Social Indicators Research最新文献

Social identity is relevant to political attitudes. Recent studies show that perceived social positions particularly shape populist attitudes. Italy is an interesting test case that has been scarcely investigated by previous research. Thus, using original data collected in 2021, this paper analyses populist attitudes in Italy and the relationship between subjective social status, status mismatch, and social resentment. This study finds that subjective status matters more than objective conditions for populist attitudes. Those who perceive themselves as being at the bottom of the social hierarchy tend to have higher levels of populist attitudes than the rest of the population. However, low social resentment can partially absorb the effect of low status. The paper provides original data from which novel insights into the debate on populism are discernible, appearing to stem more from individual perceptions than objective positions. The results also suggest some possible remedies against rising populist attitudes.

Little research has been done on parents’ coordination of their work arrangements during the COVID-19 pandemic. Synchronized work arrangements (e.g., both parents work from home) could enable working parents to maximize their togetherness, whereas desynchronized working arrangements could enable them to address some pandemic-induced challenges, such as an increased need for child care and distance education. We draw upon the Familydemic Harmonized Dataset a cross-county study offering data on work and family outcomes collected in Canada, Germany, Italy, Poland, Sweden, and the US. Using a sample of dual-earner heterosexual parents, this study examines whether working parents harmonized their transitions between home-based work and the workplace during the COVID-19 pandemic and explores factors that potentially contributed to this coordination process. The findings reveal that working couples’ transitions to home-based work from the workplace were synchronized. Parents with similar educational attainment were more likely to experience such coordination than couples with different levels of education. Cohabiting couples in married/registered unions were more likely to transition to home-based work simultaneously than non-registered cohabiting couples. The duration of synchronized home-based work episodes decreased with the number of children, and the length of synchronized workplace attendance increased with the age of the children.

This paper explores the cause-and-effect relationship between the elderly population and global economic growth, focusing on different continents. A panel dataset spanning from 1961 to 2020 is utilized, with Gross Domestic Product (GDP) serving as the key measure for economic growth, represented as the percentage change in annual GDP. The study specifically centers on individuals aged 65 and above as a percentage of the total population. The analysis employs a Panel Granger causality test to assess the impact of the elderly population on economic growth. The results reveal a unidirectional Granger causality for Africa and Oceania, suggesting a one-way influence from the elderly population to economic growth. Conversely, instances of bidirectional Granger causality are identified for Asia, Europe, North America, and South America, indicating a mutual influence between the elderly population and economic growth during the study period. The study concludes that an endogenous relationship between economic growth and the elderly population emerges, but notably, this relationship becomes apparent only after an economy has completed its transition in economic development. This implies that the dynamics of the elderly population and economic growth are interlinked, with the nature of their interaction becoming more pronounced in the later stages of economic development.

Water–energy–food (WEF) risks and security are widely concerned, but there are few quantitative studies on WEF security assessment, especially lacking of researches at the urban scale. This paper puts forward a measurement framework for assessing urban WEF security from social and economic perspectives, including dimensions of availability, accessibility, affordability, safety, and stability, and applies it to the WEF security assessment in the Yangtze River Delta urban agglomeration (YRDUA) by using an extended Multi-attribute Border Approximation Area Comparison (MABAC) method based on cloud model-CRITIC method and game theory. Based on the evaluation, social network analysis is used to study relations between cities in urban WEF security and determines key cities in the network. Results show that urban WEF security in most cities are positive; five dimensions of the WEF security level in each city show unbalanced characteristics; the level of energy security varies greatly among cities, followed by water and food security; urban WEF security from an economic perspective in most cities are positive, while it from a social perspective in almost half cities are positive; the spatial relation network of urban WEF security in YRUDA presents a core–edge structure; key cities in the region include Suzhou, Wuxi, and Changzhou. The evaluation framework and models help comprehensively evaluate urban WEF security at social and economic levels and put forward suggestions to enhance urban WEF security and promote horizontal cooperation among cities.

Over the last two decades, involuntary part-time (IPT) employment has become a more and more pressing issue in Europe, especially in the southern countries, where IPT today constitutes most part-time employment. Using INAPP-PLUS data and different discrete choice model estimations, this paper aims to shed light on the factors that explain the IPT growth in Italy, focusing on what influences the IPT status at the individual, household and labour market levels. The main hypothesis is that what influences the IPT work derive from a combination of workers’ individual, household, and job characteristics which may engender limited power during the bargaining process. The empirical results, based on gender-specific models, highlight that characteristics associated with the IPT status significantly changed over time, reporting a convergent path between the gender profiles of IPT employment. However, IPT employment for women still appears to be mainly originated from the gendered division of domestic and care tasks, while this phenomenon seems to be mainly driven by the labour demand side for men.

Intimate partner violence (IPV) is a worldwide issue. One of the latest developments in its theoretical framework deals with the concept of polyvictimisation – the simultaneous occurrence of physical, emotional, and sexual abuse. However, the literature lacks an overall measure of violence for surveys. The aim of this research is to study IPV within the framework of the ecological model. A model-based composite indicator that takes into account the relationship between domestic abuse and individual characteristics of respondents, family dynamics, and community and societal traits is built using survey data. The data are from the Demographic and Health Survey collected in eleven African countries on women aged 15–49. The employed structural equation model shows the importance of individual characteristics while community and societal factors are less relevant. The composite indicator is also used for classification and ranking purposes, allowing areas where socio-educational interventions are more urgent to be identified.

Is the association between debt and feeling of depression so fundamental that it occurs across time and place? Are some countries better at mitigating the depression related to debt than others? This paper addresses these questions by taking advantage of three harmonised longitudinal surveys, consisting of older adults in 21 European countries and the US. A series of logistic regression models show that, net of differences in other socioeconomic variables, people with household non-mortgage debt have higher odds of depression, measured using dichotomised versions of depressive symptom scores, in all countries. These associations are in many countries as strong as the association between low education level and depression. The association is particularly strong in countries with poor debt discharge legislation or low levels of indebtedness, both of which may be regarded as indicators of stigma related to debts. Overtime the association between debt and depression seems to be elevated within countries when the unemployment rate increases. These findings demonstrate how the links between debt and mental health are embedded in its institutional and economic contexts.

Exogenous events have the potential to affect citizens’ risk-perceptions, (in)security sentiments, electoral choices, policy preferences and institutional trust levels. It has been shown that migrant and refugee flows also affect citizens’ trust and policy preferences. The 2015 refugee crisis as it has come to be known, shook Europe’s cohesion and tested the existing immigration and asylum policies as well as acted as a further stimulus to populist/right wing Eurosceptic parties with an agenda of anti-immigrant restrictive policies. Expectedly, it has attracted considerable attention in the relevant literature. Building on existing studies that examine various aspects associated with the 2015 refugee crisis, the present paper examines its effect on institutional trust levels in Europe. Specifically, it focuses on trust towards the national government, the EU and the two state security services the police and the armed forces. To this effect, the study draws data from successive Eurobarometer surveys before and after the crisis. Employing segmented-type regression models as well as Oaxaca decomposition models it probes into the 2015 refugee crisis’ impact on the levels of institutional trust using over 400,000 responses to the relevant Eurobarometer questions. The results reported herein suggest the presence of “a rally around the flag effect”. Nonetheless, macroeconomic factors such as GDP growth and unemployment as well as differences in behavioural responses also explain a large part of the observed gap in trust before and after the 2015 refugee crisis.

This study introduces an innovative tool to analyse how various inequality factors, including geography, race, and gender, contribute to overall inequality. Traditional approaches typically partition populations into groups based on a single factor and assess inequality by additively decomposing an inequality measure into within- and between-group components. After discussing the theoretical impossibility of additively decomposing the Gini index into within- and between-group components, in fact, we propose a Gini decomposition into two highly informative within- and between-components, with substantial improvement upon the usual assessment of horizontal inequality. This method represents a significant advancement over the traditional horizontal inequality assessment, which only compares group means and overlooks the complexities of differences between groups. Our approach accurately captures the nuances of group disparities, offering a robust measure of horizontal inequality. Through rigorous simulations and empirical analysis of the OECD Income Distribution Database, we validate the effectiveness of our method in evaluating and understanding inequality. This work enriches the toolkit available to researchers in the field by offering a framework for selecting the most suitable measure of horizontal inequality, along with the code for implementing the proposed decomposition.

In this paper we estimate the Head Count Ratio (HCR) and two fuzzy poverty measures at provincial level in Morocco using data from the Household Budget Survey (HBS). As the sample size is not always sufficient to provide reliable direct estimates, we use a Fay–Herriot model with additive logistic transformation and meteorological covariates to obtain estimates with lower mean squared errors. Among our main results, we find out that the Fuzzy Monetary measure provides more accurate estimates than the Head Count Ratio when conducting small area estimation exercises. Also, we empirically notice that the set of covariates at our disposal allows us to obtain better estimates for each supplementary poverty measure that we identify.