Corruption and health expenditure in Italy

The vulnerability of health sector to corruption lies in the complex interaction between the social environment and the institutional setting of health systems. We investigate this interaction in the case of Italy, speci�cally looking at the impact of corruption on health expenditure. In Italy corruption is a social phenomenon. Health sector has been often involved in corruption o¤ences and decentralized health expenditure is considerably out of control. We show that the impact of corruption on health expenditure is positive, along with ageing population, technological change and supply factors inducing demand in pharmaceuticals and hospitalization. Moreover, the empirical analysis demonstrates that corruption a¤ects pharmaceutical expenditure and accredited private hospital expenditure, suggesting implications for health governance and policy

The Health Care Expenditure and Income: A Global Perspective

This paper investigates the long-run economic relationship between health care expenditure and income in the world using data on 167 countries over the period 1995-2012, collected from the World Bank data set. The analysis is carried using panel data methods that allow one to account for unobserved heterogeneity, temporal persistence, and cross-section dependence in the form of either a common factor model or a spatial process. We estimate a global measure of income elasticity using all countries in the sample, and for sub-groups of countries, depending on their geo-political area and income. Our findings suggest that at the global level, health care is a necessity rather than a luxury. However, results vary greatly depending on the sub-sample analyzed. Our findings seem to suggest that size of income elasticity depends on the position of different countries in the global income distribution, with poorer countries showing higher elasticity

Explaining (in)efficiency in higher education: a comparison of parametric and non-parametric analyses to rank universities

In recent years more and more numerous are the rankings published in the newspapers or technical reports available, covering many aspects of higher education, but in many cases with very conflicting results between them, due to the fact that universities’ performances depend on the set of variables considered and on the methods of analysis employed. The aim of this study is to rank higher education institutions (HEIs) in Italy, comparing parametric and non-parametric approaches: we firstly apply a so-called double bootstrap Data Envelopment Analysis (DEA) to generate unbiased coefficients (Simar and Wilson, 2007) and then a Stochastic Frontier Analysis (SFA), modelling the production set through an output distance function, applying a within transformation to data as developed by Wang and Ho (2010), to evaluate which determinants have an impact on universities’ efficiencies. The findings reveal that, on average and among the macro-areas of the country, the level of efficiency does not change significantly among estimation methods which, instead, generate different rankings. This may guide universities’ managers and policymakers as rankings have a strong impact on academic decision-making and behaviour, on the structure of the institutions and also on students and graduates recruiters. Variables describing institution, market place and environment have an important role in explaining (in)efficiency

Explaining (in)efficiency in higher education: a comparison of parametric and non-parametric analyses to rank universities

In recent years more and more numerous are the rankings published in the newspapers or technical reports available, covering many aspects of higher education, but in many cases with very conflicting results between them, due to the fact that universities’ performances depend on the set of variables considered and on the methods of analysis employed. The aim of this study is to rank higher education institutions (HEIs) in Italy, comparing parametric and non-parametric approaches: we firstly apply a so-called double bootstrap Data Envelopment Analysis (DEA) to generate unbiased coefficients (Simar and Wilson, 2007) and then a Stochastic Frontier Analysis (SFA), modelling the production set through an output distance function, applying a within transformation to data as developed by Wang and Ho (2010), to evaluate which determinants have an impact on universities’ efficiencies. The findings reveal that, on average and among the macro-areas of the country, the level of efficiency does not change significantly among estimation methods which, instead, generate different rankings. This may guide universities’ managers and policymakers as rankings have a strong impact on academic decision-making and behaviour, on the structure of the institutions and also on students and graduates recruiters. Variables describing institution, market place and environment have an important role in explaining (in)efficiency

L'analisi costi benefici

In questo capitolo si riportano le principali teorie dell'analisi costi benefic

Crisi economica e Mezzogiorno Resiliente

Causa della resilienza economica nelle regioni del Meridione