Sensitivity analysis of network DEA illustrated in branch banking

Users of data envelopment analysis (DEA) often presume efficiency estimates to be robust. While traditional DEA has been exposed to various sensitivity studies, network DEA (NDEA) has so far escaped similar scrutiny. Thus, there is a need to investigate the sensitivity of NDEA, further compounded by the recent attention it has been receiving in literature. NDEA captures the underlying performance information found in a firm?s interacting divisions or sub-processes that would otherwise remain unknown. Furthermore, network efficiency estimates that account for divisional interactions are more representative of a dynamic business. Following various data perturbations overall findings indicate positive and significant rank correlations when new results are compared against baseline results - suggesting resilience. Key findings show that, (a) as in traditional DEA, greater sample size brings greater discrimination, (b) removing a relevant input improves discrimination, (c) introducing an extraneous input leads to a moderate loss of discrimination, (d) simultaneously adjusting data in opposite directions for inefficient versus efficient branches shows a mostly stable NDEA, (e) swapping divisional weights produces a substantial drop in discrimination, (f) stacking perturbations has the greatest impact on efficiency estimates with substantial loss of discrimination, and (g) layering suggests that the core inefficient cohort is resilient against omission of benchmark branches. Various managerial implications that follow from empirical findings are discussed in conclusions.

Empirical Assessment of Manufacturing Companies Efficiency in Nigeria:Data Envelopment Analysis (DEA) Approach

This study dwells on data envelopment analysis and industry analysis. The study analyzed the technical efficiency of twenty (20) selected manufacturing companies for the period 2015 to 2016 using input and output oriented data envelopment analysis (DEA) approach. Findings arising from the study indicate that 35% of the quoted sampled manufacturing firms in Nigeria were scale efficient while 65% were scale inefficient in the period observed. Thirty percent (30%) of the manufacturing companies on the basis of constant return to scale (CRS) were technically efficient while 70% of them were technically inefficient in the period observed. Forty percent (40%) of the companies in terms of variable return to scale (VRS) were technically efficient while 60% were not technically efficient in the context of variable return to scale. The study concluded that manufacturing firms in Nigeria are not optimally performing with input and output mix of variables. It is therefore recommended that there is need for them to scale down cost of production through appropriate strategic decisions. Keywords: Technical efficiency, data envelopment analysis, firm performanc

Efficiency Analysis of Islamic Banking in Hderabad City Sindh

Interest (Riba) is stringently prohibited in Islam. It is very difficult task to transform a Riba based economy into non-interested based economy. This transformation of economy can take place slowly. Development of Islamic banking industry shows that is growing very rapidly. This study will help to estimate the efficiency of Islamic banking in Hyderabad by applying Data Envelopment Analysis (DEA). Technical, cost and income efficiency will be calculated through DEA. Tobit model will also be applied to investigate the influence of different factors on efficiencies of Islamic banks. Average technical efficiency score of Islamic banking under constant (variable) return to scale was 0.837 (0.929), 0.774 (0.943) and 0.913 (0.967) respectively in 2010, 2011 and 2012. Islamic bank should increase assets and profits which have positive impact on efficiency, while liabilities and no of branches had negative impact on efficiency. Average cost efficiency score of Islamic banking under constant (variable) return to scale was 0.623 (0.730), 0.621 (0.854) and 0.879 (0.929) respectively in 2010, 2011 and 2012. Average income efficiency score of Islamic banking under constant (variable) return to scale was 0.365(0.614), 0.387(0.709) and 0.416(0.687) respectively in 2010, 2011 and 2012. The efficiency of Islamic banks is increasing day by day in Hyderabad Sindh. Keywords: Islamic banking, Riba, Interest, technical efficiency, profits, Hyderabad

Dealing with the Endogeneity Problem in Data Envelopment Analysis

Endogeneity, and the distortions on the estimation of economic models that it causes, is a familiar problem in the econometrics literature. Although non-parametric methods like data envelopment analysis (DEA) are among the most used techniques for measuring technical efficiency, the effects of endogeneity on such efficiency estimates have received little attention. The aim of this paper is twofold. First, we further illustrate the endogeneity problem and its causes in production processes like the correlation between one input and the efficiency level. Second, we use synthetic data generated in a Monte Carlo experiment to analyze how different levels of positive and negative endogeneity can impair DEA estimations. We conclude that although DEA is robust to negative endogeneity, a high positive endogeneity level, i.e., a high positive correlation between one input and the true efficiency level, significantly and severely biases DEA performance

Dealing with the Endogeneity Problem in Data Envelopment Analysis

Endogeneity, and the distortions on the estimation of economic models that it causes, is a familiar problem in the econometrics literature. Although non-parametric methods like data envelopment analysis (DEA) are among the most used techniques for measuring technical efficiency, the effects of endogeneity on such efficiency estimates have received little attention. The aim of this paper is twofold. First, we further illustrate the endogeneity problem and its causes in production processes like the correlation between one input and the efficiency level. Second, we use synthetic data generated in a Monte Carlo experiment to analyze how different levels of positive and negative endogeneity can impair DEA estimations. We conclude that although DEA is robust to negative endogeneity, a high positive endogeneity level, i.e., a high positive correlation between one input and the true efficiency level, significantly and severely biases DEA performance

Local Government Efficiency: Evidence from the Czech Municipalities

We measure cost efficiency of 202 Czech municipalities of extended scope in period 2003-2008. The study is the first application of overall efficiency measurement of the local governments in the new EU member states, and the second in post-communist countries. We measure government efficiency through established quantitative and qualitative indicators of the provision of education, cultural facilities, infrastructure and other local services. First, we employ non-parametric approach of the data envelopment analysis and adjust the efficiency scores by bootstrapping. Second, we employ the stochastic frontier analysis and control for effects of various demographic, economic, and political variables. We compare scores under our preferred specification, i.e. pseudo-translog time-variant stochastic-frontier analysis with determinants, with alternative scores. The determinants that robustly increase inefficiency are population size, distance to the regional center, share of university-educated citizens, capital expenditures, subsidies per capita, and the share of self-generated revenues. Concerning political variables, increase in party concentration and the voters' involvement increases efficiency, and local council with a lower share of left-wing representatives also tend to be more efficient. We interpret determinants both as indicators of slack, non-discretionary inputs, and unobservable outputs. The analysis is conducted also for the period 1994-1996, where political variables appear to influence inefficiency in a structurally different way. From comparison of the two periods, we obtain that small municipalities improve efficiency significantly more that large municipalities.Public spending efficiency, Data Envelopment Analysis, Stochastic Frontier Analysis, local governments

Exploring the association between primary care efficiency and health system characteristics across European countries: a two-stage data envelopment analysis.

BACKGROUND: Primary care is widely seen as a core component of resilient and sustainable health systems, yet its efficiency is not well understood and there is a lack of evidence about how primary care efficiency is associated with health system characteristics. We examine this issue through the lens of diabetes care, which has a well-established evidence base for effective treatment and has previously been used as a tracer condition to measure health system performance. METHODS: We developed a conceptual framework to guide the analysis of primary care efficiency. Using data on 18 European countries during 2010-2016 from several international databases, we applied a two-stage data envelopment analysis to estimate (i) technical efficiency of primary care and (ii) the association between efficiency and health system characteristics. RESULTS: Countries varied widely in terms of primary care efficiency, with efficiency scores depending on the range of population characteristics adjusted for. Higher efficiency was associated with bonus payments for the prevention and management of chronic conditions, nurse-led follow-up, and a financial incentive or requirement for patients to obtain a referral to specialist care. Conversely, lower efficiency was associated with higher rates of curative care beds and financial incentives for patients to register with a primary care provider. CONCLUSIONS: Our results underline the importance of considering differences in population characteristics when comparing country performance on primary care efficiency. We highlight several policies that could enhance the efficiency of primary care. Improvements in data collection would enable more comprehensive assessments of primary care efficiency across countries, which in turn could more effectively inform policymaking

Efficiency evaluation of South Africa tertiary education institutions using data envelopment analysis

With an increasing number of students enrolling at higher education institutions in South Africa, it has become important to investigate whether these institutions are using their resources adequately. This study uses data envelopment analysis (DEA) to estimate the efficiency of 23 South African tertiary education institutions based on both teaching and research outputs. Using DEA we are able to rank South African universities according to their use of resources in these two areas. These rankings can identify institutions which are performing well and also those which require improvement. The effect that merging institutions has on this efficiency is also determined. Owing to the limited sample size, variable reduction techniques, including the efficiency contribution measure (ECM) and principal components analysis (PCA-DEA), were used to improve the discrimination of the analysis

AN ASSESSMENT OF THE IMPACT OF UNDESIRABLE OUTPUTS ON THE PRODUCTIVITY OF UNITED STATES MOTOR CARRIERS

The U.S. economy depends heavily on the trucking industry as it moves 70% of the entire nation's freight. With the inclusion of $295 billion in truck trade with Canada and$195.6 billion in truck trade with Mexico in 2007, it is apparent that any disruption in truck traffic will lead to rapid economic instability (ATA Releases: American Trucking Trends 2008 - 2009, 2008). Yet, the critical nature of the trucking industry comes at a societal price. Indeed, undesirable outputs, e.g., truck crashes and associated injuries and fatalities, have very significant economic and human consequences. This dissertation uses Data Envelopment Analysis (DEA) to investigate the impact of undesirable outputs on the productivity of the motor carrier industry during the years 1999-2003. Previous DEA studies at the firm level have focused on the relationship between inputs and desirable outputs. The proposed approach in this dissertation simultaneously considers both the positive and negative outputs. This dissertation addresses two key problems with the DEA analysis technique previously identified by Yang and Pollit (2009): i.e., failure to take into consideration undesirable outputs and the failure to assess the impact of exogenous variables on the DEA scores of individual firms. As a result, this study will provide a new perspective into the productivity of U.S. motor carriers by incorporating both of these considerations into a more comprehensive DEA analysis. It will also provide opportunities to evaluate how individual firms might change their mix of inputs in order to simultaneously maximize desirable outputs and minimize undesirable ones