Quaderni di Dipartimento [serie ordinaria – Anno 2019]

We analyse how the availability of immigrant workers in the elderly care sector affects the labour force participation of Italian females aged between 45 and 65. We estimate a selection bias correction model and exploit an IV strategy based on the role of migration networks in determining the geographical distribution of immigrants over time. Our main findings show that the local availability of foreign–born caregivers has a positive impact on the number of hours worked by Italian women, especially those with high–educational levels and living in the Northern regions. The effect on participation rates are instead positive and significant only for low–educated women and for women living in Central Italy.

A recent reform in the Italian labour market has modified the permanent contract by reducing firing costs. Using a discontinuity in the application of the reform, we evaluate its the effect on the probability of being still employed 600 days later. In contrast with theoretical predictions, we find that the job survival probability is not smaller for the treated and even significantly larger in some cases. We investigate the composition of permanent workers hired after the reform, as we find evidence of treated firms hiring workers eligible for a significant reduction of non-wage labour costs.

We study the retirement effects on mental health using a fuzzy regression discontinuity design based on the eligibility age to the state pension in the Netherlands. We find that the mental effects are heterogeneous by gender and marital status. Retirement of partnered men positively affects mental health of both themselves and their partners. Single men retiring experience a drop in mental health. Female retirement has hardly any effect on their own mental health or the mental health of their partners. Part of the effects seem to be driven by loneliness after retirement.

Panel logit models have proved to be simple and effective tools to build Early Warning Systems (EWS) for financial crises. But because crises are rare events, the estimation of EWS does not usually account for country fixed effects, so as to avoid losing all the information relative to countries that never face a crisis. I propose using a penalized maximum likelihood estimator for fixed-effects logit-based EWS where all the observations are retained. I show that including country effects, while preserving the entire sample, greatly improves the predictive power of EWS with respect to the pooled, random-effects and standard fixed-effects models.

This paper addresses the question of the relevance of macroeconomic determinants in forecasting the evolution of stock markets volatilities and co-volatilities. Our approach combines the Cholesky decomposition of the covariance matrix with the use of the Vector Logistic Smooth Transition Autoregressive Model. The model includes predetermined variables and takes into account the asymmetries in volatility process. Structural breaks and nonlinearity tests are also implemented to  determine the number of regimes and to identify the transition variables. The model is applied to realized volatility of stock indices of several countries in order to evaluate the role of economic variables in predicting the future evolution of conditional covariances. Our results show that the forecast accuracy of our model is signicantly dierent from the accuracy of the forecasts obtained via other standard approaches.

Aim of this paper is to propose new bipolarization indices based on he Bonferroni and De Vergottini indices of inequality.The new bipolarization indices follow the approach of Foster and Wolfson and are based on new subgroup decomposition of Bonferroni and De Vergottini indices of inequality. We also provide the conditions under which the new polarization indices satisfy the Increased Spread and Increased Bipolarity axioms. Finally, a simulation study has been carried out to compare the different sensitivity of the new bipolarization indices to progressive transfers. Also, an empirical application based on EU-SILC data for Italy ober the period 2007-2011 show the appeal of our proposal. 

We study the impact of the domestic stability pact on the budget forecast errors of Italian municipalities. The identification of the causal effect exploits a quasi-natural experiment generated by the removal in 2001 of the fiscal restraints on budget decisions for municipalities with less than 5,000 inhabitants and by stricter budgetary restrictions and severe penalties for noncompliers in 2002. We find that relaxing fiscal rules had a sizeable impact on budget forecast errors, especially in 2002. Revenue (expenditure) forecast errors for municipalities below 5,000 inhabitants became indeed 26% (22%) larger than in the past.

The aim of this study is to investigate the exact nature of Phillips' (1958) findings. We show that the application of the simplest type of wavelet basis function developed by Haar in 1910 allows to replicate the output of Phillips' data transformation procedure,
i.e. the six mean coordinates. Specifically, the resemblance between the coarsest scale level coefficients from the Haar wavelet filter and the six crosses suggests the long-term nature of Phillips' (wage-unemployment) relationship. The application of the Haar wavelet filter allows us to examine the effects of two main features of Phillips' 'unorthodox' averaging procedure: the arbitrarily choice of variable-width intervals and the choice of sorting observations in ascending order of unemployment rate values. Our results show that the arbitrary selection of intervals affects only the smoothness (regularity) of the nonlinear pattern of the wage-unemployment relationship, but not its shape which is determined by sorting and grouping unemployment rate values in ascending order. Indeed, when observations are ordered according to a chronological sequence a simple linear relationship is evident. These findings are robust to different samples, 1861-1913 and 1861-1958.

We study how unemployment benefit eligibility affects the layoff exit rate by exploiting quasiexperimental variation in eligibility rules in Italy. By using a difference-in-differences estimator, we find an instantaneous increase of about 12% in the layoff probability when unemployment benefit eligibility is attained, which persists for about 16 weeks. These findings are robust to different identifying assumptions and are mostly driven by jobs started after the onset of the Great Recession, in the South and for small firms. We argue that the moral hazard from the employer's side is the main force driving these layoffs.

This paper provides a micro-econometric analysis of the factors facilitating the introduction of responsible innovations by firms, with a focus on those aimed at improving occupational health and safety. These innovations have been rarely investigated with quantitative methods, especially if compared to those aimed at protecting the environment. Accordingly, we also assess whether firms pursuing health and safety innovations are also those ascribing high importance to the reduction of environmental impacts. The evidence provided by using firm-level data taken from the Italian Community Innovation Surveys highlights the key role played by some external sources of knowledge and internal human resource practices for the achievement of responsible innovations. Many similarities but also important differences between firms emerge, according to whether they are committed to health and safety or environmental innovation.

The paper presents an agent based model reproducing a stylized credit network that evolves endogenously through the individual choices of rms and banks. We introduce in this framework a anancial stability authority in order to test the e ects of different prudential policy measures designed to improve the resilience of the economic system. Simulations show that a combination of micro and macro prudential policies reduces systemic risk, but at the cost of increasing banks' capital volatility.
Moreover, agent based methodology allows us to implement an alternative meso regulatory framework that takes into consideration the connections between firms and banks. This policy targets only the more connected banks, increasing their capital requirement in order to reduce the di usion of local shocks. Our results support the idea that the meso prudential policy is able to reduce systemic risk without a ecting the stability of banks'capital structure.

The welfare impact of immigration is a hot topic especially for countries at the external borders of the European Union. This paper studies how immigrants affect public health expenditure across Italian regions during the period 2003-2015. Identification strategy is based on shift{share instruments, which are also robust to pull factors that might attract immigrants in Italy and to internal migration of natives. We find that a 1 percentage point increase in immigrants over total population leads to a decrease in public health expenditure per capita by about 3.9% (i.e. around 70 euro per capita). This evidence is confirmed when focusing on needy immigrants from low income countries with less developed welfare systems. Among possible channels, we find no
support for any crowding out effects from public to private health services by natives due to increasing immigration neither for the effect of entry barriers limiting the immigrants' reliance on public healthcare. Our results are driven by immigrants' demographic structure: foreigners are mostly males and younger workers that call for less health spending, according to a positive selection mechanism.