Abstract-This paper investigates the efficiency of the Indonesian commercial Bankss, compares the efficiency of different groups of ownership, and investigates the productiveness alteration during the period of 1994-2008. We use consistent informations for 70 Bankss, and groups them into four groups based on ownership, i.e. authorities owned, local authorities owned, private owned and joint venture and foreign owned. By using Data Envelopment Analysis ( DEA ) , it reveals that during the covered period, the mean of efficiency for overall sample was 0.866, while the most efficient bank group was authorities owned followed by joint venture and foreign owned, in which the mean of efficiency was 0.953 and 0.943, severally. Furthermore, during the sample period covered, productivity growing increased by 0.5 per centum yearly, supported by technological alteration that grew 1.7 per centum yearly, while at the same period efficiency alteration declined by 1.1 per centum yearly.

Keywords-bank efficiency, productiveness alteration, Data Envelopment Analysis, Malmquist Index, Indonesia

Introduction

Banking system is really of import for the modern economic system. As a fiscal mediator, Bankss gather nest eggs, allocate resources, and supply liquidness and payment services. Sing this critical function, it is really of import to develop a sound banking system in which Bankss operate with good public presentation. To mensurate public presentation of banking sector, two sorts of measuring are widely used, viz. fiscal ratio steps and efficiency steps. Financial ratio steps have been common to measure profitableness every bit good as liquidness and solubility ratios. In the banking industry, CAMELS has been good known as a step of fiscal public presentation. The utilizing of efficiency steps has become more popular sing that the ability of fiscal ratios steps to capture a comprehensive image of public presentation is limited and such steps do non adequately concentrate on the long-term public presentation facets.

This paper attempts to: ( I ) investigate efficiency of the Indonesian commercial Bankss during 1994-2008 by utilizing Data Envelopment Analysis ( DEA ) ; ( two ) compare the efficiency of different ownership groups and investigates the important differences by utilizing Analysis of Variance ( ANOVA ) ; ( three ) look into the productiveness alteration during that period by using Malmquist index.

OVERVIEW OF THE INDONESIAN BANKING SECTOR

The fiscal liberalisation at its initial stage, in early 1980s, was a portion of broader structural accommodation policies imposed by the Indonesian governments to response the worsening monetary value of oil and worldwide recession raising troubles in balance of payment and financial place. The governments introduced the first fiscal reform bundle in June 1983. The reforms enacted in this bundle included get rid ofing Bank Indonesia ‘s control over involvement rates on sedimentations and loans, extinguishing recognition ceilings for state-owned Bankss, and phasing out the pattern of funding state-owned Bankss by agencies of authorities liquidness credits.

The large knock of fiscal reforms was launched on October 27, 1988. The reforms included: get rid ofing entry barriers that allow the set up of new Bankss, get rid ofing limitation on opening up new subdivisions, leting state-owned companies to lodge up to 50 per centum of their financess in private Bankss, cut downing modesty demands to bring on liquidness, presenting legal loaning bounds demand, leting Bankss to publish portions, and taking revenue enhancement freedom on involvement to equalise the intervention between involvement payment and dividends.

Following that, the Indonesian governments had continuously introduced farther reforms in protective and preventative models. During 1989-1990, the governments introduced a new ordinance on legal loaning bound, enforcing limitation on net unfastened place to restrict foreign adoption, and launched a step to restrict recognition plans provided by the cardinal bank. Many of the old reforms became statute under the new banking jurisprudence stipulated in March 1992. This jurisprudence significantly changed the position of the province Bankss by doing them limited liability companies, provided for foreign ownership of Indonesian Bankss, and introduced prudential steps such as bounds to concentrated loans and loans to associated involvements while beef uping the supervisory powers of the banking governments by giving them power to publish directives and to shut and neutralize unsound Bankss [ 1 ] . Finally, in 1993-1996, it phased in more prudential ordinances and supervisory tools for guaranting bank soundness-from coverage demands, to self-regulation, to capital adequateness, plus quality, direction, net incomes, and liquidness ( CAMEL ) bank evaluations. By end-1996, prudential patterns in Indonesia ‘s banking sector were mostly in line with those recommended by the Basel Committee and comparable to those adopted in the US and EU [ 2 ] .

As expected, fiscal liberalisation had improved the Indonesian fiscal system. There is no uncertainty that after the deregulating, the quality and handiness of banking services has increased markedly. Although operating environment of bank sector had improved, Indonesia was hit by terrible fiscal crisis in 1997. The currency crisis hit the Indonesian economic system had so evolved into a matured banking crisis. Mention to [ 3 ] , the state of affairs of banking sector diminution can be attributed as banking crisis if meets at least one of these four conditions: ( I ) ratio of non-performing assets exceeds 10 per centum ; ( two ) the cost of delivering more than 2 per centum of GDP ; ( three ) banking jobs doing nationalisation of Bankss ; and ( four ) bank tallies or sedimentation freezings or enforcing across-the-board warrant. Confirmed to this definition, the Indonesian banking sector truly in the crisis, manifested in these indexs: ( I ) ratio of non-performing assets to entire assets was estimated at 60-85 per centum of all loans [ 4 ] ; ( two ) estimated cost of delivering was Rp 643 trillion ( about US $ 89 billion ) , or 60 per centum of GDP [ 5 ] ; ( three ) some Bankss were nationalized ; and ( four ) bank tally happened on some Bankss even after enforcing cover warrant.

In response to the banking crisis, under the way of the IMF, the governments took some major intercessions, among others were: ( I ) the closing of 16 little Bankss in November 1997 ; ( two ) intercession into 54 Bankss in February 1998: ( three ) the take-over of 7 Bankss and closing of another 7 in April 1998 ; ( four ) the closing of four Bankss antecedently taken over in April 1998 ; ( V ) the closing of 38 Bankss together with a return -over of 7 Bankss and joint recapitalization of 7 Bankss in March 1999 ; and ( six ) a recapitalization of six state-owned Bankss and 12 regional Bankss during 1999-2000 [ 6 ] . Later, after restructuring was completed, the antecedently taken-over Bankss were re-privatized. The denationalization policy is expected to profit the domestic banking industry by advancing administration, transportation of engineering, and enhance hazard direction competences. Besides those intercession policies, the governments besides introduced significant fiscal reforms in banking sector. As cited in the first Letter of Intent to the IMF, fiscal reform included “ the institutional, legal, and regulative model for banking operation to guarantee the outgrowth of a sound and efficient fiscal system ” . In this respects, the governments launched prudential supervising, fiscal coverage, and relevant commercial Torahs, every bit good as implementing sedimentation insurance strategy. In order to better the effectivity of banking supervising, the new Central Bank Act ( Act figure 23 of 1999 ) gave independent position to the Bank Indonesia, which is free from the intercession of the authorities.

Further steps were introduced to go on bank consolidation. They included raising capital demands to monetary value little private Bankss out of the market, every bit good as presenting the “ individual presence policy ” and cut downing the depositor warrant degree that lead to a natural consolidation in the fiscal services industry in Indonesia [ 7 ] . A clear consequence of such consolidation was uninterrupted diminution of bank figure, from a pre-crisis figure of 239 to 142 in 2002 and 126 in 2008.

Methodology

Data Envelopment Analysis ( DEA )

In measuring bank efficiency, we can utilize either parametric or non-parametric methodological analysiss. The difference between these two attacks lies on how they handle random mistake and their premise sing the form of the efficient frontier [ 8 ] . Each of the techniques has its ain strengths and failings. As in [ 9 ] , the advantage of parametric attack is leting noise in the measuring of inefficiency, while the advantage of non-parametric is simple and easy to cipher since it does non necessitate specification of functional signifier. Common parametric attacks are the Stochastic Frontier Approach ( SFA ) , the Thick Frontier Approach ( TFA ) and the Distribution Free Approach ( DFA ) , while the common non-parametric techniques are the Data Development Analysis ( DEA ) and the Free Disposal Hull Analysis ( FDH ) .

DEA has become popular under non-parametric attacks, chiefly attributable to its flexibleness in application, and ability to cover with multiple inputs and end products. DEA can be used to measure the efficiency of a house by comparing it with a ‘best pattern ‘ or end product efficient house. An end product efficient house is one that can non increase its end product unless it besides increases one or more of its input, whereas an end product inefficient house is one that can increase its end product without increasing its inputs. An end product efficient house would hold a mark of 100 % as being located on the end product efficient frontier whereas an end product inefficient house would be inside the frontier and hold a mark of less than 100 % . Similarly an input efficient house is one that can non cut down its inputs without cut downing its end product whereas an input inefficient house can. However, the tonss can merely be used for comparings within the sample. DEA allows the research worker to choose multiple end products and inputs in complex production environments based on managerial concerns [ 10 ] . Furthermore, DEA does non necessitate stipulating either the functional signifier of the theoretical account being tested or the weights to be used for consolidating multiple inputs and/or end products [ 11 ] . As such, DEA efficiency estimations are extremely sensitive to informations mistakes and outliers, therefore attention has to be taken in using and construing DEA consequences.

Malmquist Productivity Index

Using the DEA, there are three options for mensurating the productiveness alterations, which are Fisher index, Tornqvist index and the Malmquist Index. The Malmquist index has three chief advantages relative to the Fischer and Tornqvist Indices [ 12 ] : ( I ) it does non necessitate the net income maximization or the cost minimisation premise ; ( two ) it does non necessitate information on the input and end product monetary values ; ( three ) if the research worker has panel informations, it allows the decomposition of productiveness alterations into two constituents ( proficient efficiency alteration or catching up and proficient alteration or alterations in the best pattern ) . Its chief disadvantage is the necessity to calculate the distance maps. However, the informations enclosure analysis ( DEA ) technique can be used to work out this job.

The Malmquist index steps entire factor productiveness ( TFP ) change between two informations points by ciphering the ratio of the distances of each informations point relative to a common engineering and it requires the inputs and end products from one clip period to be assorted with the engineering of another clip period. Following [ 13 ] , this paper adopts the output-oriented Malmquist productiveness alteration index, mentioning the accent on the equi-proportionate addition of end products, within the context of a given degree of input. The output-oriented Malmquist productiveness alteration index can be expressed as follows:

( 1 )

Where:

Mj = Malmquist productiveness index

Dj = Distance map

ten and y = represent inputs and end products, severally, across clip period T to t+1.

Equation above nowadayss the constituent of the Malmquist Index. The ratio outside the brackets is equal to the alteration of proficient efficiency ( EFFCH ) between clip T and t+1, stand foring the alteration in the comparative distance of the ascertained production from the maximal possible production ; while the constituent inside the brackets is the geometric mean of the two productiveness indexes, stand foring the displacement in production engineerings ( proficient alteration, TECHCH ) between clip T and t+1. The merchandise of the two constituents ( EFFCH and TECHCH ) is the Malmquist productiveness alteration ( entire factor productiveness alteration, TFPCH ) . In add-on, proficient efficiency alteration ( EFFCH ) can be farther decomposed into pure proficient efficiency alteration ( PECH ) and scale efficiency alteration ( SECH ) .

Variables and Datas

One of the critical facets in using DEA is to make up one’s mind input and end product variables. The literature provides two chief attacks in placing inputs and end products viz. production attack and intermediation attack [ 14 ] . The production attack defines the bank activity as production of services and views the Bankss as utilizing physical inputs such as labour and capital to supply sedimentations and loans histories. In other manus, intermediation attack positions Bankss as the go-between of fiscal services and assumes that Bankss collect sedimentations, utilizing labour and capital, so intermediate those beginnings of financess into loans and other gaining assets. Intermediation attack is more suited and most widely used in the banking literature [ 8 ] . In line with this, this paper uses intermediation attack for designation of inputs and end products.

This paper specifies three inputs and three end products. The inputs are entire sedimentations, involvement disbursals, and other operating disbursals ; while the end products are entire loans, involvement income, and other runing grosss. We use consistent informations for 70 Bankss from 1994 to 2008. It consists of 3 authorities owned, 24 local authorities owned, 34 private owned, and 9 joint venture and foreign owned. Data is obtained from Indonesian Banking Directory, assorted editions, published by the Indonesian cardinal bank, Bank Indonesia ; and Indonesian Banking Indicators & A ; Financial Performance Rating, CD Rom, assorted editions, published by Ekofin Konsulindo.

Table 1 shows the descriptive statistics of DEA inputs and end products used in this survey, including mean, standard divergence, lower limit and upper limit. Table 1 illustrates the disparity of the operations of assorted commercial Bankss during 1994 and 2008 clip period. While some Bankss were big there were really little Bankss every bit good. This disparity of the graduated table of operation may play an of import function in the finding of the public presentation. However, this survey does non explicitly account for the scale consequence on public presentation.

To give illustration on the representativeness of the sample, Fig. 1 provides comparing between sample assets with entire assets of the banking sector. Although the per centum of sample assets to entire assets significantly declined after 1998, it kept more than 60 % .

Table 1. DESCRIPTIVE STATISTICS OF MAIN VARIABLES

Variable

Mean

Std. Deviation

Minute

Soap

Loans

4,689,335

12,540,479

8,084

161,061,059

Interest income

1,065,099

2,761,625

1,384

28,076,399

Other runing

149,905

417,207

13

6,066,730

grosss

A

A

A

A

Deposits

3,500,219

8,640,759

1,148

73,519,757

Interest disbursals

650,143

1,956,426

563

31,005,886

Other runing

476,628

1,968,324

349

40,555,255

disbursals

A

A

A

A

N=1050

A

A

A

A

FIGURE 1. RATIO OF SAMPLE ASSETS TO TOTAL ASSETS

RESULTS AND DISCUSSION

Fig. 2 shows mean variable return to graduated table ( VRS ) proficient efficiency from 1994 to 2008, reflecting the development of efficiency of the Indonesian commercial Bankss. Before the crisis, the efficiency was systematically increased from 0.883 in 1994 to 0.939 in 1997. During the crisis, it slumped from 0.939 in 1997 to 0.854 in 1998 and 0.812 in 1999. After important betterment from 0.812 in 1999 to 0.876 in 2000, the efficiency was fluctuated with declined figure during mini fiscal crisis ( 2004-2005 ) and planetary fiscal crisis ( 2007-2008 ) .

As mentioned before, efficient house will hold mark of 100 % or 1.00. Fig. 3 identifies the per centum of efficient Bankss during the covered period. We can detect that the kineticss of the per centum of efficient Bankss was parallel with the kineticss of efficiency. Before the crisis, the per centum was steadily increased from 34 % in 1994 to 40 % in 1997. During the crisis it slumped from 40 % in 1997 to 37 % in 1998 and 1999. The highest per centum during the after crisis period was 44 % in 2003, and the lowest was 36 % in 2004 and 2007. In footings of ownership, the highest per centum of efficient Bankss belonged to authorities owned, followed by joint venture and foreign owned, local authorities owned, and private owned.

This sequence was consistent with the mean of efficiency generated from one-way ANOVA as shown in Table 2. During the covered period, authorities owned Bankss outperform all other groups of Bankss. Following authorities owned are joint venture and foreign owned, local authorities owned, and private owned.

This determination is really interesting as it is different with many old surveies that came up with the decision of lower status of authorities owned. However, this determination is non sole, sing some other surveies found the same consequence. For illustration, survey of [ 15 ] found that during the period of 2001-2003, authorities owned was the most efficient Bankss in Indonesia. Another survey [ 16 ] analysing the degree of efficiency of commercial Bankss in Indonesia during 2007 besides found that the most efficient bank group was authorities owned. The high quality of authorities Bankss can be seen as a consequence of banking reforms in which they could run expeditiously based on the market mechanism with good administration, off from the authorities intercession.

Furthermore, Table 2 besides shows that the difference of mark between authorities owned and joint venture and foreign owned is really little, intending that high quality of foreign ownership was still evidenced in this survey. As literature tells us, foreign ownership everyplace in developing states tends to be superior given the fact that they make the least attempt to widen the subdivision web beyond the metropolitan countries, they are entitled with better engineerings, and they deal with healthy clients every bit good as transnational companies [ 17 ] .

With respect to productiveness alteration, Table 3 reveals that during the covered period, productiveness growing increased by 0.5 per centum yearly. We can observe, nevertheless, that the productiveness growing was declined when the economic system was in the terrible fiscal crisis ( 1997/1998-1998/1999 ) and mini fiscal crisis ( 2004/2005 ) . The diminution for those three old ages was 7.3 % , 7.2 % , and 12.3 % , severally. The diminution of productiveness growing during the crisis is consistent with the findings of old surveies, e.g. [ 6 ] and [ 18 ] . In another manus, the addition of productiveness growing after the banking sector restructuring confirms the positive consequence of the policies implemented by the governments. This determination can enrich the position on the debate-both theoretical and empirical-about the consequence of bank restructuring on the bank public presentation. In the instance of Indonesia, some old empirical surveies show assorted findings, e.g. [ 19 ] found positive consequence, while [ 20 ] found negative consequence.

From Table 3 we besides note that the productiveness growing during the covered period was supported by technological alteration that grew 1.7 per centum yearly ; while at the same period efficiency alteration declined by 1.1 per centum yearly.

Decision

The survey finds that the most efficient bank group during the covered period was authorities owned, followed by joint venture and foreign owned ; while local authorities owned and private owned were in the least efficient topographic points. As such, we can reason that the authorities ownership is justified every bit long as it is operated with good administration by avoiding authorities intercession, such as directing loaning to prefer parties or politically affiliated parties. Furthermore, the publicity of foreign ownership is of import to better the operational conditions of the Indonesian banking sector.

Another determination of the survey is that the productiveness alteration of the Indonesian commercial Bankss during the covered period was due to technological alteration alternatively of proficient efficiency alteration. It implies the importance of developing engineering and invention in accomplishing productiveness of banking sector.

FIGURE 2. MEAN VRS TECHNICAL EFFICIENCY

FIGURE 3. Percentage OF EFFICIENT BANKS BY GROUP

Table 2. Consequence OF ANOVA

Bank group

Nitrogen

Mean

Std. Deviation

Gov

45

0.953

0.1077

Local gov

360

0.915

0.1066

Private

510

0.803

0.1706

Foreign & A ; JV

135

0.943

0.1032

Entire

1050

0.866

0.1538

Table 3. MALMQUIST INDEX SUMMARY OF ANNUAL MEANS

Year

Effch

Techch

Pech

Sech

Tfpch

1994/95

0.983

0.973

0.982

1.000

0.956

1995/96

1.043

1.005

1.020

1.023

1.048

1996/97

1.033

0.975

1.068

0.967

1.007

1997/98

0.778

1.191

0.895

0.870

0.927

1998/99

0.994

0.928

0.939

1.059

0.923

1999/00

1.204

0.852

1.097

1.098

1.026

2000/01

0.982

1.131

0.997

0.985

1.111

2001/02

0.983

1.030

0.989

0.994

1.012

2002/03

1.010

0.993

1.028

0.983

1.003

2003/04

0.924

1.149

0.955

0.968

1.062

2004/05

0.998

0.878

0.992

1.006

0.877

2005/06

1.045

0.992

1.020

1.024

1.037

2006/07

0.953

1.125

0.976

0.977

1.072

2007/08

0.964

1.077

0.989

0.976

1.039

Mean

0.989

1.017

0.995

0.994

1.005