The Short- and Long-Term Career Effects of Graduating in a Recession: Hysteresis and Heterogeneity in the Market for College Graduates
Bibliographic record
Abstract
The standard neo-classical model of wage setting predicts short-term effects of temporary labor market shocks on careers and low costs of recessions for both more and less advantaged workers. In contrast, a vast range of alternative career models based on frictions in the labor market suggests that labor market shocks can have persistent effects on the entire earnings profile. This paper analyzes the long-term effects of graduating in a recession on earnings, job mobility, and employer characteristics for a large sample of Canadian college graduates with different predicted earnings using matched university-employer-employee data from 1982 to 1999, and uses its results to assess the importance of alternative career models. We find that young graduates entering the labor market in a recession suffer significant initial earnings losses that eventually fade, but after 8 to 10 years. We also document substantial heterogeneity in the costs of recessions and important effects on job mobility and employer characteristics, but small effects on time worked. These adjustment patterns are neither consistent with a neo-classical spot market nor a complete scarring effect, but could be explained by a combination of time intensive search for better employers and long-term wage contracting. All results are robust to an extensive sensitivity analysis including controls for correlated business cycle shocks after labor market entry, endogenous timing of graduation, permanent cohort differences, and selective labor force participation.
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 | 0.001 | 0.005 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".