Labor force composition and underemployment trends, 1969–1980

Underemployment indicators are both ‘objective’ indicators of individual well-being and social welfare and ‘normative’ indicators for programmatic use. Components of an underemployment indicator framework, the Labor Utilization Framework (LUF), are operationally defined and shown to be closely related to a family of proposed alternatives. Using CPS data, a 12-year time series of LUF indicators is developed for the U.S. labor force and its key subgroups. The across-time heterogeneity of the labor force is analyzed in relation to a ‘basic’ demographic group-by-LUF-by-time contingency, showing how the complexity of labor force structure that emerges from a multi-state indicator of underemployment can be rigorously modeled. Standard loglinear models, which focus on the temporal aspects of data from repeated cross-sectional surveys, provide the analytic technique. Changes in the demographic composition of the labor force account for about 30% of the overall period variability, and age structure has made the most important contribution to the compositional change.     

Testing the Comparability of Different Types of Social Indicators Across Groups

The social indicator movement has realized a considerable increase in importance during the last 50 years. This happened not the least by the publications in the journal Social Indicators Research. Social indicators have been developed for many aspects of life. The scores on these indicators often are compared through time and across groups. An essential requirement for such research is that the measures used are comparable through time and across groups. The comparability through time is not such a big problem but the comparability of measures across groups is not so obvious. This requires harmonization of indicators based on objective variables and invariance testing for indicators based on subjective and objective variables. In this paper we discuss how the comparability of different types of social indicators based on subjective and objective variables can be tested using invariance testing. This is a relevant issue because the existing testing procedure is designed for only one type of social indicators and this test is not directly applicable on the other types of social indicators.     

A Benefit Recipiency Approach to Analysing Differences and Similarities in European Welfare Provision

In comparative welfare state research, the question of how to measure and understand cross-country differences and similarities in extents of public welfare provision has led to a major discussion about the indicators that could be used for this purpose. Much scholarly attention approaching this so-called ‘dependent variable problem’ concentrates on social expenditure or on social rights data as indicators of ‘welfare stateness’ or ‘welfare generosity’. However, recently, micro-level data on benefit receipt as another promising but hitherto underused indicator was brought into this discussion. The article at hand extends existing knowledge about the conceptual, methodological and empirical potentials and challenges of this alternative indicator compared to the two prevailing indicators. For the empirical analysis, it uses cash benefit recipiency data from the EU-SILC to investigate differences and similarities in extents of public welfare provision between 29 European countries for the period 2003–2012. The study reveals parallels to findings from research in which indicators of social expenditure and social rights are applied, but it also adds new insights beyond their cost and paper reality. This is mainly the case where priority is given to household-related assistance benefits rather than individual insurance benefits. The main conclusion of the paper is that the benefit recipiency indicator—despite not being flawless and requiring further research—complements existing knowledge on differences and similarities in welfare provision by European welfare states.     

Time in the Development of Indicators on Sustainable Wellbeing: A Local Experiment in Developing Alternative Indicators

This paper is a theoretical and methodological study on the topics of distribution of and competition between time spans dedicated to social activities in the development of sustainable well-being indicators. This article seeks to answer the following question: why and how should we take into account social time in the development of alternative indicators? To bring to light the complex relationship between well-being, sustainability and people’s relationship to time, this article draws on an experiment aimed at developing Regional Sustainable Well-being Indicators (Indicateurs de Bien-être Soutenable Territorialisés—IBEST), which took place in the Grenoble urban area. This experiment was based on two methodologies; the first one being a quantitative survey, and the second one being a series of qualitative interviews coupled with a participatory approach. One of the datasheet indicators developed following this methodological crossover is the activity times balancing indicator, which allows us to take into consideration the pressure affecting time spent on social activities (work, leisure, families and civic engagement).     

Some social indicators for multiple family housing

This research suggests some social indicator candidates for families housed in multiple-family environments. Objective, subjective, and behavioral data sets are all represented in the analysis. This range of social statistics and the utilization of appropriate statistical analysis are viewed as necessary conditions for generating social indicators rather than simply relying on arbitrarily selected social statistics and assume they are indicators. Analysis of 1253 interviews in 88 Alberta subsidized housing projects reveals that subjective data from the tenant category of housing variables rank highest in accounting for present levels of user satisfaction and are viewed therefore as reasonable social indicators with respect to that issue.     

Proposal for a Dynamic Composite Indicator: Application in a Comparative Analysis of Trends in the EU Member States Towards the Europe 2020 Strategy

This paper contributes, with a dynamic approach, to the research on the creation of comparable composite indicators by presenting a proposal for an exploratory factor analysis protocol to enable a comparative trend analysis. The originality of the study lies in the three dimensions of information for analysis: observations, variables and units of time. The proposal involves various stages of analysis with the ultimate, albeit not exclusive, aim of obtaining what is known as a Global Dynamic Indicator. The analysis process begins by structuring the data into a three-dimensional global matrix, thereby conditioning, while also, and primarily, enriching the later stages. A combination of multiple factor analysis and a clustering technique is the selected approach for successfully meeting the challenges involved. The appropriateness and versatility of the proposal are validated through the analysis of the trends of the EU member states towards the targets set by the 2020 Strategy. The study period runs from 2009 to 2018. The empirical work enables the visualisation and quantification of trend differences and similarities across member states collectively and individually, and across all the variables and years selected for analysis. The relevant findings will be quantified by means of a synthetic indicator for each unit of time and a global indicator for the period as a whole. Some of the conclusions reached by this paper are consistent with those already published by various authors.

     

Preaching to the Choir: Are the Commission’s Recommendations Already Applied?

As we have seen, the Commission’s final report outlines a comprehensive framework by defining some guidelines by: (a) identifying the limits of GDP as an indicator of economic performance and social progress, including measurement problems; (b) considering what additional information might be required for the production of more relevant social progress indicators; and (c) assessing the feasibility of alternative measurement and presentation tools. The report argues that GDP should not be completely eliminated by the options for measuring progress, but must be integrated with other information. In particular, the Committee defines three major areas in which indicators should be developed: economic conditions, quality of life and sustainability. In the European scene, but not only, there are many initiatives that aim at measuring the progress of countries and well-being through different conceptual frameworks and by using several indicators. This work intends to analyze some of those relevant initiatives by comparing and confronting them to the Commission’s recommendations, in order to check what already fits the commission recommendations and what still needs to be defined in that perspective.     

Living Near to Attractive Nature? A Well-Being Indicator for Ranking Dutch,Danish, and German Functional Urban Areas

While nature is widely acknowledged to contribute to people’s well-being, nature based well-being indicators at city-level appear to be underprovided. This study aims at filling this gap by introducing a novel indicator based on the proximity of city-residents to nature that is of high-amenity. High-amenity nature is operationalized by combining unique systematic data on people’s perceptions of what are the locations of attractive natural areas with data on natural land cover. The proposed indicator departs from the usual assumption of equal well-being from any nature, as it approximates the ‘actual’ subjective quality of nature near people’s homes in a spatially explicit way. Such indicator is used to rank 148 ‘cities’ in the Netherlands, Denmark, and Germany. International comparability of the indicator is enhanced by the use of a definition of cities as functional urban areas (FUAs), which are consistently identified across countries. Results demonstrate that the average ‘nearness’ of FUA populations to high amenity nature varies widely across the observed FUAs. A key finding, that complements insights from existing city-level indicators, is that while populations of FUAs with higher population densities may live relatively far from nature in general, they also live, on average, closer to high-amenity nature than inhabitants of lower density FUAs. Our results may stimulate policy-debates on how to combine urban agglomeration with access to natural amenities in order to account for people’s wellbeing.     

How are the Kids Doing? How do We Know?

With a focus on the United States, this paper addresses the basic social indicators question: How are we doing? More specifically, with respect to children, how are our kids (including adolescents and youths) doing? These questions can be addressed by comparisons: (1) to past historical values, (2) to other contemporaneous units (e.g., comparisons among subpopulations, states, regions, countries), or (3) to goals or other externally established standards. The Child and Youth Well-Being Index (CWI), which we have developed over the past decade, uses all three of these points of comparison. The CWI is a composite index based on 28 social indicator time series of various aspects of the well-being of children and youth in American society that date back to 1975, which is used as a base year for measuring changes (improvements or deterioration) in subsequent years. The CWI is evidence-based not only in the sense that it uses time series of empirical data for its construction, but also because the 28 indicators are grouped into seven domains of well-being or areas of social life that have been found to define the conceptual space of the quality of life in numerous studies of subjective well-being. Findings from research using the CWI reported in the paper include: (1) trends in child and youth well-being in the United States over time, (2) international comparisons, and (3) best-practice analyses.     

Mapping Social Quality Clusters and Its Implications

Comparative studies of social quality (SQ) are intricately entangled with social indicators for conducting the theoretical analysis of social reality. Thus, how to utilize and compare the data of social indicators constitutes a crucial issue for SQ comparisons. Since social quality studies possess a strong synthetic feature of analysis, the convenient method of indicator studies by listing score ranking by country seems insufficient to meet the research needs. This study will explore a new way of performing SQ comparisons through a measure of mapping that compiles a different SQ profile and elucidates its clustering effect. Through utilizing World Value Surveys, we present data on SQ-related issues from this database and analyze them through a new technical design. In this way, we identify three SQ clusters and providing some explanations about the rationale of this classification, through which the particular method of SQ analysis and their policy implications are demonstrated.     

Race,intervening variables,and two components of low birth weight

The low birth weight (LBW) gap between blacks and whites has remained largely unexplained in past research. Most previous research on the topic has focused on LBW as a single entity, and without using a causal framework for. analysis. The present study examines the determinants of race differences in the two main components of LBW-preterm birth (PRETERM) and intrauterine growth retardation (IUGR)-within a partially causal framework that includes social and proximate explanatory variables. The data come from the 1988 National Survey of Family Growth. This study asks, first, through what intervening variables do race and other exogenous sociodemographic variables operate to raise the risk of these adverse pregnancy outcomes? Second, what are the determinants of the two components of LBW when all explanatory variables are included in the model? The findings reveal differences in how race (and other exogenous variables) act through downstream variables to affect PRETERM and IUGR, as well as differences in the net determinants of these pregnancy outcomes. The models are better able to account statistically for race differences in IUGR (which is explained by intervening sociodemographic, attitude, and behavior variables) than in PRETERM (which is explained partly by intervening health variables).     

Employment Quality: Are There Differences by Types of Contract?

Measuring welfare state generosity in developing and transitional welfare states is often challenged not only by lack of comparative quantitative data, but also by issues of conceptual stretching. This paper demonstrates and discusses the use of one of the key measures of welfare entitlement generosity developed in the comparative welfare state research in the context of post-communist countries of Central and Eastern Europe (CEE). With the new time series data provided by the Comparative Welfare Entitlements Dataset CWED2, comparative approaches including the CEE countries have become feasible. This paper first discusses quantitative measures of welfare entitlement generosity in the tradition of the social rights of citizenship approach and how they can be applied for cross-country comparisons. It then demonstrates empirically how the emerging CEE welfare states’ generosity compares to mature “old” OECD welfare states. Finally, the paper shows the potential and the pitfalls of quantitative measures of welfare state generosity by discussing, to what extent do indicators of social security scheme generosity measure the same in established and emerging welfare states, which functional equivalents may be relevant in the context of emerging welfare states and how far can we stretch our theoretical concepts.     

Dynamic Well-Being: Connecting Indicators of what People Anticipate with Indicators of what they Experience

There are many indicators of a person’s well-being that could be used for policy purposes. Few would argue that any single indicator of well-being is appropriate in all contexts and, increasingly, social scientists are attempting to integrate the various indicators. Further successful integration depends on understanding how the various indicators of well-being relate to one another in a dynamic way. This paper attempts to connect indicators of what people anticipate to indicators of what is actually experienced and, in so doing, inform the normative debate about the appropriateness of different indicators in policy contexts.     

Is Inequality a Latent Construct? An Assessment of Economic Inequality Indicators and Their Relation with Social Cohesion in Europe

In this article, we analyse the relation between different economic inequality indicators and social cohesion. Previous research usually narrows down economic inequality to income inequality, or distinguishes several types of economic inequality. Little attention has until now been given to how different aspects of economic inequality might be related to each other and can have an effect on social cohesion. This article analyses several indicators of economic inequality and makes a distinction between indicators measuring income inequality, poverty, economic strain and unequal distributions of wealth. Arguing that these indicators represent different aspects of inequality, we hypothesise that they cannot be reduced to one latent concept of inequality and have specific relations with social cohesion. In order to test this hypothesis, we conducted an exploratory factor analysis. This resulted in two different factors: one associated with economic hardship, and one associated with imbalances in market outcomes. This would imply that inequality indicators can be classified into two underlying concepts. Secondly, we related the factor scores of the two latent concepts to the social cohesion indicators via regression analyses. This paper focuses on European countries and uses pooled data from the European Social Survey (period 2006–2012), in combination with macro-level data drawn from the OECD, Eurostat and the World Bank. The results demonstrate that the strength of the link between inequality and citizens’ attitudes depends on the type of inequality indicator we analyse: only the factor economic deprivation can be significantly linked to social cohesion.     

The Development of the Good Relations Measurement Framework in Britain: A Template for Experiential Social Measurement

This article explores the development of the Good Relations Measurement Framework (GRMF), the first attempt in Britain to create a framework designed to measure how people experience their lives, specifically in relation to their interactions with each other. It provides a reference point for others seeking to construct social indicator measurement frameworks which capture the experiential in the social policy field. In a wider sense, it provides a case study of the use of social indicators within the policy process in the modern polity. The overall objective of the GRMF is to measure the state of Good Relations in Britain. Seven key areas emerged as being crucial for the development of measurement frameworks during the construction of the GRMF. Firstly, a decision has to be taken about the extent to which social measurement frameworks are confined to measurement only or are to have a normative element. Secondly, a working definition of the subject area is needed early in the process. Thirdly, an element of consultation with the public is important. A fourth issue relates to the practical method of construction through the use of ‘long lists’ of potential indicators, and finding a balance between an ‘ideal’ list of potential indicators emerging from public consultation and a second list of existing indicators drawn from existing surveys. A fifth issue relates to the availability of social indicator data at an appropriate geographical level. A sixth issue is that social indicators drawn from different surveys are not always comparable. A final factor is that while quantitative indicators are useful as a tool of social measurement, qualitative research adds a further dimension which is especially important in particular circumstances.     

Modeling urbanism: Economic,social and environmental stress in cities

The time has come for urban social indicator research to converge with the basic substantive efforts of urban researchers. Such a convergence may propel both basic and applied researchers toward more fruitful outcomes. This paper argues that the traditional model of urbanism provides the medium for the convergence. When urbanism is conceptualized to be multidimensional, seemingly discreet indicators of demographic, economic, social, and environmental conditions in cities may be incorporated into a more general model of urban structure and change. Specifically, using social indicators for 195 cities from ZPG's Children's Stress Index and the 1990 U.S. Census, we show empirically: (1) Urbanism is a complex factor with four distinct dimensions: demographic scale, economic stress, social stress, and environmental stress. (2) These four dimensions of urbanism may be reliably measured with standard composite variables used in today's social indicator research. (3) Within the Urbanism factor there are causal connections among the separate dimensions, the most basic of which is that asserted by arguments from the traditional theory of urbanism; specifically, that population size, density, and social heterogeneity are causally linked to stress in economic, social, and environmental systems of the city.     

Social indicators of youth development and educational performance: A programmatic statement

This paper argues for the use of social indicators, in conjunction with the traditional norm-referenced and criterion-referenced tests, to assess the effects of local educational systems. A conceptual framework for the study of educational performance is presented, interrelating (1) personal resources invested by youth, (2) opportunities for development, (3) developmental behaviors, (4) educational system impacts, and (5) other contextual variables, which together affect (6) progress toward adulthood. Four types of variables and 15 content areas that should be monitored are described, with examples of social indicators for each. Procedures are presented for selecting variables, collecting time-series data, and analyzing and reporting the indicators, relying entirely on existing data sources. Appendices include a data base screening form, a statistic screening form, and a list of United States national, state, county, and city sources of time-series data relevant to youth development and educational performance.     

Sense of Community and the Perception of the Socio-Physical Environment: A Comparison Between Urban Centers of Different Sizes Across Europe

Measures of subjective well-being, and especially life evaluations, or judgments about how happy people are with their lives as a whole, enrich and empower social indicators research. They do this by requiring other social indicators as explanatory variables and providing a coherent encompassing framework within which the relative importance of other social indicators can be established.     

Indicators of development in Wisconsin counties: 1970

This research focused on the problem of measuring economic and social ‘development’. Existing theories of economic and social change were used to select important indicators of development. For each indicator, principal components analysis was used to collapse several related variables into a single index. The indexes were labeled economic base, economic growth, personal economic opportunity, health inputs, health status, educational inputs, and educational attainment. In each case, selection of variables and indexes were constrained by two factors: (1) the data had to be available from secondary sources; (2) the selection of the indicators, and the procedure, had to be easily understood and cheaply and quickly repeatable by state or local agency personnel. In general the indexes were consistent with each other and the variables enter into the indexes with the expected sign. The high correlation among the indexes suggests that they may indeed measure some underlying attribute, development. There is no rigorous or absolute measure of development against which to check the validity of the indexes. However, the results have been judged ‘reasonable’ measures of development by the state agency staff and local development groups which have utilized the indexes.     

Application of the Rural Development Index to Analysis of Rural Regions in Poland and Slovakia

The main purpose of this research was to construct a multi-dimensional (composite) index measuring the overall level of rural development and quality of life in individual rural regions of a given EU country. In the Rural Development Index (RDI) the rural development domains are represented by hundreds of partial socio-economic, environmental, infrastructural and administrative indicators/variables at NUTS-4 level (e.g. 991 variables/indicators describing various aspects of rural development in Poland; 340 variables/indicators in Slovakia). The weights of economic, social and environmental domains entering the RDI index are derived empirically from the econometrically estimated intra- and inter-regional migration function after selecting the “best” model from various alternative model specifications (e.g. panel estimate logistic regression nested error structure model, spatial effect models, etc.). The RDI is empirically applied to analysis of the main determinants of rural/regional development in individual rural areas in years 2002–2005 in Poland and Slovakia at NUTS-4 level. Due to its comprehensiveness the RDI Index is suitable both to analysis of the overall level of development of rural areas and to an evaluation of the impacts (impact indicator) of RD and structural programmes at regional levels (NUTS 2–5).