Bibliographic record
Abstract
Gold rushes are periods of economic boom, generally associated with large increases in expenditures aimed at securing claims near new found veins of gold. An interesting aspect of gold rushes is that, from a social point of view, much of the increased activity is wasteful since it contributes simply to the expansion of the stock of money. In this paper, we explore whether business cycle fluctuations may sometimes be driven by a phenomenon akin to a gold rush. In particular, we present a model where the opening of new market opportunities causes an economic expansion by favoring competition for market share, which is essentially a dissolution of rents. We call such an episode a market rush. We construct a simple model of a market rush that can be embedded into an otherwise standard Dynamic General Equilibrium model, and show how market rushes can help explain important features of the data. We use a simulated-moment estimator to quantify the role of market rushes in fluctuations. We find that market rushes may account for over half the short run volatility in hours worked and a third of the short run volatility of output.
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 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 0.001 |
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".