Discussion Paper
No. 2017-90 | November 03, 2017
Camilo Almanza, Jhon James Mora Rodríguez and Andrés Cendales
Profit efficiency of banks in Colombia with undesirable output: a directional distance function approach

Abstract

This study investigates the sources of bank efficiency in Colombia over the period 2000–2011. To perform this research, the authors propose a score of bank efficiency using the directional distance function, which was estimated using data envelopment analysis. Additionally, they use an ordered probit panel regression to explore the effects of some market-related and bank-specific factors on efficiency. The authors´ results show that the non-inclusion of non-performing loans (NPLs) leads to higher bank inefficiency indicators, which are significantly different from those obtained when NPLs are included. Further, the authors find that economic growth, capital risk, foreign and national banks, and account liquidity risk explain, in part, the efficiency of Colombian banks.

JEL Classification:

D22, G21

Links

Cite As

[Please cite the corresponding journal article] Camilo Almanza, Jhon James Mora Rodríguez, and Andrés Cendales (2017). Profit efficiency of banks in Colombia with undesirable output: a directional distance function approach. Economics Discussion Papers, No 2017-90, Kiel Institute for the World Economy. http://www.economics-ejournal.org/economics/discussionpapers/2017-90


Comments and Questions



Anonymous - Referee report
April 09, 2018 - 11:11
The paper examines the bank efficiency using a novel method. It is an interesting approach, but improvements in the methodology may be needed in order to obtain more robust results. Major comment:1. I understand the directional measure in Eq.(2), hence the scale efficiency indicator S in Eq.(6), is calculated from the 17 banks. The efficiency of the banks is subsequently determined by the sign of S. However, without properly setting up a test, the conclusion from current calculations is not convincing. This methodology could be improved by defining a test statistic, applying a bootstrap procedure to S, and interpret the banks’ efficiency from the p-values. See, for example, Toma et al (2017, doi: https://doi.org/10.1016/j.ecolind.2017.07.049). Minor comment:1. mu_1 and mu_2 are not defined in the equation of PTE (after Eq.7)2. It may be good to check the robustness of the results.3. In Conclusion section, the authors mention “Tobit regression” which may be wrong.

Camilo Almanza, Jhon James Mora Rodríguez, and Andrés Cendales - Reply to Referee Report 1
April 12, 2018 - 19:24
see attached file
[ Download attached file ]