What are the Costs and Benefits of Social Security Investing in Equities
Bibliographic record
Abstract
Policymakers have long known that the retirement of the baby boom generation would produce significant deficits for the Social Security program. Restoring balance will require raising taxes, reducing benefits, or both. Some observers argue that shifting a portion of the Social Security trust fund from bonds to stocks, as part of a comprehensive reform package, could reduce the size of the required tax increases or benefit cuts. Other countries, such as Canada and Japan, invest a portion of their social security assets in equities, so precedents exist. Equity investments, however, would expose the program to greater financial risk and, potentially, greater political risk. This brief, based on a recent paper, assesses the costs and benefits of investing in equities. The discussion proceeds as follows. The first section provides background on the debate over investing trust fund reserves in equities. The second section investigates how investing in equities would have affected the finances of Social Security if the policy had been adopted in the past and if the policy were adopted today as part of a package to restore solvency over the next 75 years. It also includes a welfare analysis to address the contention that people will not value lower taxes in good times as much as they will dislike tax hikes in bad times. The third section addresses the non-financial issues associated with equity investing, such as the impact on capital markets and corporate governance and how to account for the possibility of higher expected returns without giving the impression that the government could solve all its problems simply by selling bonds and buying stocks. The final section concludes that both retrospective and prospective analyses suggest that investing a portion of the Social Security trust fund in equities would improve its finances; little evidence exists that trust fund equity investments would disrupt the stock market; equity investments could be structured to avoid government interference with capital markets or corporate decision making; and accounting for returns on a risk-adjusted basis would avoid the appearance of a free lunch.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".