17 datasets found
  1. U.S. Unemployment Rates

    • kaggle.com
    Updated Jun 10, 2024
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    Guillem SD (2024). U.S. Unemployment Rates [Dataset]. https://www.kaggle.com/datasets/guillemservera/us-unemployment-rates
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jun 10, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Guillem SD
    License

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

    Area covered
    United States
    Description

    Introduction

    The U.S. job market, with its dynamic trends and fluctuating unemployment rates, serves as an important barometer for the nation's economic health. All rates provided in this dataset are seasonally adjusted. Delving into the intricacies of unemployment rates by age and gender helps researchers, policymakers, and analysts uncover underlying patterns and address potential disparities.

    Usage Examples

    • Economic Research: Study the historical unemployment trends to gauge economic cycles.
    • Policy Making: Inform labor market policies and interventions based on age or gender disparities.
    • Business Strategy: Companies can analyze job market conditions when considering expansions or contractions.
    • Academic Projects: Students and educators can use the dataset for case studies, dissertations, or classroom projects.

    Image Source Photo by Ron Lach : https://www.pexels.com/photo/woman-looking-for-jobs-in-newspaper-9832700/

    Dataset Contents

    This dataset, sourced from the FRED API, provides: - df_sex_unemployment_rates.csv: A breakdown of U.S. unemployment rates based on gender. - df_unemployment_rates.csv: Unemployment rates categorized by various age groups, ranging from young entrants (ages 16-17) to seasoned professionals (55 and above).

    Together, these data files offer a comprehensive insight into the nuances of unemployment in the U.S., highlighting potential disparities in the job market across different age groups and between men and women.

  2. Data from: News media in crisis: a sentiment and emotion analysis of US news...

    • figshare.com
    zip
    Updated May 22, 2024
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    Lingli Yu; Ling Yang (2024). News media in crisis: a sentiment and emotion analysis of US news articles on unemployment in the COVID-19 pandemic [Dataset]. http://doi.org/10.6084/m9.figshare.25879897.v1
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    zipAvailable download formats
    Dataset updated
    May 22, 2024
    Dataset provided by
    figshare
    Figsharehttp://figshare.com/
    Authors
    Lingli Yu; Ling Yang
    License

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

    Description

    This study, integrating sentiment, emotion, discourse, and timeline analyses together, conducts a corpus-based sentiment analysis of the news articles on unemployment from the New York Times in 2020, to capture the emotional dynamics conveyed by the newspaper as the pandemic-induced unemployment developed in the US. The results reveal that positive sentiment in the news articles on unemployment is significantly higher than negative sentiment. In emotion analysis, “trust” and “anticipation”rank the first and second among the eight emotions, while “fear”and “sadness” top the negative emotions. Complemented with a discourse analysis approach, the study reveals that the change of the sentiments and emotions over time is linked with the evolution of the pandemic and unemployment, the policy response as well as the protests against ethnic inequalities. This study highlights the important role mainstream news media play in information dissemination and solution-focused reportage at the time of severe crisis.This dataset contains 14 documents for the data of 2 sentiments and 8 emotions, generated by Python. It includes NRC lexicon categories for the sentiments and emotions in the study (data1-10), top 10 high-frequency words associated to the sentiments and emotions in each of the 12 subcorpora (data11-12), and monthly values of the sentiments and emotions in 2020 (data 13-14).

  3. p

    Labour Force Survey Job Permanency

    • data.peelregion.ca
    • hub.arcgis.com
    Updated Apr 16, 2020
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    Regional Municipality of Peel (2020). Labour Force Survey Job Permanency [Dataset]. https://data.peelregion.ca/datasets/labour-force-survey-job-permanency
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    Dataset updated
    Apr 16, 2020
    Dataset authored and provided by
    Regional Municipality of Peel
    License

    https://data.peelregion.ca/pages/licensehttps://data.peelregion.ca/pages/license

    Area covered
    Description

    The Labour Force Survey (LFS) is the only survey conducted by Statistics Canada designed to provide the official unemployment rate every month, with a monthly sample size of approximately 56,000 households. It is the earliest and most timely indicator of the pulse of the labour market in Canada. Statistics Canada provides a Guide to the Labour Force Survey.Note: This dataset primarily focuses on employees: those who do paid work for others. Therefore, totals do not align to totals in Labour Force Characteristics dataset, which focuses on everyone in the labour force.DefinitionsEmployee - A person who does paid work for others.Work - Includes any work for pay or profit, that is, paid work in the context of an employer-employee relationship or self-employment. It also includes work performed by those working in family business without pay (unpaid family workers).Permanent - A permanent job is one that is expected to last as long as the employee wants it, business conditions permitting. That is, there is no predetermined termination date.Temporary - A temporary job has a predetermined end date, or will end as soon as a specified project is completed. Information is collected to allow the sub-classification of temporary jobs into four groups: seasonal; temporary, term or contract, including work done through a temporary help agency; casual job; and other temporary work.Employment - Employed persons are those who, during the reference week, did any work for pay or profit or had a job and were absent from work. Self-employment - Working owners of an incorporated business, farm or professional practice, or working owners of an unincorporated business, farm or professional practice. The latter group also includes self-employed workers who do not own a business (such as babysitters and newspaper carriers). Self-employed workers are further subdivided by those with or without paid help. Also included among the self-employed are unpaid family workers. They are persons who work without pay on a farm or in a business or professional practice owned and operated by another family member living in the same dwelling. They represented approximately 1% of the self-employed in 2016.Unemployment - Unemployed persons are those who, during reference week, were without work, were available for work and were either on temporary layoff, had looked for work in the past four weeks or had a job to start within the next four weeks.

  4. r

    High school completion and future youth unemployment: new evidence from High...

    • resodate.org
    Updated Oct 2, 2025
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    Mingliang Li (2025). High school completion and future youth unemployment: new evidence from High School and Beyond (replication data) [Dataset]. https://resodate.org/resources/aHR0cHM6Ly9qb3VybmFsZGF0YS56YncuZXUvZGF0YXNldC9oaWdoLXNjaG9vbC1jb21wbGV0aW9uLWFuZC1mdXR1cmUteW91dGgtdW5lbXBsb3ltZW50LW5ldy1ldmlkZW5jZS1mcm9tLWhpZ2gtc2Nob29sLWFuZC1iZXlvbmQ=
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    Dataset updated
    Oct 2, 2025
    Dataset provided by
    ZBW
    ZBW Journal Data Archive
    Journal of Applied Econometrics
    Authors
    Mingliang Li
    Description

    In this paper, I provide new evidence from High School and Beyond (HSB) on the effects of compulsory attendance on high school completion and future youth unemployment. I develop Bayesian estimation approaches to the simultaneous equation model with ordered probit and two-limit censored regression and the bivariate duration model, accounting for the heterogeneity in returns to education and the nonlinearity in the effects of compulsory attendance. I find substantial variability in returns to education across schools and evidence of diminishing marginal effects of compulsory attendance on high school completion. The simulation results suggest that increasing the compulsory attendance age raises the probability of completing high school and reduces the proportion of time the individuals are unemployed. These effects are much more pronounced for disadvantaged students but less pronounced for advantaged students, suggesting the potential effects of compulsory attendance on reducing the inequality in education and employment.

  5. c

    Data from: Are Young College Graduates Losing Their Edge in the Job Market?

    • clevelandfed.org
    Updated Nov 24, 2025
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    Federal Reserve Bank of Cleveland (2025). Are Young College Graduates Losing Their Edge in the Job Market? [Dataset]. https://www.clevelandfed.org/publications/economic-commentary/2025/ec-202514-are-young-college-graduates-losing-their-edge-in-the-job-market
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    Dataset updated
    Nov 24, 2025
    Dataset authored and provided by
    Federal Reserve Bank of Cleveland
    Description

    High school graduates in their twenties have consistently experienced a higher unemployment rate than college graduates in the same age range. However, the unemployment gap between the two education groups has recently narrowed, reaching its lowest level since the late 1970s. This Economic Commentary shows that this narrowing coincides with a decades-long decline, one that began around 2000, in the job-finding rate among young college graduates.

  6. T

    Philippines Unemployment Rate

    • tradingeconomics.com
    • pt.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Oct 8, 2025
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    TRADING ECONOMICS (2025). Philippines Unemployment Rate [Dataset]. https://tradingeconomics.com/philippines/unemployment-rate
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    json, excel, xml, csvAvailable download formats
    Dataset updated
    Oct 8, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

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

    Time period covered
    Mar 31, 1986 - Sep 30, 2025
    Area covered
    Philippines
    Description

    Unemployment Rate in Philippines decreased to 3.80 percent in September from 3.90 percent in August of 2025. This dataset provides - Philippines Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  7. c

    How Insured Are Workers Against Unemployment? Unemployment Insurance and the...

    • clevelandfed.org
    Updated Oct 15, 2024
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    Federal Reserve Bank of Cleveland (2024). How Insured Are Workers Against Unemployment? Unemployment Insurance and the Distribution of Liquid Wealth [Dataset]. https://www.clevelandfed.org/publications/economic-commentary/2024/ec-202416-unemployment-insurance-and-distribution-of-liquid-wealth
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    Dataset updated
    Oct 15, 2024
    Dataset authored and provided by
    Federal Reserve Bank of Cleveland
    Description

    In this Economic Commentary , we analyze the relationship between unemployment insurance (UI) recipiency and insurance by examining the wealth distribution of workers who have been through an unemployment spell. We focus on the net liquid wealth gap between recipients and nonrecipients of UI along the income distribution of the unemployed. Using recent data from the Survey of Income and Program Participation at the individual level, we estimate that UI recipients at the bottom half of the income distribution tend to have higher median net liquid wealth than nonrecipients, putting nonrecipients in a potentially vulnerable economic position during periods of unemployment. Replication codes for this paper are available at https://github.com/avdluduvice/LuduviceTruss-Williams_UI .

  8. X01: Labour Force Survey single-month estimates

    • ons.gov.uk
    • cy.ons.gov.uk
    xlsx
    Updated Nov 11, 2025
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    Office for National Statistics (2025). X01: Labour Force Survey single-month estimates [Dataset]. https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/employmentandemployeetypes/datasets/labourforcesurveysinglemonthestimatesx01
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    xlsxAvailable download formats
    Dataset updated
    Nov 11, 2025
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    Single-month estimates of employment, unemployment and economic inactivity, UK, rolling three-monthly figures published monthly, seasonally adjusted. Labour Force Survey.

  9. g

    Eurobarometer 37.1 (Apr-May 1992)

    • search.gesis.org
    • datacatalogue.cessda.eu
    Updated Jul 1, 2012
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    European Commission, Brussels; DG X - Information Communication Culture Surveys Research Analyses (2012). Eurobarometer 37.1 (Apr-May 1992) [Dataset]. http://doi.org/10.4232/1.10901
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    application/x-stata-dta(7257419), application/x-spss-por(13427664), application/x-spss-sav(7768115), (3418)Available download formats
    Dataset updated
    Jul 1, 2012
    Dataset provided by
    GESIS Data Archive
    GESIS search
    Authors
    European Commission, Brussels; DG X - Information Communication Culture Surveys Research Analyses
    License

    https://www.gesis.org/en/institute/data-usage-termshttps://www.gesis.org/en/institute/data-usage-terms

    Time period covered
    Apr 20, 1992 - May 19, 1992
    Variables measured
    v418 - D10 SEX, v4 - PART NUMBER, v456 - P7 REGION I, v13 - WEIGHT EURO 6, v3 - EDITION NUMBER, v457 - P7 REGION II, v14 - WEIGHT EURO 10, v15 - WEIGHT EURO 12, v419 - D11 AGE EXACT, v446 - D29 INCOME HH, and 454 more
    Description

    The main topics of this Eurobarometer are:

    1. Paying attention to product information,

    2. Social security,

    3. Older people and retirement questions.

    Topics: Citizenship and eligibility to vote at place of residence; general contentment with life; personal opinion leadership and frequency of political discussions; interest in politics; postmaterialism; frequency of listening to news on the radio, television and reading news in the paper.

    1. Product information: paying attention to product information before purchase of foods and non-foodstuffs; detailed information on significance of selected product information in the decision to purchase vegetables, ready-to-serve meals, fruits, meat, fish, clothing, cosmetics, furniture, televisions, washing and cleansing agents; additionally desired product information and preference for Europe-wide standardization.

    2. Social security: judgement on the social security system and social security in the country; preference for government or individual provision and Europe-wide standardization; adequate welfare for the unemployed, the old, the sick and the poor in the country; preference for national or European decisions in questions of establishing minimum income, unemployment benefit and pensions; attitude to equal treatment of locals and foreigners in questions of social security; impact from longer-term illnesss and disabilities; contacts with doctors during the last month or restrictions due to illness; inclination to visit the doctor for selected health complaints; utilization of medical check-ups; appropriateness of a percentage of the costs of selected medical services for patients; self-treatment and use of medication on doctor´s orders; general judgement on provision of medical care in the country; attitude to the public health system and judgement on services (scale); possession of a private health insurance or supplementary insurances; attitude to government support for the less well-off; assumed insufficient knowledge of the less well-off about support services to which they are entitled; doing without support for fear of discrimination; family responsibility for prosperity of family members and government responsibility for elimination of poverty (scale); judgement on the length of maternity leave and support servicesduring this time; attitude to particular help for single-parents; child allowance for everyone or only for parents less financially well-off; times of unemployment during the last five years; probability of future unemployment; preference for high unemployment support of short duration or low unemployment support for a longer time; attitude to the rights and duties of the unemployed regarding rejecting jobs available and further education; assumed reduction of the number of unemployed from reduction of support.

    3. Older people and retirement questions: most important problems of older people; attitude to older people (scale); expected development of the retirement age and retirement income; increase in the welfare state with increased support for older people; desire for equal treatment of men and women regarding retirement age, pension fund contributions and pensions; assessment of appropriate participation of older people in politics, in social activities and in the media; attitude to permitted paid occupation of the retired; perceived discrimination of older people in professional life; attitude to legal protection against age discrimination; appropriate consideration of the interests of older people by public agencies; preferred level of guaranteed minimum income for older people; preference for care in a home or for people in need of care to remain in their home environment; looking after members of the family or friends in need of care; most able care-giver; attitude to a flexible age limit; appropriate amount of a survivor´s pension; attitude to rights to a pension for raising children and care of old family members or those in need of care; attitude to reduction of pension with work income; self-assessment of level of standard of living; assessment of general amount of pension; preference for compulsory, employer-related or private retirement insurance as well as for compulsory or private nursing care insurance.

    Demography: self-classification on a left-right continuum; union membership; marital status; age at end of education; sex; age; size of household; number of children in household; possession of durable economic goods; occupational p...

  10. c

    Financial Expectations; 15-21 April 1971

    • datacatalogue.cessda.eu
    Updated Nov 28, 2024
    + more versions
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    British Market Research Bureau (2024). Financial Expectations; 15-21 April 1971 [Dataset]. http://doi.org/10.5255/UKDA-SN-133-1
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    Dataset updated
    Nov 28, 2024
    Authors
    British Market Research Bureau
    Time period covered
    Apr 15, 1971 - Apr 21, 1971
    Area covered
    Great Britain
    Variables measured
    National, Adults, Consumers
    Description

    Abstract copyright UK Data Service and data collection copyright owner.

    These are a series of surveys containing questions asked of a monthly representative sample of 1000 adults about their financial well-being and expectations by the British Market Research Bureau.
    Main Topics:
    The questions asked in the surveys, based on those developed by Katona and others at Michigan University, are intended to measure the three factors, 'ability', 'willingness to buy' and 'timing', on which future purchasing decisions are held to depend.
    Background variables include: sex; age cohort; marital and occupational status of senior head of household and of other members of household; terminal education age; home ownership; newspaper readership; television viewing patterns and cinema attendance.

  11. g

    Panel der Hochschule der Künste Berlin 1975 - 1995

    • search.gesis.org
    • da-ra.de
    Updated Apr 13, 2010
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    Schreiber, Klaus; Espe, Hartmut; Koepcke, A.; Institut für Gesellschafts- und Wirtschaftskommunikation, Forschungsgruppe Kommunikationssoziologie an der HDK Berlin (2010). Panel der Hochschule der Künste Berlin 1975 - 1995 [Dataset]. http://doi.org/10.4232/1.2691
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    Dataset updated
    Apr 13, 2010
    Dataset provided by
    GESIS search
    GESIS Data Archive
    Authors
    Schreiber, Klaus; Espe, Hartmut; Koepcke, A.; Institut für Gesellschafts- und Wirtschaftskommunikation, Forschungsgruppe Kommunikationssoziologie an der HDK Berlin
    License

    https://www.gesis.org/en/institute/data-usage-termshttps://www.gesis.org/en/institute/data-usage-terms

    Description

    Socio-cultural changes of values. Consumer habits and conduct in media reception. Communicative effect research. Life style.

    Topics: the data set contains 51 survey waves.$June 1975: Uninhabitability of the Earth through human intervention; political goals; satisfaction with school and vocational training; smoking; restriction of automobile traffic; nuclear power; equal opportunities in vocational training.

    August 1975: New partnership in marriage; most urgent personal desire; democracy restriction; political reforms versus preservation; need and environmental risk in nuclear power; entertainment on television; education policy; media usage television.

    November 1975: Political confidence; distribution of tasks in household; environmental protection as personal task or government task; media usage; newspaper and television.

    February 1976: Economic confidence; personal economic situation;$goals in life; personal values and those of all of society; political attitude; party preference; equal opportunities in vocational training; purpose of going to college; media usage radio and commercial radio.

    May 1976: Political expectations in view of the Federal Parliament election;attitude to the achievement principle; knowledge about the inflation rate; vacation trips; economic confidence.

    August 1976: Satisfaction with personal situation; most urgent personal desire; interest in politics; judgement on the Federal Government; interest in art; leisure behavior; attitude to smoking; attitude to election advertising and party preference; economic confidence.

    November 1976: Interest in fashion and clothing; most important task of the artist; political reforms versus preservation; attitude to the economy; media usage magazines; use of cultural facilities; possession of a car and car use; attitude to the concept of freedom; art and politics.

    February 1977: Personal economic situation and income development; political knowledge about the Weimar republic; interest in art and the effect of pictures (presentation test); assessment of the need for nuclear power.

    June 1977: Attitude to ARD television; media usage newspaper; effect test of two advertising texts; fight against unemployment; attitude to advertising (scale).

    September 1977: Possession of a telephone; telephone use; attitude to telephone; beverage consumption; attitude to museums; museum trip; consumption of semi-luxury foods, tobacco and alcohol; beer; personal self-assessment.

    December 1977: General confidence; most urgent personal desire; possession of a car; environmentally compatible car; attitude to use of drugs and non-alcoholic beer.

    February 1978: Political and economic confidence; personal economic situation; attitude to vacation trips; consumer conduct with different beverages; role of women; reading habits (presentation text);

    June 1978: Comparison of two stereo systems according to sample pictures; purchase and use of stereo systems; comparison of four vacation areas Elsace, Allgaeu, Switzerland and Black Forest; world soccer championship.

    November 1978: personal confidence for 1978; most urgent personal desire; media usage newspaper, magazine, TV and radio; persuasion test of three advertisements; possession of a car; car use; traffic restriction; children in traffic; foreign aid; future image; equal role distribution in household; democracy assessment.

    February 1979: Interest in politics; distribution of tasks in household; attitude to the economy and the term freedom; political reforms versus preservation; partnership in marriage; possession of a telephone; telephone use; attitude to the telephone; personal economic situation; interest in museums and art exhibitions.

    September 1979: Human intervention makes the Earth uninhabitable; environmental protection as personal task or government task; art interest; art and politics; most important task of the artist; attitude to the achievement principle; historical knowledge and political attitude to Prussia; equal opportunities in vocational training; media usage magazines; use of cultural facilities; personal clothing style; use of semi-luxury foods, tobacco and alcohol and beverage consumption; possession of technical goods.

    December 1979: General confidence; most urgent personal desire; personal economic situation; media usage radio and radio commercials; attitude to advertising (scale); purpose of college; fighting unemployment; smoking; party preference; possession of a car and car use; leisure be...

  12. Data from: The Effect of Higher Education on Entrepreneurial Activities and...

    • figshare.com
    • search.datacite.org
    tiff
    Updated May 30, 2023
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    Jan Hunady; Marta Orviska; Peter Pisar (2023). The Effect of Higher Education on Entrepreneurial Activities and Starting Up Successful Businesses [Dataset]. http://doi.org/10.6084/m9.figshare.7885787.v4
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    tiffAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Jan Hunady; Marta Orviska; Peter Pisar
    License

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

    Description

    The paper deals with the potential relationship between higher education and entrepreneurial activities. Universities and other higher education institutions could be seen as boosting entrepreneurship in the region. University graduates could be more often involved in starting up a new business and the university itself could commercialize their innovations by creating academic spin-off companies. The paper aims to examine the potential effect of higher education on the probability of starting a business as well as its further success. Based on the data for 40 EU and non-EU countries, retrieved from a Eurobarometer survey, we conducted probit and IV probit regressions. These have tested the assumed relationship between higher education and entrepreneurial activities. Our results strongly suggest that higher education can often be very beneficial for starting up a new business and this seems to be one of the factors determining the success of new businesses. Furthermore, those respondents who attended courses related to entrepreneurship appear to be more active in starting-up a business and this seems to be also positively correlated with the company's future success. Interestingly, university graduates from Brazil, Portugal and India in particular, tend to appreciate the role that their universities have played in acquiring the skills to enable them to run a business.

  13. D

    Staat van het land : GPD enquête 1998

    • ssh.datastations.nl
    bin, c, pdf, tsv, xml +1
    Updated Jun 22, 2025
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    B.M.S. van Praag, SEO, UVA, J.P. Hop, SEO, Universiteit van Amsterdam (primary investigator); B.M.S. van Praag, SEO, UVA, J.P. Hop, SEO, Universiteit van Amsterdam (primary investigator) (2025). Staat van het land : GPD enquête 1998 [Dataset]. http://doi.org/10.17026/DANS-Z77-ZY5K
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    zip(19493), c(346006), xml(1879), bin(67154), bin(1303992), tsv(39977146), pdf(1298165)Available download formats
    Dataset updated
    Jun 22, 2025
    Dataset provided by
    DANS Data Station Social Sciences and Humanities
    Authors
    B.M.S. van Praag, SEO, UVA, J.P. Hop, SEO, Universiteit van Amsterdam (primary investigator); B.M.S. van Praag, SEO, UVA, J.P. Hop, SEO, Universiteit van Amsterdam (primary investigator)
    License

    https://doi.org/10.17026/fp39-0x58https://doi.org/10.17026/fp39-0x58

    Description

    This round of GPD surveys (GPD = Geassocieerde Pers Diensten = Associated Press Services ), a voluntary reply regional newspaper survey, was held in january1998 and covers various topics like lifesituation, work and unemployment, housing, environment, time-spending, income and spending, health and political and social opinions. Themes: Child care / work: status of occupation, employment, unemployment, starting year first job, duration of current employment, working hours, nr. of vacation days, commuting, job security; unemployed: duration expection, last income, job seeking / housing: age of house, type of dwelling, ownership, costs: rent, mortgage etc., value of house, rent, subsidy, garden, balcony, isolation, urbanization, annoyances, satisfaction with house, neighbourhood, town, available services, social contacts / Time budget / Financial situation: expenses, income, sources of income, income stability, career perspective, flexible working, retirement, satisfaction with income level / Politics: voting behaviour, vote intention, labour union membership, important issues in life / Religion: religious affiliation, denomination, church attendance, religious attitudes / satisfaction with political and social institutions and policies, judgement on, sympathy for prominent politicians, immigration, ethnic minorities, multicultural society, opinion on Europeans, contacts with allochtoneous, EU, monetary union, the Euro / Work, behaviour and health: opinion on working conditions, satisfaction with living conditions, health complaints, weight, heigth, worries, personal problems, mood, loneliness, smoking, drinking, use of drugs, quality of life, lottery, gambling. Background variables include: sex, age, type of family, marital status, number of children, country of birth.

  14. f

    Data from: How to reach an elusive INDC target: macro-economic implications...

    • tandf.figshare.com
    docx
    Updated May 31, 2023
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    Baris Karapinar; Hasan Dudu; Ozge Geyik; Aykut Mert Yakut (2023). How to reach an elusive INDC target: macro-economic implications of carbon taxation and emissions trading in Turkey [Dataset]. http://doi.org/10.6084/m9.figshare.8858213.v1
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    docxAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    Taylor & Francis
    Authors
    Baris Karapinar; Hasan Dudu; Ozge Geyik; Aykut Mert Yakut
    License

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

    Description

    This paper employs a computable general equilibrium model (CGE) to analyse how a carbon tax and/or a national Emissions Trading System (ETS) would affect macroeconomic parameters in Turkey. The modelling work is based on three main policy options for the government by 2030, in the context of Turkey’s mitigation target under its Intended Nationally Determined Contribution (INDC), that is, reducing greenhouse gas (GHG) emissions by up to 21% from its Business as Usual (BAU) scenario in 2030: (i) improving the productivity of renewable energy by 1% per annum, a target already included in the INDC, (ii) introducing a new flat rate tax of 15% per ton of CO2 (of a reference carbon price in world markets) imposed on emissions originating from carbon-intensive sectors, and (iii) introducing a new ETS with caps on emission permits. Our base path scenario projects that GHG emissions in 2030 will be much lower than Turkey’s BAU trajectory of growth from 430 Mt CO2-eq in 2013 to 1.175 Mt CO2-eq by 2030, implying that the government’s commitment is largely redundant. On the other hand, if the official target is assumed to be only a simple reduction percentage in 2030 (by 21%), but based on our more realistic base path, the government’s current renewable energy plans will not be sufficient to reach it. Turkey’s official INDC is based on over-optimistic assumptions of GDP growth and a highly carbon-intensive development pathway;A carbon tax and/or an ETS would be required to reach the 21% reduction target over a realistic base path scenario for 2030;The policy options considered in this paper have some effects on major sectors’ shares in total value-added. Yet the reduction in the shares of agriculture, industry, and transportation does not go beyond 1%, while the service sector seems to benefit from most of the policy options;Overall employment would be affected positively by the renewable energy target, carbon tax, and ETS through the creation of new jobs;Unemployment rates are lower, economic growth is stronger, and households become better off to a larger extent under an ETS than carbon taxation. Turkey’s official INDC is based on over-optimistic assumptions of GDP growth and a highly carbon-intensive development pathway; A carbon tax and/or an ETS would be required to reach the 21% reduction target over a realistic base path scenario for 2030; The policy options considered in this paper have some effects on major sectors’ shares in total value-added. Yet the reduction in the shares of agriculture, industry, and transportation does not go beyond 1%, while the service sector seems to benefit from most of the policy options; Overall employment would be affected positively by the renewable energy target, carbon tax, and ETS through the creation of new jobs; Unemployment rates are lower, economic growth is stronger, and households become better off to a larger extent under an ETS than carbon taxation.

  15. g

    Applicant Countries Eurobarometer 00 (pilot study)

    • search.gesis.org
    • da-ra.de
    Updated Mar 8, 2016
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    European Commission, Brussels DG Education and Culture (EAC-D2, Public Opinion Analysis) (2016). Applicant Countries Eurobarometer 00 (pilot study) [Dataset]. http://doi.org/10.4232/1.12074
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    application/x-spss-sav(4876237), application/x-spss-por(7283240), (1300), application/x-stata-dta(4005636)Available download formats
    Dataset updated
    Mar 8, 2016
    Dataset provided by
    GESIS Data Archive
    GESIS search
    Authors
    European Commission, Brussels DG Education and Culture (EAC-D2, Public Opinion Analysis)
    License

    https://www.gesis.org/en/institute/data-usage-termshttps://www.gesis.org/en/institute/data-usage-terms

    Time period covered
    Jan 17, 2000 - Feb 7, 2000
    Variables measured
    d12 - Income, age - TREND: Age, d13 - TREND: Sex, q10 - TREND: EU image, zanr - ZA Study Number, d1 - TREND: Nationality, edition - ZA Edition ID, d6_a - TREND: Own: House, q7_a - TREND: News on TV, d3 - TREND: Age education, and 238 more
    Description

    Attitude towards the EU and EU enlargement.

    Topics: life satisfaction; subjective rating of the development of the general life situation, the economic situation, the financial situation of the household, personal job situation, national labor market situation and the personal professional outlook in the coming year; native language; knowledge of foreign languages; frequency of political discussions with friends; self-rated opinion leadership; frequency of news consumption (television, newspaper and radio); interest in following news topics: local and national politics, social issues, EU, economics, sports, the environment, foreign politics, culture; spontaneous associations with the EU; general attitude towards the EU; knowledge of international institutions and trust into these institutions: UN, UNESCO, NATO, EU, European Parliament, European Commission, OSCE, Council of Europe, European Court of Human Rights, International Court of Justice; Self-rated knowledge about the EU (scale); awareness of application for EU membership by own country; accession to EU of own country as a good thing; approval of EU membership of own country if a referendum was held; advantageousness of EU accession for the own country, the own person and following groups: people with and without foreign language skills, entrepreneurs, politicians, professionals such as doctors or lawyers, young people, children, employees, industrial workers, medium-sized businesses, teachers, civil servants, middle-aged people, farmers, the rural population, the unemployed, pensioners, elderly, population of the capital, cultural, religious and other minorities; some regions benefit more than others, all population groups; agreement with the following statements: accession of the own country would be beneficial for the EU, increasing size of EU increases security and peace, would promote the national economy, increase the influence of the own country in Europe, satisfaction of the national government accession policy, increasing influence of the EU in the world if number of members increases, historical and geographical legitimacy of EU membership of the country, increased cultural wealth and standard of living, rising unemployment due to EU enlargement; expected and desired EU accession year of the own country; consent to possible EU accession of Bulgaria, Cyprus, the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Malta, Poland, Romania, Slovakia, Slovenia and Turkey; EU or own country as preferred decision-making authority for the following policies: defense, environmental protection, currency, Humanitarian Aid, health and welfare, broadcasting and press, poverty reduction, combating unemployment, agriculture and fisheries, regional compensation, education, science and technology, information on EU , non-European foreign policy, culture, immigration, asylum, fighting against organized crime, police, justice, refugee resettlement, combat of youth delinquency, urban crime and human trafficking, the fight against drugs; preferred source of information about the EU; desire for additional information on the following topics: history of the EU, the EU institutions, European Economic and Monetary Union, Euro, European economy, European single market, further financial / economic issues, agriculture in the EU, European Foreign and Security Policy, international relations of the EU; regional policy of the EU, the European budget, European research and development policy, education policy, cultural policy, youth policy, EU citizenship, consumer protection and environmental protection in the EU, European social policy.

    Demography: nationality; family situation; age at end of education; gender; age; occupation; professional position; degree of urbanization; household size; possession of durable goods, role of respondent in the household: main breadwinner, responsible for purchases and household maintenance, religious affiliation, frequency of church attendance, household income

  16. d

    Businesses and Responsibility

    • da-ra.de
    Updated 1995
    + more versions
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    EMNID, Bielefeld (1995). Businesses and Responsibility [Dataset]. http://doi.org/10.4232/1.2650
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    Dataset updated
    1995
    Dataset provided by
    GESIS Data Archive
    da|ra
    Authors
    EMNID, Bielefeld
    Time period covered
    Jul 1993 - Aug 1993
    Description

    Sampling Procedure Comment: Multi-stage stratified random sample (ADM-Master-Sample)

  17. e

    Sudan Labor Market Panel Survey, SLMPS 2022 - Sudan

    • erfdataportal.com
    Updated Aug 24, 2023
    + more versions
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    Economic Research Forum (2023). Sudan Labor Market Panel Survey, SLMPS 2022 - Sudan [Dataset]. https://www.erfdataportal.com/index.php/catalog/265
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    Dataset updated
    Aug 24, 2023
    Dataset authored and provided by
    Economic Research Forum
    Time period covered
    2022
    Area covered
    Sudan
    Description

    Abstract

    The Sudan Labor Market Panel Survey 2022 (SLMPS 2022) is the first wave of a planned longitudinal study of the Sudanese labor market designed to elucidate the way in which human resources are developed and deployed in the Sudanese economy. The SLMPS 2022 is a nationally-representative household survey on a panel of about 5,000 households planned to be repeated every six years. The focus of the survey is to understand key relationships between labor market processes and outcomes and other socio-economic processes such as education, training, family formation and fertility, internal and international migration, gender equality and women's empowerment, enterprise development, housing acquisition, and equality of opportunity and intergenerational mobility.

    The SLMPS 2022 is modeled on similar surveys carried out in Egypt in 1998, 2006, 2012, and 2018 in Jordan in 2010 and 2016, and in Tunisia in 2014. All of these surveys started out with a sample of 5,000 households in the first wave and then the sample grew as a results of household splits and the addition of a refresher sample in every new wave. The SLMPS 2022 also includes modules from the Living Standards Measurement Study Plus (LSMS+) surveys that focus on gender disaggregated asset, employment, and entrepreneurship data. Given the level of detail desired in the individual level information, it is crucial in this survey that the information be collected from the individual him or herself rather than from any informant in the household. Therefore, the survey design calls for a number of visits to the same household to make sure that each individual aged five and older can be interviewed in person.

    ===============================================================================================

    For details on the key characteristics of the SLMPS 2022, see: Krafft C., Assaad R., and Cheung R.(2023). Introducing the Sudan Labor Market Panel Survey 2022. Economic Research Forum Working Paper No. 1647

    https://erf.org.eg/publications/introducing-the-sudan-labor-market-panel-survey-2022/

    Geographic coverage

    The sample was designed to provide estimates of the indicators at the national level, for urban and rural areas, and for all regions.

    For detailed information on the regions and governorates used in the SLMPS 2022 Sample, see: Krafft C., Assaad R., and Cheung R.(2023). Introducing the Sudan Labor Market Panel Survey 2022. Economic Research Forum Working Paper No. 1647

    https://erf.org.eg/publications/introducing-the-sudan-labor-market-panel-survey-2022/

    Analysis unit

    1- Households. 2- Individuals. 3- Household Enterprises.

    Universe

    The survey covered a national sample of households and all household's members aged five and above. In addition, the survey covered enterprises operated by the household.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    A fundamental challenge when designing the SLMPS sample was the lack of a recent, nationally representative sample frame. The last national population census in Sudan was in 2008, before the secession of South Sudan. There had also been limited updating of administrative borders and maps. The first level of administrative geography in Sudan is the state (wilaya), and there are 18 states in Sudan. The second level of administrative geography in Sudan is the locality (mahaliya), and CBS had updated the borders of localities in 2017 to 189 distinct geographies (each locality nested within a single state).). The principal investigators (C. Krafft and R. Assaad) used the updated borders combined with 2020 population estimates based on remote sensing data to create our sampling frame and draw our sample. These sources were supplemented with additional data to identify refugee and IDP camps and areas for our strata. The planned sample design was a random stratified cluster sample made up of 5,000 households sub-divided into 250 primary sampling units (PSUs). The strata represented in the sample are: (i) refugee camps, (ii) refugee areas (areas with non-camp refugee settlements), (iii) IDP camps, (iv) IDP areas (areas with non-camp IDP settlements), (v) other (non-refugee/non-IDP) rural areas,

    (vi) other urban areas.

    For details on the sampling of the SLMPS 2022, see: Krafft C., Assaad R., and Cheung R.(2023). Introducing the Sudan Labor Market Panel Survey 2022. Economic Research Forum Working Paper No. 1647

    https://erf.org.eg/publications/introducing-the-sudan-labor-market-panel-survey-2022/

    Sampling deviation

    The realities of the sample frame and the logistics of fielding led to a number of deviations from the planned sample in fielding. While the initial sample was estimated to have a reasonable number of households in each PSU based on satellite imaging and population projections, there were cases where a PSU did not, in fact, have any or many households. All PSU locations were reviewed first in the CBS offices to identify locations that were empty or where there appeared to be five or fewer households and these locations were replaced with backup PSUs. There were a variety of reasons why a PSU might have few or no households, including that it consisted of industrial/commercial (not residential) buildings, that it was a mine or grain storage area, or that it had rocks or grain silos that looked like residences. When office review determined there were at least five or more potential households on the satellite maps, fielding was attempted. However, a number of issues arose in the field as well. Upon visiting, buildings were determined to be non-residential, or were abandoned. Furthermore, a number of locations were determined to be unsafe to field, a status that even changed and fluctuated frequently during the fieldwork. Persistent sandstorms also prevented fielding in specific localities. The rainy season likewise made some locations inaccessible for fielding. Backup samples were created; initially one urban and one rural backup were provided per state, and further backups were drawn as needed to replace PSUs that could not be fielded. Backups were, if possible, from the same strata and always from the same state. When possible, additional backups were also drawn from the same locality in an attempt to minimize bias. However, there were cases when an entire locality became inaccessible. Ultimately, 152 PSUs from the original sample of 250 were fielded in the initially planned locations. Nine of the initially planned backups were used. For the remainder, 24 were replaced by the first replacement given, 17 by the second, 17 by the third, 9 by the fourth, 6 by the fifth, 4 by the seventh, and the remaining 12 by various higher order replacements. Repeated replacements tended to occur in localities with a high share of buildings (e.g. mines, grain storage) that the population estimates likely mistook for residences.

    ===============================================================================================

    For details on the sampling of the SLMPS 2022, see: Krafft C., Assaad R., and Cheung R.(2023). Introducing the Sudan Labor Market Panel Survey 2022. Economic Research Forum Working Paper No. 1647

    https://erf.org.eg/publications/introducing-the-sudan-labor-market-panel-survey-2022/

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The SLMPS questionnaires consist of a household questionnaire and an individual questionnaire, with modules. The modules built on and ensured substantial comparability with other LMPSs. The household questionnaire includes: (i) identifiers and household location (ii) roster of household members (iii) housing conditions and durable assets (iv) current household member migrants abroad (v) remittances (vi) other income and transfers (vii) shocks and coping mechanisms (viii) non-agricultural enterprises, including information on characteristics, employment of household members and others, assets, expenditures, and revenue (ix) agricultural assets, land and parcels, capital equipment, livestock, crops, and other agricultural income. The individual questionnaire collects data from all individuals 5 and older (children under five are captured in the household roster). The individual questionnaire elicits information about (i) residential mobility (ii) father's, mother's and sibling characteristics (including siblings abroad) (iv) health (v) education level and detailed educational history (vi) training experiences (vii) skills (viii) current employment and unemployment (viii) job characteristics for the primary and secondary job (ix) labor market history (x) costs and characteristics of marriage (ix) fertility (xii) women's employment (xiii) wages from primary and any secondary jobs (xiv) return migration, refugee, and IDP experiences for Sudanese respondents (xv) modules for immigration and refugees for non-Sudanese respondents (xvi) information technology (xvi) savings and borrowing (xvii) attitudes (xviii) time use (a full 24 hour diary for adults and a shorter module for children) and (xix) a series of questions on rights to parcels, livestock, and durables.

    For more details, see the questionnaires in the documentation.

    Response

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Guillem SD (2024). U.S. Unemployment Rates [Dataset]. https://www.kaggle.com/datasets/guillemservera/us-unemployment-rates
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U.S. Unemployment Rates

Monthly unemployment data from the FRED, spanning from 1948 to present.

Explore at:
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Jun 10, 2024
Dataset provided by
Kagglehttp://kaggle.com/
Authors
Guillem SD
License

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

Area covered
United States
Description

Introduction

The U.S. job market, with its dynamic trends and fluctuating unemployment rates, serves as an important barometer for the nation's economic health. All rates provided in this dataset are seasonally adjusted. Delving into the intricacies of unemployment rates by age and gender helps researchers, policymakers, and analysts uncover underlying patterns and address potential disparities.

Usage Examples

  • Economic Research: Study the historical unemployment trends to gauge economic cycles.
  • Policy Making: Inform labor market policies and interventions based on age or gender disparities.
  • Business Strategy: Companies can analyze job market conditions when considering expansions or contractions.
  • Academic Projects: Students and educators can use the dataset for case studies, dissertations, or classroom projects.

Image Source Photo by Ron Lach : https://www.pexels.com/photo/woman-looking-for-jobs-in-newspaper-9832700/

Dataset Contents

This dataset, sourced from the FRED API, provides: - df_sex_unemployment_rates.csv: A breakdown of U.S. unemployment rates based on gender. - df_unemployment_rates.csv: Unemployment rates categorized by various age groups, ranging from young entrants (ages 16-17) to seasoned professionals (55 and above).

Together, these data files offer a comprehensive insight into the nuances of unemployment in the U.S., highlighting potential disparities in the job market across different age groups and between men and women.

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