Життєздатність пенсійних гарантійних схем щодо пенсій із визначеними виплатами в посткризовий період
Bibliographic record
Abstract
Many countries have established mandatory guarantee funds for such financial sector as banking, capital markets and insurance. But there are only few developed countries that provided some guarantees to those retired with pension benefits plans. The main feature of defined benefits schemes is that their participants know the size of the future pensions beforehand. However, provision of this level of pension demands constant correction of the size of contributions paid to the schemes that most often depend on a situation at the financial market and assets’ market value. But, nowadays plan sponsors (employers who pay contributions to the pension fund) become bankrupt more often than ten-fifteen years ago. Thus defined benefits pension schemes of their employees are underfunded. Developed countries apply different security mechanisms to protect defined pension benefits: solvency requirements, pension guarantee schemes (funds), and sponsor support. However, the most efficient are Pension benefit guarantee schemes in which the funding risks are born by the specially created pension guarantee funds. One of the oldest Pension benefit guarantee funds is the federal government’s Pension Benefit Guaranty Corporation (PBGC) of the USA established in 1974 under the Enactment of the Employee Retirement Income Security Act (ERISA). Ontario is the only jurisdiction in Canada with benefit guarantee insurance, the Pension Benefit Guarantee Fund, introduced in 1980, around the time when there had been a chain of plant closures at heavy industry. In some European countries (UK, Germany, Sweden and Switzerland) and Japan there are also national pension guarantee systems established to protect a pension fund and its beneficiaries against default risk of its sponsor. Many retirement benefits protection schemes were put in place as a result of political reactions to adverse events leading to loss of benefits for workers. The conducted in this paper analysis of mentioned schemes showed that there is no single approach in the creation and operation of guarantee schemes in pension benefit sector. Countries have there own economic and even more political reasons to establish such institutions. Also, there is growing concern about the funding status of defined benefit pension plans because of the increase in bankruptcy rates among plans’ sponsors. Therefore there are some arguments for and against Pension benefit guarantee schemes and possible governmental involvement in guarantee schemes. Arguments put forward in their favour is that they can provide some defence against the poor and incomplete design of the pension contract and the lack of diversification associated with defined benefit schemes. Arguments against – are risks that can arise as a consequence of their introduction. These risks include adverse selection, moral hazard, systematic risk and political risk.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.028 | 0.013 |
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".