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France manufacturing surprise indicator (SA)

France manufacturing surprise indicator (SA) stood at -5.76 in Sep 2026, according to INSEE – Institut national de la statistique et des études économiques (BDM). It is one of the indicators in the INSEE business surveys table (Value · Monthly), with a complete series running from Apr 1990 to Sep 2026. The complete series with an interactive chart, free to download.

Source: INSEE – Institut national de la statistique et des études économiques (BDM)Last updated: Curated by Bui Thanh Phuc
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This indicator in the INSEE business surveys table

Indicator09-202608-202607-202606-202605-202604-202603-202602-202601-202612-2025
Monthly business survey in goods-producing industries - Manufacturing industry - Surprise indicator - SA series-5.76-12.191.34-5.84-1.29-7.15-9.96-11.14-12.19-5.93
Employment climate summary indicator - All sectors - Metropolitan France97.999.298.698.294.699.799.597.995.694.7
Business climate summary indicator - All sectors - Metropolitan France96.497.897.49593.994.197.598.699.298.5

Understanding france manufacturing surprise indicator (SA)

Tracking the divergence between preliminary survey outcomes and historical projection models, this measure isolates unexpected shifts specifically within goods-producing establishments. By capturing the degree to which industrial sentiment departs from econometric forecasts, the index separates structural momentum from temporary noise inherent in factory-level polling. The formulation exclusively targets unanticipated departures in executive replies, omitting stable or expected trajectories that match established cyclical patterns. While broad composite sentiment gauges reflect general executive mood across all reporting branches, this variant isolates forecast errors, highlighting sudden accelerations or decelerations unique to the industrial core.

Interpreting the index requires careful attention to potential retrospective adjustments in underlying baseline models and seasonal filters. Early estimates rely on partial response sets from corporate panels, leaving initial readings vulnerable to subsequent adjustments when late replies are incorporated. Analysts should avoid isolated period-on-period changes, as single-month readings frequently exhibit volatility; instead, examining persistence across consecutive releases provides a clearer signal of shifting industrial momentum. Comparisons against broader composite sentiment indicators can clarify whether an unexpected industrial movement is part of a generalized macroeconomic shift or isolated entirely to factory-floor dynamics.

Frequently asked questions

What does the manufacturing surprise indicator actually measure?
It quantifies how much actual monthly survey outcomes from goods-producing firms deviate from statistical expectations and forecasting models.
Why focus exclusively on surprise elements rather than raw survey balances?
Isolating unexpected departures helps analysts separate normal seasonal fluctuations from sudden, genuine shifts in factory sentiment.
How should preliminary index readings be handled by researchers?
Users should watch for subsequent methodological revisions and evaluate multi-month persistence rather than reacting to single-month fluctuations.

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