Corporate Balance Sheets in Developed Economies: Implications for Investment
Bibliographic record
Abstract
In this paper, the authors examine the aggregate national balance-sheets of non-financial corporations in Australia and the G7 countries with a view to assessing both their financial structure and their financial position. More importantly, the authors investigate whether the financial position of non-financial corporations (i.e., debt-to-equity ratio) is material to the economy's investment prospects and whether the importance of this channel differs depending on the structure of corporate financing i.e., bank-based or market-oriented financing structures. Based on a dynamic business investment error-correction model that controls for the opportunity cost of capital and output growth, the authors test the above hypotheses using a quarterly panel dataset of eight developed economies over the 1992-2005 period. Their empirical results suggest that the financial position of non-financial corporations has a statistically significant impact on aggregate business investment growth, although the effect is quantitatively modest. Thus, their findings are consistent with the prediction of models that feature credit market imperfections such as costly information and asymmetric information. Moreover, the effect of corporate financial position appears to be statistically equivalent regardless of whether a country's corporations predominantly finance their investments through bank borrowing or market-oriented financing.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".