Social Indicators Research最新文献

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.

The United Nations’ Human Development Index remains a widely used and accepted measure of human development. Although it has been revised over the years to address various critiques, a remaining concern is the way the three dimensions are aggregated into the single index. A deterioration in one dimension can be compensated for by an improvement in another. Since compensability is inextricably linked with trade-offs and intensity of preferences, a non-compensatory (i.e., Condorcet) approach to aggregation is employed in this paper. Although non-compensatory approaches have been employed previously, this paper adds to the literature by undertaking an application of the Condorcet approach to the entire HDI. This approach, which does not use intensities of preferences, ensures that the degree of compensability connected with the aggregation model is at the minimum possible level. To achieve this, country level rankings are then compared to those for the 2020 Human Development Index which aggregates dimensions using a geometric mean. The findings demonstrated substantial changes in rank-order between the HDI and Condorcet approach. This outcome provides empirical evidence which demonstrates that the non-compensatory Condorcet approach can mitigate issues of compensation present within the geometric aggregation technique currently employed by the HDI. These findings have potential implications in aiding the identification and employment of potential policy priorities—specifically, the notion that policy should emphasise the development of a country as opposed to economic growth alone.

Abstract

This study aims to improve the measurement of multidimensional poverty for the purpose of analyzing gender differences while considering the limitations of household surveys. To effectively analyze gender disparities, it addresses three issues that are often overlooked in the literature: disregard for within-household inequalities in household-level indicators; disregard for ineligible populations in indicators that represent only a specific group; and disregard for intermediate deprivation situations in cutoff-based poverty estimations. Using data from the Brazilian Consumer Expenditure Survey 2017–2018, we create two indexes with indicators that are key aspects in gender and feminist analyses. Applying a fuzzy approach and the Alkire–Foster method, we estimate multidimensional poverty and gender differences from three perspectives: intrahousehold, interhousehold, and intracouple. We also calculate inequality among the poor and intracouple gender gaps proposing fuzzy versions for these analyses. The main findings suggest that women are disadvantaged in terms of work and time quality, economic security, and access to resources—all of which are crucial components of agency or degree of empowerment.

This paper explores the dynamics of social exclusion as measured by material and social deprivation in the particularly exposed category of single-parent households. We aim to assess whether there is true state dependence in deprivation and the role of other household factors, as well as that of the macro-economic and social welfare scenario. We use 2015–2018 European Union Statistics on Income and Living Conditions longitudinal data to explore a large set of European countries. We estimate three-level dynamic probit models that enable us to account for micro- and country-level unobserved heterogeneity. Our results suggest that material and social deprivation is likely to be a trap for single-parent households and that this effect is stronger for these households than for those composed of two adults and children. Among single-parent households, those headed by a female are worse off than those headed by a male. The policy implications of these findings are also discussed.

The abundance of country-level socio-economic development indices is of limited help unless sub-country-level indices on the quality of policies are also available. Tracing the regional indices landscape of India, this study proposes the state-level Environment Policy Stringency Index for Indian states. Capturing Indian states' policies across six areas with weight determination done deploying principal component analysis and Data Envelopment Analysis-Benefit of Doubt approach, the composite index calculated in the study also examines the scores grouping the sub-national units based upon the income levels. Besides ranking for inter-state comparison, the proposed index is significantly associated with particulate matter pollution levels in states. This study has three key contributions: conceptualising the principal-based sub-national index while making a case for developing sub-country level policy indices, identifying state-level environment policy variables and constructing an Environment Policy Stringency Index for Indian states.

Addressing South Asia’s poverty, this research presents an exhaustive case study of Pakistan, exploring poverty dynamics at national and provincial levels, emphasizing the urban–rural divide. The study uses the most recent income and expenditure surveys from 2013 and 2015 and applies the Cost of Basic Needs methodology based on strong theoretical and empirical grounds. The research adjusts for price variation within and among provinces. It uses traditional Foster-Greer-Thorbecke measures and innovative measures like the Watts and Sen indices. Findings reveal a poverty decline in Pakistan between 2013 and 2015, with significant provincial variations in this decline. Despite a minor decline in the headcount ratio of the larger provinces, their poverty shares increased in 2013–15, showing a regional convergence trend with growing disparities in poverty headcount and depth. Using indices like Watts and Sen gives a more complete, nuanced poverty understanding, highlighting the need for their adoption alongside traditional measures. The research ends with policy implications, emphasizing the importance of targeted poverty reduction strategies to address regional disparities effectively. This research offers insights into South Asia’s poverty dynamics and contributes significantly to SDG 1—ending poverty. The Pakistan case study is a valuable reference for other countries, guiding accurate poverty measurement, effective policy-making, and efficient SDGs performance tracking.