How Has the Two-Day Weekend Policy Affected Labour Supply and Household Work in China?
Bibliographic record
Abstract
This paper examines the effects of working time reduction policy on labour supply (hours of work and whether an individual takes a second job) and household production, by exploiting the Chinese Two-Day Weekend Policy, which effectively reduced weekly working days from six to five in May 1995, as a natural experiment. We construct a theoretical model that predicts a decline in labour supply in both private and public sectors as work hours were reduced. In theory, the time spent on household production may increase or decrease or the time spent on the second job may increase or decrease depending on how much agents care about household production or the income from a second job. Using the China Health and Nutrition Survey, we adopt a difference-in-differences strategy to estimate the policy effects on work hours of wage earners in both public and private sectors. Relative to the control group deemed unaffected by the policy change, our estimates show that the Two-Day Weekend Policy significantly reduced the working hours of wage earners by 4 percent and the public sector by 5 percent while increasing the probability of having a second job by 3 percent and reducing the time spent on household work by 98-107 minutes per week. The results are robust to different specifications and a propensity score matching technique.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".