On Italian Households’ Economic Inadequacy Using Quali-Quantitative Measures

Motivated by an interest in investigating factors associated with poverty risks in Italy, our study provides insight into the relationship between various socio-economic, demographic, and behavioural variables and a new measure of the economic inadequacy of households. We propose that a household is in a condition of economic inadequacy when it simultaneously has difficulty making ends meet and is in arrears with payments of commitments for more than 90 days. To analyse the determinants of economic inadequacy, we use cross-sectional microdata collected through a structured questionnaire from a 2012 survey of household income and wealth conducted by the Bank of Italy. The results of the analysis show that the probability of economic inadequacy for Italian households is higher when the household is located in regions in southern Italy, has a low equivalent income, registers a decrease in income compared with that of a normal year, has a low liquidity ratio, pays rent for the house of residence, is over-indebted, is indebted to friends and relatives, and has an unhappy and impatient household head. We also propose constructing a composite indicator at the regional level that combines the percentage of households in relative poverty, as measured by the Italian National Institute of Statistics, and the percentage of households that we identify as existing in a condition of economic inadequacy. The composite indicator allows us to take into account some aspects of household living conditions that are not included in the measure of relative poverty.     

CUSTOMER OWNERSHIP AND QUALITY PROVISION IN PUBLIC SERVICES UNDER ASYMMETRIC INFORMATION

The implementation of projects producing external effects is often a source of disagreement and conflict between hosting and nonhosting communities. The article focuses on the impact of participatory ownership on conflict resolution and social welfare in the presence of asymmetric information and imperfect quality monitoring. We show that in such situations the participatory solution may help solve deadlocks that money transfers to a for‐profit operator cannot solve. The analysis highlights three main factors behind this fact. First, a customer‐owned cooperative internalizes, at least partially, the external effects generated by the project. Second, the alignment of cooperative members' preferences with those of the social planner reduces (in some cases eliminates) the distortions caused by information asymmetries. Third, cooperatives require less costly monitoring than their for‐profit counterparts. We also show that cooperatives' productive inefficiency with respect to for‐profits may emerge endogenously as a consequence of a lower pressure to compete on costs for the market. (JEL H23, L33, P13)     

Regional Well-Being and its Inequality in the OECD Member Countries

This paper analyses the inequality between the regions of the Organization for Economic Co-operation and Development (OECD) member countries by using stochastic multi-objective acceptability analysis and the associated multivariate Gini index. By considering a large number of possible combinations of weights, the distribution of the potential rankings for each region is used to measure multidimensional inequality both within and between countries. Our results show that beyond the expected two clubs of rich and poor countries, a third group of countries emerges that belongs neither to the top nor to the bottom of the ranking, an outcome that can be attributed to the presence of significant economic differences among regions within those countries. Most of the inequality lies between countries, but regional well-being also significantly varies within the same countries and we find an inverse U-shape connection between regional well-being and its inequality within the OECD member countries.

     

A neural network clustering model for miscellaneous components production planning

The growing importance of providing service to customers, e.g. post-sale assistance, supplying of spare parts, upgrading and integration of new elements in installed systems, enhances the importance of planning and management of upgrading parts in most manufacturing industries. These parts are generally characterized by high technical heterogeneity and have a highly variable and difficult to forecast demand. In some areas (especially the most dynamic, e.g. high-tech products), these kinds of components are quite common, and represent a very strong relation between the manufacturing firm and the market. These parts are generally too many to be efectively supported on a planning database system with individual records and too heterogeneous ( and sometimes with a too high value) to be supported all together in a single record. In this paper, we want to study the application of adaptive techniques for the clustering of these components in classes based on the similarities in their market behaviour in order to build an optimal database for planning production and supplying of these components.     

Using Expert Models in Human Reliability Analysis—A Dependence Assessment Method Based on Fuzzy Logic

In human reliability analysis (HRA), dependence analysis refers to assessing the influence of the failure of the operators to perform one task on the failure probabilities of subsequent tasks. A commonly used approach is the technique for human error rate prediction (THERP). The assessment of the dependence level in THERP is a highly subjective judgment based on general rules for the influence of five main factors. A frequently used alternative method extends the THERP model with decision trees. Such trees should increase the repeatability of the assessments but they simplify the relationships among the factors and the dependence level. Moreover, the basis for these simplifications and the resulting tree is difficult to trace. The aim of this work is a method for dependence assessment in HRA that captures the rules used by experts to assess dependence levels and incorporates this knowledge into an algorithm and software tool to be used by HRA analysts. A fuzzy expert system (FES) underlies the method. The method and the associated expert elicitation process are demonstrated with a working model. The expert rules are elicited systematically and converted into a traceable, explicit, and computable model. Anchor situations are provided as guidance for the HRA analyst's judgment of the input factors. The expert model and the FES‐based dependence assessment method make the expert rules accessible to the analyst in a usable and repeatable way, with an explicit and traceable basis.     

A Social‐Cognitive Model of Pandemic Influenza H1N1 Risk Perception and Recommended Behaviors in Italy

The outbreak of the pandemic influenza H1N1 2009 (swine flu) between March and April 2009 challenged the health services around the world. Indeed, misconceptions and worries have led the public to refuse to comply with precautionary measures. Moreover, there have been limited efforts to develop models incorporating cognitive, social‐contextual, and affective factors as predictors of compliance with recommended behaviors. The aim of this study was to apply a social‐cognitive model of risk perception and individual response to pandemic influenza H1N1 in a representative sample of Italian population. A sample of 1,010 Italians of at least 18 years of age took part in a telephone survey. The survey included measures of perceived preparedness of institutions, family members and friends’ levels of worry, exposure to media campaigns (social‐contextual factors), perceived coping efficacy, likelihood of infection, perceived seriousness, personal impact, and severity of illness (cognitive evaluations), affective response and compliance with recommended behaviors. Results demonstrated that affective response fully mediated the relationship between cognitive evaluations and social‐contextual factors (with the exception of exposure to media campaigns) and compliance with recommended behaviors. Perceived coping efficacy and preparedness of institutions were not related to compliance with recommended behaviors.     

The optimum growth rate for population under critical-level utilitarianism

We characterize optimal consumption, capital, and population growth of a production economy under critical-level utilitarianism. First, we show that neither classical utilitarianism nor average utilitarianism can avoid a corner solution for the population growth rate, in that under the former, population grows at the maximum speed (the so-called repugnant conclusion) while under the latter, it grows at the minimum. Second, we show that critical level utilitarianism yields an interior solution for the population growth rate provided the critical level belongs to a positive, open interval. Finally, we characterize the transition to the steady state and perform comparative dynamics analysis.     

CAN LONG‐RUN RESTRICTIONS IDENTIFY TECHNOLOGY SHOCKS?

Galí's innovative approach of imposing long‐run restrictions on a vector autoregression (VAR) to identify the effects of a technology shock has become widely utilized. In this paper, we investigate its reliability through Monte Carlo simulations using calibrated business cycle models. Overall, Galí's methodology appears to be fruitful: the impulse responses derived from the artificial data generally have the same sign and qualitative pattern as the true responses, and the approach can be informative in discriminating between alternative models. However, our results reveal some important quantitative shortcomings, including considerable estimation uncertainty about the impact of technology shocks on macroeconomic variables. More generally, the conditions under which the methodology performs well appear considerably more restrictive than implied by the key identifying assumption. This underscores the importance of using economic models to guide in the implementation of the approach, in interpreting the results, and in assessing its limitations. (JEL: C32, E32, O33)