Household Saving in Germany: Results of the First SAVE Study
Bibliographic record
Abstract
Germany is an interesting country to study saving among older households since nearly everyone - whether in the middle income bracket or richer - saves substantial amounts in old age. Only households in the lowest quarter of the income distribution spend more between the ages of 60 and 75 than they save. Our paper exploits newly collected data, the first wave of the so-called SAVE panel, specifically collected to understand economic, psychological and sociological determinants of saving. Overall, we find extraordinarily stable savings patterns. More than 40% of German households save regularly a fixed amount. About 25% of German households plan their savings and have a clearly defined savings target in mind. Most of German household saving is in the form of contractual saving, such as saving plans, whole life insurance and building society contracts. This makes the flow of saving rather unresponsive to economic fluctuations, such as income shocks. Most households prefer to cut consumption if ends do not meet. In particular the elderly do not like to use credit cards, and they eschew debt. We suspect large cohort differences and will study them once further waves of the SAVE panel will become available.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".