Tommaso Agasisti

Beyond frontiers: comparing the efficiency of higher education decision‐making units across more than one country

We employ Data Envelopment Analysis to compute the technical efficiency of Italian and English higher education institutions. Our results show that, in relation to the country‐specific frontier, institutions in both countries are typically very efficient. However, institutions in England are more efficient than those in Italy when we compare jointly their performances. We also look at the evolution of technical efficiency scores over a four‐year period, and find that, in line with an error‐correction hypothesis, Italian universities are improving their technical efficiency while English universities are obtaining stable scores. Policy implications are addressed.

Heterogeneity and the evaluation of efficiency: the case of Italian universities

A random parameters stochastic frontier model is applied to Italian data in order to evaluate the cost function and efficiency of higher education institutions. The method yields useful information about inter-institutional variation in cost structure and technical efficiency. Returns to scale and scope are evaluated for the typical university, and it is found that these returns are almost ubiquitously decreasing, a finding with clear policy implications.

Governance models of university systems—towards quasi‐markets? Tendencies and perspectives: A European comparison

The results of an in‐depth study into the university systems of the main countries of the European Union are presented in this paper. The objective is to define theoretical models of the market forms of university education and to apply them in a comparative international study. The analysis shows a general tendency to organise these systems according to ‘managed competition’ mechanisms in which the state plays a role in financing the system and regulating the quality of the study courses offered by the universities (quasi‐markets).

Data envelopment analysis to the Italian university system: theoretical issues and policy implications

In this paper, we consider the problem of determining technical efficiency of the Italian universities, focusing on policy and benchmarking implications. Using Data Envelopment Analysis (DEA), the individual universitys efficiency is computed. We run several elaborations matching teaching and research variables representing the education production process. Computational results are given for 58 Italian public universities. We find a core of universities that perform well for various input and output specifications. We choose to focus on a single elaboration, selected on statistical grounds, to derive some policy implications.

Efficiency and quality of care in nursing homes: an Italian case study.

This study investigates efficiency and quality of care in nursing homes. By means of Data Envelopment Analysis (DEA), the efficiency of 40 nursing homes that deliver their services in the north-western area of the Lombardy Region was assessed over a 3-year period (2005–2007). Lombardy is a very peculiar setting, since it is the only Region in Italy where the healthcare industry is organised as a quasi-market, in which the public authority buys health and nursing services from independent providers—establishing a reimbursement system for this purpose. The analysis is conducted by generating bootstrapped DEA efficiency scores for each nursing home (stage one), then regressing those scores on explanatory variables (stage two). Our DEA model employed two input (i.e. costs for health and nursing services and costs for residential services) and three output variables (case mix, extra nursing hours and residential charges). In the second-stage analysis, Tobit regressions and the Kruskall–Wallis tests of hypothesis to the efficiency scores were applied to define what are the factors that affect efficiency: (a) the ownership (private nursing houses outperform their public counterparts); and (b) the capability to implement strategies for labour cost and nursing costs containment, since the efficiency heavily depends upon the alignment of the costs to the public reimbursement system. Lastly, even though the public institutions are less efficient than the private ones, the results suggest that public nursing homes are moving towards their private counterparts, and thus competition is benefiting efficiency.

Assessing the Cost Efficiency of Italian Universities.

Abstract This study uses Data Envelopment Analysis to evaluate the cost efficiency of 52 Italian public universities. In addition to being one of the first such cost studies of the Italian system, it explicitly takes into account the internal cost structure of institutions’ education programs; a task not prevalent in past Data Envelopment Analysis studies on higher education institutions. The findings highlight biases in efficiency measurement arising from not separating the sample into those institutions with medical faculties and those without. Efficiency scores are also shown to vary considerably when education quality measures are input‐based or output‐based. From a policy perspective, our findings suggest that limiting the enrollment growth of some institutions while expanding enrollments in others could reduce system‐wide costs and improve overall efficiency.

Comparing German and Italian Public Universities: Convergence or Divergence in the Higher Education Landscape?

In this paper we examine and compare the efficiency of Italian and German public universities and its evolution in the period 2001-2007. This topic is particularly important because of two main reasons: (i) as the universities are funded through public money in both countries, it is necessary to assess whether it has been used efficiently – especially in a period of pressures on public budgets; (ii) the comparison among (similar) European countries can stimulate a benchmarking exercise that can be useful for managerial and policy making purposes. Using data envelopment analysis (DEA) we first derive efficiency scores for higher education institutions in both countries. In a second step, we apply a Tobit regression in order to detect external factors associated with the efficiency of universities. Overall, the results show that German universities are more efficient than their Italian counterparts. However the latter are catching-up: in the period 2001-2007 their efficiency improved more rapidly. Among the external factors, three are statistically related to efficiency: the presence of a medical faculty, the regional unemployment rate, and the regional share of workers employed in science and technology.

The Efficiency of Italian Secondary Schools and the Potential Role of Competition; A Data Envelopment Analysis Using OECD-PISA2006 Data

In this study, data envelopment analysis (DEA) is used to compute efficiency scores for a sample of Italian schools by employing OECD-PISA2006 data aggregated at school level. Efficiency has been defined as the ability to transform inputs (resources, student background, etc.) into outputs (student achievement). Different versions of the DEA models were estimated to test result robustness, including a DEA bootstrapping procedure. In a second-stage analysis, the factors affecting school efficiency are investigated through a Tobit regression. Among these factors, alternative indicators of competition were included. The results show that at least one indicator of competition is statistically associated with higher performances of schools, suggesting that there is a potential role for improving school results by increasing the number of schools competing each other. These findings are consistent with a previous analysis conducted on the same dataset by estimating an educational production function. Policy implications are presented in the last part of the study.

Performances and spending efficiency in higher education: a European comparison through non‐parametric approaches

The objective of this paper is an efficiency analysis concerning higher education systems in European countries. Data have been extracted from OECD data‐sets (Education at a Glance, several years), using a non‐parametric technique – data envelopment analysis – to calculate efficiency scores. This paper represents the first attempt to conduct such an efficiency analysis at a system‐level in a cross‐country comparison, while focusing only on tertiary education. The role of the public sector has also been analysed, by looking at the percentage of public spending devoted to higher education, and the way the public funds are used (channelled through private subsidies or directly assigned to institutions). It has been found that there is a small core of efficient units (e.g. Switzerland, United Kingdom), and that the influence of the public sector seems to play a role in determining efficiency scores. Many elements, related to critical policies, have also been analysed adopting a semi‐parametric approach, to better explain the performances and efficiency differentials. Some key‐policy implications have been derived.

Market forces and competition in university systems: theoretical reflections and empirical evidence from Italy

This paper deals with the reforming processes in higher education (HE) from centralised systems towards more competitive ones. In particular, I discuss these issues referring to the Italian case, and the market‐like mechanisms introduced in it during 1990s and early 2000s. The focus of the paper is in analysing the effects of the increasing competition on teaching performance of universities. For this purpose, I develop a theoretical model, moving from the framework of yardstick competition (YC), to describe the functioning of a competition model based on comparing performance of institutions. Then, I apply this model using data from the Italian university system. The results suggest that an increasingly competitive environment effectively improves the universities’ performance, which is also influenced by other factors, namely the characteristics of the institutions themselves and of their students, and by the resources available. As the exploratory nature of the study, these findings must be validated through future research.