MacroDataHub

Île-de-France unemployment beneficiaries: Seine-et-Marne

Île-de-France unemployment beneficiaries: Seine-et-Marne stood at 53,407 persons in Dec 2025, according to France Travail – statistiques et études (statistiques.francetravail.org). It is one of the indicators in the Unemployment benefits (monthly) table (Value · Monthly), with a complete series running from Jan 2020 to Dec 2025. The complete series with an interactive chart, free to download.

Source: France Travail – statistiques et études (statistiques.francetravail.org)Last updated: Curated by Bui Thanh Phuc
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This indicator in the Unemployment benefits (monthly) table

Indicator12-202511-202510-202509-202508-202507-202506-202505-202504-202503-2025
Île-de-France
Seine-et-Marne53,40753,87053,25352,76453,21950,17849,70951,29151,74753,672
Val-d'Oise50,72351,07450,76750,26150,71047,91246,97148,28348,67050,045

Understanding île-de-France unemployment beneficiaries: Seine-et-Marne

Quantifying the headcount of residents within this expansive eastern Parisian basin department who receive monthly unemployment insurance disbursements. The measure captures individuals who have accumulated sufficient prior employment credits to qualify for compensation, omitting those who exhaust their entitlements or rely on other welfare tiers. Residence within the specified administrative boundaries is the sole geographic inclusion criterion.

Interpreting the data requires accounting for the mixed urban-rural composition of the territory, which creates distinct labor dynamics compared to the dense metropolitan core. Analysts should be aware that early estimates undergo routine administrative revisions. Year-on-year comparisons are recommended to filter out seasonal processing delays and provide a clearer perspective on underlying economic health.

Frequently asked questions

What happens to the count when a recipient's benefit duration expires?
The individual is automatically removed from this compensated beneficiary headcount.
Does the mixed urban and rural nature of the territory affect the data?
Different local employment sectors can create varying claim patterns across different parts of the department.
Are month-on-month figures reliable for spotting sudden economic shifts?
Short-term changes can be skewed by administrative processing lags, making annual comparisons safer.

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