New tools for dealing with errors-in-variables in DEA.

Errors in variables; Tool;

New Tools for Dealing with Errors-in-Variables in DEA.

We develop a series of novel conceptual tools to systematically account for errors-in-variables in Data Envelopment Analysis (DEA). These tools allow for statistical inference while requiring minimal statistical distribution assumptions, and therefore constitute a valuable addition to the tools currently available for dealing with errors-in-variables. An empirical application for large European Union financial institutions illustrates the proposed approach.Data Envelopment Analysis (DEA), errors-in-variables, efficiency depth, robust reference sets, financial institutions

Conceptual modelling: framework, principles, and future research

The conceptual modelling task in a simulation project is very important and yet is still generally regarded as more of an art than a science. The meaning and nature of conceptual modelling are discussed and a framework set out. The overall aim should be to choose the best model for the project and conceptual modelling can be viewed as a difficult optimisation problem that can be tackled effectively using a creative search process that develops alternative models and predicts their performance throughout the project. An experiment relating model characteristics to some aspects of performance is described and this type of experiment may inform the process of predicting model performance. Based on advice from the literature and my own previous work on conceptual modelling 17 principles of conceptual modelling are suggested. Conceptual modelling research is still at an early stage and ideas for future research are proposed

Perspectives on safety culture

Overviewing selected elements from the literature, this paper locates the notion of safety culture within its parent concept of organisational culture. A distinction is drawn between functionalist and interpretive perspectives on organisational culture. The terms ‘culture’ and ‘climate’ are clarified as they are typically applied to organisations and to safety. A contrast is drawn between strategic top down and data-driven bottom up approaches to human factors as an illustrative aspect of safety. A safety case study is used to illustrate two measurement approaches. Key issues for future study include valid measurement of safety culture and developing methods to adequately represent mechanisms through which safety culture might influence, and be influenced by, other safety factors

Resilient Quantum Computation: Error Models and Thresholds

Recent research has demonstrated that quantum computers can solve certain types of problems substantially faster than the known classical algorithms. These problems include factoring integers and certain physics simulations. Practical quantum computation requires overcoming the problems of environmental noise and operational errors, problems which appear to be much more severe than in classical computation due to the inherent fragility of quantum superpositions involving many degrees of freedom. Here we show that arbitrarily accurate quantum computations are possible provided that the error per operation is below a threshold value. The result is obtained by combining quantum error-correction, fault tolerant state recovery, fault tolerant encoding of operations and concatenation. It holds under physically realistic assumptions on the errors.Comment: 19 pages in RevTex, many figures, the paper is also avalaible at http://qso.lanl.gov/qc

Non-Parametric Tests for Firm Efficiency in Case of Errors-in-Variables

This paper develops a novel statistic for firm efficiency called efficiency depth thatallows for statistical inference in case of errors-in-variables. We derive statistical teststhat require minimal statistical assumptions; neither the sample distribution nor thenoise level is required. An empirical illustration for European banks illustrates that -despite the minimal assumptions- the tests can have substantial discriminating powerin practical applications.errors-in-variables;firm efficiency;nonparametric analysis

Efficiency of Financial Institutions: International Survey and Directions for Future Research

This paper surveys 130 studies that apply frontier efficiency analysis to financial institutions in 21 countries. The primary goals are to summarize and critically review empirical estimates of financial institution efficiency and to attempt to arrive at a consensus view. We find that the various efficiency methods do not necessarily yield consistent results and suggest some ways that these methods might be improved to bring about findings that are more consistent, accurate, and useful. Secondary goals are to address the implications of efficiency results for financial institutions in the areas of government policy, research, and managerial performance. Areas needing additional research are also outlined.