Individual and Aggregate Labor Supply in Heterogeneous Agent Economies with Intensive and Extensive Margins
Bibliographic record
Abstract
We study business cycle fluctuations in heterogeneous-agent general equilibrium models that feature both intensive and extensive margins of labor supply. A nonconvexity in the mapping between time devoted to work and labor services combined with idiosyncratic shocks generates operative extensive and intensive margins. We consider calibrated versions of this model that differ in the value of a key preference parameter for labor supply and the extent of heterogeneity. The model is able to capture the salient features of the empirical distribution of hours worked, including how individuals transit within this distribution. We then study how the various specifications influence labor supply responses to aggregate technology shocks. We ask to what extent our predictions for business cycle fluctuations are affected by abstracting from the intensive margin and instead assuming that adjustment occurs only along the extensive margin. We find that abstracting from intensive margin adjustment can have large effects on the volatility of aggregate hours even if fluctuations along the intensive margin are small.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".