Business Fixed Investment and “Bubbles”: The Japanese Case
Bibliographic record
Abstract
Abstract: The two key questions which motivate our work are: do bubbles exist (in the sense that stock market prices do not always correspond to the present value of expected future profitability) and, if bubbles exist, do they have an effect on business fixed investment? The case of Japan is particularly interesting because of the dramatic movements in the Japanese stock market and the wide perception that these were associated with a bubble. We use a variety of techniques to analyze these questions. Fist, we examine financing and investment patterns to gauge firms' reactions to the 1980s stock market run-up. Second, we test subsets of the orthogonality conditions associated with the empirical first-order conditions for fixed investment. Third, we use a linear projection to decompose stock market prices into fundamental and bubble components, allowing us to carry out parametric estimates of the effect of the bubble component on fixed investment. The data strongly suggest that there was a bubble that had an economically important statistically significant effect on business fixed investment in Japan.;
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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) | 0.001 | 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".