Filomena Maggino

From Composite Indicators to Partial Orders: Evaluating Socio-Economic Phenomena Through Ordinal Data

In this paper we present a new methodology for the statistical evaluation of ordinal socio-economic phenomena, with the aim of overcoming the issues of the classical aggregative approach based on composite indicators. The proposed methodology employs a benchmark approach to evaluation and relies on partially ordered set (poset) theory, a branch of discrete mathematics providing tools for dealing with multidimensional systems of ordinal data. Using poset theory and the related Hasse diagram technique, evaluation scores can be computed without performing any variable aggregation into composite indicators. This way, ordinal scores need not be turned into numerical values, as often done in evaluation studies, inconsistently with the real nature of the phenomena at hand. We also face the problem of “weighting” evaluation dimensions, to account for their different relevance, and show how this can be handled in pure ordinal terms. A specific focus is devoted to the binary variable case, where the methodology can be specialized in a very effective way. Although the paper is mainly methodological, all of the basic concepts are illustrated through real examples pertaining to material deprivation.

Partial Orders in Socio-economics: A Practical Challenge for Poset Theorists or a Cultural Challenge for Social Scientists?

In this “position paper” we discuss the potential role of partial order theory in socio-economic statistics and social indicators construction. We maintain that the use of concepts and tools from poset theory is needed and urgent to improve currently adopted methodologies, which often prove ineffective for exploiting ordinal data. We also point out that the difficulties in spreading partial order tools are cultural in nature, and that some open-mindedness is needed among social scientists. We address these issues introducing some examples of open questions in socio-economic data analysis: (i) the problem of multidimensional poverty evaluation, (ii) the problem of assessing inequality and societal polarization, and (iii) the problem of clustering in multidimensional ordinal datasets.

Different Scales for Different Survey Methods: Validation in Measuring the Quality of University Life

This chapter explores the assessment of subjective measurement instruments in terms of definition and selection of items and also in the identification of more suitable scales. The work presented here addresses the comparison of several scales in separate types of questionnaires (paper and/or CATI). It provides a conceptual framework and empirical analysis. Finally, it draws conclusions based on these analyses.

Challenges, Needs and Risks in Defining Wellbeing Indicators

Actually, crossing Alex’s scientific life corresponded also to crossing the renewed worldwide debate on the role of social indicators in promoting the wellbeing of individual and nations. My contribution to this collection re-considers some reflections I already wrote on measuring progress of societies.

Assessing the Subjective Wellbeing of Nations

The issue presented in this chapter produced and produces wide debates, starting from the definition of the main concept involved, seen often in different dualisms, subjective vs. objective, subjective wellbeing vs. objective wellbeing, and subjective indicators vs. objective indicators.

Perception and Evaluation of the Quality of Life in Florence, Italy

In 2003, the City of Florence (Italy) in conjunction with the Department of Statistics at the University of Florence conducted research regarding the citizens’ perception and evaluation of the quality of life (QOL) in the city of Florence. The focus of the study was to identify residents’ needs and develop programs and policies to enhance their QOL. The study also attempted to develop specific indicators of QOL aimed at measuring and assessing the levels of suitability of the living conditions that the city of Florence offers to its inhabitants.

Linking forest diversity and tree health: preliminary insights from a large-scale survey in Italy

Forest health is currently assessed in Europe (ICP Forests monitoring program). Crown defoliation and dieback, tree mortality, and pathogenic damage are the main aspects considered in tree health assessment. The worsening of environmental conditions (i.e., increase of temperature and drought events) may cause large-spatial scale tree mortality and forest decline. However, the role of stand features, including tree species assemblage and diversity as factors that modify environmental impacts, is poorly considered. The present contribution reanalyses the historical dataset of crown conditions in Italian forests from 1997 to 2014 to identify ecological and structural factors that influence tree crown defoliation, highlighting in a special manner the role of tree diversity. The effects of tree diversity were explored using the entire data set through multivariate cluster analyses and on individual trees, analysing the influence of the neighbouring tree diversity and identity at the local (neighbour) level. Preliminary results suggest that each tree species shows a specific behaviour in relation to crown defoliation, and the distribution of crown defoliation across Italian forests reflects the distribution of the main forest types and their ecological equilibrium with the environment. The potentiality and the problems connected to the possible extension of this analysis at a more general level (European and North American) were discussed.

Towards More Complexity in Subjective Well-Being Studies

The interest in measuring what matters for most individuals has led to the development of many indicators. Scientific approaches have made it possible to improve the incorporation of subjective perceptions into objective indicators. The perpetual quest for objectivity has led remaining subjectivity to be undesired and be considered as biases. This is partly a consequence of the epistemological ground on which Western science is built, in particular the Aristotelian principle of non-contradiction. The present contribution is an invitation to reconsider what is usually considered as “objective” and “subjective” and to incorporate them in a more complex framework in order to gain more understanding within subjective well-being studies in a scientific manner.

Indicators of happiness vs. quality of happiness: methodology and theory

In order to proceed with exploring the methodological issues related to the measurement (indicators of happiness) and evaluation (quality of happiness), it is important to clarify what we mean by the term ‘happiness’. The debate around the definition of a new approach of measuring well-being of nations has put ‘happiness’ at the centre of concerns by highlighting, among others, two aspects to be considered: the individual observation and the subjective dimension. The necessity to consider the individual perspective, completely ignored by the traditional GDP approach, in measuring countries’ well-being is broadly urged and accepted. Many point out that the most important dimension of the individual perspective is represented by the subjective perception, defined in terms of happiness. However, focusing on the individual perspective, especially if that is done exclusively on a subjective perception, is affected by some risk. This contribution aims at exploring the conceptual issues related to those risks, which refer to some dualisms around well-being (subjective vs. objective, happiness vs. subjective experience, individual vs. community, present vs. future). These issues are important in order to define the indicators able to monitor happiness and to support its quality assessment.

Non-aggregative Assessment of Subjective Well-Being

In this paper, we introduce a new methodology for socio-economic evaluation with ordinal data, which allows to compute synthetic indicators without variable aggregation, overcoming some of the major problems when classical evaluation procedures are employed in an ordinal setting. In the paper, we describe the methodology step by step, discussing its conceptual and analytical structure. For exemplification purposes, we apply the methodology to real data pertaining to subjective well-being in Italy, for year 2010.