A Bootstrap Test for Circular Data

In this article, variance stabilizing filters are discussed. A new filter with nice properties is proposed which makes use of moving averages and moving standard deviations, the latter smoothed with the Hodrick-Prescott filter. This filter is compared to a GARCH-type filter. An ARIMA model is estimated for the filtered GDP series, and the parameter estimates are used in forecasting the unfiltered series. These forecasts compare well with those of ARIMA, ARFIMA, and GARCH models based on the unfiltered data. The filter does not color white noise.     

Environmental and economic assessment for the optimal configuration of a sustainable solid waste collection system: a ‘kerbside’ case study

The article presents a case study concerning the improvement of the ‘kerbside’ waste collection system, now increasingly implemented in many Italian municipalities, as an alternative to traditional bring collection, with the aim of increasing the quality of waste collection and the collection rate, in order to reduce the final impact on the environment. A planning model for an integrated waste management system based on kerbside collection is presented. A heuristic procedure is also applied in order to obtain some admissible solutions of the real problem in reasonable computational time. The economic and environmental impacts are considered as significant elements for the evaluation and validation of the obtained solutions. Five alternative configurations of kerbside system, diverging in number of sub-area, synchrony of vehicles and directionality of the arcs, are compared in an economic point of view. Finally, Life-Cycle Assessment is used as a tool to compare the overall potential environmental impacts of the alternative of kerbside collection systems and also to compare the kerbside system with the traditional bring one. The different scenarios of kerbside system are comparable in terms of damage on the impact categories, while the bring system is the worst one, in terms of damage on human health, in the consumption of resources and also for the total damage score.     

Parameterized complexity of k-anonymity: hardness and tractability

The problem of publishing personal data without giving up privacy is becoming increasingly important. A precise formalization that has been recently proposed is the k-anonymity, where the rows of a table are partitioned into clusters of sizes at least k and all rows in a cluster become the same tuple after the suppression of some entries. The natural optimization problem, where the goal is to minimize the number of suppressed entries, is hard even when the stored values are over a binary alphabet or the table consists of a bounded number of columns. In this paper we study how the complexity of the problem is influenced by different parameters. First we show that the problem is W[1]-hard when parameterized by the value of the solution (and k). Then we exhibit a fixed-parameter algorithm when the problem is parameterized by the number of columns and the number of different values in any column. Finally, we prove that k-anonymity is still APX-hard even when restricting to instances with 3 columns and k=3.     

Evidence of Convergence Clubs Using Mixture Models

Cross-country economic convergence has been increasingly investigated by finite mixture models. Multiple components in a mixture reflect groups of countries that converge locally. Testing for the number of components is crucial for detecting “convergence clubs.” To assess the number of components of the mixture, we propose a sequential procedure that compares the shape of the hypothesized mixture distribution with the true unknown density, consistently estimated through a kernel estimator. The novelty of our approach is its capability to select the number of components along with a satisfactory fitting of the model. Simulation studies and an empirical application to per capita income distribution across countries testify for the good performance of our approach. A three-clubs convergence seems to emerge.     

A dwindling middle class? Italian evidence in the 2000s

In recent years, increasing attention has been paid to household impoverishment in Italy. Most of previous analyses dealing with this issue are based on summary statistics, which may not capture the whole income distribution. This paper employs a non-parametric tool, the “relative distribution”, to describe patterns of changes in the entire Italian household income distribution over the period 2000–2004. This approach also allows for a decomposition of the relative density to isolate changes due to differences in location from changes due to differences in shape, thus enabling deeper analysis of income polarization. During the 2000s there was a significant location effect, and also increased income polarization, which has particularly affected incomes below the median. Analyses by social groups, according to the employment status of the household head, show significant re-distribution effects within groups.     

Some computational aspects of the generalized von Mises distribution

This article deals with some important computational aspects of the generalized von Mises distribution in relation with parameter estimation, model selection and simulation. The generalized von Mises distribution provides a flexible model for circular data allowing for symmetry, asymmetry, unimodality and bimodality. For this model, we show the equivalence between the trigonometric method of moments and the maximum likelihood estimators, we give their asymptotic distribution, we provide bias-corrected estimators of the entropy, the Akaike information criterion and the measured entropy for model selection, and we implement the ratio-of-uniforms method of simulation.     

The tone of business model disclosure: an impression management analysis of the integrated reports

The rising emphasis on the business model (BM) as a reportable element reflects the view that it constitutes one of the key starting points for investors’ analysis. In spite of this, recent academic and professional studies describe current reporting on BMs as uninformative: too optimistic, generic and incomplete. The International Integrated Reporting Council (IIRC) claims that these limitations may be overcome by means of an “Integrated Report”, an innovative report which is expected to offer a complete and balanced representation of how organizations create value by mean of their BMs. The paper investigates the informativeness of BM disclosure questioning whether companies adopt impression management (IM) strategies by manipulating the tone of the BM disclosures provided in their reports. We perform a manual content analysis of all the reports identified in the IIRC website and a multivariate statistical analysis to assess if a positive tone of BM disclosure is significantly associated with weak corporate governance, bad performance and low verifiability of the disclosure itself. Our findings support the idea that managers use BM disclosure as an IM strategy. This evidence has relevant implications for both accounting scholars and practitioners, since it questions the role of integrated reporting in improving corporate reporting on BMs.     

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.