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 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 | 0.000 |
| 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".