New insights on measuring bank branches efficiency through DEA:transactional, operational, and profit assessments

This thesis presents a number of methodological developments that were raised by a real life application to measuring the efficiency of bank branches. The advent of internet banking and phone banking is changing the role of bank branches from a predominantly transaction-based one to a sales-oriented role. This fact requires the development of new forms of assessing and comparing branches of a bank. In addition, performance assessment models must also take into account the fact that bank branches are service and for-profit organisations to which providing adequate service quality as well as being profitable are crucial objectives. This study analyses bank branches performance in their new roles in three different areas: their effectiveness in fostering the use of new transaction channels such as the internet and the telephone (transactional efficiency); their effectiveness in increasing sales and their customer base (operational efficiency); and their effectiveness in generating profits without compromising the quality of service (profit efficiency). The chosen methodology for the overall analysis is Data Envelopment Analysis (DEA). The application attempted here required some adaptations to existing DEA models and indeed some new models so that some specialities of our data could be handled. These concern the development of models that can account for negative data, the development of models to measure profit efficiency, and the development of models that yield production units with targets that are nearer to their observed levels than targets yielded by traditional DEA models. The application of the developed models to a sample of Portuguese bank branches allowed their classification according to the three performance dimensions (transactional, operational and profit efficiency). It also provided useful insights to bank managers regarding how bank branches compare between themselves in terms of their performance, and how, in general, the three performance dimensions are connected between themselves.

Productivity analysis and measurement

The state of the art in productivity measurement and analysis shows a gap between simple methods having little relevance in practice and sophisticated mathematical theory which is unwieldy for strategic and tactical planning purposes, -particularly at company level. An extension is made in this thesis to the method of productivity measurement and analysis based on the concept of added value, appropriate to those companies in which the materials, bought-in parts and services change substantially and a number of plants and inter-related units are involved in providing components for final assembly. Reviews and comparisons of productivity measurement dealing with alternative indices and their problems have been made and appropriate solutions put forward to productivity analysis in general and the added value method in particular. Based on this concept and method, three kinds of computerised models two of them deterministic, called sensitivity analysis and deterministic appraisal, and the third one, stochastic, called risk simulation, have been developed to cope with the planning of productivity and productivity growth with reference to the changes in their component variables, ranging from a single value 'to• a class interval of values of a productivity distribution. The models are designed to be flexible and can be adjusted according to the available computer capacity expected accuracy and 'presentation of the output. The stochastic model is based on the assumption of statistical independence between individual variables and the existence of normality in their probability distributions. The component variables have been forecasted using polynomials of degree four. This model is tested by comparisons of its behaviour with that of mathematical model using real historical data from British Leyland, and the results were satisfactory within acceptable levels of accuracy. Modifications to the model and its statistical treatment have been made as required. The results of applying these measurements and planning models to the British motor vehicle manufacturing companies are presented and discussed.

Evaluating productive efficiency:comparative study of commercial banks in Gulf countries

Financial institutes are an integral part of any modern economy. In the 1970s and 1980s, Gulf Cooperation Council (GCC) countries made significant progress in financial deepening and in building a modern financial infrastructure. This study aims to evaluate the performance (efficiency) of financial institutes (banking sector) in GCC countries. Since, the selected variables include negative data for some banks and positive for others, and the available evaluation methods are not helpful in this case, so we developed a Semi Oriented Radial Model to perform this evaluation. Furthermore, since the SORM evaluation result provides a limited information for any decision maker (bankers, investors, etc...), we proposed a second stage analysis using classification and regression (C&R) method to get further results combining SORM results with other environmental data (Financial, economical and political) to set rules for the efficient banks, hence, the results will be useful for bankers in order to improve their bank performance and to the investors, maximize their returns. Mainly there are two approaches to evaluate the performance of Decision Making Units (DMUs), under each of them there are different methods with different assumptions. Parametric approach is based on the econometric regression theory and nonparametric approach is based on a mathematical linear programming theory. Under the nonparametric approaches, there are two methods: Data Envelopment Analysis (DEA) and Free Disposal Hull (FDH). While there are three methods under the parametric approach: Stochastic Frontier Analysis (SFA); Thick Frontier Analysis (TFA) and Distribution-Free Analysis (DFA). The result shows that DEA and SFA are the most applicable methods in banking sector, but DEA is seem to be most popular between researchers. However DEA as SFA still facing many challenges, one of these challenges is how to deal with negative data, since it requires the assumption that all the input and output values are non-negative, while in many applications negative outputs could appear e.g. losses in contrast with profit. Although there are few developed Models under DEA to deal with negative data but we believe that each of them has it is own limitations, therefore we developed a Semi-Oriented-Radial-Model (SORM) that could handle the negativity issue in DEA. The application result using SORM shows that the overall performance of GCC banking is relatively high (85.6%). Although, the efficiency score is fluctuated over the study period (1998-2007) due to the second Gulf War and to the international financial crisis, but still higher than the efficiency score of their counterpart in other countries. Banks operating in Saudi Arabia seem to be the highest efficient banks followed by UAE, Omani and Bahraini banks, while banks operating in Qatar and Kuwait seem to be the lowest efficient banks; this is because these two countries are the most affected country in the second Gulf War. Also, the result shows that there is no statistical relationship between the operating style (Islamic or Conventional) and bank efficiency. Even though there is no statistical differences due to the operational style, but Islamic bank seem to be more efficient than the Conventional bank, since on average their efficiency score is 86.33% compare to 85.38% for Conventional banks. Furthermore, the Islamic banks seem to be more affected by the political crisis (second Gulf War), whereas Conventional banks seem to be more affected by the financial crisis.

Is the post-reform growth of the Indian manufacturing sector efficiency driven? Empirical evidence from plant level data

It is generally believed that the structural reforms that were introduced in India following the macro-economic crisis of 1991 ushered in competition and forced companies to become more efficient. However, whether the post-1991 growth is an outcome of more efficient use of resources or greater use of factor inputs remains an open empirical question. In this paper, we use plant-level data from 1989–1990 and 2000–2001 to address this question. Our results indicate that while there was an increase in the productivity of factor inputs during the 1990s, most of the growth in value added is explained by growth in the use of factor inputs. We also find that median technical efficiency declined in all but one of the industries between 1989–1990 and 2000–2001, and that change in technical efficiency explains a very small proportion of the change in gross value added.

How important is ownership in a market with a level playing field? The Indian banking sector revisited

Private ownership of firms is often argued to lead to better firm performance than public ownership. However, the theoretical literature and the empirical evidence indicate that agency problems may affect the performance of privately owned firms. At the same time, competition and hard budget constraints can induce state-owned firms to operate efficiently. In India, banking sector reforms and deregulation were initiated in 1992, encouraging entry and establishing a level playing field for all banks. Data for the financial years 1995–1996 through 2000–2001 suggest that, by 1999–2000, ownership was no longer a significant determinant of performance. Rather, competition induced public-sector banks to eliminate the performance gap that existed between them and both domestic and foreign private-sector banks.

Does ownership always matter? Evidence from the Indian banking industry

Existing empirical evidence on the ownership-performance issue is weighted towards the property rights hypothesis that private enterprises are superior to public enterprises. However, very few studies examine a developing country in which the strong link between the market for corporate control and the efficiency of private enterprises assumed by the property rights hypothesis may not be satisfied. Our study of the Indian banking industry confirms our expectation that, in the absence of well-functioning capital markets, there may not be significant differences in the performance of private and public enterprises. Our analysis highlights the importance of creating appropriate institutions prior to pursuing privatization in developing countries.

Is a little sunshine all we need? On the impact of sunshine regulation on profits, productivity and prices in the Dutch drinking water sector

This paper analyzes the performance of Dutch drinking water utilities before and after the introduction of sunshine regulation, which involves publication of the performance of utilities but no formal price regulation. By decomposing profit change into its economic drivers, our results suggest that, in the Dutch political and institutional context, sunshine regulation was effective in improving the productivity of publicly organised services. Nevertheless, while sunshine regulation did bring about a moderate reduction in water prices, sustained and substantial economic profits suggest that it may not have the potential to fully align output prices with economic costs in the long run. In methodological terms, the DEA based profit decomposition is extended to robust and conditional non-parametric efficiency measures, so as to account better for both uncertainty and differences in operating environment between utilities.

FDI horizontal and vertical effects on local firm technical efficiency

Differencing from previous studies on foreign direct investment (FDI) spillovers to domestic enterprises which mainly focus on productivity, in this paper we take a different perspective by analysing the impacts of FDI to technical efficiency of domestic firms. The paper goes beyond the current literature to shed some light on the spillover effects of FDI to technical efficiency of small and medium enterprises in a developing country. By exploiting a firm-level panel dataset and using SFA models following Battese and Coelli (1995), the paper is able to analyse horizontal spillovers through imitation and competition and labour mobility as well as vertical spillovers through backward and forward linkages on technical efficiency. The paper contributes to the understanding of potential effects on foreign invested enterprises on domestic economy in general and local enterprises performance in particular. Thus it importantly assists policy making by the government of developing countries, where FDI is believed to create technical spillovers on domestic enterprises.

Corporate governance and accounting conservatism:evidence from the banking industry

Research Question/Issue: In this paper, we empirically investigate whether US listed commercial banks with effective corporate governance structures engage in higher levels of conservative financial accounting and reporting. Research Findings/Insights: Using both market- and accrual-based measures of conservatism and both composite and disaggregated governance indices, we document convincing evidence that well-governed banks engage in significantly higher levels of conditional conservatism in their financial reporting practices. For example, we find that banks with effective governance structures, particularly those with effective board and audit governance structures, recognize loan loss provisions that are larger relative to changes in nonperforming loans compared to their counterparts with ineffective governance structures. Theoretical/Academic Implications: We contribute to the extant literature on the relationship between corporate governance and quality of accounting information by providing evidence that banks with effective governance structures practice higher levels of accounting conservatism. Practitioner/Policy Implications: The findings of this study would be useful to US bank regulators/supervisors in improving the existing regulatory framework by focusing on accounting conservatism as a complement to corporate governance in mitigating the opaqueness and intense information asymmetry that plague banks.

An overview of Total Factor Productivity estimations adjusted for pollutant outputs:an application to sugarcane farming

The conventional Total Factor Productivity (TFP) measurement does not incorporate the effects of undesirable outputs, which are harmful to the environment. Using sugarcane farming in Kenya, this paper illustrates the differences between the conventional Malmquist index measures where the environment variable is not adjusted and environment-adjusted measures using both hyperbolic and directional distance functions. The mean TFP change estimates for the conventional Malmquist index, adjusted hyperbolic index and Luenberger indicator were 3.13%, 0.11% and 2.21%, respectively. The conventional non-adjusted measure lies between the two adjusted measures of hyperbolic index and Luenberger indicator. © 2012 Inderscience Enterprises Ltd.

Economic efficiency of smallholder maize producers in Western Kenya:a DEA meta-frontier analysis

Maize is the main staple food for most Kenyan households, and it predominates where smallholder, as well as large-scale, farming takes place. In the sugarcane growing areas of Western Kenya, there is pressure on farmers on whether to grow food crops, or grow sugarcane, which is the main cash crop. Further, with small and diminishing land sizes, the question of productivity and efficiency, both for cash and food crops is of great importance. This paper, therefore, uses a two-step estimation technique (DEA meta-frontier and Tobit Regression) to highlight the inefficiencies in maize cultivation, and their causes in Western Kenya.

Estimation of productivity in Korean electric power plants:a semiparametric smooth coefficient model

This paper analyzes the impact of load factor, facility and generator types on the productivity of Korean electric power plants. In order to capture important differences in the effect of load policy on power output, we use a semiparametric smooth coefficient (SPSC) model that allows us to model heterogeneous performances across power plants and over time by allowing underlying technologies to be heterogeneous. The SPSC model accommodates both continuous and discrete covariates. Various specification tests are conducted to compare performance of the SPSC model. Using a unique generator level panel dataset spanning the period 1995-2006, we find that the impact of load factor, generator and facility types on power generation varies substantially in terms of magnitude and significance across different plant characteristics. The results have strong implication for generation policy in Korea as outlined in this study.

Estimating the efficiency of healthcare facilities providing HIV/AIDS treatment in Zambia:a data envelopment approach

Zambia and many other countries in Sub-Saharan Africa face a key challenge of sustaining high levels of coverage of AIDS treatment under prospects of dwindling global resources for HIV/AIDS treatment. Policy debate in HIV/AIDS is increasingly paying more focus to efficiency in the use of available resources. In this chapter, we apply Data Envelopment Analysis (DEA) to estimate short term technical efficiency of 34 HIV/AIDS treatment facilities in Zambia. The data consists of input variables such as human resources, medical equipment, building space, drugs, medical supplies, and other materials used in providing HIV/AIDS treatment. Two main outputs namely, numbers of ART-years (Anti-Retroviral Therapy-years) and pre-ART-years are included in the model. Results show the mean technical efficiency score to be 83%, with great variability in efficiency scores across the facilities. Scale inefficiency is also shown to be significant. About half of the facilities were on the efficiency frontier. We also construct bootstrap confidence intervals around the efficiency scores.

Neural network DEA for measuring the efficiency of mutual funds

Efficiency in the mutual fund (MF), is one of the issues that has attracted many investors in countries with advanced financial market for many years. Due to the need for frequent study of MF's efficiency in short-term periods, investors need a method that not only has high accuracy, but also high speed. Data envelopment analysis (DEA) is proven to be one of the most widely used methods in the measurement of the efficiency and productivity of decision making units (DMUs). DEA for a large dataset with many inputs/outputs would require huge computer resources in terms of memory and CPU time. This paper uses neural network back-ropagation DEA in measurement of mutual funds efficiency and shows the requirements, in the proposed method, for computer memory and CPU time are far less than that needed by conventional DEA methods and can therefore be a useful tool in measuring the efficiency of a large set of MFs. Copyright © 2014 Inderscience Enterprises Ltd.

Evaluation efficiency of large-scale data set with negative data:an artificial neural network approach

Data envelopment analysis (DEA) is the most widely used methods for measuring the efficiency and productivity of decision-making units (DMUs). The need for huge computer resources in terms of memory and CPU time in DEA is inevitable for a large-scale data set, especially with negative measures. In recent years, wide ranges of studies have been conducted in the area of artificial neural network and DEA combined methods. In this study, a supervised feed-forward neural network is proposed to evaluate the efficiency and productivity of large-scale data sets with negative values in contrast to the corresponding DEA method. Results indicate that the proposed network has some computational advantages over the corresponding DEA models; therefore, it can be considered as a useful tool for measuring the efficiency of DMUs with (large-scale) negative data.