Percorrer por autor "Silva, Maria C. A."
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- Benchmarking of secondary schools based on students’ results in higher educationPublication . Silva, Maria C. A.; Camanho, Ana S.; Barbosa, FláviaThe performance of secondary schools is usually assessed based on students’ results on national exams at the end of secondary education. This research uses data on academic achievements by first-year univer- sity students to benchmark secondary schools on their ability to lead students to success in higher edu- cation. The analysis is conducted using data of University of Porto and Catholic University of Porto, Portu- gal, for a three-year period, corresponding to more than 10.0 0 0 students from 65 degrees, for which the school of origin is known. A number of variables representing students’ success in Higher education were constructed for each school in our sample and aggregated through a Benefit of the Doubt indicator. Re- sults suggest that the schools’ ranking based on schools’ ability to prepare students for university success is quite different from the ranking based on results on national exams. Given these findings, we propose complementing schools’ performance assessments (traditionally based on national exam results or indi- cators of value added) with indicators that account for the preparation of students for success in future challenges, which is indisputably a key objective of secondary education. We propose a composite indi- cator for the analysis of these complementary aims as well, and results show that frontier units indeed exhibit trade offs between traditional measures of performance and our new measure of performance.
- Efficiency decomposition for multi-level multi-components production technologiesPublication . Peyrache, Antonio; Silva, Maria C. A.This paper addresses the efficiency measurement of firms composed by multiple components, and assessed at different decision levels. In particular it develops models for three levels of decision/production: the subunit (production division/process), the DMU (firm) and the industry (system). For each level, inefficiency is measured using a directional distance function and the developed measures are contrasted with existing radial models. The paper also investigates how the efficiency scores computed at different levels are related to each other by proposing a decomposition into exhaustive and mutually exclusive components. The proposed method is illustrated using data on Portuguese hospitals. Since most of the topics addressed in this paper are related to more general network structures, avenues for future research are proposed and discussed.
- Scale and scope economies in first-instance courts: Portuguese specialized vs non-specialized courtsPublication . Lopes, Nuno Q. M.; Silva, Maria C. A.This paper analyses the technical efficiency of first-instance courts and investigates the existence of scale and scope economies. To assess the technical efficiency of specialized and non-specialized court benches, we use Data Envelopment Analysis (DEA). This study uses data from 2015 to 2021, encompassing every bench within the Portuguese first-instance courts, totalling 3249 observations. Our findings reveal diseconomies of scale, with more than half of the benches experiencing increasing returns to scale, indicating that their performance would benefit from increased scale. The scale diseconomies varied by bench type: benches primarily handling civil cases and generic benches faced mostly increasing returns to scale. In contrast, those dealing predominantly with criminal cases experienced decreasing returns to scale. Additionally, we observe diseconomies of scope, indicating that generic and non-specialized benches were less efficient than specialized ones. Overall, this paper provides empirical evidence supporting the notion that the specialization of benches enhances their efficiency.
- The decomposition of efficiency in parallel network production modelsPublication . Peyrache, Antonio; Silva, Maria C. A.Kao (2012) proposed a method to decompose DMU efficiency into sub-unit efficiencies for parallel production systems. We provide a numerical example showing that the proposed method can yield negative sub-unit efficiency scores under variable returns to scale, against common sense and standard postulates requiring this score to be non-negative. As a solution, we propose a decomposition based on the directional distance function that does not suffer from this problem. In particular, we recognize that the overall inefficiency of the DMU is composed of the sub-units technical inefficiencies and a reallocation inefficiency component. The proposed method can be also applied to non-convex technologies, therefore providing a more general method to implement such a decomposition. Given the connection between the directional distance function and slack-based efficiency measurement, the method can easily be extended to this case as well.
- The United Nations SDG13 and the EU27 countries performance: a comparative analysisPublication . Sena, Marina B.; Costa, Leonardo; Leitão, Alexandra; Silva, Maria C. A.This paper evaluates the performance of the European Union 27 (EU-27), its supranational regions, and Member States (MSs) in relation to the Climate Action Sustainable Development Goal (SDG13) of the United Nations 2030 Agenda. The Alkire–Foster method is used to develop the Multidimensional Climate Action Index (MCAI) framework. Regarding individual MSs’ overall performance, the results show that Sweden (Northern Europe) performs the best and Croatia (Central and Eastern Europe) the worst. In terms of the average overall performance of individual MSs in the EU-27 and its supranational regions, only Western and Northern Europe have satisfactory scores. Moreover, the performances of the various territories differ by target. This territorial heterogeneity illustrates how the SDG13 targets may require different efforts in each territory. The scores for the MCAI group measure depict an even worse picture. Except for Northern Europe, the proportion of MSs with a satisfactory individual overall composite score (H) is lower than their average overall composite score or intensity (A). The two regions with the lowest H scores (Southern Europe and Central and Eastern Europe) also have the lowest A scores and the lowest average GDP per capita.