A Reduced Posetic Approach to the Measurement of Multidimensional Ordinal Deprivation

In this paper, we discuss the existence of particular systems of generators for posets associated to multidimensional systems of ordinal indicators and derive a reduced posetic procedure for the measurement of multidimensional ordinal deprivation. The proposal is motivated by the need to lessen the computational complexity of the original posetic procedure described in Fattore (Soc Indic Res 128(2):835–858, 2015), so as to make it applicable to larger multi-indicator systems, particularly to those comprising many variables scored on “short” scales, as typical in deprivation studies. The reduced procedure computes identification and severity functions based only on so-called lexicographic linear extensions. These are a particular generating system for the basic achievement poset, naturally associated to rankings of deprivation attributes. After motivating this choice, both from an interpretative and a computational point of view, the paper provides some simulated examples, comparing the reduced and the non-reduced procedures.     

A Two-Step Approach to Analyze Satisfaction Data

In this paper a two-step procedure based on Nonlinear Principal Component Analysis (NLPCA) and Multilevel models (MLM) for the analysis of satisfaction data is proposed. The basic hypothesis is that observed ordinal variables describe different aspects of a latent continuous variable, which depends on covariates connected with individual and contextual features. NLPCA is used to measure the level of a latent variable and MLM is adopted for detecting individual and environmental determinants of the level. This approach is suggested to analyze users’ satisfaction. In fact, NLPCA is used to create a synthetic continuous measure of satisfaction (first step) and MLM are used to detect the role of external (individual or environmental) variables that can affect the level itself (second step). The proposed two-step procedure is applied to the Eurobarometer survey data about opinion of European citizens on services of general interest (SGI) aiming to evaluate and compare the opinion about SGI in different countries. The focus is on overall level of satisfaction about four major public services: fixed telephone, electricity supply, postal and rail services. The item analyzed, which are named manifest variables, are: access easiness, price, quality, information clarity and contract fairness, as reported in the 2002 Eurobarometer survey. In the first step these variables are used to set up the synthetic indicator (the overall level) of satisfaction and, in the second step, a MLM is used to test the impact of some explanatory variables on this satisfaction.     

Away from Dissatisfaction,Closer to Well-Being: A Multidimensional Synthetic Measure

As part of the international debate on methods for measuring the social progress of a population, there has been increasing interest in individual subjective opinions about different aspects of quality of life (elementary indicators). In the literature, many methods have been introduced for producing measures of subjective well-being based on these opinions. Some of these methods aim to construct synthetic measures that allow us to consider all the aspects simultaneously. This topic often requires subjective methodological choices and/or distributional assumptions and, when the opinions are encoded by means of categorical ordinal values, the eventual quantification of the original variables. Here, starting from the Istat multipurpose survey on households’—aspects of daily life, we propose an original method for constructing a global satisfaction index. We introduce a variable based on the joint distribution of all the elementary indicators that is able to express the individual degree of global satisfaction. This approach allows us to maintain the original ordinal data scale and to avoid any aggregation formula. By comparing the observed distribution of the new variable and the theoretical one, which refers to the situation of overall dissatisfaction (all individuals are dissatisfied for every aspect), we propose three indices of global satisfaction. We also implemented two simulation studies that confirms both the efficacy and robustness of our method. We then applied it to measure the global satisfaction degree of the Italian population, using Istat multipurpose survey data for the year 2013.     

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.     

A note on the measurement of accuracy for subnational demographic estimates

Mean absolute percentage error (MAPE), the measure most often used for evaluating subnational demographic estimates, is not always valid. We describe guidelines for determining when MAPE is valid. Applying them to case study data, we find that MAPE understates accuracy because it is unduly influenced by outliers. To overcome this problem, we calculate a transformed MAPE (MAPE-T) using a modified Box-Cox method. Because MAPE-T is not in the same scale as the untransformed absolute percentage errors, we provide a procedure for calculating MAPE-R, a measure in the same scale as the original observations. We argue that MAPE-R is a more appropriate summary measure of average absolute percentage error when the guidelines indicate that MAPE is not valid.     

Ranking and Prioritization of Emergency Departments Based on Multi-indicator Systems

In this work we discuss how Emergency Departments (EDs) can be ranked on the basis of multiple indicators. This problem is of absolute relevance due to the increasing importance of EDs in regional healthcare systems and it is also complex as the number of indicators that have been proposed in the literature to measure ED performance is very high. Current literature faces this problem using synthetic (or numerically aggregated) indicators of a set of performance measures but, although simple, this solution has a number of drawbacks that make this choice inefficient: a compensation effect among the indicators; a high degree of subjectivism in the indicators weighting; opacity in the decision making; all the EDs are considered to be comparable. Indeed, the situations in which EDs are comparable (i.e. when all the performance of one ED are not lower than the performance indicators of the other) are a minority and incomparability is by itself a source of information that should be used to identify situations for which different policy actions should be designed. In this work we propose to use non compensatory composite indicators and partial ordering theory to rank and compare EDs giving value to the reasons of such an incomparability. These methods are applied on a case study of 19 EDs in an administrative region in Italy.     

Variability of Quality of Life at Small Scales: Addis Ababa,Kirkos Sub-City

Urban quality of life (QoL) is becoming a subject of urban research mainly for western and Asian countries. Such attention is due to an increasing awareness of the contribution of QoL studies in identifying intervention areas and in monitoring urban planning policies. However, most studies are carried out at city or country level that can average out details at small scales. In this paper we present a case study where the urban QoL at small scale is measured and its variability is evaluated for Kirkos sub-city of Addis Ababa, Ethiopia. The study is based on data from a household survey and some secondary data. Geographic information system (GIS) is applied to extract proximity information (e.g., distance to school facilities) and visualize the spatial distribution of QoL. Statistical methods such as factor analysis are applied to establish an index of objective QoL while coefficient of variation is applied to evaluate spatial variability of subjective QoL. The results of this study reveal that the subjective quality of life (QoL) scores show large variation in the sub-city. The mean QoL score also indicates that the respondents in the sub-city, on average, are dissatisfied with the quality of their life. Respondents with higher education level and income are on average, however, more satisfied with their QoL in the sub-city. The results reveal that the lower the QoL in the Kebele, the larger the variability of QoL within the Kebele. Such indicates how aggregation at large scale can average out the variation of QoL at small scales. The results reveal the presence of QoL variability at small scales. The comparison between the subjective and the objective QoL at Kebele level indicated a state of dissonance, adaptation, deprivation or well-being. Such results suggest that the two measures do not always indicate the same level of QoL.     

A life satisfaction scale for use with national adult samples from the USA,Canada and Mexico

This paper describes the steps we took to develop a measure of life satisfaction which appears useful for analyses of adult sample survey data from the United States, Canada, and Mexico. Our procedure is factor analysis, and our data are drawn from the 1981–82 and 1991–92 World Values Surveys conducted in the three countries. The result is a six-variable composite measure which meets the following conditions: the constituent items have face validity, the factor structure is similar across countries and also across sub-groups within countries, the factor structure is also similar in 1981–82 and 1991–92, and the factor score based on these structures is highly correlated with variables that are customarily good predictors of life satisfaction and happiness. On the basis of these results, we will be confident in using the life satisfaction measure for future multivariate analyses of the data base aimed at explaining variation in satisfaction. For the same reasons, we would recommend the life satisfaction measure for others' research with the rich World Values Surveys data base.     

The Robustness of High Danish National Happiness: A Temporal Cross-Country Analysis of Population Subgroups

Denmark’s top position in various rankings of country happiness is well-documented. This study goes beyond the national average comparisons and investigates whether Denmark’s top position is also found when we disaggregate data in line with social categories often used within the social sciences. The central measure is the empirical probability that a given population subgroup in Denmark has significantly higher happiness compared to another country’s similar subgroup in a given year. All five rounds of the European Social Survey are used but only the sixteen countries that were surveyed in each of the five rounds are included in this study. The results show that Denmark’s position at the top of the happiness scale is also robust when we look at population subgroups, but not in the sense that Denmark dominates all countries for all years. Instead, a modified version of robustness is necessary; Denmark very often has significantly higher happiness levels than in other countries, only sometimes has the same happiness levels as in other countries, very rarely is it dominated by other countries, and finally it is never dominated by other countries in all 5 years for a given subpopulation characteristic. This conclusion is quite insensitive to the applied SWB measure and the applied significance level.

     

First Order Dominance Techniques and Multidimensional Poverty Indices: An Empirical Comparison of Different Approaches

In this empirically driven paper we compare the performance of two techniques in the literature of poverty measurement with ordinal data: multidimensional poverty indices and first order dominance techniques (FOD). Combining multiple scenario simulated data with observed data from 48 Demographic and Health Surveys around the developing world, our empirical findings suggest that the FOD approach can be implemented as a useful robustness check for ordinal poverty indices like the multidimensional poverty index (MPI; the United Nations Development Program’s flagship poverty indicator) to distinguish between those country comparisons that are sensitive to alternative specifications of basic measurement assumptions and those which are not. To the extent that the FOD approach is able to uncover the socio-economic gradient that exists between countries, it can be proposed as a viable complement to the MPI with the advantage of not having to rely on many of the normatively binding assumptions that underpin the construction of the index.     

Rating the Rich: An Ordinal Classification to Determine Which Rich Countries are Helping Poorer Ones the Most

When talking about poverty, a lot of energy is expended by academics and sociologists in the identification and classification of the poor. Less attention is paid to classifying the rich. The Center for Global Development created the Commitment to Development Index in 2003, which ranks countries according to their contribution to the reduction of poverty in developing countries. Since its first report, “Ranking the rich, the Index has been quite successful. However, it has also been subject to multiple criticisms. This paper proposes the use of an ordinal classification to rate, not rank, the performance of rich countries. An ordinal classification, where an ordinal scale labels the examples, can help discovering the level of each country’s commitment to development, automatically and independently from others’ performances. It could stimulate both advocacy from civil society and the determination of more coherent public policies in rich countries for poorer ones.The methodology used is Artificial Neural Networks, a common machine learning tool for successfully solving classification problems. Experiments yield robust results, showing better outcomes than other alternative ordinal classifiers, opening the possibility of developing a classification technique which could overcome the limitations of the current ranking technique.     

Development and Governance in the Ex-Soviet Union: An Empirical Inquiry

The widespread adoption of the concept of wellbeing in the social sciences literature has allowed researchers to move beyond a narrow economic focus on income and consumption as the primary measure of inequality and poverty. Although statistical measurement and analyses of wellbeing have become increasingly feasible due to the availability of rich datasets, the empirical literature on wellbeing remains deficient in a number of ways. In this paper we argue that it is necessary that empirical studies of wellbeing encompass multiple. Applying Sen’s capability approach as our theoretical model we subsequently develop a modelling framework that applies the polychoric principal component analysis (PCA) method for the calculation of objective wellbeing and wellbeing inequality using household asset, education, health and housing dimensions. Findings from our case study of Vietnam challenge previous single dimensional analyses and reveal a number of layers to our understanding of wellbeing inequality in Vietnam. We argue that our use of polychoric PCA is especially suited to the analysis of wellbeing by explicitly incorporating the analysis of both cardinal and ordinal variables and overcoming deficiencies established in the literature relating to the use of standard PCA.

     

“Healthy” Human Development Indices

In the Human Development Index (HDI), life expectancy is the only indicator used in modeling the dimension ‘a long and healthy life’. Whereas life expectancy is a direct measure of quantity of life, it is only an indirect measure of healthy years lived. In this paper we attempt to remedy this omission by introducing into the HDI the morbidity indicator, “expected lost healthy years” (LHE), used in the World Health Report Though LHE is only weakly correlated with life expectancy and displays considerable variation across countries, the ranking of nations using the adjusted HDI is very similar to that from the HDI. Nevertheless, there are some outlier countries (including large countries like China and the United States) that experience notable changes in rank. Given the considerable variation in the morbidity data across gender, we also adjust the Gender-related Development Index (GDI) in a similar fashion. The ranking using the adjusted GDI is very similar to that from the GDI, but it has a lower rank correlation with the HDI.     

人口地理与公共品供给效率——以四川省135个县(市)为例

利用四川省135个县(市)的数据,分析人口、地理因素对县(市)公共品供给效率的影响。研究发现,2008年135个县(市)平均公共品供给效率为0.672,整体水平还有待进一步提高;县(市)辖区人口密度的提高、所辖乡镇数量的增加有助于供给效率提高;复杂的地理环境增加了公共品提供成本,降低了供给效率;乡镇辖区面积扩大及人口增加有助于供给效率的提高。研究对提高地方公共品供给效率,完善地方政府及财政层级改革颇具参考价值和意义。     

Subjective Indicators Construction by Distance Indices: An Application to Life Satisfaction Data

The construction of subjective indicators for measuring phenomena expressed in an ordinal scale is a central issue in social sciences, particularly in sociology and psychology. In this paper, we propose the use of a subjective indicator by groups of units (for example, by geographical area) based on the ‘distance’ between the empirical cumulative distribution and a hypothetical cumulative distribution of reference. This approach allows to avoid the awkward question of the ‘quantification’ of an ordinal variable, i.e., the conversion of an ordinal variable into an interval variable. As an example of application, we consider life satisfaction data coming from the annual multipurpose survey on “Aspects of Daily Life”, carried out by the Italian National Institute of Statistics, and we present a comparison with some classical methods.     

Construct Validation and Application of a Common Measure of Social Cohesion in 33 European Countries

The aim of the paper is to assess the construct validation of a multidimensional measure of social cohesion which is well theoretically grounded and has an equivalent/comparable interpretation across all European countries. Up-to-now published research on social cohesion is deficient in either one or both of these important aspects. This paper attempts to cover this gap. The task is accomplished in two steps. In the first step, we conceptualize social cohesion, flowing mainly from Bernard and Chan’s definitions of social cohesion. Based on this theoretical framework we operationalize social cohesion and derive a set of intermediate indicators in the data. By return we verify whether these indicators empirically reflect/corroborate the multidimensional structure of the concept proposed by the theory. In the second step, we examine 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. To test the validity of the theory we use multidimensional scaling and confirmatory factor analysis. Both models are able to verify the equivalence of the structural results between groups (i.e. countries). Confirmatory factor analysis produces further meaningful measures of these constructs. The analyses are based on the data from the 1999 European Values Study (EVS). The outcomes of the analyses reveal that, firstly, the existence of the multifaceted construct of social cohesion suggested by the theory has been corroborated by empirical analysis of the EVS data (i.e. social cohesion consists of components of formal and substantial relationships and political and socio-cultural domains). Secondly, the proposed constructs measuring social cohesion are equivalent across all analysed countries and thus allow the calculation of internationally comparable national scores of social cohesion. Application of the aggregate measures at the country level will illustrate the interest of the approach for further research.     

Global Cybersecurity Index (GCI) and the Role of its 5 Pillars

Computer crime is a matter of increasing concern, and worldwide action is required if the proper responses to it are to be found. One of the tools that can be deployed here is the Global cybersecurity index (GCI), a control and feedback mechanism based on a composite indicator. The GCI is based on a hierarchy of sub-indicators. The indicators used for the final aggregation of the CGI are called pillars. Five pillars are applied to rank the eleven countries that are top of the rankings in a worldwide study. In this paper, our ranking is based on these pillars, and their role is investigated using partial order methodology. It turns out that the pillars “Technical (aspects)”, “Capacity building”, and “Cooperation” are of particular importance. In conclusion, a strategy is suggested for an “individualized ranking” that may be helpful for small and medium-sized enterprises (SMEs) or other institutions. Here, we apply the procedure for the project “Awareness Laboratory SME (ALARM) information security” and put our ideas up for discussion. In particular, the mathematical method will be transferred to SMEs as a means to support the effectiveness of awareness-raising measures and to improve the security behaviour of company employees.

     

Measuring Social Capital with Aggregated Indicators: A Case of Ecological Fallacy?

Social capital has become a highly successful concept in social science despite widely perceived shortcomings in conceptualization and operationalization. The latter is frequently performed as a principal component analysis of individual survey data with subsequent aggregation to regional or national levels. The central focus of this paper is the interpretation of the diverging correlations observed between the dimensions elaborated on an individual and an aggregate level. We illustrate that the correlations of regionally aggregated components are the result of an improper application of a single-level model to a multilevel structure. This mechanism is demonstrated empirically by adopting results from the European Social Survey and elaborating dimensions of social capital from both individual and aggregate survey data for European regions. The findings clearly indicate that the observed ecological correlations are not simply spurious or inconsistent due to an ecological fallacy condition, but rather reflect the influence of regional driving forces. Researchers need to be more careful in taking account of the multilevel nature of the data in order to produce valid results. In fact, the often applied procedure of individual factorization and subsequent aggregation of data provides a mixture of the two level effects with potentially misleading implications.     

The index of overall headship: A simple measure of household complexity standardized for age and sex

This paper develops and tests an age-sex standardized measure of household complexity, defined broadly as the tendency of adults (other than spouses) to head their own households or to share households. The aim is a measure of household complexity which can be computed with a minimum of demographic data, namely, data on number of households and on the population by age and sex. The procedure is similar to that of Coale for fertility measurement (Coale, 1969); it is a form of indirect standardization in which the actual number of households is related to the number that would exist if maximum age-sex-specific household headship rates were to apply. Various forms of this indirectly standardized measure show a correlation of better than 0.9 with directly standardized measures for a sample of 33 nations for which requisite data are available. The new measure promises to extend considerably the geographical and temporal range of comparable empirical measures of household complexity.