Unpaid #care work remains a key barrier to the labour market participation of #women. The CESSDA Data Catalogue offers a Euro-wide cross-section dataset (27 countries; n=60,000+) on #GenderGaps in unpaid care. Explore its impact on job opportunities and work-life balance 👉 lnkd.in/dVXdDTvE

Finally, this article and the online tool wouldn’t be possible without the collaboration of ILO and IOM, as well as the contribution of the ILO Library, IPA-HTRI, ITCILO, and the funding support of USDOL. Thank you! 🤓 5/5

The takeaway? Evidence-based policies can advance the efforts to combat #HumanTrafficking, but we need more #research guided by robust #data and multi-stakeholder consultations.
👉 Explore the EGM: rtaproject.org/human-trafficking-egm/
👉 Learn more: doi.org/10.1080/23322705.2024.2432788 4/5

What about the interactive online tool?
The #HumanTrafficking Evidence Gap Map is informed by 238 records and 30 global stakeholders.
👉 Users can explore factors and outcomes in 3 languages
👉 Filters can help researchers and policy actors gather evidence to inform solutions 3/5

Our #research highlights:
- The most and least commonly studied factors and outcomes related to human trafficking
- Geographical variations in counter-trafficking programs and policies
- Its implications within the 4Ps (Prevention, Protection, Prosecution, Partnership) framework 2/5

Unfortunately I couldn't make it open access, but I hope the ungated version (see thread 5/5) is useful!

On a personal note, I am so glad this paper found a home! 🏠 Preprint version available: sites.google.com/view/lorrain... 5/5

The takeaway? Economic gaps persist, but some key factors, like discrimination, appear to be decreasing over time. This underscores the need for targeted integration policies. Curious? Read more in the paper: doi.org/10.1093/migration/mnae036 4/5

Conventional methods (e.g., matching and decomposition) may overestimate these disparities. Accounting for selection on unobservables reveals smaller but persistent gaps, which highlights the need for more nuanced estimation approaches. 3/5

Between 2010 and 2014, the asylum population in Switzerland was 7-11% less likely to be employed and to earn 15-19% less than other migrants. Could the way we estimate these gaps be shaping our understanding? Let’s dive deeper. 👇 2/5

For Bluesky-Curious Econ Lovers, a Quick Start guide to plugging into the economics community here.

It aims to lower the costs & boost the benefits for folks to engage here.

If it seems useful, please share it here & especially on X.
📉📈 #️⃣#️⃣
aaronsojourner.org/for-bluesky-...

This is great! Thank you!