Essays on building and evaluating two-stage DEA models of efficiency and effectiveness
dc.contributor.author | Attarwala, Abbas | |
dc.date.accessioned | 2021-07-27T20:30:08Z | |
dc.date.available | 2021-07-27T20:30:08Z | |
dc.date.issued | 2021-07-27 | |
dc.date.submitted | 2021-07-27 | |
dc.description.abstract | Researchers are not consistent in their choice of input and output variables when using two-stage data envelopment analysis (DEA) models to measure efficiency and effectiveness. This inconsistency has resulted in the development of many different two-stage DEA models of efficiency and effectiveness for the financial industry. In this dissertation, I improved the statistical method from the MASc dissertation (Attarwala, 2016) by adding more features. These features are documented in Chapter 2 on page 4 and page 5. This statistical method evaluates efficiency and effectiveness models in the banking industry. It relies on the semi-strong version of the efficient market hypothesis (EMH). The EMH is motivated by the wisdom of the crowds, discussed in Section 2.2.2. Previously (Attarwala, 2016), I found that the two-stage DEA model of Kumar and Gulati (2010) is not consistent with the semi-strong EMH for Indian and American banks. In this dissertation, using my improved statistical method, I show that the two-stage DEA model of Kumar and Gulati (2010) is not consistent with the semi-strong EMH for banks in Brazil, Canada, China, India, Japan, Mexico, South Korea and the USA from 2000- 2017. I address the question of whether a universal two-stage DEA model of efficiency and effectiveness exists by building a variable selection framework. This variable selection framework automatically generates two-stage DEA models of efficiency and effectiveness. To do this, it uses the improved statistical method and a genetic search (GS) algorithm. The variable selection framework finds the best, universal, two-stage DEA model of efficiency and effectiveness consistent with the semi-strong definition of EMH for banks in Brazil, Canada, China, India, Japan, Mexico, South Korea and the USA and from 2000-2017. I investigated the causal relationship between (a) the quantitative measures of efficiency and effectiveness from the best two-stage DEA model generated by the variable selection framework and (b) Tobin’s Q ratio, a financial market-based measure of bank performance. Not only do I provide bank managers with a reasonable proxy for measuring efficiency and effectiveness, but I also address the question of whether acting on these input and output variables improves the performance of banks in the financial market. Finally, I set up an optimization problem and find an optimal path from the two-stage DEA model of Kumar and Gulati (2010) to the best two-stage DEA model found by the variable selection framework. This optimal path provides a set of actionable items for converting a two-stage DEA model that is not consistent with the semi-strong EMH to one that is. | en |
dc.identifier.uri | http://hdl.handle.net/10012/17169 | |
dc.language.iso | en | en |
dc.pending | false | |
dc.publisher | University of Waterloo | en |
dc.subject | statistical methods | en |
dc.subject | econometrics | en |
dc.subject | two-stage DEA model | en |
dc.title | Essays on building and evaluating two-stage DEA models of efficiency and effectiveness | en |
dc.type | Doctoral Thesis | en |
uws-etd.degree | Doctor of Philosophy | en |
uws-etd.degree.department | Management Sciences | en |
uws-etd.degree.discipline | Management Sciences | en |
uws-etd.degree.grantor | University of Waterloo | en |
uws-etd.embargo.terms | 0 | en |
uws.contributor.advisor | Dimitrov, Stanko | |
uws.contributor.affiliation1 | Faculty of Engineering | en |
uws.peerReviewStatus | Unreviewed | en |
uws.published.city | Waterloo | en |
uws.published.country | Canada | en |
uws.published.province | Ontario | en |
uws.scholarLevel | Graduate | en |
uws.typeOfResource | Text | en |