Bank Ownership and Efficiency in the Aftermath of Financial Crises: Evidence from Indonesia

• DOI: http://doi.org/10.1111/rode.12071
• Date: 01 February 2014
• Author: Yohanes E. Riyanto,Rasyad A. Parinduri
• Published date: 01 February 2014

Bank Ownership and Efficiency in the Aftermath of

Financial Crises: Evidence from Indonesia

Rasyad A. Parinduri and Yohanes E. Riyanto*

Abstract

This paper examines the relationship between types of ownership of banks and their efficiency in the after-

math of a financial crisis using Greene’s “true” panel data stochastic frontier model, which takes into

account unobserved heterogeneity among banks. The Indonesian banking sector is analyzed using financial

data of 144 banks operating in Indonesia over the period of 2000Q4–2005Q2. In the aftermath of the 1997

Asian financial crisis, the cost efficiency of all banks improves over time on average. However, there is

some evidence that, as these banks improve their efficiency, state-owned banks are the least efficient banks

while joint-venture and foreign-owned banks are the most efficient.

1. Introduction

How do banks perform in the aftermath of a financial crisis? Do state-owned and

foreign-owned banks improve their efficiency equally well? What about other types of

banks such as private-domestic banks and joint-venture banks?

The literature shows that the ownership structures of banks matter: foreign-owned

banks are typically the most efficient banks and state-owned banks are the least effi-

cient ones. Bhattacharya et al. (1997), for example, show that foreign-owned banks in

India are more cost efficient than private-domestic banks. Fries and Taci (2005) and

Bonin et al. (2005) also find similar results in post-communist European countries.

Berger et al. (2009) show foreign ownership of local banks in China helps to improve

the banks’ cost efficiency; they also find state-owned banks are the least cost efficient.1

These studies use data envelopment analysis or stochastic frontier analysis (SFA).

Most use the latter because it takes into account random shocks to banks’ costs or

profits and it can handle measurement errors in input prices and outputs. Despite

SFA’s popularity, however, one estimation issue remains: how to take into account

unobserved heterogeneity among banks, which may depend on individual bank’s

characteristics.

Panel SFA, i.e. fixed effects or random effects models, can address this unobserved

heterogeneity if the unobserved characteristics are time-invariant, but the estimations

of panel stochastic frontiers introduce another problem. In panel SFA, bank specific

effects are considered as inefficiency even though this may not always be the case.

These estimators would, therefore, tend to overestimate efficiency variations.

Furthermore, random effects models assume no correlation between bank-specific

* Riyanto: Nanyang Technological University, 14 Nanyang Drive HSS 04-83, Singapore 637332. Tel: +65-

6592-1578; Fax: +65-6795-5797; E-mail: yeriyanto@ntu.edu.sg. Parinduri: Nottingham University Business

School, University of Nottingham, Malaysia Campus, Jalan Broga, 43500, Semenyih, Selangor, Malaysia.

The authors thank Jung Hur, Changhui Kang, Basant Kapur, Shandre M. Thangavelu and Julian Wright

for their helpful comments. They also thank Riza Haryadi, Dian Oktariani and Makin Toha of Bank Indo-

nesia for providing them with the dataset. Research grants from the Nanyang Technological University are

also acknowledged.

Review of Development Economics, 18(1), 93–106, 2014

DOI:10.1111/rode.12071

© 2014 The Authors. Review of Development Economics published by John Wiley & Sons Ltd.

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution

and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.