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Equivalence scales for the cost of children are estimated for one of the most developed Italian region (Lombardia) through the Engel approach. The data set is obtained from the survey on household consumption expenditures, which is hold by the Italian Central Institute for Statistics (ISTAT) in 1997, 1998, 1999 and 2000. The estimation of equivalence scales is not restricted to the share devoted to food. Besides the usual share of food and non-alcoholic beverages, 1w, we specify four further shares of necessities. The results obtained in this research show that in estimating equivalence scales through Engel curves it is very important to specify in control variables to take account for heterogeneity among families. Though the food share can still be a valid indicator to compare family welfare and then to estimate equivalence scales, in some situations it results to be misleading. The experiment of adopting broader good aggregates as indicators gives interesting results and more like...

In our research we apply a new technique of opinion analysis over Twitter data to propose a new indicator of perceived and subjective well-being: The SWBI examines many dimension of individual and social life. In the purpose to investigate whether SWBI and its single components may adequately represent the reaction of a community to changes in everyday life conditions, we propose a comparative analysis, among the Italian provinces, of perceived well-being, measured with SWBI, with objective well-being, measured with the "Il Sole 24 Ore" QoL Index. The idea is to create a composite well-being indicator which mixes stable official statistics and fluctuating social media data.

The new smartphone-based food diagnostic technologies offer significant advantages over traditional methods as they can be easily applied in various steps of the agrifood supply chain including household use and also in the food recovery field for charitable purposes, aimed at helping to reduce food waste. Further advantages include the low cost, the minimal equipment, and nonspecialized personnel required. This study evaluated the performance of two instrumental measurements of the sensors: an electronic nose (PEN3; WinMuster Airsense Analytics) and a smart portable device (FOODsniffer; ARS LAB US). The preliminary study was conducted on cape hake fillets. In order to test the performance of PEN3 and FOODsniffer, total volatile basic nitrogen (TVB-N) values were considered as the reference. Principal component analysis (PCA) and Pearson’s correlation were performed in order to compare PEN3 with TVB-N, and for the FOODsniffer evaluation, a one-way ANOVA was carried out. A significan...

With the increase of social media usage, a huge new source of data has become available. Despite the enthusiasm linked to this revolution, one of the main outstanding criticisms in using these data is selection bias. Indeed, the reference population is unknown. Nevertheless, many studies show evidence that these data constitute a valuable source because they are more timely and possess higher space granularity. We propose to adjust statistics based on Twitter data by anchoring them to reliable official statistics through a weighted, space-time, small area estimation model. As a by-product, the proposed method also stabilizes the social media indicators, which is a welcome property required for official statistics. The method can be adapted anytime official statistics exists at the proper level of granularity and for which social media usage within the population is known. As an example, we adjust a subjective well-being indicator of “working conditions” in Italy, and combine it with...

In this paper, we focus on a Bayesian network s approach to combine traditional survey and social network data and official statistics to evaluate well-being. Bayesian networks permit the use of data with different geographical levels (provincial and regional) and time frequencies (daily, quarterly, and annual). The aim of this study was twofold: to describe the relationship between survey and social network data and to investigate the link between social network data and official statistics. Particularly, we focused on whether the big data anticipate the information provided by the official statistics. The applications, referring to Italy from 2012 to 2017, were performed using ISTAT’s survey data, some variables related to the considered time period or geographical levels, a composite index of well-being obtained by Twitter data, and official statistics that summarize the labor market.

We propose using high order partial least squares path modeling (PLS-PM) to define a synthetic Italian well-being index merging traditional data, represented by the Quality of Life index proposed by “Il Sole 24 Ore”, and information provided by big data, represented by a Subjective Well-being Index (SWBI) performed extracting moods by Twitter. High order constructs allow to define a more abstract higher-level dimension and its more concrete lower-order sub-dimensions. These layered constructs have gained wide attention in applications of PLS-PM; many contributions in literature proposed their use to build composite indicators. The aim of the paper is to underline some critical issues in the use of these models and to suggest the implementation of a new adapted repeated indicator approach. Furthermore, following some recommendations proposed on the use of PLS-PM in longitudinal studies, we compare the situation in 2016 and 2017.

This paper applies a novel technique of opinion analysis over social media data with the aim of proposing a new indicator of perceived and subjective well-being. This new index, namely SWBI, examines several dimension of individual and social life. The indicator has been compared to some other existing indexes of well-being and health conditions in Italy: the BES (Benessere Equo Sostenibile), the incidence rate of influenza and the abundance of PM10 in urban environments. SWBI is a daily measure available at province level. BES data, currently available only for 2013 and 2014, are annual and available at regional level. Flu data are weekly and distributed as regional data and PM10 are collected daily for different cities. Due to the fact that the time scale and space granularity of the different indexes varies, we apply a novel statistical technique to discover nowcasting features and the classical latent analysis to study the relationships among them. A preliminary analysis suggest...

The literature on well being measurement seems to suggest that "asking" for a self-evaluation is the only way to estimate a complete and reliable measure of well being. At the same time "not asking" is the only way to avoid biased evaluations due to self-reporting. Here we propose a method for estimating the welfare perception of a community simply "listening" to the conversations on Social Network Sites. The Social Well Being Index (SWBI) and its components are proposed through to an innovative technique of supervised sentiment analysis called iSA which scales to any language and big data. As main methodological advantages, this approach can estimate several aspects of social well being directly from self-declared perceptions, instead of approximating it through objective (but partial) quantitative variables like GDP; moreover self-perceptions of welfare are spontaneous and not obtained as answers to explicit questions that are proved to bias the resul...

Interest in the well-being measurement is constantly increasing worldwide, especially due to the Stiglitz Commission suggestions, which opened several questions about its assessment and theoretical framework. This paper focuses on the Italian scenario due to the central role given to this topic by the Italian Parliament, which introduces equitable and sustainable well-being among the objectives of the government’s economic and social policy. Significant differences exist among the proposed Italian well-being indices in terms of theoretical approach, statistical rigour and aims. We propose a detailed outline of these indices useful for policy-makers, practitioners, economists and statistics scholars, with the awareness that for a good analysis, a complete and conscious description of the data is the starting point to further improve their usefulness, to maximise their advantages and to cut down their limitations.

Several studies provide evidence of the role of written communication in influencing public perception towards genetically modified organisms, whereas visual communication has been sparsely investigated. This article aims to evaluate the exposure of the Italian population to scary genetically modified organism-related images. A set of 517 images collected through Google are classified considering fearful attributes, and an index that accounts for the scary impact of these images is built. Then, through an ordinary least-squares regression, we estimate the relationship between the Scary Impact Index and a set of variables that describes the context in which the images appear. The results reveal that the first (and most viewed) Google result images contain the most frightful contents. In addition, the agri-food sector in Italy is strongly oriented towards offering a negative representation of genetically modified organisms. Exposure to scary images could be a factor that affects the n...

This paper studies the relationships between adherence to the Mediterranean diet, food-related information, and possible effects they could jointly exert on weight status. The empirical analysis was conducted via a consumer survey using face-to-face interviews, and a structural equation model was implemented to the data analysis. This model choice was led by its ability to simultaneously evaluate multiple constructs. The results outline the central role played by adherence to the Mediterranean diet and food-related information, both in terms of nutritional knowledge and expert recommendations, which seem to be the key drivers affecting healthy weight. Moreover, food label use increases the nutritional knowledge of consumers, which in turn favours a healthy diet. 

Introduzione Nell'attuale situazione di instabilità socio-economica i percorsi lavorativi delle persone sono sempre più frammentati e segnati da frequenti transizioni lavorative. Dati gli elevati costi personali e sociali legati al rimanere senza lavoro, un obiettivo importante delle politiche del lavoro è quello di attivare condizioni idonee a ridurre i tempi della transizione da un'occupazione a un'altra. La ricerca psicologica da tempo contribuisce a questa sfida indagando le risorse personali che possono agire come fattori facilitanti o, al contrario, ostacolanti la ricerca di un nuovo lavoro. Entro questo filone di ricerca, in questi ultimi anni, una grande enfasi è stata posta sul costrutto di perceived employability (occupabilità percepita-d'ora in poi PE), definito da Bernston (2008) come le credenze dell'individuo circa le proprie chance di trovare un nuovo lavoro. Tali percezioni sono influenzate sia dalle caratteristiche individuali sia dalle caratteri...

Recentemente diversi autori hanno dedicato attenzione al problema delle variabili di controllo. Nonostante le molte raccomandazioni suggerite per gestire queste variabili in modo pi\uf9 efficiente, le buone pratiche sono ancora ampiamente \ub4 ignorate, in particolare questo argomento non e stato ancora approfondito nei modelli ad equazioni strutturali. Questo lavoro propone alcune linee guida a chi deve utilizzare le variabili di controllo nei modelli ad equazioni strutturali con stima dei minimi quadrati parziali.Several authors have recently devoted more attention to the control variables methodological issue. Despite many recommendations to handle these variables more ef\ufb01ciently, good practices are still widely disregarded, and especially this topic has not yet been studied in depth for structural equation models. This paper suggests best research practices for researchers who deal with the use of control variables in partial least squares structural equation models