Long-Term Determinants of the Personal Savings Rate: Literature Review and Some Empirical Results for Canada
Bibliographic record
Abstract
This paper examines the structural determinants of the personal savings rate in Canada over the last 30 years, using cointegration techniques. The main finding is that the real interest rate, expected inflation, the ratio of the all-government fiscal balances to nominal GDP, and the ratio of household net worth to personal disposable income are the most important determinants of the trend in the personal savings rate, as measured in the National Income and Expenditure Accounts (NIEA). The results also suggest that the rapid decline in the NIEA personal savings rate in recent years largely reflects a change in the trend component of the savings rate, rather than a transitory departure from the trend. In the current environment of low inflation and government fiscal balances moving into surpluses, the trend NIEA savings rate could remain low. When using a measure of the personal savings rate based on the change in the net worth position of the personal sector (as estimated in the National Balance Sheet Accounts [NBSA]), the trend is determined by the real interest rate, expected inflation, and the ratio of household net worth to personal disposable income. However, the statistical evidence supporting this long-run relationship is not as conclusive as that for the NIEA savings rate.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.013 | 0.045 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".