International migration and the rise of the ‘civil’ nation

Scholars largely agree that immigration policies in Western Europe have switched to a liberal, civic model. Labelled as ‘civic turn’, ‘civic integration’ or ‘liberal convergence’, this model is not identically applied across countries, since national institutions, traditions and identifications still matter. Even so, the main focus is on processes which allow or prevent migrants to be incorporated into nations usually taken for granted in their meanings. Moving from policies to discourses, this article aims to interrogate what kind of nation is behind these policies as a way to further scrutinise the ‘civic turn’. Exploring how the term ‘civility’ and its adjectivisations are discursively deployed in Italian parliamentary debates on immigration and integration issues, the article points to two opposite narratives of nation. While one mobilises civility in order to rewrite the nation in terms of a common, inclusive, civic ‘we’, the other uses civility to reaffirm the conflation between national identity and the identity of the ethno-cultural majority. These findings suggest the importance of exploring the ‘civic turn’ not only across countries, but also across political parties within the same country to capture the ways in which a liberal, civic convergence in political discourses might hide divergent national boundary mechanisms.     

Reputational cues in repeated trust games

The importance of reputation in human societies is highlighted both by theoretical models and empirical studies. In this paper, we have extended the scope of previous experimental studies based on trust games by creating treatments where players can rate their opponents’ behavior and know their past ratings. Our results showed that being rated by other players and letting this rating be known are factors that increase cooperation levels even when rational reputational investment motives are ruled out. More generally, subjects tended to respond to reputational opportunities even when this was neither rational nor explainable by reciprocity.     

A Resampling Algorithm for Chaotic Time Series

In the field of chaotic time series analysis, there is a lack of a distributional theory for the main quantities used to characterize the underlying data generating process (DGP). In this paper a method for resampling time series generated by a chaotic dynamical system is proposed. The basic idea is to develop an algorithm for building trajectories which lie on the same attractor of the true DGP, that is with the same dynamical and geometrical properties of the original data. We performed some numerical experiments on some short noise-free and high-noise series confirming that we are able to correctly reproduce the distribution of the largest finite-time Lyapunov exponent and of the correlation dimension.     

On the Representation of Incomplete Preferences Over Risky Alternatives

We study preferences over lotteries which do not necessarily satisfy completeness. We provide a characterization which generalizes Expected Utility theory. We show in particular that various sure-thing axioms are needed to guaranteee the representability in terms of utility intervals rather than numbers, and to provide a linear interval order representation which is very much in the spirit of Expected Utility theory.     

Can we declare military Keynesianism dead?

This paper empirically tests the Keynesian hypothesis that government defence spending positively impacts on aggregate output, by using a long-run equilibrium model for the US and the UK.Our contribution, with respect to previous works, is twofold. First, our inferences are adjusted for structural breaks exhibited by the data concerning fiscal and monetary variables. Second, we take into account different dynamics between defence spending on aggregate output, showing that the results are sensitive to sub-sample choices. Though the estimated elasticities in both countries show a lack of significance in the more recent years of the sample, defence-spending priorities addressed to international security may revitalize pro-cyclical effects in the UK, by an industrial policy of defence shared with the EU members.     

A finite mixture model for multivariate counts under endogenous selectivity

We describe a selection model for multivariate counts, where association between the primary outcomes and the endogenous selection source is modeled through outcome-specific latent effects which are assumed to be dependent across equations. Parametric specifications of this model already exist in the literature; in this paper, we show how model parameters can be estimated in a finite mixture context. This approach helps us to consider overdispersed counts, while allowing for multivariate association and endogeneity of the selection variable. In this context, attention is focused both on bias in estimated effects when exogeneity of selection (treatment) variable is assumed, as well as on consistent estimation of the association between the random effects in the primary and in the treatment effect models, when the latter is assumed endogeneous. The model behavior is investigated through a large scale simulation experiment. An empirical example on health care utilization data is provided.     

Regional mismatch and unemployment: theory and evidence from Italy, 1977–1998

We describe the functioning of a two-region economy characterized by asymmetric wage setting. Labour market tightness in the leading-region affects wages in the whole economy. In equilibrium, net labour demand shifts towards the leading region raise unemployment elsewhere and leave regional wages unchanged, causing an increase in aggregate unemployment. Based on SHIW micro-data on earnings, we find strong evidence that wages in Italy only respond to Northern unemployment. We estimate that around 33% of the increase in Italian unemployment during 1977–1998 can be explained by regional mismatch, mainly due to an excess labour supply growth in the South.

INFORMATION SHARING IN COMMON AGENCY: WHEN IS TRANSPARENCY GOOD?

When should principals dealing with a common agent share their individual performance measures about the agent's unobservable effort for producing a public good? In a model with two principals who offer linear incentive schemes, we show that information sharing always increases total expected welfare if the principal who is less informed about the agent's effort also cares more about the agent's output. If the less‐informed principal cares somewhat (but not too much) less than the other principal about the agent's output, information sharing reduces total expected welfare. In our model the efficient information regime emerges as an equilibrium outcome. (JEL: D82, D86, M52)     

Generalized linear mixed joint model for longitudinal and survival outcomes

Longitudinal studies often entail categorical outcomes as primary responses. When dropout occurs, non-ignorability is frequently accounted for through shared parameter models (SPMs). In this context, several extensions from Gaussian to non-Gaussian longitudinal processes have been proposed. In this paper, we formulate an approach for non-Gaussian longitudinal outcomes in the framework of joint models. As an extension of SPMs, based on shared latent effects, we assume that the history of the response up to current time may have an influence on the risk of dropout. This history is represented by the current, expected, value of the response. Since the time a subject spends in the study is continuous, we parametrize the dropout process through a proportional hazard model. The resulting model is referred to as Generalized Linear Mixed Joint Model (GLMJM). To estimate model parameters, we adopt a maximum likelihood approach via the EM algorithm. In this context, the maximization of the observed data log-likelihood requires numerical integration over the random effect posterior distribution, which is usually not straightforward; under the assumption of Gaussian random effects, we compare Gauss-Hermite and Pseudo-Adaptive Gaussian quadrature rules. We investigate in a simulation study the behaviour of parameter estimates in the case of Poisson and Binomial longitudinal responses, and apply the GLMJM to a benchmark dataset.