2000
DOI: 10.1111/1467-629x.00036
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Cost efficiency in Australian non‐bank financial institutions: A non‐parametric approach

Abstract: A two-stage procedure is employed to evaluate non-bank financial institution cost efficiency. In the first stage, data envelopment analysis is used to calculate technical, allocative and cost efficiency indices using a sample of two hundred Australian credit unions. The results indicate that a typical credit union's costs in 1997 were thirty percent above what could be considered efficient on the basis of observed best practice. The major source of overall cost inefficiency would appear to be allocative ineffi… Show more

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Cited by 25 publications
(32 citation statements)
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References 30 publications
(54 reference statements)
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“…Also, it is equally important to examine which ownership type or organisational form produces stronger incentives to control inputs and/or boost outputs. The conventional way to accomplish such analysis is a two-step procedure, whereby a point estimate of X-efficiency is obtained for each firm and then the estimated efficiency scores are regressed against a set of explanatory variables (Worthington, 2000;Rezitis, 2006). Table 7 imply that banks with higher loans-to-asset ratios tend to have higher efficiency scores.…”
Section: The Determinants Of Malaysian Islamic Banks Efficiencymentioning
confidence: 99%
“…Also, it is equally important to examine which ownership type or organisational form produces stronger incentives to control inputs and/or boost outputs. The conventional way to accomplish such analysis is a two-step procedure, whereby a point estimate of X-efficiency is obtained for each firm and then the estimated efficiency scores are regressed against a set of explanatory variables (Worthington, 2000;Rezitis, 2006). Table 7 imply that banks with higher loans-to-asset ratios tend to have higher efficiency scores.…”
Section: The Determinants Of Malaysian Islamic Banks Efficiencymentioning
confidence: 99%
“…However, Sherman and Gold (1985) first applied DEA for measuring the performance of the banking sector (Molyneux et al, 1996;cited in Sathye, 2001, p. 617). Later on, Yue (1992), Favero and Papi (1995), Leightner and Lovell (1998), Gilbert and Wilson (1998), Worthington (2000), Sathye (2001), Sathye (2003), Isik and Hasan (2003), Ali et al (2004), Strum and Williams (2004), Neal (2004), Wu (2005), Ali and Hang (2006), and many others have used DEA for measuring the efficiency of the financial firms. Each sample is considered as a decision making unit (DMU) in DEA and the efficiency score is calculated for each and every DMU within the sample.…”
Section: Methodsmentioning
confidence: 99%
“…It is also regarded as an efficient frontier technique and generally computes "the inefficiency in a particular DMU by comparing it to similar DMUs regarded as efficient, rather than trying to associate a DMU's performance with statistical averages that may not be applicable to that DMU" (Avkiran, 2006, p. 276). It means that DEA compares the performance of a firm with the performance of other firms producing similar good or service and having similar size, instead of focusing on a predetermined benchmark of a performance measurement (Worthington, 2000). The efficiency score generated by DEA varies from 0 to 1.…”
Section: Methodsmentioning
confidence: 99%
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