The present paper focuses attention on the sensitivity of technical inefficiency to most commonly used one-sided distributions of the inefficiency error term, namely the truncated normal, the half-normal, and the exponential distributions. A generalized version of the half-normal, which does not embody the zero-mean restriction, is also explored. For each distribution, the likelihood function and the counterpart of the estimator of technical efficiency are explicitly stated (Jondrow, J., Lovell, C. A. K., Materov, I. S., Schmidt, P. ([1982]), On estimation of technical inefficiency in the stochastic frontier production function model, J. Econometrics19:233-238). Based on our panel data set, related to Tunisian manufacturing firms over the period 1983-1993, formal tests lead to a strong rejection of the zero-mean restriction embodied in the half normal distribution. Our main conclusion is that the degree of measured inefficiency is very sensitive to the postulated assumptions about the distribution of the one-sided error term. The estimated inefficiency indices are, however, unaffected by the choice of the functional form for the production function.Stochastic frontier, Farrell's technical inefficiency, Unbalanced panel data, Composed disturbance error, One-sided distribution,

Dans cet article, nous évaluons l’efficience des Instituts supérieurs des études technologiques tunisiens (ISET) avec la méthode non paramétrique du Data Envelopment Analysis (DEA). Il ressort des résultats empiriques que le fonctionnement de ces établissements se caractérise par une inefficience technique de l’ordre de 20 %, pouvant s’expliquer à la fois par des problèmes de taille des établissements (inefficience d’échelle de 11 % environ) et par des problèmes de gestion (inefficience pure de l’ordre de 10 %). Les résultats montrent également qu’une majorité des ISET de notre échantillon fonctionnerait de façon optimale si leur échelle de production augmentait, ce qui peut se révéler des pistes de solutions pour les pouvoirs politiques voulant promouvoir le système éducatif supérieur en Tunisie.In this paper, we evaluate the technical efficiency of Tunisian higher institutes of technological studies (ISET) with a non-parametric method, the Data Envelopment Analysis (DEA). The results show that these institutions are characterized by technical inefficiency of around 20%, which can be explained both by an inaccurate size (scale inefficiency of 11%) and by management problems (pure inefficiency of around 10%). We also find that a majority of the ISET in our sample would operate optimally if they could increase their scale of production. This can be a way for policy makers who want to promote higher education in Tunisia

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Precise data acquisition, characterization, and finding the relationship between permittivity variations of human skin with degree of burns is critically important because It further helps in the development of excellent sensor devices for diagnostics and treatment of patients suffering from burns and scalds. This work is also a part of the European “Senseburn” project that focuses to develop a non-invasive diagnostic tool for the assessment of human burns based on its degree and depth in the clinical setup. In this work, several Ex-vivo burnt samples were collected from the Uppsala University Hospital (Akademiska sjukhuset, Sweden), and out of that, eight samples with different burn degrees and of various human body parts were selected for the analysis. The dielectric characterization of the categorized samples was done by using an open-end co-axial probe kit. The measurement was made systematically and clinician feedback forms were maintained throughout the process. The measurement data followed the FASTCLUS procedure which was analyzed initially using density plot, Convergence, and cubic clustering criteria respectively. The dielectric characterization was made from 500 MHz to 10 GHz with 1001 points and from the previous sensor designs, the results were found to be excellent between 500 MHz to 5 GHz. For the statistical analysis, 11 frequency points were considered for 8 samples. The results of the basic statistical analysis using the FASTCLUS procedure resulted in 88 data sets. Later, data sets were analyzed based on the cluster-wise of all samples and sample-wise clusters. Every sample was made with two clusters i.e, cluster 1 which consisted of healthy sectors, and cluster 2 which consisted of burnt sectors. Furthermore, we found that the permittivity differences of clusters are proportional to the degree of the burns. This is pivotal information and It helps to improve the functioning of the diagnostic microwave sensors by designing them according to the permittivity variations. For this purpose, an extensive campaign of around 1000 measurements across a band of 1–30 GHz was done and it leads to the conclusion that each skin region of interest (ROI) provides unique dielectric properties.

This article studies the inequalities in measurements of the risk aversion in the context of the financial investments in Tunisia. We clarify initially the factors constitutive of the risk aversion. The studied actors are individual decision makers. The tackled questions are the risk attitude (including the risks known as extremes), its perception, its evaluation, the decision-making in risky universe. The empirical data were collected through experimental sessions carried out in Tunisia. We propose a framework of analysis for the study of the investors preferences based on an operational econometric modeling. The estimated models are the ordered probit and the ordered probit with random effects. The model with random effects has the advantage of making it possible to test the heterogeneity of the individuals and to measure the inequality in risk aversion of the investors, and this, by studying the components between and within-individual of the variance of the risk aversion.