Social Indicators Research最新文献

Abstract

Increasing clothing (over)consumption, supported by the fast fashion industry, has caused a significant reduction in clothing costs, raised major sustainability challenges, and highlighted the need for engaging in more sustainable consumption behaviour to mitigate the negative environmental, social, and economic consequences. Although green purchase behaviour is now well understood, extant literature still lacks a comprehensive approach to explain consumers behaviour (especially that of the younger generations) with respect to sustainable clothing. Using survey data collected through a structured questionnaire, this study aims to assess whether Generation Z is more inclined to buy sustainable or eco-friendly clothing than Generation Y. Given the non-random selection of respondents, analysis was conducted using propensity score matching to correct for potential bias based on a set of observable confounders. The results show that Generation Z is more likely to buy second-hand clothing, whereas Generation Y is more interested in clothes made of organic and eco-sustainable fabrics.

Studies on social vulnerability have been consolidated as indispensable for understanding the risks of natural disasters, as well as for the constitution of efficient management strategies to face disasters. Using usual methodologies to determine the dimension of risks, this study presents and discusses social vulnerability at the intra-urban municipal scale, in order to contribute to the understanding of sustainability from social factors, besides subsidizing the integration between citizens and managers in a Brazilian case. Information on the criticality of populations and their disaster response capacity was considered, using public data available in a national database. The analysis of the main components and the cartographic representation of the data resulted in 24 variables, aggregated into five dimensions of analysis for criticality, and in 22 variables, which composed seven dimensions for response capacity. As a product of these two dimensions, it was observed that peripheral areas, with low income, lacking infrastructural resources and close to water bodies are the most socially vulnerable. The methodological strategy adopted can be applied at other scales of analysis. It also provides a basis for the design of actions and planning that contemplate the participation of multiple social actors for possible resilience, besides providing an opportunity for discussions on disaster vulnerability as an indispensable variable for urban sustainability.

The “traditional view” on the historical decline of child labour has emphasised the role of the approval of effective child labour (minimum working age) laws. Since then, the importance of alternative key driving factors such as schooling, demography, household income or technology has been highlighted. While historically leading countries such as England and industrial labour have been studied, peripheral Europe and a full participation rate also including agriculture and services have received limited research attention. The contribution of this paper is to provide a first empirical explanation for the child labour decline observed in a European peripheral country like Portugal using long historical yearly data. For doing so, we use long series of Portugal’s child labour participation rate and several candidate explanatory factors. We implement cointegration techniques to relate child labour with its main drivers. We find that not only factors related to the “traditional view” were important for the Portuguese case. In fact, a mixture of legislation, schooling, demography, income, and technological factors seem to have contributed to the sustainable fall of Portugal’s child labour. Hence, explanations for observed child labour decline seem to differ by country and context, introducing a more nuanced view of the existing literature.

This study examines the effects of educational attainment and household income on wealth accumulation in Vietnam using various Vietnam Household Living Standards Surveys (VHLSSs) in 2008, 2018 and 2020. We use the threshold regression to separate households into different groups depending on their assets. We find that owning a university degree is optimal to maximize wealth accumulation for households in 2008. However, post-graduate qualifications are needed for wealth accumulation in 2018 and 2020. For those household heads without a university degree, owning advanced training certificates provides the best opportunity to accumulate household wealth in all three surveys. Besides, our empirical results confirm that household income played no role in wealth accommodation in 2008. Interestingly, household income positively contributes to wealth accumulation for households with assets above the threshold of VND 634.40 m in 2020. However, the effect is negative for households with assets below the threshold of VND 440.25 m in 2018. We also find that households with widowed or divorced household heads are associated with lower wealth accumulation. Another interesting finding is that living in urban areas reduces wealth accumulation for households whose assets are below VND 440.25 m in 2018. These findings largely remain unchanged when Lewbel’s (Lewbel, Journal of Business and Economic Statistics 30:67–80, 2012) instrument variable estimator is used to ensure the robustness of the empirical results.

By means of probabilistic graphical models, in this paper, we present a new framework for exploring relationships among indicators commonly included in the Multidimensional Poverty Index (MPI). In particular, we propose an Ising model with covariates for modeling the MPI as an undirected graph. First, we prove why Ising models are consistent with the theoretical distribution of MPI indicators. Then, a comparison between our estimates and the association measures typically used in the literature is provided. Finally, we show how undirected graphs can complement the MPI policy-relevant properties, apart from discovering further insightful patterns that can be useful for policy purposes. This novel approach is illustrated with an empirical application for the global MPI indicators of Guinea and Ecuador, taking living areas and monetary poverty as covariates, respectively.

The literature on atypical employment has largely focused on the individual level. This paper provides a novel account of the dynamics of atypical employment, specifically part-time and temporary employment, within couples. Analyzing a sample of 29 European countries using 2016 EU-SILC data, it investigates the association between partner and own atypical employment. The results show that temporary employment does come in couples, in that partner temporary employment is associated with a higher likelihood of own temporary employment. A significant portion of this result is driven by individuals with partners in temporary employment themselves exhibiting characteristics predisposing them to temporary employment. These results are largely consistent across Europe. Accumulation of part-time employment is also observed, albeit at a smaller scale. However, it occurs at the two extremes of the income distribution only, among very low-earning and very high-earning couples. In contrast, in the middle of the income distribution, there is no association between partner and own part-time employment, which is more consistent with classic household specialization patterns. An association between partner and own part-time employment is only found in a minority of European countries, most systematically in Northern and Western Europe, but also in some Southern and Eastern European countries.

This article compares the properties of individual- and household-based multidimensional child poverty approaches. Specifically, it contrasts UNICEF’s multiple overlapping deprivation analysis (MODA) with the Global Multidimensional Poverty Index (MPI) developed by the Oxford Poverty and Human Development Initiative. MODA focuses on children and is rooted in the child rights approach, while MPI has been developed for households and follows Sen’s (1985) capabilities approach. We demonstrate their similarities and differences using two recent multiple indicator cluster surveys: Sierra Leone and Lao People’s Democratic Republic. The analysis suggests that MODA tends to produce higher multidimensional child poverty headcount rates than MPI, both because of the differences in the survey items used to construct the indicators of deprivation and because of how the indicators are aggregated and weighted. The study also shows that both MODA and MPI are highly sensitive to the exclusion of any one indicator from the analysis. Thus it is crucial to have valid information on the same indicators when tracking multidimensional poverty over time, e.g. for monitoring progress towards the sustainable development goals. Yet they are both robust to reductions in deprivation on just one indicator, suggesting that policies targeting only one component of the overall index would have a limited impact on the MD deprivation rate.

The Metropolitan Economic Freedom Index (MEFI) ranks cities based on their support of free market enterprise. In its current state, MEFI purports to measure three constructs (government spending, taxation, and labor market freedom) with three equally weighted variables for each one, assuming perfect substitutability of variables. This study investigates the statistical consistency of MEFI through Confirmatory Factor Analysis. Multiple models investigate current variable selection by providing a potentially better indicator of labor market freedom, aggregation assumptions by removing the requirements for fixed and equal weights, and statistical consistency by evaluating the fit between the data and models. Results indicate that the current MEFI model is not statistically consistent with the data, that weighting of variables should not be equal, that variable selection should be investigated, and that constructs should be re-imagined. The models investigated provide an initial starting point for redefining MEFI.

Italy is characterised by a significant dualistic economy, which also includes an extensive underground sector. The aim of this study is to analyse the relationship between the quality of legislation and irregular employment in Italy. Our contribution consists of two components: the theoretical modelling of the impact of regulatory quality on the informal economy and the empirical validation of the predictions of the theoretical model using data from the Italian region between 2004 and 2019. The results confirm the theoretical and empirical arguments in favour of the need for laws to curb the informal sector. The regions with the highest institutional standards tend to have a lower percentage of irregular workers that fosters and encourages the legality of the labor market. Some robustness tests back up the main conclusions which show how important following rules is for strengthening the internal economy and for lowering the number of illegal workers.

The gender dimension of the Sustainable Development Goals (SDG) is integral to the goals established to foster the development of nations, as it is intertwined with other goals and enhances their attainability. Thus, this study examines 28 indicators belonging to the goals of the sustainable development objectives, distinguishing between the gender SDGs (6 indicators) and other SDGs (22 indicators), all of which were reported by 110 countries in the year 2023. The assessment considers four regions: the African continent (28 countries), the Americas region (21 countries), Asia-Oceania (29 countries), and Europe (32 countries). The STATICO multivariate technique is used (consisting of four Co-inertia analyses and one Partial Triadic Analysis) to study the interactions among the indicators. The goal is to determine whether differences or similarities exist between these indicators within each region and to make a comparative assessment across countries. The study’s findings show the existing covariances between the various targets of the 2030 Agenda and indicate that in Europe, the gender dimension is more closely integrated with the other SDGs than in the other regions. In Africa, substantial variations between countries are observed, while Asia, Oceania, and the Americas face challenges in specific indicators and countries in terms of achieving sustainable development.