Productivity Changes and Risk Management in Indonesian Banking: An Application of a New Approach to Constructing Malmquist Indices

In this study, we utilise a new, non-parametric efficiency measurement approach which combines the semi-oriented radial measure data envelopment analysis (SORM-SBM-DEA) approach for dealing with negative data (Emrouznejad et al., 2010) with the slacks-based efficiency measures of Tone (2001, 2002) to analyse productivity changes for Indonesian banks over the period Quarter I 2003 to Quarter II 2007. Having constructed the Malmquist indices, using data provided by Bank Indonesia (the Indonesian central bank), for the banking industry and different bank types (i.e., listed and Islamic) and groupings, we then decomposed the industry’s Malmquist into its technical efficiency change and frontier shift components. Finally, we analysed the banks’ risk management performance, using Simar and Wilson’s (2007) truncated regression approach, before assessing its impact on productivity growth. The first part of the Malmquist analysis showed that average productivity changes for the Indonesian banking industry tended to be driven, over the sample period, by technological progress rather than by frontier shift, although a relatively stable pattern was exhibited for most of the period. However, at the beginning of the considered period, state-owned and foreign banks, as well as Islamic banks, exhibited volatile productivity movements, mainly caused by shifts in the technological frontier. With respect to the risk management analysis, most of the balance sheet variables were shown to have had the expected impact on risk management efficiency. While the risk management decomposition of technical efficiency change and frontier risk components demonstrated that, by the end of the sample period, the change in risk management efficiency and risk management effects had the same dynamic pattern, resulting in the analogous dynamics for technical efficiency changes. Therefore, a strategy based on the gradual adoption of newer technology, with a particular focus on internal risk management enhancement, seems to offer the highest potential for boosting the productivity of the financial intermediary operations of Indonesian banks.Indonesian Finance and Banking; Productivity; Efficiency.

A New Approach to Dealing With Negative Numbers in Efficiency Analysis: An Application to the Indonesian Banking Sector

In one of the first stand-alone studies covering the whole of the Indonesian banking industry, and utilising a unique dataset provided by the Indonesian central bank, this paper analyses the levels of intermediation-based efficiency obtaining during the period 2003-2007. Using a new approach (i.e., semi-oriented radial measure Data Envelopment Analysis, or ‘SORM DEA’) to handling negative numbers (Emrouznejad et al., 2010) and combining it with Tone’s (2001) slacks-based model (SBM) to form an input-oriented, non-parametric SORM SBM model, we firstly estimate the relative average efficiencies of Indonesian banks, both overall, by group, as determined by their ownership structure, and by status (‘listed’/’Islamic’). For robustness, a range-directional (RD) model suggested by Silva Portela et al. (2004) was also employed to handle the negative numbers. In the second part of the analysis, we adopt Simar and Wilson’s (2007) bootstrapping methodology to formally test for the impact of size, ownership structure and status on Indonesian bank efficiency. In addition, we formally test the two models most widely suggested in the literature for controlling for bank risk – namely, those involving the inclusion of provisions for loan losses and equity capital respectively as inputs – to check the robustness of the results to the choice of risk variable. The results demonstrate a high degree of sensitivity of the average bank efficiency scores to the choice of methodology for handling negative numbers – with the RD model consistently delivering efficiency scores some 14% on average above those from the SORM SBM model – and to the choice of risk control variable under the RD model, but only a limited sensitivity to the choice of risk control variable under the SORM SBM model. With respect to group rankings, most model combinations find the ‘state-owned’ group to be the most efficient, with average overall efficiency levels ranging between 64% and 97%; while all model combinations find the ‘regional government-owned’ group to be the least efficient, with average overall efficiency levels ranging between 41% and 64%. As for the impact of bank ‘status’ on the efficiency scores, both the Islamic banks and the listed banks perform better than the industry average in the majority of model combinations. Finally, the results for the impact of scale on the efficiency scores are ambiguous. Under the RD model, and irrespective of the choice of risk control variable, size is very important in determining intermediation-based efficiency. Under the SORM SBM model, however, large banks’ performance is not significantly different from that of the medium-sized banks when equity capital is used as the risk control variable, although the medium-sized banks do out-perform small banks. Moreover, when loan loss provisions are used as the risk control variable, medium-sized banks are shown to significantly out-perform both large and small banks, with the large banks being the least efficient.Indonesian Finance and Banking; Efficiency.

Efficiency in Indonesian Banking: Recent Evidence

In one of the first stand-alone studies covering the whole of the Indonesian banking industry, and utilising a unique dataset provided by the Indonesian central bank, this paper analyses the levels of intermediation-based efficiency obtaining during 2007. Using Tone’s (2001) input-oriented, non-parametric, slacks-based DEA model, and modifying it where necessary to deal with negative inputs and outputs (Sharp et al. 2006), we firstly estimate the relative average efficiencies of Indonesian banks, both overall, and by group, as determined by their total asset size and status. In the second part of the analysis, we adopt Simar and Wilson’s (2007) bootstrapping methodology to eliminate the ‘bias’ in the efficiency estimates and to formally test for the impact of size and status on Indonesian bank efficiency. The results from the initial analysis show that: (i) average bank efficiency within the industry during 2007 lay between 62% – 67%; (ii) the most efficient group of banks was the ‘state-owned’ group with an average efficiency score of over 90%, with the least efficient group being the ‘regional government-owned’ banks with average efficiency scores between 45% and 58%; (iii) ‘listed banks’ performed better, on average, than ‘non-listed banks’; and (iv) ‘Islamic banks’, despite their different operational structure when compared with conventional banks, enjoyed average efficiency scores between 54% and 74%. In the second stage of the analysis, the bias-corrected efficiency scores demonstrate that ‘regional government-owned’, ‘foreign exchange’, ‘non-foreign exchange’, ‘joint-venture’ and ‘foreign’ groupings were significantly less efficient than ‘state-owned’ banks, with the first-mentioned being the most inefficient and the other groupings ranked in ascending order of efficiency, as listed. Moreover, large banks were shown to be more efficient than their smaller counterparts, providing support for Bank Indonesia’s consolidation policies.Indonesian Finance and Banking; Efficiency.

Efficiency and Malmquist Indices of Productivity Change in Indonesian Banking

In this study we utilise a non-parametric, slacks-based model (SBM) approach to analyse efficiency and productivity changes for Indonesian banks over the period January 2006 to July 2007. Efficiency scores and Malmquist productivity indices are estimated using the approach for efficiency and super-efficiency estimation suggested by Tone (2001, 2002). Additionally, the Malmquist indices are decomposed into technical efficiency change and technological shift components. Using monthly supervisory data provided by Bank Indonesia we find that, under the intermediation approach to efficiency estimation, average bank efficiency was reasonably stable during the sample period, ranging between 70% and 82%, with 92 of the 130 banks in existence at that time having efficiency scores of over 70%, including 10 with (super)efficiency scores above unity. We also find that technical efficiencies under the Intermediation approach to describing the banking production process are relatively stable. Malmquist results for the industry suggest that the main driver of productivity growth is technological progress. A strategy based on the gradual adoption of newer technology, according to our results, thus seems to have the highest potential for boosting the productivity of the financial intermediary operations of Indonesian banks.Indonesian Finance and Banking; Productivity; Efficiency.

Banking Efficiency and Stock Market Performance: An Analysis of Listed Indonesian Banks

This paper examines the monthly efficiency and productivity of listed Indonesian banks and their market performance through the prism of two modelling techniques, efficiency and super-efficiency, over the period January 2006 to July 2007. Within this research strategy we employ Tone’s (2001) non-parametric, Slacks-Based Model (SBM) and Tone’s (2002) super-efficiency SBM combining them with recent bootstrapping techniques, namely the non-parametric truncated regression analysis suggested by Simar and Wilson (2007). In the case of the SBM efficiency scores, the Simar and Wilson methodology was adapted to two truncations, whereas in the super-efficiency framework the original technique was utilised. As suggested by neo-classical theory, we find that the stock market values banks in accordance with their performance. Moreover, it is found that the JCI index of the Indonesian Stock Exchange is positively related to bank efficiency. Another interesting finding is that the coefficient for the share of foreign ownership is negative and statistically significant in the super-efficiency modelling. This suggests that Indonesian banks with foreign ownership tend to be less efficient than their domestic counterparts. Finally, Malmquist productivity results suggest that, over the study’s horizon, the sample banks displayed volatile productivity patterns in their profit-generating operations.Indonesian Banking, Emerging Markets, Productivity, Efficiency.

Productivity changes in Indonesian banking: application of a new approach to estimating Malmquist indices

In this study, we utilise a new, non-parametric efficiency measurement approach which combines the semi-oriented radial measure data envelopment analysis (SORM DEA) approach for dealing with negative data (Emrouznejad et al., 2010) with the slacks-based efficiency measure of Tone (2001, 2002), to analyse efficiency and productivity changes for Indonesian banks over the period Quarter I 2003 to Quarter IV 2007. Using quarterly data based on supervisory data provided by Bank Indonesia we find that, under the intermediation-based approach to efficiency estimation, average Indonesian bank efficiency somewhat declined during the sample period, from 73% to 63%, reaching a nadir of 53% at end-June 2007. With respect to the bank groupings, Indonesian ‘state-owned’ banks were the most efficient at the beginning of the sample period (with average efficiency of 92%) but, by the end of the sample period, they had been usurped by the ‘joint-venture’ and ‘non-foreign exchange private’ banks. The regional government-owned banks were found to be the least efficient throughout. Finally, Malmquist results for the Indonesian banking industry suggest that the main driver of productivity growth is technological progress. A strategy based on the gradual adoption of newer technology, according to our results, thus seems to have the highest potential for boosting the productivity of the financial intermediary operations of Indonesian banks

A new approach to dealing with negative numbers in efficiency analysis: an application to the Indonesian banking sector

In one of the first stand-alone studies covering the whole of the Indonesian banking industry, and utilising a unique dataset provided by the Indonesian central bank, this paper analyses the levels of intermediation-based efficiency obtaining during the period 2003-2007. Using a new approach (i.e., semi-oriented radial measure Data Envelopment Analysis, or ‘SORM DEA’) to handling negative numbers (Emrouznejad et al., 2010) and combining it with Tone’s (2001) slacks-based model (SBM) to form an input-oriented, non-parametric SORM SBM model, we firstly estimate the relative average efficiencies of Indonesian banks, both overall, by group, as determined by their ownership structure, and by status (‘listed’/’Islamic’). For robustness, a range-directional (RD) model suggested by Silva Portela et al. (2004) was also employed to handle the negative numbers. In the second part of the analysis, we adopt Simar and Wilson’s (2007) bootstrapping methodology to formally test for the impact of size, ownership structure and status on Indonesian bank efficiency. In addition, we formally test the two models most widely suggested in the literature for controlling for bank risk – namely, those involving the inclusion of provisions for loan losses and equity capital respectively as inputs – to check the robustness of the results to the choice of risk variable. The results demonstrate a high degree of sensitivity of the average bank efficiency scores to the choice of methodology for handling negative numbers – with the RD model consistently delivering efficiency scores some 14% on average above those from the SORM SBM model – and to the choice of risk control variable under the RD model, but only a limited sensitivity to the choice of risk control variable under the SORM SBM model. With respect to group rankings, most model combinations find the ‘state-owned’ group to be the most efficient, with average overall efficiency levels ranging between 64% and 97%; while all model combinations find the ‘regional government-owned’ group to be the least efficient, with average overall efficiency levels ranging between 41% and 64%. As for the impact of bank ‘status’ on the efficiency scores, both the Islamic banks and the listed banks perform better than the industry average in the majority of model combinations. Finally, the results for the impact of scale on the efficiency scores are ambiguous. Under the RD model, and irrespective of the choice of risk control variable, size is very important in determining intermediation-based efficiency. Under the SORM SBM model, however, large banks’ performance is not significantly different from that of the medium-sized banks when equity capital is used as the risk control variable, although the medium-sized banks do out-perform small banks. Moreover, when loan loss provisions are used as the risk control variable, medium-sized banks are shown to significantly out-perform both large and small banks, with the large banks being the least efficient

Productivity changes and risk management in Indonesian banking: an application of a new approach to constructing Malmquist indices

In this study, we utilise a new, non-parametric efficiency measurement approach which combines the semi-oriented radial measure data envelopment analysis (SORM-SBM-DEA) approach for dealing with negative data (Emrouznejad et al., 2010) with the slacks-based efficiency measures of Tone (2001, 2002) to analyse productivity changes for Indonesian banks over the period Quarter I 2003 to Quarter II 2007. Having constructed the Malmquist indices, using data provided by Bank Indonesia (the Indonesian central bank), for the banking industry and different bank types (i.e., listed and Islamic) and groupings, we then decomposed the industry’s Malmquist into its technical efficiency change and frontier shift components. Finally, we analysed the banks’ risk management performance, using Simar and Wilson’s (2007) truncated regression approach, before assessing its impact on productivity growth. The first part of the Malmquist analysis showed that average productivity changes for the Indonesian banking industry tended to be driven, over the sample period, by technological progress rather than by frontier shift, although a relatively stable pattern was exhibited for most of the period. However, at the beginning of the considered period, state-owned and foreign banks, as well as Islamic banks, exhibited volatile productivity movements, mainly caused by shifts in the technological frontier. With respect to the risk management analysis, most of the balance sheet variables were shown to have had the expected impact on risk management efficiency. While the risk management decomposition of technical efficiency change and frontier risk components demonstrated that, by the end of the sample period, the change in risk management efficiency and risk management effects had the same dynamic pattern, resulting in the analogous dynamics for technical efficiency changes. Therefore, a strategy based on the gradual adoption of newer technology, with a particular focus on internal risk management enhancement, seems to offer the highest potential for boosting the productivity of the financial intermediary operations of Indonesian banks

Efficiency in Indonesian banking: Recent evidence

In one of the first stand-alone studies covering the whole of the Indonesian banking industry, and utilising a unique dataset provided by the Indonesian central bank, this paper analyses the levels of intermediation-based efficiency obtaining during 2007. Using Tone’s (2001) input-oriented, non-parametric, slacks-based DEA model, and modifying it where necessary to deal with negative inputs and outputs (Sharp et al. 2006), we firstly estimate the relative average efficiencies of Indonesian banks, both overall, and by group, as determined by their total asset size and status. In the second part of the analysis, we adopt Simar and Wilson’s (2007) bootstrapping methodology to eliminate the ‘bias’ in the efficiency estimates and to formally test for the impact of size and status on Indonesian bank efficiency. The results from the initial analysis show that: (i) average bank efficiency within the industry during 2007 lay between 62% – 67%; (ii) the most efficient group of banks was the ‘state-owned’ group with an average efficiency score of over 90%, with the least efficient group being the ‘regional government-owned’ banks with average efficiency scores between 45% and 58%; (iii) ‘listed banks’ performed better, on average, than ‘non-listed banks’; and (iv) ‘Islamic banks’, despite their different operational structure when compared with conventional banks, enjoyed average efficiency scores between 54% and 74%. In the second stage of the analysis, the bias-corrected efficiency scores demonstrate that ‘regional government-owned’, ‘foreign exchange’, ‘non-foreign exchange’, ‘joint-venture’ and ‘foreign’ groupings were significantly less efficient than ‘state-owned’ banks, with the first-mentioned being the most inefficient and the other groupings ranked in ascending order of efficiency, as listed. Moreover, large banks were shown to be more efficient than their smaller counterparts, providing support for Bank Indonesia’s consolidation policies

Efficiency and Malmquist indices of productivity change in Indonesian banking

In this study we utilise a non-parametric, slacks-based model (SBM) approach to analyse efficiency and productivity changes for Indonesian banks over the period January 2006 to July 2007. Efficiency scores and Malmquist productivity indices are estimated using the approach for efficiency and super-efficiency estimation suggested by Tone (2001, 2002). Additionally, the Malmquist indices are decomposed into technical efficiency change and technological shift components. Using monthly supervisory data provided by Bank Indonesia we find that, under the intermediation approach to efficiency estimation, average bank efficiency was reasonably stable during the sample period, ranging between 70% and 82%, with 92 of the 130 banks in existence at that time having efficiency scores of over 70%, including 10 with (super)efficiency scores above unity. We also find that technical efficiencies under the Intermediation approach to describing the banking production process are relatively stable. Malmquist results for the industry suggest that the main driver of productivity growth is technological progress. A strategy based on the gradual adoption of newer technology, according to our results, thus seems to have the highest potential for boosting the productivity of the financial intermediary operations of Indonesian banks