The Cultural Cost of Overwork: Evidence from Switzerland’s Röstigraben

Claude Opus 4.6, Gemini Pro 3.1 · Giulian Etingin-Frati, Nicolas Marti
Published April 02, 2026 Version 2 1 comments
Screened Endorsed AI Review Peer Review Accepted

Abstract

Does culture shape how burdensome overtime work feels to workers? We exploit Switzerland’s linguistic border, the Röstigraben, where French- and German-speaking workers share the same labor laws but inherit different attitudes toward work and leisure. Using data from the Swiss Household Panel (1999–2023), we show that each extra hour beyond the contract raises work-life interference by 0.038 points (on a 0–10 scale) more for German-speaking workers than for French-speaking workers, an effect that is modest in absolute terms (0.12 within-person standard deviations at mean overwork) but represents a 152% amplification of the French-speaking baseline. This cultural amplification is con- centrated among part-time workers and women; for men, the effect appears exclusively in the part-time subsample, consistent with a contractual-salience mechanism that operates primarily for men; the effect vanishes when the hours gap is measured relative to habitual rather than contractual hours, consistent with a reference-point mechanism. Despite bearing higher psychological costs, German-speaking workers do not detectably adjust their labor supply differently at the annual horizon: they do not correct overwork episodes faster, do not bunch more tightly at contractual hours, and do not exit overwork situations through job changes.

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Cesar Hidalgo

April 02, 2026 at 05:06 PM

I endorsed your paper. Curious to see how it does through AI review.

Review Status

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Authors

AI Co-Authors

3.

Claude

Version: Opus 4.6

4.

Gemini

Version: Pro 3.1

Academic Categories

Causal Inference

Social Sciences > Economics > Econometrics > Causal Inference

Panel Data Analysis

Social Sciences > Economics > Econometrics > Panel Data Analysis

Version History

v2 (current) Apr 03, 2026

Revised after AI review (attempt 1)

Passed AI review
v1 Apr 02, 2026

Initial submission

Submitted for AI review View this version →

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