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

Maryam Badrizadeh () and Joseph C. Paradi
Additional contact information
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

Chapter Chapter 14 in Data Science and Productivity Analytics, 2020, pp 391-413 from Springer

Abstract: 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.

Date: 2020
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-3-030-43384-0_14

Ordering information: This item can be ordered from
http://www.springer.com/9783030433840

DOI: 10.1007/978-3-030-43384-0_14

Access Statistics for this chapter

More chapters in International Series in Operations Research & Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().