Elisa Tosetti

Skill Dispersion and Firm Productivity: An Analysis with Employer‐Employee Matched Data

We study the relation between workers’ skill dispersion and firm productivity using a unique data set of Italian manufacturing firms with individual records on all their workers. Our measure of skill is the individual worker’s effect from a wage equation. We find that a firm’s productivity is positively related to skill dispersion within occupational status groups (production and nonproduction workers) and negatively related to skill dispersion between these groups. Consistently, most of the overall skill dispersion is within and not between firms. These findings are consistent with some recent hierarchical models of the firms’ organizational structure.

Health Expenditure and Income in the United States

This paper investigates the long-run economic relationship between health care expenditure and income in the US at a State level. Using a panel of 49 US States over the period 1980-2004, we study the non-stationarity and co-integration between health spending and income, ultimately measuring income elasticity of health care. The tests we adopt allow us to explicitly control for cross-section dependence and unobserved heterogeneity. Specifically, in our regression equations we assume that the error has a multifactor structure, which may capture global shocks and local spill overs in health expenditure. Our results suggest that health care is a necessity rather than a luxury, with an elasticity much smaller than that estimated in other US studies. Further, we detect significant spatial concentration in US health spending. Our broad perspective of cross-section dependence as well as the methods used to capture it give new insights on the debate over the relationship between health spending and income.

A REVIEW AND COMPARISON OF TESTS OF CROSS‐SECTION INDEPENDENCE IN PANELS

In this paper we review and compare diagnostic tests of cross-section independence in the disturbances of panel regression models. We examine tests based on the sample pairwise correlation coefficient or on its transformations, and tests based on the theory of spacings. The ultimate goal is to shed some light on the appropriate use of existing diagnostic tests for cross-equation error correlation. Our discussion is supported by means of a set of Monte Carlo experiments and a small empirical study on health. Results show that tests based on the average of pairwise correlation coefficients work well when the alternative hypothesis is a factor model with non-zero mean loadings. Tests based on spacings are powerful in identifying various forms of strong cross-section dependence, but have low power when they are used to capture spatial correlation. Copyright

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

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.

Stochastic Frontier Models for Long Panel Data Sets: Measurement of the Underlying Energy Efficiency for the OECD Countries

In this paper we propose a general approach for estimating stochastic frontier mod- els, suitable when using long panel data sets. We measure efficiency as a linear combi- nation of a finite number of unobservable common factors, having coefficients that vary across firms, plus a time-invariant component. We adopt recently developed economet- ric techniques for large, cross sectionally correlated, non-stationary panel data models to estimate the frontier function. Given the long time span of the panel, we investigate whether the variables, including the unobservable common factors, are non-stationary, and, if so, whether they are cointegrated. To empirically illustrate our approach, we estimate a stochastic frontier model for energy demand, and compute the level of the “underlying energy efficiency” for 24 OECD countries over the period 1980 to 2008. In our specification, we control for variables such as Gross Domestic Product, energy price, climate and technological progress, that are known to impact on energy consumption. We also allow for hetero- geneity across countries in the impact of these factors on energy demand. Our panel unit root tests suggest that energy demand and its key determinants are integrated and that they exhibit a long-run relation. The estimation of efficiency scores points at European countries as the more efficient in consuming energy.