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Pension Funds and Mutual Funds Performance Measurement with a New DEA (MV-DEA) Model Allowing for Missing Variables

In: Data Science and Productivity Analytics

Author

Listed:
  • Maryam Badrizadeh

    (C/O Joseph C. Paradi, University of Toronto, The Center for Management of Technology and Entrepreneurship)

  • Joseph C. Paradi

    (C/O Joseph C. Paradi, University of Toronto, The Center for Management of Technology and Entrepreneurship)

Abstract

One of the assumptions in Data Envelopment Analysis (DEA) is that the active work units (Decision Making Units “DMU”) under study are operating under the same “culture”. However, in the real world, managers always want to compare their products/operations with similar entities (competitors), although, with some differences but in the same industry. It happens that there does not exist a model that can appropriately consider some aspects that are different in the DMU’s environments. This research introduces a novel DEA model, namely Mixed Variable DEA (MV-DEA), that provides a methodology where DMUs with some different cultural assumptions are examined relative to each other while retaining their own specific characteristics. The case examined here led us to evaluate private pension funds’ performance by considering the specific characteristics of such funds in comparison with mutual funds. Canadian private pension funds, regulated by the Federal Government of Canada, and Canadian open-ended mutual funds were studied. The results of the new MV-DEA model were compared to traditional DEA models and it was shown that the MV-DEA model provided more realistic results in our study.

Suggested Citation

  • Maryam Badrizadeh & Joseph C. Paradi, 2020. "Pension Funds and Mutual Funds Performance Measurement with a New DEA (MV-DEA) Model Allowing for Missing Variables," International Series in Operations Research & Management Science, in: Vincent Charles & Juan Aparicio & Joe Zhu (ed.), Data Science and Productivity Analytics, chapter 0, pages 391-413, Springer.
    • Handle: RePEc:spr:isochp:978-3-030-43384-0_14
    DOI: 10.1007/978-3-030-43384-0_14
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