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The purpose of this paper is to study the impact of unemployment on coronary heart diseases (CHD) in Italy on a sample of male manual workers in the private sector.

The authors investigate the association between CHD and different unemployment experiences (ever unemployed; short, mid and long cumulative unemployment), exploiting a large Italian administrative database on careers and health. The study design is based on the balancing of individuals' characteristics during a 12-year pre-treatment period; the measurement of unemployment occurrence during a seven-year treatment period; the observation of CHD occurrence during a five-year follow up. The workers characteristics and the probability of receiving the treatment are balanced by means of propensity score matching. Standard diagnostics on the balancing assumption are discussed and satisfied, while the robustness to violations of the unconfoundedness assumption is evaluated by a simulation-based sensitivity analysis.

The authors find a significant increase of CHD probability was found among workers who experience more than three years of unemployment (relative risks (RR)=1.91, p<0.1), and among those who exit unemployment starting a self-employment activity (RR=1.70, p<0.1). Using different selections of the study population, a clear pattern emerges: the healthier and more labour market attached are workers during pre-treatment, the greater is the negative impact of long-term unemployment on health (RR=2.79, p<0.01).

The very large representative sample (n=69,937) and the deep longitudinal dimension of the data (1985-2008) allowed the authors to minimize the risks of health selection and unemployment misclassification. Moreover, the adopted definition of unemployment corrected some undercoverage and misclassification issues that affect studies based on a purely administrative definition and that treat unemployment as a unique career event disregarding the duration of the experience.

The purpose of this paper is to study the factors affecting the return to work (RTW) of injured workers in an institutional setting where workers’ earnings are fully compensated during the disability period.

The authors use a unique data set matching employer-employee panel data with Italian workers’ compensation records. The authors estimate survival models accounting for workers’ unobserved heterogeneity.

Workers with higher wage growth, higher relative wages and from firms with better histories of stable employment, RTW sooner. More vulnerable workers – immigrants, females, members of smaller firms – also tend to return sooner. But even when we control for such measures of commitment, status, and job security, high-wage workers RTW sooner.

The authors use proxies as measures of commitment and status. The authors study blue-collar workers without finer job qualifications. The authors estimate a reduced form model.

In an institutional environment where the immediate cost of workers’ compensation benefits falls largely on firms, employers seem to pressure those workers whose time off is more costly, i.e., high-wage workers. The lack of evidence of ex post moral hazard behavior also demands for a better understanding of the relationship between benefits and RTW.

Workers who are induced to RTW before full recovery jeopardize their long- term health and employability. Firms that put such pressure on employees might generate social costs that can be particularity high in the case of high productivity workers.

The paper offers the first quantitative analysis of an institutional setting where injured workers face 100 percent benefits replacement rate and have job security. This allows focus on other workers’ or employers’ reasons to speed RTW. It is one of very few economics studies on this topic in the European context, providing implications for human resource managers, state regulators, and unions.

The purpose of this paper is to take into consideration the propensity to offer vocational training of a large sample of Italian private firms by retrieving cross-sectional data from INDACO (2009).

Estimating a probit model, the author assesses how the age and the gender composition of the employed workforce, as well as a set of relevant corporate characteristics, such as size, sector, geographical location, innovation strategies, R&D investments and use of social safety valves, are linked to the willingness of firms to supply on-the-job training.

First, as far as the average age of the whole employed workforce is concerned, it was found that the propensity of surveyed firms toward training provision follows an inverted U-shaped pattern. Furthermore, it was shown that larger firms have a higher training propensity with respect to small firms, and the same attitude holds for productive units that adopted innovation strategies and/or invested in R&D projects. By contrast, it was found that the propensity to support training activities is negatively correlated to the percentage of employed women and the use social valves.

The sample of business units taken into consideration is quite large, but it has some biases toward larger and manufacturing firms. Moreover, the cross-sectional perspective of the analysis does not allow implementation of the finer identification procedures that can be applied with panel data. Furthermore, the lack of employer – employee linked data does not allow to fully address the issue of compliance to training activities.

From a policy point of view, the results shown throughout the paper suggest some broad guidelines. First, especially in small firms, vocational training for young and older workers should be somehow stimulated. Moreover, as far as mature employees are concerned, those interventions should be framed in an active ageing perspective. Subsidies and targeted job placement programmes are often claimed as being the most appropriate ways to improve the underprivileged position of older workers. However, continuous learning during the whole working life still appears as the most effective device to reduce the employment disadvantages in the older years.

While there are a number of papers that study the age patterns of training participation by using workers’ data retrieved from personnel and/or labour force surveys, this work is the first attempt to provide a probabilistic assessment of the decisions of Italian firms regarding training provision by taking into account the ageing perspectives of the incumbent workforce.