Carmen Armero

Sensitivity analysis of efficiency and Malmquist productivity indices : An application to Spanish savings banks

Hypothesis testing and statistical precision in the context of nonparametric efficiency and productivity measurement have been investigated since the early 1990s. Recent contributions focus on this matter through the use of resampling methods?i.e., bootstrapping techniques. However, empirical evidence is still practically non-existent. This gap is more noticeable in the case of banking efficiency studies, where the literature is immense. In this paper, we explore productivity growth and productive efficiency for Spanish savings banks over the (initial) post-deregulation period 1992?1998 using Data Envelopment Analysis (DEA) and bootstrapping techniques. Results show that productivity growth has occurred, mainly due to improvement in production possibilities, and that mean efficiency has remained fairly constant over time. The bootstrap analysis yields further evidence, as for many firms productivity growth, or decline, is not statistically significant. With regard to efficiency measurement, the bootstrap reveals that the disparities in the original efficiency scores of some firms are lessened to a great extent. Desde principios de los anos noventa ha habido avances notables en el contraste de hipotesis dentro del contexto de la medicion de la eficiencia y la productividad mediante tecnicas parametricas. Las contribuciones mas recientes han enfocado el tema a traves de metodos de remuestreo -conocidos en la literatura como tecnicas bootstrap-. Sin embargo, practicamente no ha habido aplicaciones, algo tambien patente en el estudio de la eficiencia de la empresa bancaria. En este articulo, analizamos la eficiencia productiva y el crecimiento de la productividad de las cajas de ahorro espanolas durante el periodo 1992-1998 a traves de tecnicas no parametricas (DEA) y de tecnicas bootstrap, con el fin de poder realizar inferencia estadistica. Los resultados indican que la productividad ha aumentado, principalmente debido a una mejora en las posibilidades de produccion, mientras que la eficiencia promedio no ha variado sustancialmente. El analisis bootstrap revela que, en el caso de la productividad, para muchas empresas su aumento o disminucion no es estadisticamente significativo. En cuanto a la eficiencia, muestra que las diferencias entre empresas individuales se reducen de manera notable cuando consideramos intervalos de confianza.

Bayesian prediction inM/M/1 queues

Simple queues with Poisson input and exponential service times are considered to illustrate how well-suited Bayesian methods are used to handle the common inferential aims that appear when dealing with queue problems. The emphasis will mainly be placed on prediction; in particular, we study the predictive distribution of usual measures of effectiveness in anM/M/1 queue system, such as the number of customers in the queue and in the system, the waiting time in the queue and in the system, the length of an idle period and the length of a busy period.

A Bayesian analysis of a queueing system with unlimited service

Abstract A queueing system occurs when “customers” arrive at some facility requiring a certain type of “service” provided by the “servers”. Both the arrival pattern and the service requirements are usually taken to be random. If all the servers are busy when customers arrive, they usually wait in line to get served. Queues possess a number of mathematical challenges and have been mainly approached from a probability point of view, and statistical analysis are very scarce. In this paper we present a Bayesian analysis of a Markovian queue in which customers are immediately served upon arrival, and hence no waiting lines form. Emergency and self-service facilities provide many examples. Technically such services can be modelled as queues with an infinite number of servers. The mathematical simplicity of these queues allows for closed-form exploration of a number of issues that arise when statistically analyzing queues, whether or not the queue is in equilibrium.

Bayesian inference in Markovian queues

This paper is concerned with the Bayesian analysis of general queues with Poisson input and exponential service times. Joint posterior distribution of the arrival rate and the individual service rate is obtained from a sample consisting inn observations of the interarrival process andm complete service times. Posterior distribution of traffic intensity inM/M/c is also obtained and the statistical analysis of the ergodic condition from a decision point of view is discussed.

Antimicrobial Resistance in More than 100,000 Escherichia coli Isolates According to Culture Site and Patient Age, Gender, and Location

ABSTRACT Escherichia coli and the antimicrobial pressure exerted on this microorganism can be modulated by factors dependent on the host. In this paper, we describe the distribution of antimicrobial resistance to amikacin, tobramycin, ampicillin, amoxicillin clavulanate, cefuroxime, cefoxitin, cefotaxime, imipenem, ciprofloxacin, fosfomycin, nitrofurantoin, and trimetoprim-sulfametoxazole in more than 100,000 E. coli isolates according to culture site and patient age, gender, and location. Bayesian inference was planned in all statistical analysis, and Markov chain Monte Carlo simulation was employed to estimate the model parameters. Our findings show the existence of a marked difference in the susceptibility to several antimicrobial agents depending on from where E. coli was isolated, with higher levels of resistance in isolates from medical devices, the respiratory system, and the skin and soft tissues; a higher resistance percentage in men than in women; and the existence of a clear difference in antimicrobial resistance with an age influence that cannot be explained merely by means of an increase of resistance after exposure to antimicrobials. Both men and women show increases in resistance with age, but while women show constant levels of resistance or slight increases during childbearing age and greater increases in the premenopausal age, men show a marked increase in resistance in the pubertal age. In conclusion, an overwhelming amount of data reveals the great adaptation capacity of E. coli and its close interaction with the host. Sex, age, and the origin of infection are determining factors with the ability to modulate antimicrobial resistances.

Prediction in Markovian bulk arrival queues

This paper deals with the statistical analysis of bulk arrival queues from a Bayesian point of view. The focus is on prediction of the usual measures of performance of the system in equilibrium. Posterior predictive distribution of the number of customers in the system is obtained through its probability generating function. Posterior distribution of the waiting time, in the queue and in the system, of the first customer of an arriving group is expressed in terms of their Laplace and Laplace–Stieltjes transform. Discussion of numerical inversion of these transforms is addressed.

Understanding disease mechanisms with models of signaling pathway activities

BackgroundUnderstanding the aspects of the cell functionality that account for disease or drug action mechanisms is one of the main challenges in the analysis of genomic data and is on the basis of the future implementation of precision medicine.ResultsHere we propose a simple probabilistic model in which signaling pathways are separated into elementary sub-pathways or signal transmission circuits (which ultimately trigger cell functions) and then transforms gene expression measurements into probabilities of activation of such signal transmission circuits. Using this model, differential activation of such circuits between biological conditions can be estimated. Thus, circuit activation statuses can be interpreted as biomarkers that discriminate among the compared conditions. This type of mechanism-based biomarkers accounts for cell functional activities and can easily be associated to disease or drug action mechanisms. The accuracy of the proposed model is demonstrated with simulations and real datasets.ConclusionsThe proposed model provides detailed information that enables the interpretation disease mechanisms as a consequence of the complex combinations of altered gene expression values. Moreover, it offers a framework for suggesting possible ways of therapeutic intervention in a pathologically perturbed system.

Bootstrapping profit change: An application to Spanish banks

The aim of this study is to provide a tool which enables us to conduct statistical analysis in the context of changes in productivity and profit. We build on previous initiatives to decompose profit change into mutually exclusive and exhaustive sources. To do this we use distance functions, which are calculated empirically using linear programming techniques. However, we may not learn a great deal by solving these linear programs unless methods of statistical analysis are used to examine the properties of the relevant estimators. Our purpose is to provide a methodology based on bootstrap that allows us to conduct statistical inference for the profit change decomposition. Thus, it will be possible to answer questions such as whether variations in the profit change components, or the differences across firms, are statistically significant. We provide an application to Spanish commercial banks for the 2003/2004 period. Results suggest that profit change differentials between them are not always significant. Therefore, the validity of the conclusions which do not factor in the bootstrap may be jeopardized to varying degrees.

Statistical performance of a multiclass bulk production queueing system

Abstract In this paper, we discuss how to statistically analyze a make-to-stock production system the behaviour of which depends on a multiclass bulk queueing system. The performance of the system is evaluated in terms of the different demands of products, processing times and, mainly, through the finished product inventory and other related measures that quantify the queueing effects in the system. A numerical example which illustrates the applicability of the results in an inventory scenario is also discussed.

Bayesian methods in cost-effectiveness studies: objectivity, computation and other relevant aspects.

In a probabilistic sensitivity analysis (PSA) of a cost-effectiveness (CE) study, the unknown parameters are considered as random variables. A crucial question is what probabilistic distribution is suitable for synthesizing the available information (mainly data from clinical trials) about these parameters. In this context, the important role of Bayesian methodology has been recognized, where the parameters are of a random nature. We explore, in the context of CE analyses, how formal objective Bayesian methods can be implemented. We fully illustrate the methodology using two CE problems that frequently appear in the CE literature. The results are compared with those obtained with other popular approaches to PSA. We find that the discrepancies can be quite marked, specially when the number of patients enrolled in the simulated cohort under study is large. Finally, we describe in detail the numerical methods that need to be used to obtain the results.