A Fay–Herriot model when auxiliary variables are measured with error (2019). Springer, 1-30.

Jan Pablo Burgard (Trier University), María Dolores Esteban (University Miguel Hernández of Elche), Domingo Morales (University Miguel Hernández of Elche) and Agustín Pérez (University Miguel Hernández of Elche).

Abstract. The Fay–Herriot model is an area-level linear mixed model that is widely used for estimating the domain means of a given target variable. Under this model, the dependent variable is a direct estimator calculated by using the survey data and the auxiliary variables are true domain means obtained from external data sources. Administrative registers do not always give good auxiliary variables so that statisticians sometimes take them from alternative surveys and therefore they are measured with error. We introduce a variant of the Fay–Herriot model that takes into account the measurement error of the auxiliary variables and give two fitting algorithms that calculate maximum and residual maximum likelihood estimates of the model parameters. Based on the new model, empirical best predictors of domain means are introduced and an approximation of its mean squared error is derived. We finally give an application to estimate poverty proportions in the Spanish Living Condition Survey, with auxiliary information from the Spanish Labour Force Survey.

Keywords. Fay–Herriot model; Small area estimation; Measurement error; Monte Carlo simulation; Poverty proportion

Measuring efficiency in education: The influence of imprecision and variability in data on DEA estimates (2019). Socio-Economic Planning Sciences, 1-12.

Juan Aparicio (University Miguel Hernández of Elche), José Manuel Cordero (University of Extremadura) and Lidia Ortiz (University Miguel Hernández of Elche).

Abstract. Many studies devoted to efficiency performance evaluation in the education sector are based on measures of central tendency at school level as, for example, the average values of students belonging to the same school. Although this is a common and accepted way of summarizing data from the original observations (students), it is not less true that this approach neglects the existing dispersion of data, which may become a serious problem if variability across schools is high. Additionally, imprecision may arise when experts on each evaluated subject select the battery of questions, with different levels of difficulty, which will be the base for the final questionnaires completed by students. This paper uses data from US students and schools participating in PISA (Programme for International Student Assessment) 2015 to illustrate that schools’ efficiency measures based on aggregate data and imprecision may reflect an inaccurate picture of their performance if they are compared to measures estimated accounting for broader information provided by all students of the same school. In order to operationalize our approach, we resort to Fuzzy Data Envelopment Analysis. This methodology allows us to deal with the notion of fuzziness in some variables such as the socio-economic status of students or test scores. Our results indicate that the estimated measures of performance obtained with the fuzzy DEA approach are highly correlated with those calculated with traditional DEA models. However, we find some relevant divergences in the identification of efficient units when we account for data dispersion and vagueness.

Keywords. Efficiency; Data envelopment analysis; Fuzzy data; Education

Analysis of the structured objective clinical evaluation test (ECOE) of the sixth year at the Faculty of Medicine of the Miguel Hernández University of Elche (2019). Educación Médica, 20 (1), 29-36.

José M. Ramos (University Miguel Hernández of Elche), M. Asunción Martínez-Mayoral (University Miguel Hernández of Elche), Francisco Sánchez-Ferrer (University Miguel Hernández of Elche) Javier Morales (University Miguel Hernández of Elche), Tomás Sempere (University Miguel Hernández of Elche), Isabel Belinchón (University Miguel Hernández of Elche) and Antonio F. Company (University Miguel Hernández of Elche).

Abstract. The objective and structured clinical evaluation test (ECOE) is a method of evaluating clinical competence with evidence of validity, objectivity and reliability. In this study we set out to analyze the ECOE test of sixth grade students of medicine. Material and methods: Cross-sectional study of the ECOE test carried out at the Faculty of Medicine of the Miguel Hernández University of Elche in June 2016. 116 students participated in the test. There were 7 (35%) standardized patient stations, 5 (25%) reporting stations, 4 (20%) mannequin / procedure stations and 4 (20%) structured oral examination type stations. The median of the students’ score was 7.14 (interquartile range: 6.90-7.43). The median score of the first day students in the morning was 7.10, the first day in the afternoon was higher (7.14) and the second day in the morning was also higher (7.24; p = 0.1). The station with the lowest score was the report station (6.41) and the station with the highest score was the mannequin station / procedure (7.88) (p <0.001). Within the standardized patient stations (median = 7.12), the results of the students were better in which the patient was a physician in training (7.52). Keywords. Objective and structured clinical evaluation; Degree in medicine; Competencies

Efficiency and productivity change of regional tax offices in Spain: an empirical study using Malmquist–Luenberger and Luenberger indices (2019). Empirical Economics, Springer, 1-32.

Juan Aparicio (University Miguel Hernández of Elche), José Manuel Cordero (University of Extremadura) and Carlos Díaz-Caro (University of Extremadura).

Abstract. The paper presents an innovative empirical application to assess the efficiency of regional tax offices in Spain. The existing evidence about the performance of those administrative units is still limited; thus, our aim is to contribute to extend this line of research by incorporating three relevant issues into our empirical analysis. First, we consider the number of complaints against tax authority decisions as a quality measure of tax management. Since the evaluated units should aim to minimize the number of complaints, this variable represents an undesirable output; thus, we define a model that is adaptable to the special features of this unconventional output. Second, our empirical analysis covers the period 2005–2014; thus, we can analyze the productivity change across this 10-year period including different phases of the economic cycle. Finally, seeking robustness, we use enhanced versions of the Malmquist–Luenberger productivity index and the Luenberger productivity indicator that allow us to overcome some of the drawbacks suffered by the original approach. The results obtained with both indices are very similar and indicate that during the evaluated period tax offices suffered a slight worsening in terms of productivity, especially during the years previous to the economic crisis (2005–2008). This regression was mainly due to the technical regression experienced by the majority of units during those years.

Keywords. Efficiency; Tax offices; Public management; Productivity change; Administrative services; Operations research