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.

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]

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

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]

Saudi Arabia Economic Survey of Establishments: ER: ow Oil and Gas Extraction data was reported at 665,325,998.000 SAR th in 2016. This records a decrease from the previous number of 747,668,545.000 SAR th for 2015. Saudi Arabia Economic Survey of Establishments: ER: ow Oil and Gas Extraction data is updated yearly, averaging 824,639,180.500 SAR th from Dec 2005 (Median) to 2016, with 12 observations. The data reached an all-time high of 1,355,124,781.000 SAR th in 2013 and a record low of 654,937,072.000 SAR th in 2009. Saudi Arabia Economic Survey of Establishments: ER: ow Oil and Gas Extraction 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.

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

general authority for statistics, annual economic survey of establishments - Economic indicators for Wholesale & Retail Trade Activity-2010 | gimi9.com

Graph and download economic data for Business Tendency Surveys: Orders Inflow: Economic Activity: Manufacturing: Tendency for Luxembourg (BSOITE02LUQ460S) from Q1 1985 to Q3 2025 about Luxembourg, business sentiment, orders, business, and manufacturing.

SHE: All Japan: Exp: Traval Expenses: Airplane Fares data was reported at 1,313.000 JPY in Oct 2018. This records an increase from the previous number of 1,074.000 JPY for Sep 2018. SHE: All Japan: Exp: Traval Expenses: Airplane Fares data is updated monthly, averaging 979.000 JPY from Jan 2002 (Median) to Oct 2018, with 202 observations. The data reached an all-time high of 1,989.000 JPY in Aug 2008 and a record low of 571.000 JPY in Feb 2011. SHE: All Japan: Exp: Traval Expenses: Airplane Fares data remains active status in CEIC and is reported by Statistical Bureau. The data is categorized under Global Database’s Japan – Table JP.H069: Survey of Household Economy: All Japan.

Key Table Information.Table Title.Manufacturing: E-Commerce Statistics for the U.S.: 2022.Table ID.ECNECOMM2022.EC2231ECOMM.Survey/Program.Economic Census.Year.2022.Dataset.ECN Core Statistics Manufacturing: E-Commerce Statistics for the U.S.: 2022.Release Date.2025-01-23.Release Schedule.The Economic Census occurs every five years, in years ending in 2 and 7.The data in this file come from the 2022 Economic Census data files released on a flow basis starting in January 2024 with First Look Statistics. Preliminary U.S. totals released in January 2024 are superseded with final data shown in the releases of later economic census statistics through March 2026.For more information about economic census planned data product releases, see 2022 Economic Census Release Schedule..Dataset Universe.The dataset universe consists of all establishments that are in operation for at least some part of 2022, are located in one of the 50 U.S. states, associated offshore areas, or the District of Columbia, have paid employees, and are classified in one of nineteen in-scope sectors defined by the 2022 North American Industry Classification System (NAICS)..Methodology.Data Items and Other Identifying Records.Sales, value of shipments, or revenue ($1,000)E-Shipments value ($1,000) E-Shipments as percent of total sales, value of shipments, or revenue (%) Range indicating imputed percentage of total sales, value of shipments, or revenueDefinitions can be found by clicking on the column header in the table or by accessing the Economic Census Glossary..Unit(s) of Observation.The reporting units for the economic census are employer establishments. An establishment is generally a single physical location where business is conducted or where services or industrial operations are performed. A company or firm is comprised of one or more in-scope establishments that operate under the ownership or control of a single organization. For some industries, the reporting units are instead groups of all establishments in the same industry belonging to the same firm..Geography Coverage.The data are shown for the U.S. level only. For information about economic census geographies, including changes for 2022, see Geographies..Industry Coverage.The data are shown at the 2- through 3-digit 2022 NAICS code levels for the U.S. For information about NAICS, see Economic Census Code Lists..Sampling.The 2022 Economic Census sample includes all active operating establishments of multi-establishment firms and approximately 1.7 million single-establishment firms, stratified by industry and state. Establishments selected to the sample receive a questionnaire. For all data on this table, establishments not selected into the sample are represented with administrative data. For more information about the sample design, see 2022 Economic Census Methodology..Confidentiality.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. 7504609, Disclosure Review Board (DRB) approval number: CBDRB-FY23-099).To protect confidentiality, the U.S. Census Bureau suppresses cell values to minimize the risk of identifying a particular business’ data or identity.To comply with disclosure avoidance guidelines, data rows with fewer than three contributing firms or three contributing establishments are not presented. Additionally, establishment counts are suppressed when other select statistics in the same row are suppressed. More information on disclosure avoidance is available in the 2022 Economic Census Methodology..Technical Documentation/Methodology.For detailed information about the methods used to collect data and produce statistics, survey questionnaires, Primary Business Activity/NAICS codes, NAPCS codes, and more, see Economic Census Technical Documentation..Weights.No weighting applied as establishments not sampled are represented with administrative data..Table Information.FTP Download.https://www2.census.gov/programs-surveys/economic-census/data/2022/sector31/.API Information.Economic census data are housed in the Census Bureau Application Programming Interface (API)..Symbols.D - Withheld to avoid disclosing data for individual companies; data are included in higher level totalsN - Not available or not comparableS - Estimate does not meet publication standards because of high sampling variability, poor response quality, or other concerns about the estimate quality. Unpublished estimates derived from this table by subtraction are subject to these same limitations and should not be attributed to the U.S. Census Bureau. For a description of publication standards and the total quantity response rate, see link to program methodology page.X - Not applicableA - Relative standard error of 100% or morer - Reviseds - Relative standard error exceeds 40%For a complete list of symbols, see Economic Census Data Dictionary..Data-Specific Notes.Data users who create their own es...

SHE: All Japan: Exp: EA: Washing Machines data was reported at 597.000 JPY in May 2018. This records an increase from the previous number of 548.000 JPY for Apr 2018. SHE: All Japan: Exp: EA: Washing Machines data is updated monthly, averaging 514.000 JPY from Jan 2002 (Median) to May 2018, with 197 observations. The data reached an all-time high of 1,406.000 JPY in Mar 2014 and a record low of 328.000 JPY in Jan 2009. SHE: All Japan: Exp: EA: Washing Machines data remains active status in CEIC and is reported by Statistical Bureau. The data is categorized under Global Database’s Japan – Table JP.H070: Survey of Household Economy: All Japan.

About this dataset

Context

The dataset tabulates the population of Economy by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Economy. The dataset can be utilized to understand the population distribution of Economy by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Economy. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Economy.

Key observations

Largest age group (population): Male # 65-69 years (412) | Female # 60-64 years (490). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Economy population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Economy is shown in the following column.
• Population (Female): The female population in the Economy is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Economy for each age group.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Economy Population by Gender. You can refer the same here

United States SB: MN: Finance: PC: Increased data was reported at 3.600 % in 11 Apr 2022. This records a decrease from the previous number of 4.900 % for 04 Apr 2022. United States SB: MN: Finance: PC: Increased data is updated weekly, averaging 4.900 % from Feb 2022 (Median) to 11 Apr 2022, with 9 observations. The data reached an all-time high of 6.700 % in 14 Feb 2022 and a record low of 3.600 % in 11 Apr 2022. United States SB: MN: Finance: PC: Increased data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S047: Small Business Pulse Survey: by State: Midwest Region: Weekly, Beg Monday (Discontinued).

United States SB: ES: CS: Demand: Moderate Increase data was reported at 36.100 % in 11 Apr 2022. This records a decrease from the previous number of 41.500 % for 04 Apr 2022. United States SB: ES: CS: Demand: Moderate Increase data is updated weekly, averaging 37.700 % from Feb 2022 (Median) to 11 Apr 2022, with 9 observations. The data reached an all-time high of 44.500 % in 21 Mar 2022 and a record low of 33.300 % in 14 Mar 2022. United States SB: ES: CS: Demand: Moderate Increase data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S045: Small Business Pulse Survey: by Sector: Weekly. Beg Monday (Discontinued).

Denton economic data from the American Community Survey (ACS)

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.

Release Date: 2020-06-09.Release Schedule:.The data in this file come from the 2017 Economic Census data files released on a flow basis starting in September 2019. As such, preliminary U.S. totals released in September 2019 will be superseded with final totals, by sector, once data for all states have been released. Users should be aware that during the release of this consolidated file, data at more detailed North American Industry Classification System (NAICS) and geographic levels may not add to higher-level totals. However, at the completion of the economic census (once all the component files have been released), the detailed data in this file will add to the totals. For more information about economic census planned data product releases, see Economic Census: About: 2017 Release Schedules...Key Table Information:.U.S. totals released in September 2019 will be superseded with final totals, by sector, once data for all states have been released. .Includes only establishments and firms with payroll..Data may be subject to employment- and/or sales-size minimums that vary by industry...Data Items and Other Identifying Records: .Number of firms.Number of establishments.Sales, value of shipments, or revenue ($1,000).Annual payroll ($1,000).First-quarter payroll ($1,000).Number of employees.Range indicating percent of total sales, value of shipments, or revenue imputed.Range indicating percent of total annual payroll imputed.Range indicating percent of total employees imputed..Geography Coverage:.The data are shown for employer establishments and firms at the U.S., State, Combined Statistical Area, Metropolitan and Micropolitan Statistical Area, Metropolitan Division, Consolidated City, County (and equivalent), and Economic Place (and equivalent; incorporated and unincorporated) levels that vary by industry. For information about economic census geographies, including changes for 2017, see Economic Census: Economic Geographies...Industry Coverage:.The data are shown at the 2- through 6-digit 2017 NAICS code levels. For information about NAICS, see Economic Census: Technical Documentation: Code Lists...Footnotes:.Not applicable...FTP Download:.Download the entire table at: https://www2.census.gov/programs-surveys/economic-census/data/2017/sector53/EC1753BASIC.zip..API Information:.Economic census data are housed in the Census Bureau API. For more information, see Explore Data: Developers: Available APIs: Economic Census..Methodology:.To maintain confidentiality, the U.S. Census Bureau suppresses data to protect the identity of any business or individual. The census results in this file contain sampling and/or nonsampling error. Data users who create their own estimates using data from this file should cite the U.S. Census Bureau as the source of the original data only...To comply with disclosure avoidance guidelines, data rows with fewer than three contributing establishments are not presented. Additionally, establishment counts are suppressed when other select statistics in the same row are suppressed. For detailed information about the methods used to collect and produce statistics, including sampling, eligibility, questions, data collection and processing, data quality, review, weighting, estimation, coding operations, confidentiality protection, sampling error, nonsampling error, and more, see Economic Census: Technical Documentation: Methodology...Symbols:.D - Withheld to avoid disclosing data for individual companies; data are included in higher level totals.N - Not available or not comparable.S - Estimate does not meet publication standards because of high sampling variability, poor response quality, or other concerns about the estimate quality. Unpublished estimates derived from this table by subtraction are subject to these same limitations and should not be attributed to the U.S. Census Bureau. For a description of publication standards and the total quantity response rate, see link to program methodology page..X - Not applicable.A - Relative standard error of 100% or more.r - Revised.s - Relative standard error exceeds 40%.For a complete list of symbols, see Economic Census: Technical Documentation: Data Dictionary.. .Source:.U.S. Census Bureau, 2017 Economic Census.For information about the economic census, see Business and Economy: Economic Census...Contact Information:.U.S. Census Bureau.For general inquiries:. (800) 242-2184/ (301) 763-5154. ewd.outreach@census.gov.For specific data questions:. (800) 541-8345.For additional contacts, see Economic Census: About: Contact Us.

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