Employee Benefits Program Valuation with Multiple Decrement Model Based on PSAK 24 Post-COVID-19 Pandemic
Abstract
In this article, we evaluate the post-labor compensation program based on PSAK-24 in the new normal era of the COVID-19 pandemic. In order to create a table multiple decrements based on a single table decrement namely, death, withdrawal, total permanent disability, and retirement. In the new normal era of the COVID-19 pandemic, the benefits of death, death caused by COVID-19, withdrawal, total permanent disability, and retirement were then aggregated. The method used in this study is a quantitative method with a case study approach of COVID-19. The data used is secondary data on the number of COVID-19 positive cases in Indonesia from January 2021 to December 2022. In this study, an actuarial model, the Multiple Decrement Model, was applied to calculate the valuation of the post-labor compensation program based on PSAK-24 using five decrements as the cause of claims consisting of death, death cause of COVID-19, withdrawal, total permanent disability and retirement. The calculation results that can be seen that large annual net premiums multiple decrement cases that provide benefits according to the cause of failure getting bigger as that person gets older.
Keywords
Full Text:
DOWNLOAD [PDF]References
Academy of Actuaries, A. (2004). Fundamentals of Current Pension Funding and Accounting For Private Sector Pension Plans.
Angkasa, A. P., Lestari, D., & Devila, S. (2021). Comparison of entry age normal and projected unit credit method for funding of defined benefit pension plan. AIP Conference Proceedings, 2374. https://doi.org/10.1063/5.0059248
Anthropelos, M., & Blontzou, E. (2023). On Valuation and Investments of Pension Plans in Discrete Incomplete Markets. Risks, 11(6), 103. https://doi.org/10.3390/risks11060103
Barigou, K., Loisel, S., & Salhi, Y. (2020). Parsimonious Predictive Mortality Modeling by Regularization and Cross-Validation with and without Covid-Type Effect †. https://doi.org/10.3390/risks901
Bateman, H., Dobrescu, L. I., Liu, J., Newell, B. R., & Thorp, S. (2023). Determinants of early-access to retirement savings: Lessons from the COVID-19 pandemic. Journal of the Economics of Ageing, Vol.24. https://doi.org/10.1016/j.jeoa.2023.100441
Bayar, Y., Gavriletea, M. D., Danuletiu, D. C., Danuletiu, A. E., & Sakar, E. (2022). Pension Funds, Insurance Companies and Stock Market Development: Evidence from Emerging Markets. Mathematics, Vol. 10. Issue 13 https://doi.org/10.3390/math10132335
Boado-Penas, M. C., Brinker, L. V., Eisenberg, J., & Korn, R. (2023). Managing reputational risk in the decumulation phase of a pension fund. Insurance: Mathematics and Economics, Vol.109, pages 52–68. https://doi.org/10.1016/j.insmatheco.2022.12.005
Deshmukh, S. (2012). Multiple decrement models in insurance: An introduction using R. In Multiple Decrement Models in Insurance: An Introduction Using R. Springer India. https://doi.org/10.1007/978-81-322-0659-0
Financial Accounting Standards Board, I. of I. C. A. (2010). Pernyataan Standar Akuntansi keuangan Imbalan Kerja.
Ekasasmita, W. (2015). Model Multi Status Untuk Menentukan Premi Asuransi Critical Illness. Universitas Gadjah Mada. https://etd.repository.ugm.ac.id/penelitian/detail/88567
Ekasasmita, W., Bahri, M., Bachtiar, N., Rahim, A., & Nur, M. (2023). One-Dimensional Quaternion Fourier Transform with Application to Probability Theory. Symmetry, 15(4), 815. https://doi.org/10.3390/sym15040815
Goto, S., & Yanase, N. (2021). Pension return assumptions and shareholder-employee risk-shifting. Journal of Corporate Finance, Vol.70. https://doi.org/10.1016/j.jcorpfin.2021.102047
Idrovo-Aguirre, B. J., & Contreras-Reyes, J. E. (2021). Monetary fiscal contributions to households and pension fund withdrawals during the COVID-19 pandemic: An approximation of their impact on construction labor supply in chile. Social Sciences, Vol.10, Issue 11. https://doi.org/10.3390/socsci10110417
Jaiswal, K. M., Dudhgaonkar, S., Gharade, P., & Sharma, N. (2022). Post-valuation quality check of multiple-choice questions. International Journal of Basic & Clinical Pharmacology, 12(1), 43. https://doi.org/10.18203/2319-2003.ijbcp20223353
Josa-Fombellida, R., & Navas, J. (2020a). Time consistent pension funding in a defined benefit pension plan with non-constant discounting. Insurance: Mathematics and Economics, Vol. 94, pages 142–153. https://doi.org/10.1016/j.insmatheco.2020.07.007
Lee, H., Ahn, J. Y., & Ko, B. (2019). Construction of multiple decrement tables under generalized fractional age assumptions. Computational Statistics and Data Analysis, Vol. 133, pages 104–119. https://doi.org/10.1016/j.csda.2018.09.004
Ma, & Zhien. (2009). Dynamical Modeling and Analysis of Epidemics. https://books.google.co.id/books?hl=id&lr=&id=LT5kDQAAQBAJ&oi=fnd&pg=PR5&dq=Ma,+%26+Zhien.+(2009).+Dynamical+Modeling+and+Analysis+of+Epidemics.&ots=57gMbzVGUG&sig=1SaQunpkgwtt1ZiGOiptJCyr8fc&redir_esc=y#v=onepage&q=Ma%2C%20%26%20Zhien.%20(2009).%20Dynamical%20Modeling%20and%20Analysis%20of%20Epidemics.&f=false
Marska-Dzioba, N., & Barczak, A. (2022). Impact of COVID-19 on the Disability Fund in Poland. Sustainability (Switzerland), Vol. 14, Issue 19. https://doi.org/10.3390/su141912914
Nur, S., Daulay, R., Apriva Hidayana, R., & Halim, N. A. (2022). Pension Fund Calculation Using Traditional and Projected Unit Credit Methods for Total Actuarial Liability and Normal Cost Cases. 3(4), 132–135. http://iorajournal.org/indx.php/orics/index
Petraki, A., & Zalewska, A. (2015). Jumping over a low hurdle: Personal pension fund performance. http://ssrn.com/abstract=2250847Electroniccopyavailableat:http://ssrn.com/abstract=2250847
Shang, Y., Qi, P., Chen, H., Yang, Q., & Chen, Y. (2022). COVID-19 and its impact on tourism sectors: implications for green economic recovery. Economic Change and Restructuring. https://doi.org/10.1007/s10644-022-09456-7
Strumskis, M., & Balkevičius, A. (2016). Pension fund participants and fund managing company shareholder relations in Lithuania second pillar pension funds. Intellectual Economics, 10(1), 1–12. https://doi.org/10.1016/j.intele.2016.06.004
Walk, D., Haviv, N., Hasisi, B., & Weisburd, D. (2021). The role of employment as a mediator in correctional education’s impact on recidivism: A quasi-experimental study of multiple programs. Journal of Criminal Justice, Vol. 74. https://doi.org/10.1016/j.jcrimjus.2021.101815
Wang, P., Zheng, X., Li, J., & Zhu, B. (2020). Prediction of epidemic trends in COVID-19 with logistic model and machine learning technics. Chaos, Solitons and Fractals, 139. https://doi.org/10.1016/j.chaos.2020.110058
Williams, H., Guh, S., Barrack, A., Boss, K., & Nigam, S. (2018). Long-Term Benefits of Employee Wellness Programs: A Blue Cross Blue Shield of Louisiana (BCBSLA) Case Study. Value in Health, 21, S140. https://doi.org/10.1016/j.jval.2018.04.946
Zhang, L., Zhang, H., & Yao, H. (2018). Optimal investment management for a defined contribution pension fund under imperfect information. Insurance: Mathematics and Economics, Vol.79, pages 210–224. https://doi.org/10.1016/j.insmatheco.2018.01.007
DOI: https://doi.org/10.31764/jtam.v8i1.17417
Refbacks
- There are currently no refbacks.
Copyright (c) 2024 Wahyuni Ekasasmita, Nur Rahmi, M. Fauzan Iskandar
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
_______________________________________________
JTAM already indexing:
_______________________________________________
JTAM (Jurnal Teori dan Aplikasi Matematika) |
_______________________________________________
_______________________________________________
JTAM (Jurnal Teori dan Aplikasi Matematika) Editorial Office: