10 datasets found
  1. Low income measure (LIM) thresholds by income source and household size

    • www150.statcan.gc.ca
    • open.canada.ca
    Updated May 1, 2025
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    Government of Canada, Statistics Canada (2025). Low income measure (LIM) thresholds by income source and household size [Dataset]. http://doi.org/10.25318/1110023201-eng
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    Dataset updated
    May 1, 2025
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Government of Canadahttp://www.gg.ca/
    Area covered
    Canada
    Description

    Low income measure (LIM) thresholds by household size for market income, total income and after-tax income, in current and constant dollars, annual.

  2. Low income cut-offs (LICOs) before and after tax by community size and...

    • www150.statcan.gc.ca
    • ouvert.canada.ca
    • +1more
    Updated May 1, 2025
    + more versions
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    Government of Canada, Statistics Canada (2025). Low income cut-offs (LICOs) before and after tax by community size and family size, in current dollars [Dataset]. http://doi.org/10.25318/1110024101-eng
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    Dataset updated
    May 1, 2025
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Low income cut-offs (LICOs) before and after tax by community size and family size, in current dollars, annual.

  3. Income of individuals by age group, sex and income source, Canada, provinces...

    • www150.statcan.gc.ca
    • ouvert.canada.ca
    • +2more
    Updated May 1, 2025
    + more versions
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    Government of Canada, Statistics Canada (2025). Income of individuals by age group, sex and income source, Canada, provinces and selected census metropolitan areas [Dataset]. http://doi.org/10.25318/1110023901-eng
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    Dataset updated
    May 1, 2025
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Income of individuals by age group, sex and income source, Canada, provinces and selected census metropolitan areas, annual.

  4. f

    Calculation of out-of-pocket cap based on five-level family income.

    • plos.figshare.com
    xls
    Updated Jun 18, 2023
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    Dengfeng Wu; Fang Yu; Wei Nie (2023). Calculation of out-of-pocket cap based on five-level family income. [Dataset]. http://doi.org/10.1371/journal.pone.0194915.t011
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    xlsAvailable download formats
    Dataset updated
    Jun 18, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Dengfeng Wu; Fang Yu; Wei Nie
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Calculation of out-of-pocket cap based on five-level family income.

  5. Income per capita by country in South America 2023

    • statista.com
    Updated Sep 9, 2024
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    Statista (2024). Income per capita by country in South America 2023 [Dataset]. https://www.statista.com/statistics/913999/south-america-income-per-capita/
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    Dataset updated
    Sep 9, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    Latin America, South America, Americas
    Description

    Guyana was the South American country 20360the highest gross national income per capita, with 20,360 U.S. dollars per person in 2023. Uruguay ranked second, registering a GNI of 19,530 U.S. dollars per person, based on current prices. Gross national income (GNI) is the aggregated sum of the value added by residents in an economy, plus net taxes (minus subsidies) and net receipts of primary income from abroad. Which are the largest Latin American economies? Based on annual gross domestic product, which is the total amount of goods and services produced in a country per year, Brazil leads the regional ranking, followed by Mexico, Argentina, and Chile. Many Caribbean countries and territories hold the highest GDP per capita in this region, measurement that reflects how GDP would be divided if it was perfectly equally distributed among the population. GNI per capita is, however, a more exact calculation of wealth than GDP per capita, as it takes into consideration taxes paid and income receipts from abroad. How much inequality is there in Latin America? In many Latin American countries, more than half the total wealth created in their economies is held by the richest 20 percent of the population. When a small share of the population concentrates most of the wealth, millions of people don't have enough to make ends meet. For instance, in Brazil, about 5.32 percent of the population lives on less than 3.2 U.S. dollars per day.

  6. e

    Household Expenditure and Income Survey, HEIS 2013 - Jordan

    • erfdataportal.com
    Updated Oct 12, 2022
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    Department of Statistics (2022). Household Expenditure and Income Survey, HEIS 2013 - Jordan [Dataset]. http://erfdataportal.com/index.php/catalog/128
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    Dataset updated
    Oct 12, 2022
    Dataset provided by
    Economic Research Forum
    Department of Statistics
    Time period covered
    2013 - 2014
    Area covered
    Jordan
    Description

    Abstract

    THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 25% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE DEPARTMENT OF STATISTICS OF THE HASHEMITE KINGDOM OF JORDAN

    Surveys related to the family budget are considered one of the most important surveys types carried out by the Department Of Statistics, since it provides data on household expenditure and income and their relationship with different indicators. Therefore, most of the countries undertake periodic surveys on household income and expenditures. The Department Of Statistics, since established, conducted a series of Expenditure and Income Surveys during the years 1966, 1980, 1986/1987, 1992, 1997, 2002/2003, 2006/2007, 2008/2009, 2010/2011 and because of continuous changes in spending patterns, income levels and prices, as well as in the population internal and external migration, it was necessary to update data for household income and expenditure over time. Hence, the need to implement the Household Expenditure and Income Survey for the year 2013 arises.

    The survey was then conducted to achieve the following objectives: 1. Provide data on income and expenditure to enable computation of poverty indices and determine the characteristics of the poor and prepare poverty maps. 2. Provide data weights that reflect the relative importance of consumer expenditure items used in the preparation of the consumer price index. 3. Provide the necessary data for the national accounts related to overall consumption and income of the household sector. 4. Provide the data necessary for the formulation, follow-up and evaluation of economic and social development programs, including those addressed to eradicate poverty. 5. Identify consumer spending patterns prevailing in the society, and the impact of demographic, social and economic variables on those patterns. 6. Calculate the average annual income of the household and the individual, and identify the relationship between income and different socio-economic factors, such as profession and educational level of the head of the household and other indicators. 7. Study the distribution of individuals and households by income and expenditure categories and analyze the factors associated with it.

    The raw survey data provided by the Statistical Agency were cleaned and harmonized by the Economic Research Forum, in the context of a major project that started in 2009. During which extensive efforts have been exerted to acquire, clean, harmonize, preserve and disseminate micro data of existing household surveys in several Arab countries.

    Geographic coverage

    The General Census of Population and Housing in 2004 provided a detailed framework for housing and households for different administrative levels in the Kingdom. Where the Kingdom is administratively divided into 12 governorates, each governorate is composed of a number of districts, each district (Liwa) includes one or more sub-district (Qada). In each sub-district, there are a number of communities (cities and villages). Each community was divided into a number of blocks. Where in each block, the number of houses ranged between 60 and 100 houses. Nomads, persons living in collective dwellings such as hotels, hospitals and prison were excluded from the survey framework.

    Analysis unit

    1- Household/family. 2- Individual/person.

    Universe

    The survey covered a national sample of households and all individuals permanently residing in surveyed households.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 25% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE DEPARTMENT OF STATISTICS OF THE HASHEMITE KINGDOM OF JORDAN

    The Household Expenditure and Income survey sample, for the year 2013, was designed to serve the basic objectives of the survey through providing a relatively large sample in each sub-district to enable drawing a poverty map in Jordan. A two stage stratified cluster sampling technique was used. In the first stage, a cluster sample proportional to the size was uniformly selected, where the number of households in each cluster was considered the weight of the cluster. At the second stage, a sample of 10 households was selected from each cluster, in addition to another 5 households selected as a backup for the basic sample, using a systematic sampling technique. Those 5 households were sampled to be used during the first visit to the block in case the visit to the original household selected is not possible for any reason. For the purposes of this survey, each sub-district was considered a separate stratum to ensure the possibility of producing results on the sub-district level. In this respect, the survey framework adopted that provided by the General Census of Population and Housing Census in dividing the sample strata. To estimate the sample size, the coefficient of variation and the design effect of the expenditure variable provided in the Household Expenditure and Income Survey for the year 2010 was calculated for each sub-district. These results were used to estimate the sample size on the sub-district level so that the coefficient of variation for the expenditure variable in each sub-district is less than 10%, at a minimum, of the number of clusters in the same sub-district (8 clusters). This is to ensure adequate presentation of clusters in different administrative areas to enable drawing an indicative poverty map. It should be noted that in addition to the standard non response rate assumed, higher rates were expected in areas where poor households are concentrated in major cities. Therefore, those were taken into consideration during the sampling design phase, and a higher number of households were selected from those areas, aiming at well covering all regions where poverty spreads.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    To reach the survey objectives, 3 forms have been developed. Those forms were finalized after being tested and reviewed by specialists taking into account making the data entry, and validation, process on the computer as simple as possible.

    (1) General Form/Questionnaire This form includes: - Housing characteristics such as geographic location variables, household area, building material predominant for external walls, type of tenure, monthly rent or lease, main source of water, lighting, heating and fuel cooking, sanitation type and water cycle, the number of rooms in the dwelling, in addition to providing ownership status of some home appliances and car. - Characteristics of household members: This form focused on the social characteristics of the family members such as relation to the head of the family, gender, age and educational status and marital status. It also included economic characteristics such as economic activity, and the main occupation, employment status, and the labor sector. To the additions of questions about individual continued to stay with the family, in order to update the information at the end of each of the four rounds of the survey. - Income section which included three parts · Family ownership of assets · Productive activities for the family · Current income sources

    (2) Expenditure on food commodities form/Questionnaire This form indicates expenditure data on 17 consumption groups. Each group includes a number of food commodities, with the exception of the latter group, which was confined to some of the non-food goods and services because of their frequent spending pattern on daily basis like food commodities. For the purposes of the efficient use of results, expenditure data of the latter group was moved with the non-food commodities expenditure. The form also includes estimated amounts of own-produced food items and those received as gifts or in an in-kind form, as well as servants living with the family spending on themselves from their own wages to buy food.

    (3) Expenditure on non-food commodities form/Questionnaire This form indicates expenditure data on 11 groups of non-food items, and 5 sets of spending on services, in addition to a group of consumption expenditure. It also includes an estimate of self-consumption, and non-food gifts or other items in an in-kind form received or sent by the household, as well as servants living with the family spending on themselves from their own wages to buy non-food items.

    Cleaning operations

    ----> Raw Data

    The data collection phase was then followed by the data processing stage accomplished through the following procedures: 1- Organizing forms/questionnaires A compatible archive system, with the nature of the subsequent operations, was used to classify the forms according to different round throughout the year. This is to effectively enable extracting the forms when required for processing. A registry was prepared to indicate different stages of the process of data checking, coding and entry till forms are back to the archive system. 2- Data office checking This phase is achieved concurrently with the data collection phase in the field, where questionnaires completed in the fieldwork are immediately sent to data office checking phase. 3- Data coding A team was trained to work on the data coding phase, which in this survey is only limited to education specialization, profession and economic activity. In this respect, international classifications were use, while for the rest of the questions, all coding were predefined

  7. t

    Calculate How an Increased Conversion Rate Can Impact Your Website

    • thegood.com
    html
    Updated Jul 9, 2024
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    The Good (2024). Calculate How an Increased Conversion Rate Can Impact Your Website [Dataset]. https://thegood.com/calculators/roi-conversion/
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    htmlAvailable download formats
    Dataset updated
    Jul 9, 2024
    Dataset authored and provided by
    The Good
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    User-centered Optimization Practices Average ROI Improved Website Performance Ongoing Strategic Advisement A general practitioner isn’t going to solve your digital experience challenges. You need a team of experts to diagnose and prescribe a solution. Every Digital Experience Optimization Program™ starts with an introductory call to see if it’s a good mutual fit. Let’s talk!

  8. Adjusted prevalence ratio for avoiding visiting a dental professional in the...

    • plos.figshare.com
    xls
    Updated Jul 7, 2023
    + more versions
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    Mona Abdelrehim; Vahid Ravaghi; Carlos Quiñonez; Sonica Singhal (2023). Adjusted prevalence ratio for avoiding visiting a dental professional in the past three years due to cost, from 2003-2013-14. [Dataset]. http://doi.org/10.1371/journal.pone.0280370.t003
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    xlsAvailable download formats
    Dataset updated
    Jul 7, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Mona Abdelrehim; Vahid Ravaghi; Carlos Quiñonez; Sonica Singhal
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Adjusted prevalence ratio for avoiding visiting a dental professional in the past three years due to cost, from 2003-2013-14.

  9. Household Budget Survey 1996, Quarter 3 - Lithuania

    • catalog.ihsn.org
    Updated Jan 16, 2021
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    Department of Statistics to the Government of the Republic of Lithuania (Statistics Lithuania) (2021). Household Budget Survey 1996, Quarter 3 - Lithuania [Dataset]. https://catalog.ihsn.org/catalog/8737
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    Dataset updated
    Jan 16, 2021
    Dataset provided by
    Government of Lithuaniahttps://lrv.lt/en
    State Data Agency of Lithuaniahttps://vda.lrv.lt/
    Authors
    Department of Statistics to the Government of the Republic of Lithuania (Statistics Lithuania)
    Time period covered
    1996
    Area covered
    Lithuania
    Description

    Abstract

    The Household Budget Survey (HBS) is a sample survey of private households carried out under the responsibility of the National Statistical Office. Historically the HBS has a long tradition: since 1952 it is conducted annually. The main objectives of the HBS are to provide information on the income and expenditure of the population. The main use of the HBS is the calculation of weights for Consumer Price Index, information on the household income, expenditure, data for National Accounting, and calculation of poverty indices. The HBS does contain only information on the occupation of respondents but not on the sector they are employed in.

    Analysis unit

    Households Individuals

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    Sampling The HBS is restricted to private households and household members. Collective or institutional households are excluded. Resident foreigner households (very few cases) are included. The sampling frame is taken from the population register (census) and has sample sizes of more than 8,000 households. For the HBS a two-stage stratification with 3 strata is applied (5 largest cities, other towns, rural areas). This sampling procedure leads to restriction in representativeness of the survey regarding the following population groups: young single persons, very rich households, homeless.

    Mode of data collection

    Telephone Interview

  10. f

    Baseline characteristics of Ontarians in the five cycles of the Canadian...

    • plos.figshare.com
    xls
    Updated Jul 7, 2023
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    Mona Abdelrehim; Vahid Ravaghi; Carlos Quiñonez; Sonica Singhal (2023). Baseline characteristics of Ontarians in the five cycles of the Canadian Community Health Survey (CCHS). [Dataset]. http://doi.org/10.1371/journal.pone.0280370.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jul 7, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Mona Abdelrehim; Vahid Ravaghi; Carlos Quiñonez; Sonica Singhal
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Ontario, Canada
    Description

    Baseline characteristics of Ontarians in the five cycles of the Canadian Community Health Survey (CCHS).

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    Learn how you can add new datasets to our index.

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Government of Canada, Statistics Canada (2025). Low income measure (LIM) thresholds by income source and household size [Dataset]. http://doi.org/10.25318/1110023201-eng
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Low income measure (LIM) thresholds by income source and household size

1110023201

Explore at:
Dataset updated
May 1, 2025
Dataset provided by
Statistics Canadahttps://statcan.gc.ca/en
Government of Canadahttp://www.gg.ca/
Area covered
Canada
Description

Low income measure (LIM) thresholds by household size for market income, total income and after-tax income, in current and constant dollars, annual.

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