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Using Facebook ad data to track the global digital gender gap

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  • Fatehkia, Masoomali
  • Kashyap, Ridhi
  • Weber, Ingmar

Abstract

Gender equality in access to the internet and mobile phones has become increasingly recognised as a development goal. Monitoring progress towards this goal however is challenging due to the limited availability of gender-disaggregated data, particularly in low-income countries. In this data sparse context, we examine the potential of a source of digital trace ‘big data’ – Facebook’s advertisement audience estimates – that provides aggregate data on Facebook users by demographic characteristics covering the platform’s over 2 billion users to measure and ‘nowcast’ digital gender gaps. We generate a unique country-level dataset combining ‘online’ indicators of Facebook users by gender, age and device type, ‘offline’ indicators related to a country’s overall development and gender gaps, and official data on gender gaps in internet and mobile access where available. Using this dataset, we predict internet and mobile phone gender gaps from official data using online indicators, as well as online and offline indicators. We find that the online Facebook gender gap indicators are highly correlated with official statistics on internet and mobile phone gender gaps. For internet gender gaps, models using Facebook data do better than those using offline indicators alone. Models combining online and offline variables however have the highest predictive power. Our approach demonstrates the feasibility of using Facebook data for real-time tracking of digital gender gaps. It enables us to improve geographical coverage for an important development indicator, with the biggest gains made for low-income countries for which existing data are most limited.

Suggested Citation

  • Fatehkia, Masoomali & Kashyap, Ridhi & Weber, Ingmar, 2018. "Using Facebook ad data to track the global digital gender gap," World Development, Elsevier, vol. 107(C), pages 189-209.
  • Handle: RePEc:eee:wdevel:v:107:y:2018:i:c:p:189-209
    DOI: 10.1016/j.worlddev.2018.03.007
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    References listed on IDEAS

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    1. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2008. "Nowcasting: The real-time informational content of macroeconomic data," Journal of Monetary Economics, Elsevier, vol. 55(4), pages 665-676, May.
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    Cited by:

    1. M Vimalkumar & Jang Bahadur Singh & Sujeet Kumar Sharma, 0. "Exploring the Multi-Level Digital Divide in Mobile Phone Adoption: A Comparison of Developing Nations," Information Systems Frontiers, Springer, vol. 0, pages 1-20.
    2. Dennis M. Feehan & Curtiss Cobb, 2019. "Using an Online Sample to Estimate the Size of an Offline Population," Demography, Springer;Population Association of America (PAA), vol. 56(6), pages 2377-2392, December.
    3. Laetitia Gauvin & Michele Tizzoni & Simone Piaggesi & Andrew Young & Natalia Adler & Stefaan Verhulst & Leo Ferres & Ciro Cattuto, 2020. "Gender gaps in urban mobility," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-13, December.

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