Francesco Moscone

The impact of precarious employment on mental health: The case of Italy

Although there has been a sizeable empirical literature measuring the effect of job precariousness on the mental health of workers the debate is still open, and understanding the true nature of such relationship has important policy implications. In this paper, we investigate the impact of precarious employment on mental health using a unique, very large data set that matches information on job contracts for over 2.7 million employees in Italy followed over the years 2007-2011, with their psychotropic medication prescription. We examine the causal effects of temporary contracts, their duration and the number of contract changes during the year on the probability of having one or more prescriptions for medication to treat mental health problems. To this end, we estimate a dynamic Probit model, and deal with the potential endogeneity of regressors by adopting an instrumental variables approach. As instruments, we use firm-level probabilities of being a temporary worker as well as other firm-level variables that do not depend on the mental illness status of the workers. Our results show that the probability of psychotropic medication prescription is higher for workers under temporary job contracts. More days of work under temporary contract as well as frequent changes in temporary contract significantly increase the probability of developing mental health problems that need to be medically treated. We also find that moving from permanent to temporary employment increases mental illness; symmetrically, although with a smaller effect in absolute value, moving from temporary to permanent employment tends to reduce it. Policy interventions aimed at increasing the flexibility of the labour market through an increase of temporary contracts should also take into account the social and economic cost of these reforms, in terms of psychological wellbeing of employees.

Health Care Expenditure and Income: A Global Perspective

This paper investigates the long-run economic relationship between healthcare 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 analysed. 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. Copyright

Geographical variations in expenditure of learning disability services in England

This article investigates the determinants of local authority Learning Disability (LD) expenditure in England. It adopts a reduced form of demand and supply model, extended to account for possible interdependence between municipalities. Risk factors such as ‘people aged under 14’, ‘mortality rate’ and ‘lone parents’ seem to play an important role in explaining geographical variation of spending. Further, labour municipalities on average allocate lower resources on LD than do other political parties. Finally, results corroborate recent findings in economics that authorities interact with each other when allocating public resources.

Spatial Health Econometrics

The objective of this chapter is to introduce the reader to Spatial Health Econometrics (SHE). In both micro and macro health economics there are phenomena that are characterised by a strong spatial dimension, from hospitals engaging in local competitions in the delivery of health care services, to the regional concentration of health risk factors and needs. SHE allows health economists to incorporate these spatial effects using simple econometric models that take into account these spillover effects. This improves our understanding of issues such as hospital quality, efficiency and productivity and the sustainability of health expenditure of regional and national health care systems, to mention a few.

Sparse Estimation of Huge Networks with a Block‐Wise Structure

Networks with a very large number of nodes appear in many application areas and pose challenges for traditional Gaussian graphical modelling approaches. In this paper, we focus on the estimation of a Gaussian graphical model when the dependence between variables has a block‐wise structure. We propose a penalized likelihood estimation of the inverse covariance matrix, also called Graphical LASSO, applied to block averages of observations, and we derive its asymptotic properties. Monte Carlo experiments, comparing the properties of our estimator with those of the conventional Graphical LASSO, show that the proposed approach works well in the presence of block‐wise dependence structure and that it is also robust to possible model misspecification. We conclude the paper with an empirical study on economic growth and convergence of 1,088 European small regions in the years 1980 to 2012. While requiring a priori information on the block structure – e.g. given by the hierarchical structure of data – our approach can be adopted for estimation and prediction using very large panel data sets. Also, it is particularly useful when there is a problem of missing values and outliers or when the focus of the analysis is on out‐of‐sample prediction.

New evidence in health economics

The 2nd Health Econometrics Workshop took place at the Catholic University of Rome in Italy on 15–17 July 2010. The purpose of this meeting was to provide a forum where policy makers, economists and econometricians could discuss the use of statistical and econometric methods to address issues in the field of health economics. There were seven keynote speakers – leading scholars in the subject – invited to give their contributions: Alberto Holly, Stephen Hall, Badi Baltagi, William Greene, Andrew Jones, John Mullahy and Edward Norton. The meeting was attended by 50 participants from around the world, and 17 scientific papers were presented. Some of these works will be published in the forthcoming special issue of Empirical Economics.