Bibliographic record
Abstract
The purpose of this study was to examine the trend of defined contribution ( DC ) plan deferrals before and after the Great Recession. The investment principle of “buying when prices are low” suggests that DC plan deferral should increase during years when portfolio returns are low. The sample for this study consisted of eligible DC plan participants in the 2004, 2007, and 2010 Survey of Consumer Finances ( SCF ). The dependent variable was the elective deferral to the DC plan expressed as a percentage of the maximum amount allowed. The descriptive statistics showed that about half of respondents deferred <20% of their maximum allowable elective deferral, about a quarter of respondents deferred between 20% and 40%, and only a little more than 7% of respondents maximized their DC plan deferral in 2004 and 2007. However, the deferral rates dropped dramatically in 2010. The results of ordered logistic regression showed that respondents who had more education, were in excellent health, had more income, were willing to take investment risk, were allowed to borrow from the DC plan, were allowed to withdraw from the DC plan, and were homeowners without a mortgage were more likely to make a larger deferral to the DC plan. In general, these results were applicable for the time period. The most important implication is that many respondents were contributing relatively small percentages of the amount possible in 2004 and 2007 and that contributions were even lower in 2010. Educators, employers, and financial advisors should help workers understand the importance of participating fully or to the extent possible when making contributions to their DC plans.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| 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".