Bayesian model of provision for employee retirement benefits

Agnieszka Pobłocka , Ewa Spigarska , Grzegorz Krzykowski


Retirement benefits are an additional security for an employee that impacts present and future lives of both – an employer and an employee. The employer tries to expand the job offer and looks for additional forms of remuneration for its employees. An employee satisfied with work, encouraged by additional employee benefits (retirement benefits, jubilee awards, etc.) decides to retire after reaching the required seniority. The article presents a Bayesian approach to the valuation of a provision for employee benefits. The main goal of the article is to create a Bayesian model of provision for employee benefits. To achieve the goal, non-classical statistical methods were used to estimate the provision for an employee in accordance with current legal standards in Poland (ie the Accountancy Act, Labor law, International Accounting Standards). In the Bayesian approach, the provision for retirement is described by the posterior distribution, which can be used to estimate selected characteristics, such as. measurement position or dispersion.
Author Agnieszka Pobłocka (FM / DS)
Agnieszka Pobłocka,,
- Department of Statistics
, Ewa Spigarska (FM / DA / FAU)
Ewa Spigarska,,
- Financial Accounting Unit
, Grzegorz Krzykowski
Grzegorz Krzykowski,,
Publication size in sheets0.55
Book 11th International Scientific Conference "New Challenges of Economic and Business Development - 2019: Incentives for Sustainable Economic Growth": Riga, Latvia, May 16-18, 2019: proceedings, 2019, University of Latvia, ISBN 978-9934-18-428-4, 937 p.
Keywords in PolishPodejście Bayesowskie, rezerwy na świadczenia emerytalne dla pracowników, dodatkowy system emerytalny
Keywords in Englishbayesian approach, provision for employee benefits
Languageen angielski
Poblocka_Agnieszka_Bayesian_model_of_provision_for_employee_retirement_benefits_2019.pdf 822.12 KB
Score (nominal)5
Score sourcepublisherList
ScoreMinisterial score = 5.0, 28-01-2020, ChapterFromConference
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