Abstracts in this document, Full text as PDF files in new window.
|Chapter 1||Quest for the good society||Abstract
|Chapter 2||Criteria for the evaluation of human societies||Abstract
|Chapter 3||Indicators of livability of societies||Abstract
|Chapter 4||Measurement of happiness||Abstract
|Chapter 5||Validity of happiness as an indicator of livability||Abstract
|Chapter 6||Available data about happiness in nations||Abstract
|Chapter 7||How tha data are homogeinized||Abstract
|Chapter 8||Uses of this data-collection||Abstract
These texts were first published in: Ruut Veenhoven, 'Happiness in nations: subjective appreciation of life in 56 nations 1946-1992', RISBO, Erasmus University Rotterdam, 1993, ISBN 90-72597-46-X, 365 pages. Some of the texts have been revised, in particular chapter 4.
Utopic dreams about 'The Ideal Society' have led into a search for 'Optimal Societies'.
The present state of Social Science does not allow the deductive identification of optimal
societies, but we can approach the matter inductively.
Inductive identification of optimal societies involves five steps: 1) choice of performance criteria, 2) operationalisation of these, 3) application to a set of societies, 4) establishment of a performance rank order, and 5) finding out why some societies perform better than others.
This book considers the usefulness of average happiness as a performance criterion. The focus of this book is on step 3.
Some common criteria for the evaluation of human societies are: 1) their stability over time, 2) their productivity in goods and services, 3) the degree to which they realize particular ideals, and 4) their livability. This book focuses on the latter criterion. Livability is defined as the degree to which the provisions and requirements of a society fit with its members needs and capacities.
The livability of human societies can be estimated in two ways: The first way is to assess
the presence of living conditions deemed likely to provide a fit with citizens needs and
capacities. Clues for presence of such conditions are referred to as 'input' indicators.
The second way is to assess the degree to which citizens flourish in a society, assuming
that good flourishing results from a good fit. Manifestations of good flourishing are
health and satisfaction. They are referred to as 'output' indicators of livability.
The focus of this book is on output indicators, in particular on satisfaction. Unlike health, satisfaction has hardly been compared cross-nationally as yet. This book presents data on satisfaction with life-as-a-whole, also called 'happiness'.
Happiness is defined as the degree to which an individual judges the overall quality
of his life-as-a-whole favorably. Within this concept two 'components' of happiness are
distinguished: hedonic level of affect (the degree to which pleasant affect dominates) and
contentment (perceived realization of wants). These components represent respectively
'affective' and 'cognitive' appraisals of life and are seen to figure as subtotals in the
overall evaluation of life, called overall happiness.
Happiness as defined here can be measured by means of questioning, and hedonic level also by observations of non-verbal behavior. Though happiness is measurable in principle, not all the questionnaires and observation schedules used for its measurement are deemed acceptable. Many measures tap in fact broader phenomena than defined here. These measures are left out in this review of survey research on happiness in nations. All the data reported here are based on indicators that successfully passed a test for face-validity.
This catalog reports data on happiness in nations. It provides information about average level and dispersion of happiness.
This chapter considered whether average happiness in nations is a valid indicator of the
livability of these nations. Two kinds of validity tests were performed: First, global
tests for concurrent and congruent validity. Second, several specific checks of
some common objections against the use of happiness for this purpose.
The global tests for congruent validity showed that average happiness in nations correspond with healthiness, though not with incidence of suicide. These two alternative 'output' indicators of livability explain together 37% of the variance in happiness. The test for concurrent validity showed a strong relationship with quality of crucial living conditions in the country. Happiness is highest in the countries that provide most material comfort, social equality, political freedom and access to knowledge. Together these input indicators explain 77% of the variance in average happiness.
Various specific validity tests did not expose happiness either. The observed differences in average happiness between nations do not seem to result from cultural bias in its measurement. It is also unlikely that they result to a great extend from cultural variation in outlook on life.
All in all, it is fairly probable that the differences in happiness, as observed in survey studies, do reflect differences in livability of nations.
Data on happiness in human societies are available only for present day nation states.
These data come from cross-national surveys as well as from periodical Quality-of-Life
surveys in particular nations.
This information is raked together by combing abstracts systems, library catalogues and data-banks and mailing investigators in the field
This study collects the result of investigations that used acceptable measures of happiness. These acceptable measures are not quite identical. This chapter explains how the divergent data were classified into equivalent categories. It further considers three techniques for transforming responses to dissimilar questions into comparable scores.
Grouping comparable findings
This database presents the data by kind of happiness assessed. This breaks the data collection into four main parts: one big part on 'overall happiness', a smaller one on 'hedonic level' and two minor ones referring to 'contentment' and 'mixed indicators'. Within these parts the collection is further differentiated in tables of near-identical indicators. This results in tables by 'question-type'. Most of the tables with identical items concern overall happiness. Among these, three groups of questions some can be discerned which ask essentially the same thing, but that differ only in the rating of response. Though not 'identical', the items in these clusters are 'equivalent'. As such they qualify for conversion to a common scale. The possibilities for converting average scores on divergent indicators of happiness are however limited.
Transformation of scores on slightly differing measures of happiness
Scores on indicators of different happiness variants can not be converted to the same standard. They measure essentially different things that do not necessarily coincide.
Scores on different indicators of the same happiness variant can be converted in principle. However, in practice it is quite difficult to estimate the method effects involved. If sufficient data are available, we can inspect whether there is a linear relationship between responses yielded by different indicators in the same populations. Such data are only available for some single questions on overall happiness. We found a reliable relation in the nation scores on the two pairs of items: 1) 10-step life-satisfaction by 4-step satisfaction with way-of-life, and 2) 11-step life-satisfaction by 11-step best-worst possible life. In these cases missing values on one variable can be reliably estimated by linear regression on the basis of observed scores on the other; interpolation is less risky than extrapolation. In three pairs we found no reliable relation however: 1) happiness-in-life by satisfaction-with-life, 2) happiness-in-life by best-worst possible life, and 3) happiness-in-life by delighted-terrible life. In these latter cases we deem transformation inadvisable.
Conversion is better possible when indicators (questions) are substantially equivalent, and differ only in number and labeling of response categories. In that case standardization by expert-weighting is justified. The expert-transformation applied here successfully passed a test for congruent validity. If differences between equivalent items concern only the length of a graphic or numerical rating scale, simple linear transformation (stretching) is most appropriate.
Only the latter two standardization methods (expert-weighting and stretching) are applied in this data collection. In the tables transformed scores are mentioned for equivalent items. Transformed means are presented next to the original means.
What does this dataset serve for? First of all for establishing whether it is of any worth
itself. We need the dataset to investigate the validity of happiness as an indicator of
livability. Because happiness appeared to be a good measure of livability, the
data-collection can be used for charting livability. It allows comparison between nations
and across time.
The data-collection helps to identify determinants of livability in an inductive way. As such it will complete current deductive speculation. The dataset will also help to identify consequences of good or bad livability
The data-collection provides not only information about level of happiness in nations, but also about its dispersion. As such it allows a new view on inequality in nations.