Journal of CENTRUM Cathedra. Vol. 04, Issue 02

URI permanente para esta colecciónhttp://54.81.141.168/handle/123456789/194731

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JCC Volume 4 - Issue 2 - 2011
  • Benchmarking Peruvian Banks using Data Envelopment Analysis Charles, Vincent; Kumar, Mukesh; Zegarra, Luis Felipe; Avolio, Beatrice; 1
  • Productivity of Automobile Industries using the Malmquist Index: Evidence from the Last Economic Recession Chen, Yao; 2
  • Data Envelopment Analysis in the Presence of Partial Input-to-Output Impacts Cook, W. D; Imanirad, Raha; 3
  • Avoiding Large Differences in Weights in Cross-Efficiency Evaluations: Application to the Ranking of Basketball Players Cooper, William W; Ramón, Nuria; Ruiz, Jose L; Sirvent, Inmaculada; 4
  • Coalition Formation and Data Envelopment Analysis Färe, Rolf; Grosskopf, Shawna; Margaritis, Dimitri; 5
  • Scale Efficiency Measurement in Data Envelopment Analysis with Interval Data: A Two-Level Programming Approach Kao, Chiang; Lu, Shiang-Tai; 6
  • Applying an Efficiency Measure of Desirable and Undesirable Outputs in DEA to U.S. Electric Utilities Tone, Kaoru; Tsutsui, Miki; 7
  • Natural Resources Exchange Traded Funds: Performance Appraisal using DEA Modeling Tsolas, I. E; 8
  • Airlines Performance via Two-Stage Network DEA Approach Zhu, Joe; 9

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      Natural Resources Exchange Traded Funds: Performance Appraisal using DEA Modeling
      (Pontificia Universidad Católica del Perú. CENTRUM, 2011) Tsolas, I. E.
      The purpose of this paper is to evaluate the performance of a sample of natural resources exchange traded funds (ETFs) by applying a two-stage procedure. In the first stage, the generalized proportional distance function (GPDF) in the data envelopment analysis (DEA) context is used for the first time to measure the relative efficiency of sectoral ETFs. In the second stage, a Tobit model is employed to identify the drivers of performance. The results indicate there is scope for efficiency improvement for about half or more of the sample funds depending on the variables used in the assessments, and fund performance can be explained by fund persistence and the beta coefficient.