Construction, Validation and Application of the Measurement of Social Cohesion in 47 European Countries and Regions

This paper aims to present a theoretically based, multidimensional and comparable measurement of social cohesion, applicable in 47 European countries/regions using the most recent micro-level data of the European Value Study (EVS) from 2008 that build upon the previous research conducted on the EVS data from 1999 covering 33 countries. The analysis is conducted in five steps. In the first part, we create a set of measurable intermediate indicators that correspond to the social cohesion dimensions suggested by the theory. In the second part, we verify whether these indicators empirically corroborate the multidimensional structure of the concept proposed by the theory. The third part examines whether the obtained intermediate indicators of social cohesion form the same constructs across countries and whether they can yield a cross-country equivalent measure of social cohesion. In the fourth step, composite scores of all dimensions of social cohesion are calculated for all analysed countries/regions. The last step shows a practical application of the obtained indices and compares levels of social cohesion in six broader geographical regions of Europe to demonstrate the applicability of the measurement in comparative research.     

Fifty Years After the Social Indicators Movement: Has the Promise Been Fulfilled?

In spite of its currency both in academic research and political rhetoric, there are numerous attempts to define and conceptualize the social cohesion concept but there has been paid little attention to provide a rigorous and empirically tested definition. There are even fewer studies that address social cohesion in a framework of cross-cultural validation of the indicators testing the equivalence of the factorial structure across countries. Finally, as far as we know there is no study that attempt to provide an empirically tested multilevel definition of social cohesion specifying a Multilevel Structural Equation Model. This study aims to cover this gap. First, we provide a theoretical construct of social cohesion taking into account not only its multidimensionality but also its multilevel structure. In the second step, to test the validity of this theoretical construct, we perform a multilevel confirmatory factor analysis in order to verify if the conceptual structure suggested in first step holds. In addition, we test the cross-level structural equivalence and the measurement invariance of the model in order to verify if the same multilevel model of social cohesion holds across the 29 countries analysed. In the final step, we specify a second-order multilevel CFA model in order to identify the existence of a general factor that can be called “social cohesion” operating in society that accounts for the surface phenomena that we observe.     

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.     

Social Cohesion and the Labour Market: Societal Regimes of Civic Attitudes and Labour Market Regimes

The aim of this paper is to test the connections between the indicators used in the literature on social cohesion, which usually reflect ‘general’ values or behaviours, and indicators specific to a particular space, namely the labour market. A key question is the stability of the social cohesion’s indicators when moving from a societal level to the labour market. Based on data from the World Value Survey, and following a restrictive definition of social cohesion, a comparison is done, for European countries. Examination of the situation in the two spheres makes it possible to identify more or less homogeneous groups of countries and also to point to instabilities. ‘Regimes’ of social cohesion begin to emerge. As in most analyses, the Nordic countries (excluding Finland) have high scores in all the dimensions. Conversely, most of the new EU member states from the former Eastern bloc have low scores, particularly in the horizontal dimension of trust between individuals.     

Conceptualising and Measuring Social Cohesion in Africa: Towards a Perceptions-Based Index

Social cohesion is a key concept in development studies. Weak social cohesion is often related to slow economic growth and (violent) conflict. So far few attempts have been made to measure this complex concept in a systematic manner. This paper introduces an innovative method to measure national-level social cohesion based on survey data from 19 African countries. We distinguish three dimensions of social cohesion; i.e. the extent of perceived inequalities, the level of societal trust, and the strength of people’s adherence to their national identity. Importantly, our Social Cohesion Index (SCI) is based on individuals’ perceptions vis-à-vis these three different dimensions of social cohesion rather than certain macro-level ‘objective’ indicators such as GDP/capita or Gini-coefficients. We develop two social cohesion indices: a national average SCI and a Social Cohesion Index Variance-Adjusted (SCIVA); the latter one takes into account the level of variation across different ethnic groups within countries. The SCI and SCIVA are computed for and compared across nineteen African countries for the period 2005–2012 on the basis of Afrobarometer survey rounds 3, 4 and 5. We also investigate quantitatively the relationship between countries’ levels of social cohesion and the occurrence of a range of conflict events. As expected, we find that countries with low levels of social cohesion in a particular year according to our SCI are more likely to experience a range of different violent conflict events in the subsequent year.     

Challenges in Constructing a Multi-dimensional European Job Quality Index

There are few attempts to benchmark job quality in a multi-dimensional perspective across Europe. Against this background, we have created a synthetic job quality index (JQI) for the EU27 countries in an attempt to shed light on the question of how European countries compare with each other and how they are developing over time in terms of job quality. Taking account of the multi-faceted nature of job quality, the JQI is compiled on the basis of six sub-indices which cover the most important dimensions of job quality as identified in the literature. The paper addresses the methods used to construct the JQI and make it comparable over time. It presents the results for 2010 and briefly addresses changes over time to illustrate the potential and limits of a multidimensional European JQI. It also considers alternative specifications for various sub-indices and tests for the impact of changes in the indicators used on the outcomes. Overall, the findings appear to confirm the feasibility and desirability of attempting to assess job quality by means of a composite index that can be periodically updated. The key strength of this approach is the possibility to monitor and benchmark EU countries’ overall job quality performances and the outcomes in six sub-dimensions of job quality and compare them with each other, across gender and over time. At the same time, the limitations of such a composite index need to be borne in mind. The most important challenges are the availability (over time), timeliness and periodicity, comparability and disaggregation of data.     

The Relationship Between EU Indicators of Persistent and Current Poverty

The current poverty rate and the persistent poverty rate are both included in the European Union’s (EU's) portfolio of primary indicators of social inclusion. We show that there is a near-linear relationship between these two indicators across EU countries drawing on empirical analysis of EU-SILC and ECHP data. Using a prototypical model of poverty dynamics, we explain how the near-linear relationship arises and show how the model can be used to predict persistent poverty rates from current poverty information. In the light of the results, we discuss whether the EU's persistent poverty measure and the design of EU-SILC longitudinal data collection require modification.     

Oecd Social Indicators for 2001: a Critical Appraisal

The OECD social indicators for 2001 were critically reviewed by analysing their interrelationships across all OECD countries during the late 1990s. First, findings were provided covering the underlying structure of subsets of indicators by similarity in content as suggested by the OECD. Second, an analysis of the selected key indicators yielded five social dimensions, which were interpretedas conceptual constructs underlying the set of OECDsocial indicators at the level of the entire OECD area. Third, the relationships of each indicator withthese social dimensions were observed to aid choosing of appropriate indicators for making and evaluating social policies. Fourth, the OECDcountries were ranked according to their overall social welfare, as defined by the OECD social indicators, basedon the scores of the countries on the social dimensions. Fifth, similarities among the OECD countries were examined and it was found that the countries formed six bipolar country dimensions. The findings showed that an easily interpretable structure underlies the OECD social indicators. The paper clarified the use of the OECD social indicators for 2001 as a tool for planning and decision-making and for cross-national analyses of social policies.     

Happy to Help? Exploring the Factors Associated with Variations in Rates of Volunteering Across Europe

The frequency of formal volunteering varies widely across European countries, and rates of formal volunteering are especially low among Eastern European countries. Why are there such large differences in volunteering rates when it is known that volunteering is beneficial for well-being? Using data from the latest round of the European Social Survey, we test three hypotheses to explain these cross-national differences in volunteering. We ask whether people in countries with low frequencies of volunteering spend more of their time on informal volunteering activities; whether they differ on socio-demographic variables which are known to be linked to volunteering rates; or whether they show less well-being benefit from formal volunteering. Contrary to the first hypothesis, we find a positive correlation between formal and informal volunteering. We further conclude that national differences in rates of volunteering cannot be fully explained by differences in the social, psychological or cultural factors associated with volunteering nor the outcome of volunteering. It is likely that contextual factors, such as a country’s historical background or institutions, determine levels of volunteering to a large extent.     

Measurement Assessment in Cross-Country Comparative Analysis: Rasch Modelling on a Measure of Institutional Quality

This paper uses recent multidimensional well-being measurements to examine multidimensional well-being and inequality across the European regions in 2000 and 2014 with the use of eleven well-being indicators from the OECD Better Life Index. We use generalized mean aggregation method with alternative parameters to allow different substitutability and complementarity levels between well-being dimensions, which range between perfect substitutability and some degree of complementarity between the dimensions, to examine well-being and inequality across the European regions. Accounting for the interactions between the well-being dimensions matters for the multidimensional well-being and inequality across the European regions. The results show that the multidimensional well-being across the European regions are relatively lower when the dimensions are more seen as complements compared to the case when they are considered to be perfect substitutes. Furthermore, there is also a higher degree of multidimensional inequality across the European regions when the dimensions are considered to have some complementarity. Changes in well-being dimensions between 2000 and 2014 indicates that multidimensional well-being improved and inequality decreased in the personal and community well-being categories, but remained unchanged in material well-being category across the European regions irrespective of interaction levels between well-being dimensions. Policy implications of these multidimensional well-being indices are also evaluated by using these indices to determine the eligible regions for the European Union structural funds where the number eligible regions shows some variation depending on whether the dimensions are perfect substitutes or more of complements.

     

Social Capital or Social Cohesion: What Matters For Subjective Well-Being?

The theoretical analysis of the concepts of social capital and of social cohesion shows that social capital should be considered as a micro concept whereas social cohesion, being a broader concept than social capital, is a more appropriate concept for macro analysis. Therefore, we suggest that data on the individual level should only be used to analyze the relationship between social capital, social cohesion indicators and subjective well-being and that they do not allow commenting on the level of social cohesion in a society. For this last type of analyses aggregated indicators of social cohesion have to be computed which is not the issue of this paper. Our empirical analysis is based on individual data for Luxembourg in 2008. In general, our results suggest that investments in social capital generate monetary returns (increased income) and psychic returns (increased subjective well-being) even in a highly developed and multicultural country like Luxembourg. When we are adding on the micro level variables representing the economic domain of social cohesion following Bernard (1999), then we observe that this domain also has an effect on income and on subjective well-being. Therefore, we recommend including the economic domain in any future analysis using the concept of social cohesion.     

Happiness and Childbearing Across Europe

Using happiness as a well-being measure and comparative data from the European social survey we focus in this paper on the link between happiness and childbearing across European countries. The analysis motivates from the recent lows in fertility in many European countries and that economic wellbeing measures are problematic when considering childbearing. We find significant country differences, though the direct association between happiness and childbearing is modest. However, partnership status plays an important role for both men and women. Working fathers are always happier, whereas working mothers are not, though mothers?? happiness tends to increase with household income.     

Satisfaction with Social Contacts of Older Europeans

This paper analyses the determinants of an important component of well-being among individuals aged 50 years or older in eleven European countries: satisfaction with social contacts. We use data from the Survey of Health, Ageing and Retirement in Europe and anchoring vignettes to correct for potential differences in responses scales across countries and socio-demographic groups. On average, older Europeans report being satisfied with their social contacts, but there exist substantial differences across countries: respondents from Northern countries tend to be more satisfied than individuals from Central or Mediterranean countries. Our analysis shows that correcting for response scale differentials alters the country ranking for of satisfaction with social contacts, while it has much less effect on the estimates of what drives within country determinants.     

On the Use of Social Clocks for the Monitoring of Multidimensional Social Development

This article describes a new methodology for monitoring multidimensional social development using social clocks: comparisons with so called reference trajectories make it possible to establish the development stage of a country along a number of independent time axes, thus affording new opportunities for analyzing leads, lags, and asynchronies between variables and countries. This article explores these new possibilities and discusses some of the difficulties in the use of social clocks. To demonstrate the fruitfulness of the new concepts, the article presents an application of the methodology by analyzing the socio-economic development of ten Eastern European countries in the period before they joined the European Union.     

Bringing Affect Back in: Measuring and Comparing Subjective Well-Being Across Countries

In recent years, researchers and policymakers have paid increasing attention to cross-country comparisons of subjective well-being. Whereas classical theories of quality of life emphasize the central role of affective well-being (i.e., whether a person feels good or bad), previous comparative studies have focused almost exclusively on life satisfaction (i.e., cognitive evaluations of life). This study brings affect into the comparative study of subjective well-being, constructing a new measurement instrument that captures both the affective and cognitive dimensions of subjective well-being. Using European Social Survey data and multi-group confirmatory factor analysis, we estimate latent country means for the two dimensions and compare country rankings across the two measures. The results reveal important differences in country rankings depending on whether one focuses on affective well-being or life satisfaction. We identify crucial differences among top-ranking countries and, perhaps even more importantly, considerable differences in rankings among more moderately ranking countries. In a second step, we compare and evaluate the single-item measures commonly used in previous research with the results based on our new measures. We conclude by discussing our results in relation to previous studies, and in terms of their possible implications for future research and for policymakers bent on improving national levels of subjective well-being.     

Measuring Social Cohesion: An Experiment using the Canadian National Survey of Giving,Volunteering, and Participating

Social cohesion is a concept difficult to define and to measure. As there can be many definitions, so there can be many measurements. The main problem, either in defining or measuring the concept, is its multilevel and multidimensional nature. At one extreme, country is the most commonly used level to view social cohesion but measurement at this level is of little use for any interventions. At the other extreme, community is the most useful level but it is a social construct for which data are difficult to get, given the administrative boundaries used in social surveys. As an initial attempt to measure social cohesion at a subcountry level, this study focuses on census metropolitan areas for which data on several dimensions of social cohesion are available. We use the information gathered by the National Survey on Giving, Volunteering and Participating (NSGVP) on three dimensions of social cohesion: political (voting and volunteering), economic (occupation, income, labour force participation) and social (social interactions, informal volunteering). Using statistical techniques including factor analysis and standardization, we create an overall index of social cohesion for each CMA. We point out use of this measure for further analysis of social dynamics.     

The Relationship Between Social Capital and Individualism–Collectivism in Europe

The aim of the present study was to examine the relationship between social capital and individualism–collectivism in a sample of 50,417 individuals from 29 European countries using data from the European Social Survey Round 6 (2012). Social capital was measured in terms of generalized social trust and informal social networks; individualism–collectivism was operationalized via Schwartz’s Openness to Change–Conservation value dimension. Results from a hierarchical linear modeling analysis showed that less than 10% of variance in social capital indicators was found between countries, meaning that the level of social capital varies more substantively between individuals than between the countries. Openness to Change had a weak but statistically significant and positive relationship both with the indices of Generalized Social Trust and Informal Social Networks, which remained significant even when individual age, gender, education level, and domicile were controlled for. In sum, our findings show that the positive relationship between social capital and individualism that has been found at the cultural level also holds at the individual level: people who emphasize independent thought, action, and readiness to change are also more willing to believe that most people can be trusted and are more engaged in informal social networks. The relationship is, nevertheless, very weak and the strength of the association varies significantly across different European countries. This variation, however, cannot be explained by country differences in level of democracy or human development and the country’s wealth moderates only the individual level relationship between Openness to Change and Informal Social Networks. Our findings suggest that sources of social capital at the individual level can be found in people’s immediate social surroundings, as well as their everyday social interactions.     

Measuring World Better Life Frontier: A Composite Indicator for OECD Better Life Index

The OECD Better Life initiative recently released a comprehensive set of 11 indicators of well-being covering a group of countries. Each individual indicator corresponds to a key topic that is essential to well-being. However, the problem of aggregating them is left to users of this dataset. Using these as individual indicators, we propose a composite indicator of overall well-being, which is intended to measure the performance of each country in terms of providing well-being to its people. The ‘benefit of the doubt’ approach (BOD), a well-known aggregation tool based on a weighed sum, assigns the most favourable weights for each entity under investigation. BOD may also be considered to evaluate the performance of each entity in terms of its efficiency. Regarding individual indicators as outputs, it constructs the benchmark production frontier from observed individual indicators. A composite indicator based on BOD equals the distance between each entity’s individual indicator and the production frontier, indicating its efficiency. It is widely considered that the well-being of a country’s people stems from its productive base, which is characterized by capital assets and social infrastructures. Thus, the productive base can be considered the input used to produce well-being, which is reflected by individual indicators. Therefore, when we apply BOD to aggregate individual well-being indicators across countries, we implicitly assume that all countries have the same productive base, as BOD addresses only the output and neglects the input. This inaccurate assumption leads to a distorted performance measure. Data envelopment analysis (DEA), in which BOD has its roots, is a tool to measure the efficiency of each entity by allowing for differences in inputs as well as outputs across entities. DEA also measures efficiency by using the distance to the production frontier; however, unlike BOD, DEA constructs the production frontier more accurately by utilizing the information of inputs as well as outputs, leading to a better performance measure. We apply DEA to aggregate 11 individual well-being indicators into a composite indicator using the World Bank’s estimates of each country’s productive base. The composite indicator based on BOD is distributed similarly to and is highly correlated with the existing Human Development Indicator (HDI). It is also positively correlated with GDP per capita. On the other hand, we show that the composite indicator based on DEA is negatively correlated with HDI as well as GDP per capita.     

Cross-Cultural Analyses of Determinants of Quality of Life and Mental Health: Results from the Eurohis Study

Recent projects on international instrument development have produced a wide array of health indicators that may be used for cross-cultural field-testing, however more information on their cross-cultural performance in relation to health determinants is necessary. The current study approaches one step for international conceptual validation by analysing the association between various health determinants and different types of health outcomes (mental health, quality of life) across a range of countries or geographical areas. The current study is based on the EUROHIS project that has been conducted in a sample of 4849 adults across 10 European countries. Results highlight that interactions between health determinants with subjective mental health, general health and quality of life (QoL) differ between Western European countries, Eastern European countries and the Newly Associated States as well as Israel. Using a MIMIC model approach, we were able to show that the impact of each of the sociodemographic variables cannot be interpreted on the basis of its single loading but only seeing the interacting with other indicators. Future studies should include sociodemographics in MIMIC models in each latent factor before carrying out regressions on a larger scale. Future investigations will require larger and representative samples to (a) test models on latent factors of mental health and QoL and (b) on the basis of these findings test overall structural models across countries.     

Gender or Occupational Status: What Counts More for Well-Being at Work?

The aim of this study is to provide cross-cultural empirical support that endorses the scientific nature of Quality of Life (QoL), which a review of definitions reveals as a nomothetic and multidimensional concept (personal and environmental circumstances), made up of a set of subjective and objective indicators. Although this is commonly accepted, many instruments and authors reduce it to subjective and personal conditions. Bearing in mind the aim described, multi-group Structural Equation Modelling analysis was applied to two representative samples made up of 1217 participants aged over 60 from Mexico and Spain, recruited both at random (through the random route procedure), who completed the CUBRECAVI (Brief Questionnaire of Quality of Life). In this model two third-order latent variables are considered for QoL: personal and external factors, both made up of objective and subjective indicators. As predicted, the results permit us to state that the structural model is invariant across the two countries—that is, although the QoL construct has the same structure in the two countries, the importance of the indicators (factor loadings) and the relationships between them are not equivalent.