Social Indicators Research最新文献

Measuring financial capabilities among young people poses a challenge for scholars. In this study, we developed a set of ten scales to assess various behaviors, attitudes, and knowledge, allowing for a comprehensive examination of the construct. We designed a pool of items and invited 746 participants, aged 16 to 29, who were divided into two groups for studying the psychometric properties of the tests. The first group underwent an Exploratory Factor Analysis, while the second group underwent a Confirmatory Factor Analysis. Through these analyses, we identified five dimensions of financial behaviors, four dimensions of financial attitudes, and one dimension of knowledge or financial literacy. The scales were combined to measure two financial capabilities: Financial Saving Capability and Responsible Debt Management Capability. Furthermore, we identified distinct profiles of young people associated with each proposed financial capability. Finally, we offer a conceptual discussion of the financial capabilities construct, present scales with reliable and valid measurements, and propose avenues for future research.

Currently, extensive empirical studies exist on the impact of financial inclusion on socio-economic outcomes such as economic growth, inequality, and poverty. However, research on financial inclusion and population health is limited and still at the infant stage. Therefore, this article adds to knowledge by inquiring into the health implications of financial inclusion using a global panel dataset for 121 countries between 2004 and 2020. After accounting for endogeneity with heteroskedasticity-based instrumental variable regression and cross-sectional dependency with the Driscol–Kraay estimator, we documented that financial inclusion improves population health outcomes. We found that the effect of financial inclusion on population health outcomes also depends on the level of information and communication technology penetration and existing socio-economic conditions in a country. Following this, we showed that financial inclusion improves population health outcomes in countries with lower income inequality and higher GDP per capita, mobile and internet penetration. We further found heterogeneity in the results across geographical regions and income groups. Following these findings, we suggest that financial inclusion policies could enhance population health.

In the context of sustainable development, urban transformation should encourage the use of life cycle thinking tools for infrastructure development. By adopting sustainable economic, social, and environmental criteria, this study presents a review of sustainability assessment tools to build a framework for urban infrastructure. It incorporates a variety of methods that economists and industrial ecologists use for evaluating their projects, in addition to the LCT approach. To recognize the strategic sustainability indicators and criteria, the framework uses LCC, LCA, and SLCA in conjunction with stakeholder evaluation and multi-criteria decision analysis, which recognizes the foremost three pillars of sustainability, i.e., economy, environment, and society. Additionally, system dynamics and agent-based modelling are used to optimise the framework. The prominence of the framework is to understand the route an urban infrastructure development should follow to achieve key sustainability interests involving the interconnected environmental and socio-economic aspects. This sustainability assessment framework can be utilised by consultants or supporting agencies to help organisations carry out and monitor such projects.

Measuring and predicting price dispersion on the real estate market is an important issue for both investors and policymakers. Price dispersion in the housing market can be seen as an additional dimension for measuring social inequality and one of the main goals of public policies that focus on life satisfaction and the accumulation of permanent wealth. The article considers the Polish real estate market and proposes the prediction methods of four measures of dispersion. They are based on quantiles and allow overall measurement of dispersion. In the prediction of dispersion measures the plug-in predictors utylizing longitudinal mixed models are proposed. Furthermore, the ex ante prediction accuracy measure called the quantile of absolute prediction errors (QAPE) is assessed using the residual bootstrap estimators. QAPE allows for a comprehensive description of the distribution of prediction errors, thus fostering discussion of possible various market scenarios.

Amid the rising prevalence of working from home during the COVID-19 pandemic, scholarly interest in the effects of working from home on the fit between work and family life has regained momentum. However, little is known about whether these effects depend on workers’ role salience levels. This study examines the association between the frequency of working from home and two types of work–family conflict: (a) work-to-family conflict (WTFC) and (b) family-to-work conflict (FTWC). We also examine whether these associations are moderated by the salience workers assign to their work and family roles, as well as by workers’ gender and parenting status. To explore these issues, we apply linear regression analyses to data from 4067 employees in Wave 12 (2019–2020) of the German Family Panel Survey. Results show that working from home more frequently is generally associated with both higher WTFC and FTWC for women but not for men. However, among fathers, we found a significant association between working from home and higher WTFC. A moderated association by role salience, where higher work-role salience reduced the positive effect of working from home on FTWC, also only emerged among women. These results suggest that the link between working from home and the fit between one’s work and family is heterogenous: it varies not only by gender and parenthood status, but also partly by the importance workers assign to their various life roles.

COVID-19 disrupted both social and economic development in several dimensions. Governments of the vast majority of countries implemented strategies to battle the pandemic and its negative consequences. The question is, which countries can be assessed as successful in that matter? In this study, we use empirical tools to investigate which governmental actions and state characteristics appear proper, as reflected by pandemic misery indices. The results of our study imply that fiscal measures taken solely are not enough to confront the negative outcome of the pandemic. Interestingly, a strong rule of law, high government effectiveness, and low corruption seem to help countries get through COVID-19. These conclusions may be useful for policymakers in the context of the current and future negative shocks.

Working with SEM and cross-sectional data, and depending on the studied phenomenon, assuming an acyclic model may mean that we obtain only a partial view of the mechanisms that explain causal relationships between a set of theoretical constructs, given that variables are treated as antecedents and consequences. Our two-step approach allows researchers to identify and measure cyclic effects when working with cross-sectional data and a PLS modelling algorithm. Using the resources and appropriation theory and the sequential model of internet appropriation, we demonstrate the importance of considering cyclic effects. Our results show that opportunities for physical access followed by digital skills acquisition enhance internet usage (acyclic effects), but also that internet usage intensity, in reverse, reinforces both digital skills and physical access (cyclic effects), supporting Norris (Digital divide: civic engagement, information poverty, and the internet worldwide. Cambridge University Press, Cambridge, 2001) social stratification hypothesis regarding future evolution of the digital divide.

This study analyzed how attitudes toward welfare vary or align in Korean society based on the distribution of income and assets. It aimed to identify coalition structures based on income and asset combinations surrounding the current welfare system. The analysis revealed that regardless of income level, groups that have not accumulated sufficient assets are more likely to have positive attitudes when it comes to advocating the expansion of public welfare spending. However, with regard to redistributive policies aimed at addressing social vulnerability, it is evident that there is currently no group capable of forming a coalition with the low-income, low-asset group. Therefore, it can be predicted that in the process of reforming the social security system, an approach of universal welfare policies, providing benefits to the majority of citizens, coupled with additional benefits proportional to the taxes paid, may receive high levels of support.

According to the standards set by the International Labour Office, people of working age who have performed some remunerated work during a specified short reference period are classified as employed, regardless of how many hours they have worked, while those who have not been able to work at all (despite wanting to) are classified as unemployed. As observed by many experts in the field, this rigid division between employed and unemployed can conceal labour markets with deeply different characteristics. In particular, the average number of hours worked and, more importantly, their distribution across employees may vary significantly across countries. The aim of this paper is to define fuzzy indicators of employment and unemployment by using the available information on the number of hours worked and the satisfaction or dissatisfaction of workers with this. In this approach, each person in the labour force is assigned a degree of employment between 0 and 1, where 0 means full non-membership in the fuzzy set of employed (and full membership in the fuzzy set of unemployed) and 1 means full membership in the fuzzy set of employed. To show the potentiality of the proposed method, we apply fuzzy measures to Labour Force Survey data from 29 European countries and compare the results with the official employment and unemployment statistics published by Eurostat.

This article explores the relationship between individuals’ satisfaction with their social life and global life satisfaction during periods of economic prosperity and crisis, using data from the Panel of Social Inequalities in Catalonia, Spain (PaD 2001–2012). The study also investigates how this relationship varies across different social origins. Catalonia is a pertinent context due to its significant increase in inequality and unemployment during the 2008 Economic Crisis, positioning it among the most affected regions in Europe. The findings reveal that satisfaction with one’s social life matters for global life satisfaction, even after accounting for individual and macro characteristics. However, contrary to the initial expectations, the study demonstrates that satisfaction with one’s social life becomes less influential for global life satisfaction during the macroeconomic crisis, particularly among individuals from middle and low social origins. Furthermore, while a strong positive relationship exists between satisfaction with one’s social life and global life satisfaction during times of economic prosperity for all social groups, a robust negative relationship emerges in periods of macroeconomic crisis for individuals from high social origins. The article offers several potential explanations for these findings.