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.

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.

Economy Survey: Manufacturing: Furniture & Other: Purchases & Operating Expenditure data was reported at 295.911 NZD mn in Mar 2018. This records a decrease from the previous number of 342.618 NZD mn for Dec 2017. Economy Survey: Manufacturing: Furniture & Other: Purchases & Operating Expenditure data is updated quarterly, averaging 302.715 NZD mn from Dec 1992 (Median) to Mar 2018, with 102 observations. The data reached an all-time high of 375.240 NZD mn in Dec 2004 and a record low of 189.450 NZD mn in Mar 1993. Economy Survey: Manufacturing: Furniture & Other: Purchases & Operating Expenditure data remains active status in CEIC and is reported by Statistics New Zealand. The data is categorized under Global Database’s New Zealand – Table NZ.S003: Economy Survey: ANZSIC06.

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.

New Zealand Economy Survey: Manufacturing: Wood & Paper Product: Purchases & Operating Expenditure data was reported at 1,729.532 NZD mn in Mar 2018. This records a decrease from the previous number of 1,762.406 NZD mn for Dec 2017. New Zealand Economy Survey: Manufacturing: Wood & Paper Product: Purchases & Operating Expenditure data is updated quarterly, averaging 1,473.635 NZD mn from Dec 1992 (Median) to Mar 2018, with 102 observations. The data reached an all-time high of 1,806.195 NZD mn in Sep 2017 and a record low of 907.670 NZD mn in Mar 1993. New Zealand Economy Survey: Manufacturing: Wood & Paper Product: Purchases & Operating Expenditure data remains active status in CEIC and is reported by Statistics New Zealand. The data is categorized under Global Database’s New Zealand – Table NZ.S003: Economy Survey: ANZSIC06.

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 2012 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 9,860 enterprises out of the 126,323 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 2012 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.

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

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]

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 dataset provides values for ECONOMY WATCHERS SURVEY reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

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%.

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

Abstract

The Cambodia Socio-Economic Survey (CSES) asks questions to a country wide sample of households and household members about housing conditions, education, economic activities, household production and income, household level and structure of consumption, health, victimization, etc. There are also questions related to people in the labour force, e.g. labour force participation.

Poverty reduction is a major commitment by the Royal Government of Cambodia. Accurate statistical information about the living standards of the population and the extent of poverty is an essential instrument to assist the Government in diagnosing the problems, in designing effective policies for reducing poverty and in monitoring and evaluating the progress of poverty reduction. The Millennium Development Goals (MDG) has been adopted by the Royal Government of Cambodia and a National Strategic Development Plan (NSDP) has been developed. The MDGs are also incorporated into the “Rectangular Strategy of Cambodia”.

Cambodia is still a predominantly rural and agricultural society. The vast majority of the population get their subsistence in households as self-employed in agriculture. The level of living is determined by the household's command over labour and resources for own-production in terms of land and livestock for agricultural activities, equipments and tools for fishing, forestry and construction activities and income-earning activities in the informal and formal sector. The CSES aims to estimate household income and consumption/expenditure as well as a number of other household and individual characteristics.

The main objective of the survey is to collect statistical information about living conditions of the Cambodian population and the extent of poverty. The survey can be used for identifying problems and making decisions based on statistical data.

The main user is the Royal Government of Cambodia (RGC) as the survey supports monitoring the National Strategic Development Plan (NSDP) by different socio-economic indicators. Other users are university researchers, analysts, international organizations e.g. the World Bank and NGO’s. The World Bank has published a report on poverty profile and social indicators using CSES 2007 data . In this regard, the CSES continues to serve all stakeholders involved as essential instruments in order to assist in diagnosing the problems and designing their most effective policies. The CSES micro data at NIS is available for research and analysis by external researchers after approval by Senior Minister of Planning. The interesting research questions that could be put to the data are many; NIS welcomes new research based on CSES data.

General Objectives: CSES 2016 will continue the work started through CSES 2004 and the annual CSES 2007 to 2014 and would primarily aim at producing information needed for planning and policy making for reduction of poverty in Cambodia. Reduction of poverty has been given high priority in Cambodia's National Strategic Development Plan (NSDP 2009-2013). In addition to this, the survey data help in various other ways in developmental planning and policy making in the country. They would also prove useful for the production of National Accounts in Cambodia.

A long-term objective of the entire project is to build national capability in NIS for conducting socio-economic surveys and for utilizing survey data for planning for national development and social welfare.

Specific Objectives: Among specific objectives, the following deserve special mention: 1) Obtain data on infrastructural facilities in villages, especially facilities for schooling and health care and associated problems. 2) Obtain data on retail prices of selected food, non-food and medicine items prevailing in the villages. 3) Collect data on utilization of education, housing and land ownership 4) Collect data on household assets and outstanding loans. 5) Collect data on household's construction activities. 6) Collect information on maternal health, child health/care. 7) Collect information on health care seeking and expenditure of the household members related to illness, injury and disability. 8) Collect information on economic activities including the economic activities for children aged between 5 and 17 years. 9) Collect information on victimization by the household 10) Collect information on the presence of the household members.

Geographic coverage

National Phnom Penh / Other Urban / Other Rural

Analysis unit

• Households
• Individuals

Universe

All resident households in Cambodia

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling design in the CSES 2016 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.

Stage 1: A random sample of PSUs was selected from each stratum. The sampling method was systematic PPS (PPS=sampling with probability proportional to size). The size measure used was the number of households in the PSU according to the sampling frame.

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

Stage 3: In each selected EA a sample of 10 households was selected. The selection of households was done in the field by the supervisors/interviewers. All households in selected EAs were listed by the enumerator. The sample of households was then selected from the list by systematic sampling with a random start (the start value controlled by NIS).

Mode of data collection

Face-to-face [f2f]

Research instrument

Three different questionnaires or forms were used in the survey:

Form 1: Household listing sheets to be used in the sampling procedure in the enumeration areas.

Form 2: Village questionnaire answered by the village leader about economy and infrastructure, crop production, health, education, retail prices and sales prices of agriculture, employment and wages, and recruitment of children for work outside the village.

Form 3: Household questionnaire with questions for each household member, including modules on migration, education and literacy, housing conditions, crop production, household liabilities, durable goods, construction activities, nutrition, fertility and child care, child feeding and vaccination, health of children, mortality, current economic activity, health and illness, smoking, HIV/AIDS awareness, and victimization.

The interviewer is responsible for filling up Form 1 and Form 3 to respondents. For Form 2, the supervisors will be asked to canvass this form. In case that the supervisors are absent for any reason, the interviewers may be also asked to help fill up this form (Form 2).

Cleaning operations

The NIS team commenced their work of checking and coding and coding in begining of February after the first month of fieldwork was completed. Supervisors from the field delivered questionaires to NIS. Sida project expert and NIS Survey Manager helped in solving relevant matters that become apparent when reviewing questionires on delivery.

Response rate

The CSES 2016 enjoyed almost a 100 percent response rate. The high response rate together with close and systematic fieldwork supervision by the core group members were a major contribution for achieving high quality survey results.

Sampling error estimates

In order to provide a basis for assessing the reliability or precision of CSES estimates, the estimation of the magnitude of sampling error in the survey data were computed. Since most of the estimates from the survey are in the form of weighted ratios, thus variances for ratio estimates are computed.

The Coefficients of Variation (CV) on national level estimates are generally below 4 percent. The exception is the CV for total value of assets where there are rather high CVs especially in the urban areas, which should be expected.

The CVs are somewhat higher in the urban and rural domains but still generally below 7 percent. For the five zones, the average CVs are in the range 5 to 13 percent with a few exceptions where the CVs are above 20 percent. For provinces the CVs for food consumption are 9 percent on average.

The sample take within Primary Sampling Units (PSU) was set to 10 households per PSU in the CSES 1999. When data on variances became available, it was possible to make crude calculations of the optimal sample take within PSU. Calculations on some of the central estimates in the CSES 1999 show that the design effects in most cases are in the range 1 to 5.

Intra-cluster correlation coefficients have been calculated based on the design effects. These correlation coefficients are somewhat high. The reason is that the characteristics that are measured tend to be concentrated (clustered) within the PSUs. The optimal sample size within PSUs under different assumptions on cost ratios and intra-cluster correlation coefficients was then calculated. The cost ratio is the average cost for adding a village to the sample divided by the average cost of including an extra household in the sample. In the CSES, it was chosen to adopt a fairly low cost ratio due to the fact that the interview time per household is long. Under this assumption the optimal sample size is probably around 10 households per village for many of the CSES indicators.

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Household

UNITS IDENTIFIED: - Dwellings: Yes - Vacant units: No - Households: Yes - Individuals: Yes - Group quarters: No - Special populations: Persons without any normal residence, foreign nationals, and people in orphanages, rescue homes, ashram and vagrant houses are not covered by survey.

UNIT DESCRIPTIONS: - Households: A group of persons normally living together and taking food from a common kitchen will constitute a household. The members of a household may or may not be related by blood to one another.

Universe

All population in India, except for foreigners, the homeless, or people in orphanages, rescue homes, ashram, and vagrant houses.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: National Sample Survey Organization, Government of India

SAMPLE DESIGN: Two-staged, stratified systematic samples drawn by the country. Stage 1: In rural sector, regions are stratified based on population and crop pattern. Census villages (primary sampling units) are selected from region strata circular systematically with probability proportional to population. In urban sector, districts are stratified by population. Urban frame survey (UFS) blocks are the primary sampling units and selected from district strata circular systematically with equal probability. Stage 2: Selected large villages/blocks are split into hamlet-groups (rural) or sub-blocks (urban), some of which are randomly selected and they form the strata for Stage II, together with small villages/blocks selected in Stage I. Households are selected from those Stage II strata by circular systematically with a random start. Affluent households are over-sampled. The ratio of affluent to other households is 2:8 in rural sector and 4:6 in urban sector. In total, the central sample includes 7,284 villages and 4,792 urban blocks; the state sample includes 7,964 villages and 5,880 urban blocks.

SAMPLE UNIT: Household

SAMPLE FRACTION: .07%

SAMPLE SIZE (person records): 564,740

Mode of data collection

Face-to-face [f2f]

Research instrument

A single form that consists of 8 sections: 1) identification of sample household, 2) household characteristics, 3) demographic particulars and principal usual activity, 4) current work activity during the preceding week, 5) follow-up questions for the unemployed, 6) questions for working persons, 7) questions for children 5-14 years, and 8) questions for persons who attended domestic duties.

Response rate

COVERAGE: Entire country, in both rural and urban sectors

The Vehicle Inventory and Use Survey (VIUS) is conducted in partnership with the Bureau of Transportation Statistics, Federal Highway Administration, and the U.S. Department of Energy to better understand the characteristics and use of trucks on our nation's roads. The survey universe for the VIUS includes all private and commercial trucks registered (or licensed) in the United States. This includes: pickups; minivans, other light vans, and sport utility vehicles; other light single-unit trucks (GVW = 26,000 lbs.); and truck tractors. The VIUS sample excludes vehicles owned by federal, state, and local governments; ambulances; buses; motor homes; farm tractors; unpowered trailer units; and trucks reported to have been disposed of prior to January 1 of the survey year. VIUS provides data on the physical and operational characteristics of the nation's truck population. Its primary goal is to produce estimates of the total number of trucks and truck miles. This dataset provides national and state-level summary statistics for in-scope vehicles, excluding pickups, SUVs, minivans, and other light vans, that were used at least partially for commercial purposes.

Abstract

Susenas (National Socio-economic Survey) was held for the first time in year 1963. In the last two decades, up to year 2010, Susenas was conducted every year. Susenas was designed to have 3 modules (Module of Household Consumption/Expenditure, Module of Education and Socio-culture, and also Module of Health and Housing) and each module should be conducted every 3 years. Household Consumption/ Expenditure Module of Susenas shall be conducted in year 2011 .

To improve the accuracy of data result and in line with the increased frequency of household consumption/expenditure data request for quarterly GDP/GRDP and poverty calculation, data collection of household consumption/expenditure, it is planned that starting in 2011 it should be held quarterly. Each year, collecting data shall be conducted in March, June, September, and December.

In accordance with the 5-year cycle, in year 2012, BPS (Central Statistical Agency) shall have planned Survei Biaya Hidup-SBH (Cost of Living Survey) with the aim to generate a commodity package and a weigh diagram in the calculation of Consumer Price Index (CPI). Data of food and non-food consumption expenditures as well as household characteristics collected in SBH and Susenas has the same concept/definition, but different implementation time. In order to be more efficient in the utilization of resources of the two surveys and to have a better quality of results achieved, in year 2011 a trial of Susenas and SBH integration shall be conducted in 7 cities (Medan, Sampit, Denpasar, Kudus, Bulukumba, Tual, and South Jakarta).

Poverty data, CPI/Inflation data, GDP/GRDP are BPS strategic data that have to be released on time. Therefore, planning, field preparation, processing, and presentation of data Susenas 2011 activities and trial of integrating Susenas and SBH must be in accordance with the set schedule.

Activities of Susenas 2011 preparation shall be conducted in year 2010, covering activities of workshop/training of chief instructor with the aim to synchronize the perception toward the concept/definition as well as procedure and protocol of survey implementation. National instructor training will also be conducted in year 2010.

Geographic coverage

National coverage, representative to the district level

Analysis unit

Household Members (Individual) and Household

Universe

Susenas 2011 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

Abstract

The Iraq Household Socio-Economic Survey conducted in 2006-2007 (IHSES 2007), was Iraq's first nationwide income and expenditure survey since 1988. Based on the model of the Living Standards Measurement Surveys, it covered more than 18,000 households, collected detailed data on all aspects of household income and expenditure and generated information on a wide variety of socio-economic indicators. It also formed the basis for updating the Consumer Price Index (CPI), from an outdated index based in 1990 to a revised index with the base year of 2007. Detailed analysis of poverty, its incidence, characteristics, determinants and consequences, was undertaken using this comprehensive survey. Under the overall guidance of the Poverty Reduction Strategy High Committee (PRSHC) and a technical sub-committee, a poverty line was defined and adopted by the Council of Ministers.

Six years later, in 2012, the second round of the IHSES was completed. Learning from past and international experience on survey design, implementation and sampling, IHSES 2012 also incorporated additional modules on areas of evolving interest. It is the most comprehensive socio-economic survey as yet undertaken in Iraq.

Objectives of the survey: 1) to provide data to help measure and analyze poverty and monitor the implementation of the national strategy to alleviate poverty (issued in 2009) and update it with a new strategy, 2) to provide an integrated system of data to assess the social and economic situation of families and develop indicators related to human development, 3) to provide data meeting the requirements and needs of the national accounts, 4) to provide detailed indicators of consumer spending and the impact of various changes in it to serve the production, consumption, export and import decision-making, 5) to provide detailed indicators of the incomes of individuals and families by source, 6) to provide the data required for creating a new index record of consumer prices beyond 2012.

Geographic coverage

National coverage

Analysis unit

Households and individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

The IHSES intends to provide estimators of comparable quality for each of Iraq's 118 gadahs (districts). This implies that the sample should be explicitly stratified by gadah, with a similar sample size allocated to each gadah, regardless of its size. A sample size of 216 households per gadah is proposed, equivalent to a total sample of 25,488 households for the country.

Within each gadah, the sample will be selected in two stages, as follows:

• First, using Census Enumeration Areas (EAs) as Primary Sampling Units (PSUs), select 24 EAs with Probability Proportional to Size (PPS), using the number of households as a Measure of Size (MoS), and with implicit stratification by urban/rural and the subsequent geographical codes (nahya, mahala, village, mukataa and census block).

• Second, using households as secondary Sampling Units (SSUs), select a cluster of 9 households by systematic, equal probability sampling (SEPS) in each of the selected EAs.

The sample frames for both stages can be developed from the 2010 Census enumeration, with no updating of the household lists.

In some of the smallest gadahs, the standard PPS procedure may result in the selection of fewer than 24 EAs, with some of the larger EAs selected more than once. In those cases, two or more clusters will be taken in the EA, as needed. 2,832 EAs were selected in total. 33 of them had less than the 9 households nominally required in the second stage and were merged ex-post with neighboring EAs.

Mode of data collection

The data were collected using paper questionnaires with concurrent data entry in the field using Computer Assisted Field Entry (CAFE)

Research instrument

The survey questionnaire has four parts: Part 1 - Socio Economic Part 2 - Expenditure Part 3 - Income and other Data Part 4 - Household Diary

🇸🇦 사우디아라비아

New Zealand Economy Survey: Manufacturing: Sales: sa: Meat & Dairy Product data was reported at 7,975.021 NZD mn in Mar 2018. This records a decrease from the previous number of 8,370.430 NZD mn for Dec 2017. New Zealand Economy Survey: Manufacturing: Sales: sa: Meat & Dairy Product data is updated quarterly, averaging 4,820.441 NZD mn from Mar 1995 (Median) to Mar 2018, with 93 observations. The data reached an all-time high of 8,492.095 NZD mn in Dec 2013 and a record low of 2,524.197 NZD mn in Mar 1995. New Zealand Economy Survey: Manufacturing: Sales: sa: Meat & Dairy Product data remains active status in CEIC and is reported by Statistics New Zealand. The data is categorized under Global Database’s New Zealand – Table NZ.S005: Economy Survey: ANZSIC06: Seasonally Adjusted.

Abstract

Susenas is a survey designed to collect socio-demographic data in large area. The data collected were related to the fields of education, health / nutrition, housing / environmental, socio-cultural activities, consumption and household income, trips, and public opinion about the welfare of household. In 1992, Susenas data collection system has been updated, the information used to develop indicators of welfare (Welfare) contained in the module (information collected once every three years) drawn into the core (group information is collected each year).

In 2005 Susenas implement the module consumption / expenditure and household income. The data collected is the basic ingredient for calculating estimates of poverty based on consumption module Susenas three years (the latest data of 2002). However, given the poverty alleviation is a priority program of the current government; the Central bureau of statistic (BPS) attempted to provide data-poor national estimates on an annual basis. With the collecting data consumption / expenditure details every year it will be estimated annual number of poor people.

To meet the data needs of the government about the development of poor people every year, Panel Susenas collected the consumption and expenditure module data with the total sample of 10,000 households in 2003. The number of samples is only able to estimate the national poverty, while the demands of the availability data of poverty rate up to provincial level is increasing.

Geographic coverage

National coverage, representative to the district level

Analysis unit

Household Members (Individual) and Household

Universe

Implementation Susenas 2005 includes 278,352 households spread across. all geografls regions of Indonesian , with details of 68 288 households sample core-module and 210 064 households core sample (without modules), and 10,640 households sample of Susenas panel that is part of households sample core-module.

Kind of data

Sample survey data [ssd]

Sampling procedure

1. Susenas core

The design of sampling Susenas 2005 and Supas 2005 was conducted in an integrated manner in order to estimates some of the same variable can be done in an integrated manner. Sampling procedures Susenas 2005 for a 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).

• Phase 2, from nh selected nh census block for Susenas 2005, further referred to as census blocks Susenas. Household listing is conducted to all selected census blocks/sub-blocks.

• Phase 3, selecting m = 16 households in each census block selected systematically, for census block payloads of more than 150 households, it is necessary to selection of a sub-block census in PPS systematically with the size of the number of households P4B enumeration (April 2004).

1. Consumption Module / Household Expenditure and Household income with module sample sizes of consumption / expenditure and household income are designed for presentation at the provincial level. The module sample is section of subsample of selected sample for data estimate in district / city level (Census Block NSES), urban and rural areas. The subsample selected by Systematic Linear Sampling from selected census blocks in each district / city for urban and rural areas. Further census blocks selected (subsample) is the census block core-module, due beside enumerated with questionnaire module, also enumerated the core questionnaire. In other words, the census blocks that will be used to estimates at the provincial level (census block core-module) selected by systematic linear sampling from a list of selected census blocks in each district / city (census block core). Core-module census blocks is not selected 2004 Susenas is core census block.

2. Panel Module consumption /expenditure and household income in addition to the design of the sample selection core-module consumption / expenditure and household income above, in Susenas 2005 was also designed to perform the method of survey panel module consumption / expenditure and household income, where sample census block and panel sample of households (repetition) Susenas 2005 (the implementation in February 2005).

For the presentation of the poverty rate at the national level (February 2005), namely the implementation of the survey panel Susenas 2005 (February 2005), the number of census blocks will be selected from a sample of census blocks Susenas core-module (Susenas 2005, June 2005). The sample selection will be conducted in systematic sampling.

Mode of data collection

Face-to-face