The priorities dilemma in the EU preventive restructuring directive: Absolute or relative priority rule?

The EU Directive on Preventive Restructuring Frameworks gives the EU Member States (“MSs”) the choice between implementing two fairness rules in cross‐class cram‐down: the US‐style absolute priority rule (“APR”) or the newly conceived relative priority rule (“RPR”). This article argues that there is no good reason for the MSs to implement the RPR in domestic law. While the APR effectively protects the rights of the dissenting classes to get what they are entitled to, the RPR increases moral hazard and opportunism. Also, it might make debt investments in the EU unattractive. On top of that, this article shows that the RPR lacks a clear theoretical justification. One of the main reasons why the RPR was introduced in the Directive alongside the APR is that the RPR was thought to provide a solution to some of the APR's problems. This article considers three of those problems (i.e., the “valuation problem”, the “hold‐out problem” and the “problem of the relevant shareholders”) and explains the reasons why the RPR is not an appropriate solution for these. Among these three problems, the most troublesome one, from the perspective of the EU, is that the APR makes it difficult to award value to the equity of SMEs (the “problem of the relevant shareholders”). This article argues that using the RPR to deal with this problem would incentivize the shareholders to behave opportunistically and to orchestrate the restructuring. Instead of the RPR, this article suggests two alternative techniques which MSs can enact to better address the issue: the new value exception “in kind” and the disposable income method.     

Occupations in the European Labour Market During the COVID-19 Pandemic

In order to capture the consequences of the COVID-19 pandemic on the labour market, several aspects need to be taken into account. First, containment measures put in place in member states at different times and with different levels of severity determined the interruption of several economic activities that were considered non-essential. Second, different occupations require varying degrees of physical proximity and social interaction to be carried out; this implies that they can be considered more or less teleworkable, and affected by different levels of epidemiological risk of contagion. This paper shows the labour market impact of the pandemic on different categories of workers in the EU. Occupations are distinguished by three main characteristics: whether they are critical or non-critical, their level of technical teleworkability and the level of social interaction required in the job. We show that the impact of the COVID-19 pandemic on the labour market has been heterogeneous across occupations and that all three dimensions are relevant to determine whether and to what extent the occupations were affected by the pandemic.

     

Which food safety information sources do Italian consumers prefer? Suggestions for the development of effective food risk communication

This study investigated which information sources Italian consumers use most frequently when they have a question about food safety in order to obtain useful insights to inform food risk communication. In 2011, a national survey was conducted targeting Italian people responsible for purchasing and preparing food for their households. Respondents’ choices of information sources on food safety were correlated with their socio-demographic and behavioural characteristics, their levels of objective knowledge, their levels of trust towards some authorities and their levels of self-perception regarding risk exposure. Our data analysis identified those information channels that are most likely to reach Italians actively seeking information. Mass media (radio/television/newspapers) were the most frequently used information source, followed by the Internet. Age, educational qualification, employment status, geographical area, family status and objective knowledge were the variables that influenced the choice for information sources used by the Italian population. The frequency of buying food products, the frequency of eating put and the frequency of cooking also showed a dependency relation. The profiles of those who actively seek information were also outlined. Among these, the Mass media users’ and the Internet users’ profiles were further analysed. Results show that Italian consumers do actively seek information about food safety, revealing that food safety continues to be a concern for the Italian consumers. Their interest in this topic represents an opportunity for public health authorities to address an audience of receptive consumers. Such information will be valuable in the design of targeted communication campaigns to increase consumers’ knowledge and awareness of food safety issues and will help authorities to choose the most effective channels through which to deliver key messages.     

Italian consumers’ attitudes towards food risks: self-protective and non-self-protective profiles for effective risk communication

The study aims to assess Italian consumers’ attitudes towards food risks and seeks to outline their socio-demographic and behavioural characteristics on the basis of their attitudes (self-protective and non-self-protective) towards food risks. Using the Computer-assisted telephone interviewing survey method, a sample of 1000 Italian consumers was interviewed on risk perception issues and general eating habits. Factor analyses on the consumers’ propensities to read the label when buying a food product for the first time, their propensities to seek food-related information and their perceived levels of exposure to food risks have enabled us to define Italian consumers’ attitudes towards food risks. Distinguishing between consumers with more self-protective attitudes and those with less self-protective attitudes and identifying their distinctive socio-demographic and behavioural characteristics (e.g. gender, age, the frequency with which respondents do grocery shopping and the channels used for further inquiry) are crucial for communication campaigns aimed at reducing consumers’ exposure to food risks.     

Innovation dialectics: an extended process perspective on innovation in services

Services are characterised by the involvement of customers and other interest groups in the innovation process. The aim of this study is to understand how and why, in the service context, tensions and potential conflicts between heterogeneous interest groups unfold during processes of innovation. The empirical field in which the investigation was set is facility services, a type of business-to-business support services. The findings were extracted from a longitudinal, in-depth case study of a Danish, multi-national organisation over 13 years, complemented with an explorative study in the Danish facility service context. The findings suggest that tensions and conflicts between heterogeneous interest groups are an intrinsic element of innovation processes in services, and that emphasising them might actually support a clearer understanding of processes of innovation in services. The outcome of the analysis is a process model, which proposes innovation dialectics as one of the driving mechanisms of innovation in services.     

Cross-correlation Measures in the High-frequency Domain

Abstract

On a high-frequency scale the time series are not homogeneous, therefore standard correlation measures cannot be directly applied to the raw data. To deal with this problem the time series have to be either homogenized through interpolation, or methods that can handle raw non-synchronous time series need to be employed. This paper compares two traditional methods that use interpolation with an alternative method applied directly to the actual time series. The three methods are tested on simulated data and actual trades time series.     

GenD An Evolutionary System for Resampling in Survey Research

The paper is a preliminary research report and presents a method for generating new records using an evolutionary algorithm (close to but different from a genetic algorithm). This method, called Pseudo-Inverse Function (in short P-I Function), was designed and implemented at Semeion Research Centre (Rome). P-I Function is a method to generate new (virtual) data from a small set of observed data. P-I Function can be of aid when budget constraints limit the number of interviewees, or in case of a population that shows some sociologically interesting trait, but whose small size can seriously affect the reliability of estimates, or in case of secondary analysis on small samples. The applicative ground is given by research design with one or more dependent and a set of independent variables. The estimation of new cases takes place according to the maximization of a fitness function and outcomes a number as large as needed of ‘virtual’ cases, which reproduce the statistical traits of the original population. The algorithm used by P-I Function is known as Genetic Doping Algorithm (GenD), designed and implemented by Semeion Research Centre; among its features there is an innovative crossover procedure, which tends to select individuals with average fitness values, rather than those who show best values at each ‘generation’. A particularly thorough research design has been put on: (1) the observed sample is half-split to obtain a training and a testing set, which are analysed by means of a back propagation neural network; (2) testing is performed to find out how good the parameter estimates are; (3) a 10% sample is randomly extracted from the training set and used as a reduced training set; (4) on this narrow basis, GenD calculates the pseudo-inverse of the estimated parameter matrix; (5) ‘virtual’ data are tested against the testing data set (which has never been used for training). The algorithm has been proved on a particularly difficult ground, since the data set used as a basis for generating ‘virtual’ cases counts only 44 respondents, randomly sampled from a broader data set taken from the General Social Survey 2002. The major result is that networks trained on the ‘virtual’ resample show a model fit as good as the one of the observed data, though ‘virtual’ and observed data differ on some features. It can be seen that GenD ‘refills’ the joint distribution of the independent variables, conditioned by the dependent one. This paper is the result of deep collaboration among all authors. Cinzia Meraviglia wrote § 1, 3, 4, 6, 7 and 8; Giulia Massini wrote §5; Daria Croce performed some elaborations with neural networks and linear regression; Massimo Buscema wrote §2.     

REMITTANCES AND FINANCIAL DEVELOPMENT: SUBSTITUTES OR COMPLEMENTS IN ECONOMIC GROWTH?

Recent studies indicate that the effect of migrants’ remittances on the economic growth of receiving countries depends negatively on the level of development of the domestic financial sector. In this paper, we introduce a new indicator of financial development to measure the efficiency of the domestic banking system, and find the existence of complementarity between remittances and bank efficiency in economic growth, such that remittances promote growth only in countries whose banks function well. This result is robust to controls for other traditional measures of financial depth and institutional quality indicators.     

Herding effects in order driven markets: The rise and fall of gurus

We introduce an order driver market model with heterogeneous traders that imitate each other on a dynamic network structure. The communication structure evolves endogenously via a fitness mechanism based on agents performance. We assess under which assumptions imitation, among noise traders, can give rise to the emergence of gurus and their rise and fall in popularity over time. We study the wealth distribution of gurus, followers and non followers and show that traders have an incentive to imitate and a desire to be imitated since herding turns out to be profitable. The model is then used to study the effect that different competitive strategies (i.e. chartist & fundamentalist) have on agents performance. Our findings show that positive intelligence agents cannot invade a market populated by noise traders when herding is high.     

Interval regression models with endogenous explanatory variables

We consider the estimation of linear models where the dependent variable is observed by intervals and some continuous regressors may be endogenous. Our approach, an IV version of the technique devised by Stewart (Rev Econ Stud 50(3):737?C753, 1983), is fully parametric and two estimators are proposed: a two-step estimator and a limited-information maximum-likelihood estimator. The results can be summarized as follows: the two-step estimator has an intuitive appeal, and a Monte Carlo experiment suggests that its relative efficiency is rather satisfactory. The limited-information maximum-likelihood estimator, however, is probably simpler to implement and has the advantage of providing a framework in which several testing procedures are more straightforward to perform. The application of two-stage least squares to a proxy of the dependent variable built by taking midpoints, on the other hand, leads to inconsistent estimates; Monte Carlo evidence suggests that the bias arising from the ??midpoint?? technique is much worse than the effect of distributional misspecification. An example application is also included, which uses Australian data on migrants?? remittances; endogeneity effects are substantial and using conventional estimation methods leads to substantially misleading inference.