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.

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.

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.

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.

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%.

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

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.

🇸🇦 사우디아라비아

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]

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.

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.

This statistic presents the development of net balances for services industry domestic orders in the United Kingdom (UK), showing figures for quarters three and four of 2013 and quarters one and two of 2014. In second quarter of 2014, net balance for services sector domestic orders have closed at ** percent.

New Zealand 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. New Zealand 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. New Zealand 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.

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

A cross-national data archive located in Luxembourg that contains two primary databases: the Luxembourg Income Study Database (LIS Database) includes income microdata from a large number of countries at multiple points in time. The newer Luxembourg Wealth Study Database(LWS Database) includes wealth microdata from a smaller selection of countries. Both databases include labor market and demographic data as well. Our mission is to enable, facilitate, promote, and conduct cross-national comparative research on socio-economic outcomes and on the institutional factors that shape those outcomes. Since its beginning in 1983, the LIS has grown into a cooperative research project with a membership that includes countries in Europe, North America, and Australia. The database now contains information for more than 30 countries with datasets that span up to three decades. The LIS databank has a total of over 140 datasets covering the period 1968 to 2005. The primary objectives of the LIS are as follows: * Test the feasibility for creating a database containing social and economic data collected in household surveys from different countries; * Provide a method which allows researchers to use the data under restrictions required by the countries providing the data; * Create a system that allows research requests to be received from and returned to users at remote locations; and * Promote comparative research on the social and economic status of various populations and subgroups in different countries. Data Availability: The dataset is accessed globally via electronic mail networks. Extensive documentation concerning technical aspects of the survey data, variables list, and the social institutions of income provision in member countries are also available to users through the project Website. * Dates of Study: 1968-present * Study Features: International * Sample Size: 30+ Countries Link: * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/00150

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

UNIT DESCRIPTIONS: - Households: A group of persons normally living together and taking food from a common kitchen.

Universe

All population in India, except for under-trial prisoners in jails and indoor patients of hospitals, nursing homes, floating population without normal residence, foreign nationals, persons residing in barracks of military and paramilitary forces(not cilivian population who reside there), orphanages, rescue homes, ashrams and vagrant houses are excluded.

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/urban sector.

SAMPLE UNIT: Household

SAMPLE FRACTION: .06%

SAMPLE SIZE (person records): 602,833

Mode of data collection

Face-to-face [f2f]

Research instrument

A single form that consists of 9 sections on characteristics of sample households and household members

Response rate

COVERAGE: 100% of the Indian Union excepting (1) Ladakh and Kargil districts of Jammu and Kashmir, (2) interior villages of nagaland situated beyond 5 kms. of a bus route, and (3) villages of Andaman and Nicobar Islands remaining inaccessible throught the year.

This dataset contains the anonymised results of a survey of customers who buy groundwater for consumption in Kisumu, Kenya. Data includes information on the amount of water bought and ways in which this water was used and handled, as well as their use of water from other sources. Data about assets and services, including access to food, are also included. The surveys were carried out during February and March 2014 and include data from 137 well customers. The data were collected as part of the Groundwater2030 project, which aims to reduce the health problems that result from consumption of contaminated groundwater in urban areas of Africa. The project was co-ordinated by the University of Southampton, with partners at the University of Surrey, the Victoria Institute of Research on Environment and Development (VIRED) International, and the Jaramogi Oginga Odinga University of Science and Technology. The project was funded by the Natural Environment Research Council and the Department for International Development as part of the Unlocking the Potential of Groundwater for the Poor (UPGro) programme. Full details about this dataset can be found at https://doi.org/10.5285/6f3f1d06-4e6b-435e-a770-af7549993b88

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