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Record W2105122929 · doi:10.3138/infor.47.2.151

Public versus Private Retirement Pensions: A Stackelberg Differential Game

2009· article· en· W2105122929 on OpenAlexvenueno aff
Francisco Cabo, Ana García-González

Bibliographic record

VenueINFOR Information Systems and Operational Research · 2009
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsnot available
FundersJunta de Castilla y León
KeywordsSocial securityPensionStackelberg competitionGovernment (linguistics)Private pensionEconomicsBusinessDistribution (mathematics)Labour economicsDebtDifferential (mechanical device)FinanceMicroeconomicsMarket economy

Abstract

fetched live from OpenAlex

This paper studies the dynamic interaction between a representative employer and the government, where both play roles in providing retirement pensions to a group of retirees with heterogenous wages. Public pension expenses drive the evolution of public debt, which can be positive or negative (a Social Security trust fund) in the long run. The relative sizes of public and private pensions affect income distribution. Social Security discriminates in favor of low-paid employees, while the employer provided pension, which is assumed to be integrated with Social Security, counteracts this tilt by favoring highly-paid employees. The Social optimum, understood as the central planner outcome or the government first best, can be attained in the decentralized scenario if the degree of Social Security integration is optimally chosen by the government. In addition, pensions obtained by retirees from a flat percentage private pension are compared to the pensions obtained by assuming a private plan that is optimally integrated with Social Security.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.970
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0030.007
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.116
GPT teacher head0.327
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2009
Admission routes1
Has abstractyes

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