Wage Posting or Wage Bargaining? A Test Using Dual Jobholders
Bibliographic record
Abstract
This paper examines the behavior of dual jobholders to test a simple model of wage bargaining and wage posting. We estimate the sensitivity of wages and separation rates to wage shocks in a worker’s secondary job to assess the degree of bargaining versus wage posting in the labor market. We interpret the evidence within a model where workers facing hours constraints in their primary job may take a second, flexible-hours job for additional income. When a secondary job offers a sufficiently high wage, a worker either bargains with the primary employer for a wage increase or separates. The model provides a number of predictions that we test using matched employer-employee administrative data from Washington State. In the aggregate, wage bargaining appears to be a limited determinant of wage setting. The estimated wage response to improved outside options, which we interpret as bargaining, is precisely estimated, but qualitatively small. Wage posting appears to be more important than bargaining for wage determination overall, and especially in lower parts of the wage distribution. Observed wage bargaining takes place mainly among workers in the highest wage quartile. For this group, improved outside options translate to higher wages, but not higher separation rates. In contrast, for workers in the lowest wage quartile, wage increases in the secondary job lead to higher separation rates but no significant wage increase in the primary job, consistent with wage posting. We also find evidence in support of the hours-constraint model for dual jobholding. In particular, work hours in the primary job do not respond to wages in the secondary job, but hours and separations in the secondary job are sensitive to wages in the primary job due to income effects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.022 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.026 | 0.002 |
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".