28 datasets found
  1. Code for: Pay Transparency and the Gender Wage Gap: Evidence from Austria

    • openicpsr.org
    Updated Sep 15, 2021
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    Andreas Gulyas; Sebastian Seitz; Sourav Sinha (2021). Code for: Pay Transparency and the Gender Wage Gap: Evidence from Austria [Dataset]. http://doi.org/10.3886/E167024V1
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    Dataset updated
    Sep 15, 2021
    Dataset provided by
    American Economic Associationhttp://www.aeaweb.org/
    Authors
    Andreas Gulyas; Sebastian Seitz; Sourav Sinha
    License

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

    Time period covered
    2007 - 2018
    Area covered
    Austria
    Description

    This is the replication material for Pay Transparency and the Gender Wage Gap: Evidence from Austria, American Economic Journal: Economic PolicyWe study the 2011 Austrian Pay Transparency Law, which requires firms above a size threshold to publish internal reports on the gender pay gap. Using an event-study design, we show that the policy had no discernible effects on male and female wages, thus leaving the gender wage gap unchanged. The effects are precisely estimated and we rule out that the policy narrowed the gender wage gap by more than 0.4 p.p.. Moreover, we do not find evidence for wage compression within establishments. We discuss several possible reasons why the reform did not reduce the gender wage gap.

  2. Replication data for: The Gender Wage Gap: Extent, Trends, and Explanations

    • openicpsr.org
    Updated Sep 1, 2017
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    Francine D. Blau; Lawrence M. Kahn (2017). Replication data for: The Gender Wage Gap: Extent, Trends, and Explanations [Dataset]. http://doi.org/10.3886/E113913V2
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    Dataset updated
    Sep 1, 2017
    Dataset provided by
    American Economic Associationhttp://www.aeaweb.org/
    Authors
    Francine D. Blau; Lawrence M. Kahn
    License

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

    Description

    Using Panel Study of Income Dynamics (PSID) microdata over the 1980-2010 period, we provide new empirical evidence on the extent of and trends in the gender wage gap, which declined considerably during this time. By 2010, conventional human capital variables taken together explained little of the gender wage gap, while gender differences in occupation and industry continued to be important. Moreover, the gender pay gap declined much more slowly at the top of the wage distribution than at the middle or bottom and by 2010 was noticeably higher at the top. We then survey the literature to identify what has been learned about the explanations for the gap. We conclude that many of the traditional explanations continue to have salience. Although human-capital factors are now relatively unimportant in the aggregate, women's work force interruptions and shorter hours remain significant in high-skilled occupations, possibly due to compensating differentials. Gender differences in occupations and industries, as well as differences in gender roles and the gender division of labor remain important, and research based on experimental evidence strongly suggests that discrimination cannot be discounted. Psychological attributes or noncognitive skills comprise one of the newer explanations for gender differences in outcomes. Our effort to assess the quantitative evidence on the importance of these factors suggests that they account for a small to moderate portion of the gender pay gap, considerably smaller than, say, occupation and industry effects, though they appear to modestly contribute to these differences.

  3. f

    Kitagawa-Oaxaca-Blinder decomposition of gender pay gap for non-farm...

    • figshare.com
    bin
    Updated Jun 21, 2023
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    Goedele Van den Broeck; Talip Kilic; Janneke Pieters (2023). Kitagawa-Oaxaca-Blinder decomposition of gender pay gap for non-farm employed people aged 25–55 in Malawi, Tanzania and Nigeria. [Dataset]. http://doi.org/10.1371/journal.pone.0278188.t004
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    binAvailable download formats
    Dataset updated
    Jun 21, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Goedele Van den Broeck; Talip Kilic; Janneke Pieters
    License

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

    Area covered
    Malawi, Nigeria, Tanzania
    Description

    Kitagawa-Oaxaca-Blinder decomposition of gender pay gap for non-farm employed people aged 25–55 in Malawi, Tanzania and Nigeria.

  4. f

    Descriptive statistics.

    • figshare.com
    txt
    Updated Jun 21, 2023
    + more versions
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    Goedele Van den Broeck; Talip Kilic; Janneke Pieters (2023). Descriptive statistics. [Dataset]. http://doi.org/10.1371/journal.pone.0278188.s011
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    txtAvailable download formats
    Dataset updated
    Jun 21, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Goedele Van den Broeck; Talip Kilic; Janneke Pieters
    License

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

    Description

    The focus of this study is the implications of structural transformation for gender equality, specifically equal pay, in Sub-Saharan Africa. While structural transformation affects key development outcomes, including growth, poverty, and access to decent work, its effect on the gender pay gap is not clear ex-ante. Evidence on the gender pay gap in sub-Saharan Africa is limited, and often excludes rural areas and informal (self-)employment. This paper provides evidence on the extent and drivers of the gender pay gap in non-farm wage- and self-employment activities across three countries at different stages of structural transformation (Malawi, Tanzania and Nigeria). The analysis leverages nationally-representative survey data and decomposition methods, and is conducted separately among individuals residing in rural versus urban areas in each country. The results show that women earn 40 to 46 percent less than men in urban areas, which is substantially less than in high-income countries. The gender pay gap in rural areas ranges from (a statistically insignificant) 12 percent in Tanzania to 77 percent in Nigeria. In all rural areas, a major share of the gender pay gap (81 percent in Malawi, 83 percent in Tanzania and 70 percent in Nigeria) is explained by differences in workers’ characteristics, including education, occupation and sector. This suggests that if rural men and women had similar characteristics, most of the gender pay gap would disappear. Country-differences are larger across urban areas, where differences in characteristics account for only 32 percent of the pay gap in Tanzania, 50 percent in Malawi and 81 percent in Nigeria. Our detailed decomposition results suggest that structural transformation does not consistently help bridge the gender pay gap. Gender-sensitive policies are required to ensure equal pay for men and women.

  5. o

    Code for: Pay Transparency and the Gender Gap

    • openicpsr.org
    Updated Feb 22, 2022
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    Michael Baker; Yosh Halberstam; Kory Kroft; Alexandre Mas; Derek Messacar (2022). Code for: Pay Transparency and the Gender Gap [Dataset]. http://doi.org/10.3886/E163241V1
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    Dataset updated
    Feb 22, 2022
    Dataset provided by
    American Economic Association
    Authors
    Michael Baker; Yosh Halberstam; Kory Kroft; Alexandre Mas; Derek Messacar
    License

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

    Time period covered
    1970 - 2018
    Area covered
    Canada
    Description

    We examine the impact of public sector salary disclosure laws on university faculty salaries in Canada. The laws, which enable public access to the salaries of individual faculty if they exceed specified thresholds, were introduced in different provinces at different times. Using detailed administrative data covering the majority of faculty in Canada, and an event-study research design that exploits within-province variation in exposure to the policy across institutions and academic departments, we find robust evidence that the laws reduced the gender pay gap between men and women by approximately 20-40 percent.

  6. g

    Data from: Do- and Log-Files of article "Gender Wage Gap Opens Long before...

    • search.gesis.org
    • da-ra.de
    Updated Nov 25, 2020
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    Combet, Benita (2020). Do- and Log-Files of article "Gender Wage Gap Opens Long before Motherhood" [Dataset]. https://search.gesis.org/research_data/SDN-10.7802-1852
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    Dataset updated
    Nov 25, 2020
    Dataset provided by
    GESIS, Köln
    GESIS search
    Authors
    Combet, Benita
    License

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

    Description

    Stata Do-Files and Log-Files of Article "The Gender Wage Gap Opens Long before Motherhood. Panel Evidence on Early Careers in Switzerland", published in European Sociological Review, 2019.

    Data preparation and statistical analyses

  7. o

    Supplementary for: Francine D. Blau and Lawrence M. Kahn, “The Gender Wage...

    • openicpsr.org
    Updated Nov 7, 2024
    + more versions
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    Lawrence Kahn; Francine Blau (2024). Supplementary for: Francine D. Blau and Lawrence M. Kahn, “The Gender Wage Gap: Extent, Trends, and Explanations”, Journal of Economic Literature , 55 ,3 (Sept 2017): 789-865 [Dataset]. http://doi.org/10.3886/E210483V1
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    Dataset updated
    Nov 7, 2024
    Dataset provided by
    Cornell University
    Authors
    Lawrence Kahn; Francine Blau
    Area covered
    USA
    Description

    Using PSID microdata over the 1980-2010, we provide new empirical evidence on the extent of and trends in the gender wage gap, which declined considerably over this period. By 2010, conventional human capital variables taken together explained little of the gender wage gap, while gender differences in occupation and industry continued to be important. Moreover, the gender pay gap declined much more slowly at the top of the wage distribution that at the middle or the bottom and by 2010 was noticeably higher at the top. We then survey the literature to identify what has been learned about the explanations for the gap. We conclude that many of the traditional explanations continue to have salience. Although human capital factors are now relatively unimportant in the aggregate, women’s work force interruptions and shorter hours remain significant in high skilled occupations, possibly due to compensating differentials. Gender differences in occupations and industries, as well as differences in gender roles and the gender division of labor remain important, and research based on experimental evidence strongly suggests that discrimination cannot be discounted. Psychological attributes or noncognitive skills comprise one of the newer explanations for gender differences in outcomes. Our effort to assess the quantitative evidence on the importance of these factors suggests that they account for a small to moderate portion of the gender pay gap, considerably smaller than say occupation and industry effects, though they appear to modestly contribute to these differences.

  8. Data and Code for Pay Transparency and Gender Equality

    • openicpsr.org
    delimited
    Updated Oct 8, 2023
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    Jack Blundell; Emma Duchini; Stefania Simion; Arthur Turrell (2023). Data and Code for Pay Transparency and Gender Equality [Dataset]. http://doi.org/10.3886/E194342V1
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    delimitedAvailable download formats
    Dataset updated
    Oct 8, 2023
    Dataset provided by
    American Economic Associationhttp://www.aeaweb.org/
    Authors
    Jack Blundell; Emma Duchini; Stefania Simion; Arthur Turrell
    License

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

    Time period covered
    2013 - 2021
    Area covered
    United Kingdom
    Description

    Since 2018, UK firms with at least 250 employees have been mandated to publicly disclose gender equality indicators. Exploiting variations in this mandate across firm size and time, we show that pay transparency closes 19 percent of the gender pay gap by reducing men’s wage growth. By combining different sources of data, we also provide suggestive evidence that the public availability of the equality indicators influences employers’ response as worse performing firms and employers potentially more exposed to public scrutiny seem to reduce their gender pay gap the most.

  9. o

    Replication data for: Children and Gender Inequality: Evidence from Denmark

    • openicpsr.org
    • doi.org
    Updated Dec 7, 2019
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    Henrik Kleven; Camille Landais; Jakob Egholt Søgaard (2019). Replication data for: Children and Gender Inequality: Evidence from Denmark [Dataset]. http://doi.org/10.3886/E116366V1
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    Dataset updated
    Dec 7, 2019
    Dataset provided by
    American Economic Association
    Authors
    Henrik Kleven; Camille Landais; Jakob Egholt Søgaard
    Time period covered
    1980 - 2013
    Area covered
    Denmark
    Description

    Using Danish administrative data, we study the impacts of children on gender inequality in the labor market. The arrival of children creates a long-run gender gap in earnings of around 20 percent driven by hours worked, participation, and wage rates. We identify mechanisms driving these "child penalties" in terms of occupation, sector, and firm choices. We find that the fraction of gender inequality caused by child penalties has featured a dramatic increase over the last three to four decades. Finally, we show that child penalties are transmitted through generations, from parents to daughters, suggesting an influence of childhood environment on gender identity.

  10. Descriptive statistics across gender for non-farm employed people aged 25–55...

    • plos.figshare.com
    bin
    Updated Jun 21, 2023
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    Goedele Van den Broeck; Talip Kilic; Janneke Pieters (2023). Descriptive statistics across gender for non-farm employed people aged 25–55 in urban Malawi, Tanzania and Nigeria. [Dataset]. http://doi.org/10.1371/journal.pone.0278188.t003
    Explore at:
    binAvailable download formats
    Dataset updated
    Jun 21, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Goedele Van den Broeck; Talip Kilic; Janneke Pieters
    License

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

    Area covered
    Malawi, Nigeria, Tanzania
    Description

    Descriptive statistics across gender for non-farm employed people aged 25–55 in urban Malawi, Tanzania and Nigeria.

  11. o

    Data and Code for: The Long-Run Effects of Taking Up Paid Leave on Women’s...

    • openicpsr.org
    Updated Dec 15, 2023
    + more versions
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    Martha Bailey; Tanya Byker; Elena Patel; Shanthi Ramnath (2023). Data and Code for: The Long-Run Effects of Taking Up Paid Leave on Women’s Careers: Evidence from a Regression Discontinuity Design and U.S. Tax Data [Dataset]. http://doi.org/10.3886/E195866V2
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    Dataset updated
    Dec 15, 2023
    Dataset provided by
    American Economic Association
    Authors
    Martha Bailey; Tanya Byker; Elena Patel; Shanthi Ramnath
    License

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

    Description

    We use administrative tax data to analyze the cumulative, long-run effects of California’s 2004 Paid Family Leave Act (CPFL) on women’s employment, earnings, and childbearing. A regression-discontinuity design exploits the sharp increase in the weeks of paid leave available under the law. We find no evidence that CPFL increased employment, boosted earnings, or encouraged childbearing, suggesting that CPFL had little effect on the gender pay gap or child penalty. For first-time mothers, we find that CPFL reduced employment and earnings roughly a decade after they gave birth.

  12. d

    Replication Data for: 'Gender Differences in Job Search and the Earnings...

    • dataone.org
    • dataverse.harvard.edu
    Updated Jan 19, 2024
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    Cortes, Patricia; Pan, Jessica; Pilossoph, Laura; Reuben, Ernesto; Zafar, Basit (2024). Replication Data for: 'Gender Differences in Job Search and the Earnings Gap: Evidence from the Field and Lab' [Dataset]. http://doi.org/10.7910/DVN/VNKB25
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    Dataset updated
    Jan 19, 2024
    Dataset provided by
    Harvard Dataverse
    Authors
    Cortes, Patricia; Pan, Jessica; Pilossoph, Laura; Reuben, Ernesto; Zafar, Basit
    Description

    The data and programs replicate tables and figures from "Gender Differences in Job Search and the Earnings Gap: Evidence from the Field and Lab," by Cortes, Pan, Pilossoph, Reuben, and Zafar. Please see the README_jobsearch_qje file for additional details.

  13. f

    Robustness checks.

    • plos.figshare.com
    txt
    Updated Jun 21, 2023
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    Goedele Van den Broeck; Talip Kilic; Janneke Pieters (2023). Robustness checks. [Dataset]. http://doi.org/10.1371/journal.pone.0278188.s015
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    txtAvailable download formats
    Dataset updated
    Jun 21, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Goedele Van den Broeck; Talip Kilic; Janneke Pieters
    License

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

    Description

    Stata do-file for additional robustness checks. (DO)

  14. Data and Code for: How Do Beliefs about the Gender Wage Gap Affect the...

    • openicpsr.org
    Updated Mar 3, 2021
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    Sonja Settele (2021). Data and Code for: How Do Beliefs about the Gender Wage Gap Affect the Demand for Public Policy? [Dataset]. http://doi.org/10.3886/E134041V1
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    Dataset updated
    Mar 3, 2021
    Dataset provided by
    American Economic Associationhttp://www.aeaweb.org/
    Authors
    Sonja Settele
    License

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

    Area covered
    USA
    Description

    I conduct a survey experiment to study the relationship between people's beliefs about the size of the gender wage gap and their demand for policies aimed at mitigating it. Beliefs causally affect support for equal pay legislation and affirmative action programs, but cannot account for the polarization in policy views by partisanship and gender. Changes in policy demand seem to be driven by changes in beliefs about discrimination in labor markets and fairness concerns, while self-interest appears less important. I provide evidence that pessimism about the effectiveness of government intervention limits the elasticity of policy demand to perceived wage differentials.

  15. Replication data for: The Expanding Gender Earnings Gap: Evidence from the...

    • openicpsr.org
    Updated May 1, 2017
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    Claudia Goldin; Sari Pekkala Kerr; Claudia Olivetti; Erling Barth (2017). Replication data for: The Expanding Gender Earnings Gap: Evidence from the LEHD-2000 Census [Dataset]. http://doi.org/10.3886/E113512V1
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    Dataset updated
    May 1, 2017
    Dataset provided by
    American Economic Associationhttp://www.aeaweb.org/
    Authors
    Claudia Goldin; Sari Pekkala Kerr; Claudia Olivetti; Erling Barth
    Description

    The gender earnings gap is an expanding statistic over the lifecycle. We use the LEHD Census 2000 to understand the roles of industry, occupation, and establishment 14 years after leaving school. The gap for college graduates 26 to 39 years old expands by 34 log points, most occurring in the first 7 years. About 44 percent is due to disproportionate shifts by men into higher-earning positions, industries, and firms and about 56 percent to differential advances by gender within firms. Widening is greater for married individuals and for those in certain sectors. Non-college graduates experience less widening but with similar patterns.

  16. Decomposition.

    • plos.figshare.com
    txt
    Updated Jun 21, 2023
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    Goedele Van den Broeck; Talip Kilic; Janneke Pieters (2023). Decomposition. [Dataset]. http://doi.org/10.1371/journal.pone.0278188.s012
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    txtAvailable download formats
    Dataset updated
    Jun 21, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Goedele Van den Broeck; Talip Kilic; Janneke Pieters
    License

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

    Description

    Stata do-file to construct Table 4, S2 and S3 Tables. (DO)

  17. Economic Estimates: Earnings 2024 for DCMS Sectors

    • gov.uk
    Updated Jun 11, 2025
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    Department for Culture, Media and Sport (2025). Economic Estimates: Earnings 2024 for DCMS Sectors [Dataset]. https://www.gov.uk/government/statistics/economic-estimates-earnings-2024-for-dcms-sectors
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    Dataset updated
    Jun 11, 2025
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Department for Culture, Media and Sport
    Description

    About

    These economic estimates are used to provide an estimate of the contribution of DCMS sectors to the UK economy, measured by employee median earnings. These estimates are calculated based on the Office for National Statistics (ONS) Annual Survey of Hours and Earnings (ASHE).

    Content

    DCMS Sectors

    These statistics cover the contributions of the following DCMS sectors to the UK economy;

    • civil society
    • creative industries
    • cultural sector
    • gambling
    • sport

    Tourism is not included as the data is not available for the latest year (2024) of the publication but is available for the time series 2016-2023.

    Users should note that there is overlap between DCMS sector definitions. In particular, several cultural sector industries are simultaneously creative industries. The release also includes estimates for the audio visual sector and computer games sector but they do not form part of the DCMS total.

    A definition for each sector is available in the tables published alongside this release. Further information on all these sectors is available in the associated technical report along with details of methods and data limitations.

    Headline findings

    As of April 2024, median annual earnings for employees in the included DCMS sectors were £32,000; 1.3% greater than the UK overall (£31,602). Median annual earnings for included DCMS sectors have grown at a slightly slower rate than the UK overall compared to the previous year, 6.1% and 7.1% respectively (not adjusted for inflation). Compared to pre-pandemic (2019), median annual earnings have grown at a slightly slower rate in included DCMS sectors, an increase of 25.0%, than for the UK overall, which grew 26.7%.

    Employees in the creative industries (£42,399) and overlapping cultural sector (£32,432) had higher median annual earnings than the UK overall but employees in the civil society (£29,434), gambling (£25,435), and sport sectors (£21,802) had lower median annual earnings.

    As of April 2024, for every £1.00 earned by a man employed in the included DCMS sectors, a woman earns £0.80. This means that there is a gender pay gap of 18.3%, larger than the UK overall (13.1%). This has narrowed by 1.3 percentage points from last year (19.6%), and by 2.6 percentage points from 2019 (22.9%).

    Released

    First published on 3rd April 2025.

    Pre-release access

    A document is provided that contains a list of ministers and officials who have received privileged early access to this release. In line with best practice, the list has been kept to a minimum and those given access for briefing purposes had a maximum of 24 hours.

    Office for Statistics Regulation

    Our statistical practice is regulated by the Office for Statistics Regulation (OSR). OSR sets the standards of trustworthiness, quality and value in the https://code.statisticsauthority.gov.uk/the-code/" class="govuk-link">Code of Practice for Statistics that all producers of official statistics should adhere to.

    You are welcome to contact us directly with any comments about how we meet these standards by emailing evidence@dcms.gov.uk. Alternatively, you can contact OSR by emailing regulation@statistics.gov.uk or via the OSR website.

    The responsible analyst for this release is Nicholas Hamilton Wu.

    For further details about the estimates, or to be added to a distribution list for future updates, please email us at evidence@dcms.gov.uk.

  18. f

    Gender wage gaps in the formal and informal sectors in Ghana

    • figshare.com
    csv
    Updated May 23, 2025
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    Razak Ayariga (2025). Gender wage gaps in the formal and informal sectors in Ghana [Dataset]. http://doi.org/10.6084/m9.figshare.29133476.v1
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    csvAvailable download formats
    Dataset updated
    May 23, 2025
    Dataset provided by
    figshare
    Authors
    Razak Ayariga
    License

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

    Area covered
    Ghana
    Description

    This paper examines gender earnings gaps in Ghana using data from the Ghana Living Standards Survey (GLSS7). Focusing on both the formal and informal sectors, we apply Oaxaca–Blinder decompositions and Recentered Influence Function (RIF) regressions to investigate mean and distributional disparities in log earnings between men and women. The evidence points towards a long-term gender pay gap, with females receiving significantly less than males, particularly in the informal economy. RIF regressions along the wage distribution show that the gender wage gap is more substantial in the upper quantiles in the informal sector. In contrast, the formal sector has narrower or even reversed gaps at specific quantiles.

  19. U.S. wage and salary workers: weekly earnings by gender and ethnicity 2023

    • statista.com
    Updated Mar 24, 2025
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    Abigail Tierney (2025). U.S. wage and salary workers: weekly earnings by gender and ethnicity 2023 [Dataset]. https://www.statista.com/topics/11801/gender-inequality-in-the-united-states/
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    Dataset updated
    Mar 24, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Abigail Tierney
    Area covered
    United States
    Description

    This statistic shows the median weekly earnings of full-time wage and salary workers in the United States by gender and ethnicity in 2023. The usual weekly earnings of a male Asian American wage worker was 1,635 U.S. dollars in 2023.

  20. o

    Replication data for: Gender Norms and Relative Working Hours: Why Do Women...

    • openicpsr.org
    Updated May 1, 2018
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    Sarah Fleche; Anthony Lepinteur; Nattavudh Powdthavee (2018). Replication data for: Gender Norms and Relative Working Hours: Why Do Women Suffer More Than Men from Working Longer Hours Than Their Partners? [Dataset]. http://doi.org/10.3886/E114484V1
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    Dataset updated
    May 1, 2018
    Dataset provided by
    American Economic Association
    Authors
    Sarah Fleche; Anthony Lepinteur; Nattavudh Powdthavee
    Description

    Constraints that prevent women from working longer hours are argued to be important drivers of the gender wage gap in the United States. We provide evidence that in couples where the wife's working hours exceed the husband's, the wife reports lower life satisfaction. By contrast, there is no effect on the husband's satisfaction. The results still hold when controlling for relative income. We argue that these patterns are best explained by perceived fairness of the division of household labor, which induces an aversion to a situation where the wife works more at home and on the labor market.

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Andreas Gulyas; Sebastian Seitz; Sourav Sinha (2021). Code for: Pay Transparency and the Gender Wage Gap: Evidence from Austria [Dataset]. http://doi.org/10.3886/E167024V1
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Code for: Pay Transparency and the Gender Wage Gap: Evidence from Austria

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Dataset updated
Sep 15, 2021
Dataset provided by
American Economic Associationhttp://www.aeaweb.org/
Authors
Andreas Gulyas; Sebastian Seitz; Sourav Sinha
License

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

Time period covered
2007 - 2018
Area covered
Austria
Description

This is the replication material for Pay Transparency and the Gender Wage Gap: Evidence from Austria, American Economic Journal: Economic PolicyWe study the 2011 Austrian Pay Transparency Law, which requires firms above a size threshold to publish internal reports on the gender pay gap. Using an event-study design, we show that the policy had no discernible effects on male and female wages, thus leaving the gender wage gap unchanged. The effects are precisely estimated and we rule out that the policy narrowed the gender wage gap by more than 0.4 p.p.. Moreover, we do not find evidence for wage compression within establishments. We discuss several possible reasons why the reform did not reduce the gender wage gap.

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