MacroDataHub

France jobseekers in Brittany: category A

France jobseekers in Brittany: category A stood at 127,590 persons in Aug 2026, according to DARES – Direction de l'animation de la recherche, des études et des statistiques (Ministère du Travail). It is one of the indicators in the Registered jobseekers (DARES) table (Value · Monthly), with a complete series running from Jan 1996 to Aug 2026. The complete series with an interactive chart, free to download.

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This indicator in the Registered jobseekers (DARES) table

Indicator08-202607-202606-202605-202604-202603-202602-202601-202612-202511-2025
Category A (no work at all)
Brittany127,590128,420129,170129,040128,590128,630128,110127,220128,330129,110
Nouvelle-Aquitaine258,080264,750261,970260,100256,670256,830255,400253,360255,630256,980

Understanding france jobseekers in Brittany: category A

The metric documents the volume of registered jobseekers residing in Brittany who recorded zero hours of professional activity during the reference monthly period. This count excludes individuals who engaged in partial or intermittent employment arrangements, maintaining a strict focus on those completely without work. The regional allocation depends on the official residential address declared by the registrant to the employment agency network.

Analyzing this series requires careful consideration of local tourism and fishing cycles that introduce significant seasonal variations into regional employment statistics. Monthly figures can be volatile due to temporary administrative processing backlogs or weather-driven hiring cycles, making annual comparisons much more reliable for trend identification. Revisions to preliminary numbers occur periodically as local offices finalize status changes. Researchers comparing this regional data with national totals should account for distinct demographic and economic structures unique to the area.

Frequently asked questions

Are individuals with short-term part-time jobs counted in this Brittany series?
No, the series is restricted to those who performed zero hours of work during the reference month.
What causes periodic volatility in these regional monthly figures?
Local tourism, fishing cycles, and administrative processing variations often create temporary monthly fluctuations.
How should analysts evaluate changes over time in this dataset?
Year-on-year comparisons are recommended to bypass seasonal noise that obscures underlying labor market trends.

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