Recurrence in Workers' Compensation Claims: Estimates from a Multiple Spell Hazard Model

This paper estimates both single and multiple spell hazard models using a sample of workers' compensation claims (with soft tissue musculoskeletal injuries) from Ontario, Canada. Most of the results in this paper are consistent with the estimates in the existing literature. However, the duration elasticities for workers' compensation benefits and pre-injury earnings from the multiple spell hazard models are much larger than the estimates from the single spell models. This suggests that the estimates in existing literature that use single spell hazard models may underestimate the effect of benefits and pre-injury earnings on the duration of soft tissue musculoskeletal claims.     

Learning to detect deception from three communication channels

A Lie Detection Test—a videotape of senders delivering truthful and deceptive messages—was administered to subjects via one of three channels: Face only, speech only, or face plus speech. Feedback information, identifying the messages as truthful or deceptive, was given to some subjects (learning condition) but not to others (control). It was found that subjects in the learning condition performed better overall relative to control subjects, regardless of the channel presented to them. In addition, however, accuracy of subjects in the learning condition improved progressively over the course of the test (relative to control), for the speech only and face plus speech channels but not for the face only channel. This effect was interpreted in terms of the limited number of deception cues offered by the face.     

Decomposition by subpopulations of the Zenga-84 inequality curve and the related index $$\zeta $$: an application to 2014 Bank of Italy survey

Statistical Methods & Applications - This paper describes an innovative procedure to decompose by subpopulations the values assumed by the Zenga-84 inequality curve Z(p). This decomposition...     

Robust estimation of dynamic fixed-effects panel data models

This paper extends an existing outlier-robust estimator of linear dynamic panel data models with fixed effects, which is based on the median ratio of two consecutive pairs of first-order differenced data. To improve its precision and robustness properties, a general procedure based on higher-order pairwise differences and their ratios is designed. The asymptotic distribution of this class of estimators is derived. Further, the breakdown point properties are obtained under contamination by independent additive outliers and by the patches of additive outliers, and are used to select the pairwise differences that do not compromise the robustness properties of the procedure. The proposed estimator is additionally compared with existing methods by means of Monte Carlo simulations.     

‘I Became a Mom’: Identity Changes in Mothers Receiving Public Assistance

ABSTRACT

This phenomenological study used individual, semistructured, face-to-face interviews to explore motherhood experiences among 15 women receiving public assistance in a large urban area on the West coast. A primary phenomenon observed was that motherhood was described as an experience of identity change, with resulting emotional, behavioral, and sense-of-self changes. Within this broad theme, two categories emerged: the experience and process of change, and consequences of change. It was concluded that motherhood may serve as an important catalyst for change in some women and that the context of poverty is essential for understanding the motherhood experience. These results suggest that interventions aimed at leveraging emerging motherhood identities may be beneficial in setting women on the path out of poverty, drug addiction, and incarceration. Future research should examine the consequences of maternal change within the specific context of the stages of change documented in the recovery process from drug addiction.     

Measuring the Behavioural Component of the S&P 500 and its Relationship to Financial Stress and Aggregated Earnings Surprises

Scholars in management and economics have shown increasing interest in isolating the behavioural dimension of market evolution. Indeed, by improving forecast accuracy and precision, this exercise would certainly help firms to anticipate economic fluctuations, thus leading to more profitable business and investment strategies. Yet, how to extract the behavioural component from real market data remains an open question. By using monthly data on the returns of the constituents of the S&P 500 index, we propose a Bayesian methodology to measure the extent to which market data conform to what is predicted by prospect theory (the behavioural perspective), relative to the (standard) subjective expected utility theory baseline. We document a significant behavioural component that reaches its peaks during recession periods and is correlated to measures of financial volatility, market sentiment and financial stress with expected sign. Moreover, the behavioural component decreases around macroeconomic corporate earnings news, while it reacts positively to the number of surprising announcements.     

Innovation through tradition in the Italian coffee industry: an analysis of customers’ perceptions

The extant literature reveals how firms may innovate by exploiting past competencies and resources, hence proposing innovation through tradition as an emerging strategy to compete. Previous research largely demonstrates that the effectiveness of an innovation strategy is strictly dependent on the capability of firms to communicate the right message to their customers. Therefore, leveraging products’ attributes becomes fundamental to strategically position their commercial offerings in the minds of the target audience. Nevertheless, despite the well-known relevance of this issue, scant attention has been devoted to investigate the product attributes that consumer’s associate with innovation and with tradition when companies deploy strategies based on “innovation through tradition”. Accordingly, our study aims at covering this gap, by empirically analyzing the consumers’ perception of innovation and tradition in the Italian coffee industry through a positioning analysis. Our research allowed us to identify two sets of product attributes that consumers associate with innovation and tradition. The results show that in many cases the innovation-related and tradition-related attributes are strongly negatively correlated, but in some case the correlation is weak or close to zero. These attributes reveal that in some cases innovation and tradition can be combined in the perception of consumers, rather than representing opposite constructs. This result suggests that companies can effectively communicate the strategy of innovation through tradition to the consumers’ minds, but this must be done by choosing the right attributes.     

On generalized semi-Pareto and semi-Burr distributions and random coefficient minification processes

A characterization of Pareto type III distribution is obtained. As a generalization of the Pareto distribution, a new class of distributions called the generalized Pareto distributions is introduced and a characterization of this class is obtained. We introduce a new class of autoregressive models with semi-Pareto marginals and study its properties. As a generalization of semi-Pareto distribution, we introduce semi-Burr distribution and develop a random coefficient autoregressive model with semi-Burr marginal distributions.