Preliminary and Very Incomplete- Comments Welcome Please Do not Circulate Without the Authors ’ Permission
Bibliographic record
Abstract
We provide evidence that firms engaged in the production of investment goods face higher baseline idiosyncratic risk than firms producing consumption goods. In a model of capital accumulation where the protection of investors ’ rights is incomplete, this difference in volatility induces a wedge between the returns on investment in the two sectors. Everything else equal, risk-sharing and firm size will be lower in the investment good sector. We investigate the implications of different levels of investor protection for important features of economic devel-opment. We find that countries with better institutions tend to (i) have higher investment rates, (ii) be richer, (iii) have a lower relative price of capital goods, (iv) have a higher measured aggregate TFP, and (v) have a larger relative firm size in the investment goods sector. We provide evidence in support of the latter prediction. Key words. JEL Codes:. ∗We thank Thomas Philippon and Gianluca Violante, as well seminar attendants at NYU and the 2004 SED Meeting in Florence, for their comments and suggestions. All remaining errors are our own responsibility. We are specially grateful to Thomas Philippon and Lubomir Litov for helping us with the data. Castro acknowledges financial support from the SSHRC (Canada) and the FCAR
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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 | 0.008 | 0.117 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.483 | 0.269 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".