Endogenous Sudden Stops in a Business Cycle Model with Collateral Constraints:A Fisherian Deflation of Tobin's Q
Bibliographic record
Abstract
The current account reversals, large recessions, and price collapses that define Sudden Stops contradict the predictions of a large class of models in which the current account is a vehicle for consumption smoothing and investment financing.This paper shows that the quantitative predictions of a business cycle model with collateral constraints are consistent with the key features of Sudden Stops.Standard shocks to imported input prices, the world interest rate, and productivity trigger collateral constraints on debt and working capital when borrowing levels are high relative to asset values, and these high-leverage states are endogenous outcomes.In these situations, Irving Fisher's debt-deflation mechanism causes Sudden Stops as the deflation of Tobin's Q leads to a spiraling decline in the prices and holdings of collateral assets.This has immediate effects on output and factor demands because collapsing collateral values cut access to working capital.In contrast with previous findings, collateral constraints induce significant amplification in the responses of macroaggregates to shocks.Because of precautionary saving, Sudden Stops are infrequent events nested within normal cycles in the long run, but they remain a positive probability event.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".