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The Efficiency of Indonesian Pension Funds: A Two-Stage Additive Network DEA Approach

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  • Paskalis Seran

    (Department of Management, Faculty of Economics and Business, Universitas Kristen Satya Wacana, Jl Diponegoro 52-60, Salatiga 50711, Indonesia
    Department of Management, Faculty of Economics and Business, Universitas Katolik Widya Mandira, Jl. A. Yani 50-52-25, Kupang 85225, Indonesia)

  • Usil Sis Sucahyo

    (Department of Management, Faculty of Economics and Business, Universitas Kristen Satya Wacana, Jl Diponegoro 52-60, Salatiga 50711, Indonesia)

  • Apriani Dorkas Rambu Atahau

    (Department of Management, Faculty of Economics and Business, Universitas Kristen Satya Wacana, Jl Diponegoro 52-60, Salatiga 50711, Indonesia)

  • Supramono Supramono

    (Department of Management, Faculty of Economics and Business, Universitas Kristen Satya Wacana, Jl Diponegoro 52-60, Salatiga 50711, Indonesia)

Abstract

Employer pension funds (EPFs) manage funds contributed by their members and sponsors with the ultimate goal of providing adequate pension benefits for beneficiaries upon retirement. The critical issue for EPFs is, therefore, their efficiency. This study aims to investigate Indonesian EPFs’ technical efficiency and its determinants using data from 38 EPFs actively operating in 2011–2017. By conceptualizing EPFs’ management processes as a network, this study employs the two-stage additive network data envelopment analysis (DEA) to measure the performance of EPFs based on their overall efficiency, operational efficiency, and investment efficiency. A regression analysis is then performed to examine the determinants of EPFs’ efficiency. The results reveal that investment efficiency is the main source of EPFs’ overall inefficiency, implying that more attention should be directed towards investment management when the EPFs seek to improve their overall performance. The regression analysis shows that size and ownership are the most significant factors that determine EPFs’ efficiency. Ownership positively correlates with both overall efficiency and investment efficiency, while size negatively affects investment efficiency. This study concludes that in order to improve their overall performance, EPFs need to make more efforts in investment management, while accounting for size and ownership as important determinants. This study provides a projection analysis model as a practical guidline for EPFs to improve their performance.

Suggested Citation

  • Paskalis Seran & Usil Sis Sucahyo & Apriani Dorkas Rambu Atahau & Supramono Supramono, 2023. "The Efficiency of Indonesian Pension Funds: A Two-Stage Additive Network DEA Approach," IJFS, MDPI, vol. 11(1), pages 1-19, February.
  • Handle: RePEc:gam:jijfss:v:11:y:2023:i:1:p:28-:d:1054283
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    References listed on IDEAS

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    1. Nicholas Barr & Peter Diamond, 2006. "The Economics of Pensions," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 22(1), pages 15-39, Spring.
    2. Premachandra, I.M. & Zhu, Joe & Watson, John & Galagedera, Don U.A., 2012. "Best-performing US mutual fund families from 1993 to 2008: Evidence from a novel two-stage DEA model for efficiency decomposition," Journal of Banking & Finance, Elsevier, vol. 36(12), pages 3302-3317.
    3. Chiang Kao, 2014. "Efficiency Decomposition in Network Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Wade D. Cook & Joe Zhu (ed.), Data Envelopment Analysis, edition 127, chapter 0, pages 55-77, Springer.
    4. Kao, Chiang, 2016. "Efficiency decomposition and aggregation in network data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 255(3), pages 778-786.
    5. Silberston, Aubrey, 1972. "Economies of Scale in Theory and Practice," Economic Journal, Royal Economic Society, vol. 82(325), pages 369-391, Supplemen.
    6. Sunaryo Sunaryo & Alvia Santoni & Endri Endri & Muhammad Nusjirwan Harahap, 2020. "Determinants of Capital Adequacy Ratio for Pension Funds: A Case Study in Indonesia," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 11(4), pages 203-213, July.
    7. Kao, Chiang, 2014. "Network data envelopment analysis: A review," European Journal of Operational Research, Elsevier, vol. 239(1), pages 1-16.
    8. Timothy J. Coelli & D.S. Prasada Rao & Christopher J. O’Donnell & George E. Battese, 2005. "An Introduction to Efficiency and Productivity Analysis," Springer Books, Springer, edition 0, number 978-0-387-25895-9, February.
    9. Michiel Bijlsma & Johannes Bonekamp & Casper Ewijk & Ferry Haaijen, 2018. "Funded Pensions and Economic Growth," De Economist, Springer, vol. 166(3), pages 337-362, September.
    10. Gosse A.G. Alserda & Jacob A. Bikker & Fieke S.G. Van Der Lecq, 2018. "X-efficiency and economies of scale in pension fund administration and investment," Applied Economics, Taylor & Francis Journals, vol. 50(48), pages 5164-5188, October.
    11. Felisitas Defung & Ruhul Salim & Harry Bloch, 2016. "Has regulatory reform had any impact on bank efficiency in Indonesia? A two-stage analysis," Applied Economics, Taylor & Francis Journals, vol. 48(52), pages 5060-5074, November.
    12. Mukul Asher & Azad S. Bali, 2015. "Public Pension Programs in Southeast Asia: An Assessment," Asian Economic Policy Review, Japan Center for Economic Research, vol. 10(2), pages 225-245, July.
    13. Cook, Wade D. & Seiford, Larry M., 2009. "Data envelopment analysis (DEA) - Thirty years on," European Journal of Operational Research, Elsevier, vol. 192(1), pages 1-17, January.
    14. Hongxian Zhang & Liang Guo & Maggie Hao, 2018. "Corruption, governance, and public pension funds," Review of Quantitative Finance and Accounting, Springer, vol. 51(4), pages 883-919, November.
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