404,077.000 SAR th in 2009 and a record low of 6,337,222.000 SAR th in 1996. Saudi Arabia Economic Survey of Establishments: EE: ow Accommodation data remains active status in CEIC and is reported by General Authority for Statistics. The data is categorized under Global Database’s Saudi Arabia – Table SA.S001: Economic Survey of Establishments: Enterprise Revenues and Expenditures.

Abstract

The Indonesia Social and Economic Survey (SUSENAS) is designed in order to collect social population data, which is relatively in the wide scope. In 1992, SUSENAS data collecting system was renewed. Information which is used to arrange population welfare indicator in module (questionnaire is collected every three year) is joined in to core (questionnaire is collected every year). At that time being, SUSENAS provides tools that can be used to supervise population welfare level, formula government program, and analyze population welfare improvement programs impact.

Questionnaire core, consist some questions asking about condition and member of population attitude, which have tight relationship with welfare aspects. Here are some example question “are you still attend school”, “are you in health disruption”, “how do you take care your health”, “who was the birth helper”, “how long the baby got the wet nursing” and immunization to the children be asked. Beside all question above, also been collected education info, household economic activity, and especially for the ever- married women have been asked about age when she got married, number of child, and Family Planning attitude.

Questionnaire module has taken turns to be collected in 3 years. At the first year, household income and expenditure were collected, at the second year household welfare socio-culture, trips and criminality module were collected, and finally at the last year health, nutrition, education and housing were collected. Information is module is more detail and comprehensive question if it is compared to the same topic question in the core.

Questionnaire core are collected in order to get important information to anticipate some changes that could be happened every year. They are also helpful for short- term planning, and the questions could be related to module's questions such as expenditures. Questionnaire module is useful to analyze problems, which are unneeded to be supervised every year or to analyze government intervention, such as poverty and malnutrition.

Since 1993, sample size of SUSENAS core is enlarged to produce simple statistic in Regency/ Municipality level. This-new progress gave data analyzers a new dimension. At that time being, some Regencies have been arranged their people welfare statistic/ indicator.

Geographic coverage

National coverage, representative to the district level

Analysis unit

Household Members (Individual) and Household

Universe

Susenas 2012 cover 300,000 household sample spread all over Indonesia where each quarter distribute about 75,000 household sample (including 500 households additional sample for Survey in Maluku Province). The result from each quarter can produce national and provincial level estimates. Meanwhile from the cummulative four quarter, the data can be presented until the district/municipality level.

Kind of data

Sample survey data [ssd]

Sampling procedure

From the master sampling frame (Nh enumeration areas) were retractable sample enumeration areas in a probability proportional to size (pps) method, nh acquired 30,000 enumeration areas. Then divided into 4 quarters so that each quarter 7,500 enumeration areas. The next stage selected one census block (BS) in a probability proportional to size (pps) method, whereas size is the number of households from SP 2010 RBL1. The last stage, of each BS Susenas been selected for a number of common household (m = 10) based on the results of systematic updating of listing of households using SP 2010 C1 VSEN2011 List - P. Then do the enumeration of 75,000 households.

Mode of data collection

Face-to-face [f2f]

Abstract

A comprehensive and detailed statistical database of any economic activity is a prerequisite for planning and policy making and this applies to economic activities that play a major role in most modern world economies.

The Palestinian Central Bureau of Statistics is pleased to issue the eighteenth volume of economic surveys for the Palestine, including statistical tables of findings. This edition presents the findings of the surveys conducted for 2013 as the reference year and covers most of the economic activities operating in the Palestine since 1994.

Economic surveys of various fields constitute the basic foundations for the compilation of National Accounts for Palestine. It is hoped that they will also fulfill the various needs and expectations of users in both the public and private sectors.

Geographic coverage

Palestine

Analysis unit

Enterprises

Universe

The eighteenth round of the economic survey series was conducted based on the Establishments Census of 2012. The economic surveys series cover activities in accordance with ISIC-4.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample of the economic surveys series is a single-stage stratified random-systematic sample in which the enterprise constitutes the primary sampling unit (PSU). Three levels of strata were used to draw up an efficient representative sample (i.e. economic activity, size of workforce and geographical location). The sample size in 2012 was 9,425 enterprises out of the 126,309 enterprises comprising the survey frame.

Mode of data collection

Face-to-face [f2f]

Research instrument

All of the economic surveys series used the same questionnaire, with a few different characteristics for each survey. The design of the 2013 questionnaire takes into account the major economic variables pertaining to the sector examined and the needs to be met to compile the National Accounts for Palestine.

The questionnaire included these variables: 1. The persons engaged in enterprise and compensation of these employees. 2. Value of output from the main activity and secondary activity. 3. Production inputs of goods and services. 4. Payments and transfers. 5. Taxes on production. 6. Assets and capital formation.

Cleaning operations

To ensure the quality and consistency of data, a set of measures was introduced as follows: - Creation of a data entry program prior to the collection of data to ensure this would be ready. - A set of validation rules were applied to the program to check the consistency of data. - The efficiency of the program was pre-tested by entering a few questionnaires, including incorrect information, and checking its efficiency in capturing the incorrect information. - Well-trained data entry personnel were selected and trained for main data entry. - Weekly data files were received by project management to be checked for accuracy and consistency: correction notes were provided to data entry management for implementation.

Response rate

Response rate: 85.2%

Sampling error estimates

Statistical Errors: - Statistical Errors: The findings of the survey are affected by statistical errors due to using sampling in conducting the survey for the units of the target population, which increases the chances of having variances from the actual values we expect to obtain from the data had we conducted the survey using comprehensive enumeration. The variance of the key goods in the survey was computed and dissemination was carried out on the level of the Palestinian Territory for reasons related to sample design and computation of the variance of the different indicators.

Non-Statistical Errors These types of errors could appear on one or all the survey stages that include data collection and data entry. - Response errors: these types of errors are related to, responders, fieldworkers, and data entry personnel's. And to avoid mistakes and reduce the impact has been a series of actions that would enhance the accuracy of the data through a process of data collection from the field and the data processing.

The Annual Business Survey (ABS) provides information on selected economic and demographic characteristics for businesses and business owners by sex, ethnicity, race, and veteran status. Further, the survey measures research and development (for microbusinesses), new business topics such as innovation and technology, as well as other business characteristics. The U.S. Census Bureau and the National Center conduct the ABS jointly for Science and Engineering Statistics within the National Science Foundation. The ABS replaces the five-year Survey of Business Owners (SBO) for employer businesses, the Annual Survey of Entrepreneurs (ASE), the Business R&D and Innovation for Microbusinesses survey (BRDI-M), and the innovation section of the Business R&D and Innovation Survey (BRDI-S). https://www.census.gov/programs-surveys/abs.html

Saudi Arabia Economic Survey of Establishments: ER: ow Agriculture, Hunting and Related Services data was reported at 92,540,192.000 SAR th in 2016. This records an increase from the previous number of 91,710,533.000 SAR th for 2015. Saudi Arabia Economic Survey of Establishments: ER: ow Agriculture, Hunting and Related Services data is updated yearly, averaging 70,133,347.500 SAR th from Dec 2005 (Median) to 2016, with 12 observations. The data reached an all-time high of 92,540,192.000 SAR th in 2016 and a record low of 53,527,672.000 SAR th in 2005. Saudi Arabia Economic Survey of Establishments: ER: ow Agriculture, Hunting and Related Services data remains active status in CEIC and is reported by General Authority for Statistics. The data is categorized under Global Database’s Saudi Arabia – Table SA.S001: Economic Survey of Establishments: Enterprise Revenues and Expenditures.

Abstract

The World Bank Enterprise Survey (WBES) is a firm-level survey of a representative sample of an economy's private sector. The surveys cover a broad range of topics related to the business environment including access to finance, corruption, infrastructure, competition, and performance.

Geographic coverage

National coverage

Analysis unit

The primary sampling unit of the study is the establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Universe

All formal (i.e., registered) private sector businesses (with at least 1% private ownership) and with at least five employees. In terms of sectoral criteria, all manufacturing businesses (ISIC Rev 4. codes 10-33) are eligible; for services businesses, those corresponding to the ISIC Rev 4 codes 41-43, 45-47, 49-53, 55-56, 58, 61-62, 69-75, 79, and 95 are included in the Enterprise Surveys. Cooperatives and collectives are excluded from the Enterprise Surveys. All eligible establishments must be registered with the registration agency. In the case of the Philippines, the listing from the PSA’s List of Establishments (LE), a registrar of businesses operating in the Philippines, was used. The registration agency is the Securities and Exchange Commission (SEC).

Kind of data

Sample survey data [ssd]

Sampling procedure

The WBES use stratified random sampling, where the population of establishments is first separated into non-overlapping groups, called strata, and then respondents are selected through simple random sampling from each stratum. The detailed methodology is provided in the Sampling Note (https://www.enterprisesurveys.org/content/dam/enterprisesurveys/documents/methodology/Sampling_Note-Consolidated-2-16-22.pdf). Stratified random sampling has several advantages over simple random sampling. In particular, it:

• produces unbiased estimates of the whole population or universe of inference, as well as at the levels of stratification
• ensures representativeness by including observations in all of those categories
• produces more precise estimates for a given sample size or budget allocation, and
• may reduce implementation costs by splitting the population into convenient subdivisions.

The WBES typically use three levels of stratification: industry classification, establishment size, and subnational region (used in combination). Starting in 2022, the WBES bases the industry classification on ISIC Rev. 4 (with earlier surveys using ISIC Rev. 3.1). For regional coverage within a country, the WBES has national coverage.

Note: Refer to Sampling Structure section in "The Philippines 2024 World Bank Enterprise Survey Green Economy Implementation Report" for detailed methodology on sampling.

Mode of data collection

Face-to-face [f2f]

Research instrument

The standard WBES questionnaire covers several topics regarding the business environment and business performance. These topics include general firm characteristics, infrastructure, sales and supplies, management practices, competition, innovation, capacity, land and permits, finance, business-government relations, exposure to bribery, labor, and performance. Information about the general structure of the questionnaire is available in the Enterprise Surveys Manual and Guide (https://www.enterprisesurveys.org/content/dam/enterprisesurveys/documents/methodology/Enterprise-Surveys-Manual-and-Guide.pdf).

The questionnaire implemented in the Philippines 2024 WBES Green Economy included additional questions tailored for the Business Ready Report covering infrastructure, trade, government regulations, finance, labor, and other topics.

Response rate

Overall survey response rate was 76.4%.

This mail survey collected economic data on inshore commercial shrimp fishermen who held licenses to commercially harvest shrimp in state waters of the U.S. Gulf of Mexico throughout 2012. It is designed to complement a similar economic data collection of commercial shrimp harvesters in offshore waters of the Gulf (those holding a federal shrimp permit). Data regarding vessel values, indebtedness, commercial shrimp harvesting activities, revenues, and expenses were collected in order to produce simple standardized financial statements, including a balance sheet, cash flow statement, and income statement for the average or typical vessel.

Abstract

Data required in the development planning among others is data of education, health, housing, consumption/expenditure of household. Such data is very useful for the Government in the planning of either sector or cross-sector development. In order to provide such data, Central Statistical Agency (BPS) conducts National Socioeconomic Survey (Susenas) almost every year since 1963. Susenas data currently is also the data that is highly required to fulfill the Millennium Development Goals (MDG's) data.

In year 2006, according to its rotation Susenas module is the module on socio-cultural and education. Module of Susenas samples as many as of 291,888 households are the same as Core Susenas so that the estimated numbers are expected to be obtained up to the level of district/city. Field implementation like last year shall be conducted by a team of one (1) Team Coordinator (Teamcoord) and two (2) Enumerators (PCS). By this system, it is expected that the field implementation can be accelerated and the quality result of field census can be improved.

Lately BPS is demanded to be able to present data up to the smallest level namely sub-district (kecamatan) level and even to village level. This requirement of data is inseparable from the quality data results. For 2006 Susenas, presentation up to the level of district/city might cause problems if the samples are not met (high RSE) or rare cases that cannot represent, so that the data do not correspond to the actual condition. To anticipate this, there is an activity that have to be conducted by District/City BPS or Provincial BPS namely verification of data quality prior to sending / presenting data to BPS. This activity is critical as BPS data quality depends on data quality generated by District/City BPS as well as Provincial BPS. In order to achieve an accurate and timely data, coordination between units in the regions seems very influential.

Geographic coverage

National coverage, representative to the district level

Analysis unit

Household Members (Individual) and Household

Universe

Implementation of the 2006 Susenas includes 278,352 sample households spread across all geographic regions of Indonesia, with details of 68,800 sample household core-module and 209 552 households sample core (without module). Data from the sample core can presented at the national, provincial, and district / city. Data from sample core-module, can be presented at national and provincial levels. Data from sample core-module can be distinguished according to the type of area (urban and rural) and data from a sample of core at national and provincial levels can be presented according to the type of area, while the Core data presented at district / city level can not be differentiated according to the type of area.

Kind of data

Sample survey data [ssd]

Sampling procedure

The design of Sampling

1. Core Susenas

The design of the sample Susenas 2006 was sample designs phased two both for urban and rural areas. Sample selection for urban and rural areas is done separately. Sampling procedures Susenas 2006 for the county / city are as follows:

• Phase 1, from sample frame census block are to be selected census block nh (h = 1, for urban; h = 2, for rural) by probability proportional to size (pps) method whereas size is the number of households from P4B census result (April 2004). Household listing is conducted to all selected census blocks/sub-blocks.

• Phase 2, from every selected census blocks/sub-blocks, then, to be selected m = 16 households from the listing result systematically. For census block that has contents of more than 150 households, selection of one census sub-block in PPS-systematic is required with the size of household number of P4B census result. Household listing is conducted to all selected census blocks/sub-blocks.

1. Socio-Cultural and Educational Modules

Module data collected in 2006 Susenas includes detailed data on socio-cultural and educational. Sample size selected census blocks Socio-Cultural and Education Modules designed for presentation at provincial level. Further samples selected block census module socio-cultural and educational is sample block census core-module. Sample block census core-module is a subsample of the sample block census core. The selection subsample block census core-module is done by systematic linear method from block census core. Sample block census core is designed to estimate welfare statistics at the district / city.

Mode of data collection

Face-to-face

United States - Labour Force Survey - quarterly levels: Employment - by economic activity: Services: All persons for G7 was 298404700.00000 Persons in October of 2024, according to the United States Federal Reserve. Historically, United States - Labour Force Survey - quarterly levels: Employment - by economic activity: Services: All persons for G7 reached a record high of 298404700.00000 in October of 2024 and a record low of 227482922.60660 in January of 2000. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Labour Force Survey - quarterly levels: Employment - by economic activity: Services: All persons for G7 - last updated from the United States Federal Reserve on November of 2025.

Abstract

Survey is a technique of gathering information from the public by asking a number of structured questions to respondents. In this case, the key to the success of the collection of information is on the interview process. In addition, the interviewer skills in interacting with respondents in determining the quality of information collected. The interviewer has the main task to make the respondents can participate in surveys and records information from respondents. Interviewer influence on the success of a survey can be seen in three conditions, which is: First, the interviewer plays a major role in the code 1 answers rate (response rate) were obtained. Second, the interviewer is responsible to initiating (initation) and motivate respondents. Third, the interviewer should handle the parts interactions interviews and debriefing process raw (no bias). Key to a successful interview is the interviewer is able to invite respondents to participate were interviewed, ensure confidentiality and managed to properly explain the purpose of the survey is being conducted.

Geographic coverage

Coverage provincial representative to the level of the village / district

Analysis unit

The unit of analysis are every household member, from every selected household collected general information regarding name, relationship with Head of household, sex and age.

This survey will also ask a number of questions regarding household consumption, as well as a wide range of household characteristics and participation in community activities. In each village will be selected one RT (RT) and in each selected RT will be interviewed 9 household, which one of it is the Head of RT household.

Universe

Household

Kind of data

Sample survey data

Mode of data collection

Face-to-face [f2f]

Abstract

The CSES is a household survey with questions to households and the household members. In the household questionnaire there are a number of modules with questions relating to the living conditions, e.g. housing conditions, education, health, expenditure/income and labour force. It is designed to provide information on social and economic conditions of households for policy studies on poverty, household production and final consumption for the National Accounts and weights for the CPI.

The main objective of the survey is to collect statistical information about living standards of the population and the extent of poverty. Essential areas as household production and cash income, household level and structure of consumption including poverty and nutrition, education and access to schooling, health and access to medical care, transport and communication, housing and amenities and family and social relations. For recording expenditure, consumption and income the Diary Method was applied for the first time. The survey also included a Time Use Form detailing activities of household members during a 24-hour period.

Another main objective of the survey is also to collect accurate statistical information about living standards of the population and the extent of poverty as an essential instrument to assist the government in diagnosing the problems and designing effective policies for reducing poverty, and in evaluating the progress of poverty reduction which are the main priorities in the "Rectangular Strategy" of the Royal Government of Cambodia.

Geographic coverage

National Phnom Penh/Other Urban/Other Rural Provinces/Groups of provinces

Analysis unit

Households

Individuals

Universe

All resident households in Cambodia

Kind of data

Sample survey data [ssd]

Sampling procedure

In this section the sampling design and the sample selection for CSES 2009, is described. The sampling design for the 2009 survey is the same as that used for the CSES 2004. The sampling design for the 2004 CSES is described in for instance National Institute of Statistics (2005a).

The sampling frame for the 2009 survey is based on preliminary data from the General Population Census conducted in 2008. The sample is selected as a three stage cluster sample with villages in the first stage, enumeration areas in the second stage and households in the third.

The Sampling Frame

Preliminary data from the General Population Census 2008 was used to construct the sampling frame for the first stage sampling, i.e. sampling of villages. All villages except 'special settlements' were included in the frame. In all, the first stage sampling frame of villages consisted of 14,073 villages, see Appendix 1. Compared to previous years the frame used for the 2009 survey based on the census 2008 was more up to date than in previous surveys which were based on the population census 1998.

The following variables were used from the census; Province code, province name, district code, district name, commune code, commune name, village code, village name, urban-rural classification of villages, the number of households per village and, the number of enumeration areas in the village.

In the second-stage Enumeration Areas (EA) are selected in each selected village. In most villages only one EA was selected but in some large villages more than one was selected.

For the third stage, the sampling of households, a frame was constructed in field. For selected EAs the census map of the village, including EAs and residences, was given to enumerator who updated the map and listed the households in the selected EA. A sample of households was then selected from the list.

Stratification

The sampling frame of villages was stratified by province and urban and rural. There are 24 provinces and each village is classified as either urban or rural which means that in total we have 48 strata, see Appendix 1. Each stratum of villages was sorted by district, commune and village code.

Sampling

The sampling design in the CSES 2009 survey is a three-stage design. In stage one a sample of villages is selected, in stage two an Enumeration Area (EA) is selected from each village selected in stage one, and in stage three a sample of households is selected from each EA selected in stage two. The sampling designs used in the three stages were:

Stage 1. A systematic pps sample of villages, Primary Sampling Units (PSUs) was selected from each stratum,

i.e. without replacement systematic sampling with probabilities proportional to size. The size measure used was the number of households in the village according to the sampling frame.

Stage 2. One EA was selected by Simple Random Sampling (SRS), in each village selected in stage 1.

As mentioned above, in a few large villages more than one EA was selected.

Stage 3. In each selected EA a sample of households was selected by systematic sampling.

The selection of villages and EAs were done at NIS while the selection of households in stage three was done in field. As mentioned in section 1.1 all households in selected EAs were listed by the enumerator. The sample of households was then selected from the list.

Sample sizes and allocation

The sample size of PSUs, were, as in the 2004 survey, 720 villages (or EAs). In urban villages 10 households were selected and in rural 20 households. In all 12,000 households were selected.

Urban and rural villages were treated separately in the allocation. The allocation was done in two steps. First the sample sizes for urban and rural villages in the frame were determined and then sample sizes for the provinces within urban and rural areas were determined, i.e. the strata sample sizes.

The total sample size was divided into to two, one sample size for urban villages and the other for rural villages. The calculation of the sample sizes for urban and rural areas were done using the proportion of consumption in the two parts of the population. Data on consumption from the CSES 2007 survey was used. The resulting sample sizes for urban villages was 240 and for rural 480. (Some adjustments of the calculated sample sizes were done, resulting in the numbers 240 and 480).

Allocation of the total sample size on the strata within urban and rural areas respectively, was done in the following way. The sample size, i.e. the number of PSUs, villages, selected from stratum h, is proportional to the number of households in stratum h, i.e.

n(Ih)=n1(Mh/Sum of Mh) (1.1)

where,

is the sample size in stratum h, i.e. the number villages selected in stratum h,

is the total sample size of villages for urban or rural villages,

H is the number of strata in urban or rural areas,

is the number of households in stratum h according to the frame.

As mentioned above, the sample size calculations are done separately for urban and rural villages, i.e. for strata with urban villages (1.1) is used with nI = 240 and is the number of households in urban villages in the frame and for rural villages (1.1) is used with nI = 480 and is the

number of households in rural villages in the frame.

Monthly samples

In section 1.3 the selection of the annual sample was described. The annual sample was divided into 12 monthly samples of equal sizes. The monthly samples consisted of 20 urban and 40 rural villages. The division of the annual sample into monthly samples was done so that as far as possible each province would be represented in each monthly sample. Since the sample size of villages in some provinces is smaller than 12, all provinces were not included in all monthly samples. Also, the outline of the fieldwork with teams of 4 enumerators and one supervisor puts constraints on how to divide the annual sample into monthly samples. The supervisors must travel between the villages in a team and therefore the geographical distance between the villages surveyed by a team cannot be too large.

Estimation

Totals, ratios such as means or proportions were estimated for the population or for subgroups of population, i.e. domains of study. The domains were defined by e.g. region or sex. Means and proportions were estimated by first estimating totals and then calculating the ratio of two estimated totals. To estimate totals from a sample survey weights are needed.

Mode of data collection

Face-to-face [f2f]

Research instrument

Four different questionnaires or forms were used in the survey:

1. Household listing form

The Household listing and mapping were done prior to the sampling. During the household listing the enumerator recorded household information on e.g. location, number of members and principal economic activity.

1. Village questionnaire

The Village questionnaire was used to gather basic common information on:

    1. Demographic information

    2. Economy & Infrastructure

    3. Rainfall & Natural disasters

    4. Education

    5. Health

    6. Retail prices (food and non-food items)

    7. Employment & Wages

    8. Access to common property resources during the last 5 years

    9. Sale prices of agricultural land in the village

    10. Recruitment of children for work outside the village 

1. Household questionnaire

The following modules were included in the Household questionnaire:

1. Initial visit

01A. List of household member

01B. Food, beverages and tobacco consumption during the last 7 days

01C. Recall non-food expenditures

01D. Vulnerability

1. Education & Literacy

2. Information on migration (includes past and current migration)

   1. Housing

3. Household economic activities

05A.Land ownership

05B.Production of