Endogenously Procyclical Liquidity, Capital Reallocation, and q
Bibliographic record
Abstract
By analyzing a stochastic equilibrium with endogenous liquidity in the capital market, this paper explains the puzzling fact that capital reallocation across firms is procyclical while dispersion in Tobin's q across firms is acyclical or counter cyclical. Capital is reallocated across firms through a frictional market modeled by search and matching. The market tightness captures liquidity in this market and is endogenously determined as buyers choose whether to enter the market. Capital creation is also endogenous as capital makers choose whether to incur a cost to make capital. When aggregate productivity increases, more capital is created. At the same time, more buyers enter the capital market to buy capital in an attempt to capture the increased value of a productive firm. As a result, market liquidity increases and more capital is reallocated. The price of capital increases, which increases q of low-value firms and reduces q of high-value firms. The mean and standard deviation in q across firms respond ambiguously to an increase in aggregate productivity. These results are robust to the addition of heterogeneity in firm-specific productivity.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".