A theory of unanimous jury voting with an ambiguous likelihood

Theory and Decision - We examine collective decision-making in a jury voting game under the unanimity rule when voters have ambiguous beliefs. Unlike in existing studies (Ellis in Theoretical...     

Bayesian Conditional Mean Estimation in Log‐Normal Linear Regression Models with Finite Quadratic Expected Loss

Log‐normal linear regression models are popular in many fields of research. Bayesian estimation of the conditional mean of the dependent variable is problematic as many choices of the prior for the variance (on the log‐scale) lead to posterior distributions with no finite moments. We propose a generalized inverse Gaussian prior for this variance and derive the conditions on the prior parameters that yield posterior distributions of the conditional mean of the dependent variable with finite moments up to a pre‐specified order. The conditions depend on one of the three parameters of the suggested prior; the other two have an influence on inferences for small and medium sample sizes. A second goal of this paper is to discuss how to choose these parameters according to different criteria including the optimization of frequentist properties of posterior means.     

Executive compensation in banks: insights from CEO equity incentives and securitization transactions

This paper investigates whether CEO equity incentives promote risk-taking activities in the financial industry. Prior research shows that, during the recent credit crisis, banks whose CEOs had high equity incentives performed significantly worse than banks whose CEOs had low equity incentives. A possible explanation for this result is that the incentive to boost stock price induced CEOs to take risks that turned out to be extremely costly. Focusing on securitization transactions that were among the fundamental causes of the financial crisis and using a sample of US financial institutions, the paper provides evidence that banks whose CEOs had high equity incentives engaged in securitization transactions to a greater extent than did financial institutions guided by CEOs with low equity incentives. Moreover, the paper shows that CEOs with high equity incentives securitized riskier loans than did CEOs with low incentives. This study helps to clarify the role of equity-based compensation in promoting risk-taking behaviors in banks.     

Modelling work history patterns in the Italian labour market

We focus on work histories of new entrants in 1998 in the Italian labour market. For workers in the private sector, we define a standard and three non-standard history patterns. We profile the workers through a mixed-effect multinomial logit model and show that certain features may be associated with the probability of belonging to one or the other category. Furthermore, we show that there are differential effects on wages associated with non-standard patterns. A closer look at best performing non-standard workers shows that even for them an early contractual stabilization may not always be expected.     

Joint analysis of occurrence and time to stability after entrance into the Italian labour market: an approach based on a Bayesian cure model with structured stochastic search variable selection

Precarious employment is a serious social problem, especially in those countries, such as Italy, where there are limited benefits from social security. We investigate this phenomenon by analysing the initial part of the career of employees starting with unstable contracts for a panel of Italian workers. Our aim is to estimate the probability of getting a stable job and to detect factors influencing both this probability and the duration of precariousness. To answer these questions, we use an ad hoc mixture cure rate model in a Bayesian framework.     

Disability and work intensity in Italian households

Review of Economics of the Household - The 2030 Agenda of the United Nations clearly sets the inclusion of persons with disabilities in the labour market as a main goal. However, especially in care...     

Robust linear mixed models for Small Area Estimation

Hierarchical models are popular in many applied statistics fields including Small Area Estimation. One well known model employed in this particular field is the Fay–Herriot model, in which unobservable parameters are assumed to be Gaussian. In Hierarchical models assumptions about unobservable quantities are difficult to check. For a special case of the Fay–Herriot model, Sinharay and Stern [2003. Posterior predictive model checking in Hierarchical models. J. Statist. Plann. Inference 111, 209–221] showed that violations of the assumptions about the random effects are difficult to detect using posterior predictive checks. In this present paper we consider two extensions of the Fay–Herriot model in which the random effects are assumed to be distributed according to either an exponential power (EP) distribution or a skewed EP distribution. We aim to explore the robustness of the Fay–Herriot model for the estimation of individual area means as well as the empirical distribution function of their ‘ensemble’. Our findings, which are based on a simulation experiment, are largely consistent with those of Sinharay and Stern as far as the efficient estimation of individual small area parameters is concerned. However, when estimating the empirical distribution function of the ‘ensemble’ of small area parameters, results are more sensitive to the failure of distributional assumptions.