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Displaying results 1 to 4 of 4.

  1. The 2021 PREDICT dataset methodology
    Author: Benages, Eva; Hernández, Leonardo; Mínguez, C.; Pascual, F.; Robledo, J. C.; Rosell, I.; Salamanca, J.; Solaz, M.; Righi, R.; Samoili, S.; Vazquez-Prada Baillet, M.
    Published: 2022
    Publisher:  Publications Office of the European Union, Luxembourg

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    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
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    Source: Union catalogues
    Contributor: De Prato, Giuditta (HerausgeberIn); Cardona, Mélisande (HerausgeberIn); López-Cobo, M. (HerausgeberIn); Mas, Matilde (HerausgeberIn); Fernández de Guevara, Juan (HerausgeberIn)
    Language: English
    Media type: Ebook
    Format: Online
    ISBN: 9789276460589
    Other identifier:
    Series: JRC technical report
    EUR ; 30945
    JRC ; 126918
    Subjects: R&D; ICT; innovation; statistics; digital economy; ICT industry analysis; ICT R&D and innovation
    Scope: 1 Online-Ressource (circa 242 Seiten), Illustrationen
  2. Identifying and correcting bias in big crowd-sourced online genealogies
    Author: Chong, Michael; Alburez-Gutierrez, Diego; Del Fava, Emanuele; Alexander, Monica; Zagheni, Emilio
    Published: [2022]
    Publisher:  Max Planck Institute for Demographic Research, Rostock, Germany

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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    Series: MPIDR working paper ; WP 2022, 005 (January 2022)
    Subjects: Denmark; Finland; France; Norway; Sweden; USA; bias; genealogy; mortality; statistics
    Scope: 1 Online-Ressource (circa 35 Seiten), Illustrationen
  3. Methodological issues related to the use of online labour market data
    Author: Fabo, Brian; Kureková, Lucia Mýtna
    Published: [2022]
    Publisher:  International Labour Organization, Geneva, Switzerland

    This report provides a mapping of existing research that employs online labour market data, covering both online job vacancies (demand side) and online applicant data (CVs) (supply side). We discuss and assess a variety of tools and empirical methods... more

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    This report provides a mapping of existing research that employs online labour market data, covering both online job vacancies (demand side) and online applicant data (CVs) (supply side). We discuss and assess a variety of tools and empirical methods that have been used to address specific disadvantages of this data, such as non-representativeness or fluctuations in data quantity and structure; these may be due to external shocks, such as the COVID-19 pandemic. We find that while this research field has expanded rapidly, including with respect to geographical coverage, many empirical studies do not engage with the methodological aspects and weaknesses of online labour market data and take them at face value. We highlight that there are legitimate research approaches, which are inductive in nature, focused on discovering patterns and trends in underlying data. These are by definition less concerned with generalizability of findings, as they have different objectives. For this body of research, online labour market data open new avenues for understanding developments in labour markets. We also argue that biases in online labour market data emerge due to multiple factors. With respect to the order of discrepancies between online labour market data and representative data sources, these are typically not paramount. Different techniques have been adopted to deal with the non-representativeness problem, such as statistical techniques; adapting the research questions and research focus to the quality of data; and use of mixed methods, including qualitative methods, to increase the robustness of results.

     
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    Source: Union catalogues
    Language: English
    Media type: Ebook
    Format: Online
    ISBN: 9789220372821; 9789220372838; 9789220372845; 9789220372852
    Other identifier:
    hdl: 10419/263129
    Series: ILO working paper / International Labour Organization ; 68 (June 2022)
    Subjects: employment; skilled workers; unskilled workers; occupational qualification; skills; lifelong learning; information and communication technologies; Internet; statistics; labour statistics; labour force survey; data analysis; data collecting; survey; databases
    Scope: 1 Online-Ressource (circa 43 Seiten), Illustrationen
  4. Engendering informality statistics: gaps and opportunities
    working paper to support revision of the standards for statistics on informality
    Author: Gardner, Jessica; Walsh, Kieran; Frosch, Michael
    Published: [2022]
    Publisher:  International Labour Organization, Geneva, Switzerland

    Informality is a dynamic and multidimensional concern that demands gender-sensitive data. In 2018, globally, more than 60% of employment was informal. However, global averages hide that in more countries the share of women in informal employment... more

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    Resolving-System (kostenfrei)

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    Max-Planck-Institut für ausländisches öffentliches Recht und Völkerrecht, Bibliothek
    Inter-library loan:
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    Location:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signature:
    DS 709
    Inter-library loan:
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    Informality is a dynamic and multidimensional concern that demands gender-sensitive data. In 2018, globally, more than 60% of employment was informal. However, global averages hide that in more countries the share of women in informal employment exceeds that of men. Also, women in the informal economy are often in the most unprotected situations - as domestic workers, home-based workers and contributing family workers - where a lack of visibility can increase their vulnerability. The ILO and its partners are working to engender informality statistics to improve gender data and support countries to respond to data needs on women's economic empowerment. This working paper was written to support the ILO Working Group for the Revision of the standards for statistics on informality. It explores the demand for gender data on informality and the measurement challenges faced. The paper highlights the opportunities emerging from the revision of statistical standards on informality that are set to be adopted in 2023.

     
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    Source: Union catalogues
    Language: English
    Media type: Ebook
    Format: Online
    ISBN: 9789220381304; 9789220381311; 9789220381328; 9789220381335
    Other identifier:
    hdl: 10419/278232
    Series: ILO working paper / International Labour Organization ; 84 (November 2022)
    Subjects: informal employment; informal economy; gender; statistics; labour statistics
    Scope: 1 Online-Ressource (circa 37 Seiten), Illustrationen