Purging data before productivity analysis

被引:16
作者
Avkiran, Necmi K. [1 ]
Thoraneenitiyan, Nakhun [2 ]
机构
[1] Univ Queensland, Sch Business, Ipswich, Qld 4305, Australia
[2] Sripatum Univ, Fac Business Adm, Bangkok 10900, Thailand
关键词
Productivity; Purging data; Measurement error; Environment; DATA ENVELOPMENT ANALYSIS; SLACKS-BASED MEASURE; COMMERCIAL-BANKS; FINANCIAL INSTITUTIONS; PROFIT EFFICIENCY; COST EFFICIENCY; PERFORMANCE; DEA; DEREGULATION; INDUSTRY;
D O I
10.1016/j.jbusres.2009.03.014
中图分类号
F [经济];
学科分类号
02 ;
摘要
Studies of productivity often ignore measurement error and fail to distinguish between exogenous and endogenous factors in adjusting for the environment. This failure may misguide managerial decisions on bench marking, ranking, and remuneration. I-or example, common relative efficiency techniques Such as data envelopment analysis (DEA) assume away the measurement error. This article combines DEA with stochastic frontier analysis in a synergistic multiple-stage analysis to purge the estimate of managerial performance of measurement error and exogenous factors. Removing the impact of measurement error indicates the largest rise in productivity, Removing the impact of exogenous factors raises discriminatory power. The method offers a number of innovations over other studies in the literature. The article is also the first to investigate the profit efficiency of the commercial banks in the United Arab Emirates. (C) 2009 Elsevier Inc. All rights reserved
引用
收藏
页码:294 / 302
页数:9
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