Increases in Business Investment Rates in OECD Countries in the 1990s
Bibliographic record
Abstract
Increases in business investment rates in OECD countries in the 1990s:How much can be explained by fundamentals?In several OECD countries, investment rates in the business sector grew strongly in the second half of the 1990s.In some cases, the strength of private investment relative to output growth had raised concerns about the risk of capital overhang and the prospect of a prolonged period of slow capital formation in order to bring investment levels back to more sustainable levels.It is possible that the stock market boom has contributed to a rise of investment demand to an excessive level, not only in the United States, but also in the United Kingdom, Canada, Scandinavia and Greece.The purpose of this paper is to assess the contribution of fundamental determinants to the change in investment in the second half of the 1990s, based on the estimation of panel cointegration equations for gross business investment for 18 OECD countries from 1970 to 1999.In addition to the levels of real GDP and a measure of the cost of capital, the set of explanatory variables includes four alternative proxies for financial market development.The inclusion of the latter variables helps to identify a coefficient for output that is close to one as well as a coefficient for the cost of capital that is both negative and significant.Based on these estimation results, the rise in the volume of business investment observed in a number of countries during the second half of the 1990s can only be partly explained by the set of basic determinants.On that basis, the empirical analysis would tend to support the view that investment had exceeded its steady-state level, not least in the United States.However, as suggested by the recent pick-up in investment, the size of the capital overhang in the United States might turn out to be smaller than feared, especially once the increases in trend output growth and depreciation rates are taken into account.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".