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OECD Guidelines on Measuring Subjective Well-being © OECD 2013 Chapter 4 Output and analysis of subjective well-being measures The statistical data for Israel are supplied by and under the responsibility of the relevant Israeli authorities. The use of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements in the West Bank under the terms of international law. Note by Turkey: The information in this document with reference to “Cyprus” relates to the southern part of the Island. There is no single authority representing both Turkish and Greek Cypriot people on the Island. Turkey recognises the Turkish Republic of Northern Cyprus (TRNC). Until a lasting and equitable solution is found within the context of the United Nations, Turkey shall preserve its position concerning the “Cyprus issue”. 179 4. OUTPUT AND ANALYSIS OF SUBJECTIVE WELL-BEING MEASURES Introduction This chapter provides guidance regarding the release and use of subjective well-being data. It briefly re-caps the policy and public interest in the data (outlined in Chapter 1, Concept and validity), before covering how information can be reported and analysed. This includes the statistical outputs that may be released; basic information about the methods of analysis that may be adopted; and a discussion of key interpretive issues, placing particular emphasis on the extent to which levels of subjective well-being can be expected to vary in different circumstances. The chapter is divided into three main sections, summarised in Table 4.1. The first and largest section focuses on the use of subjective well-being data to complement existing measures of well-being. This includes examination of trends in subjective well-being over time, the distribution of subjective well-being across different groups within society, and its distribution across different countries. The first part of this section outlines approaches to measuring well-being and the value added that subjective well-being brings relative to other measures. The second part of the section then describes how subjective well-being can be reported, including the summary statistics that may be of interest. Finally, issues in the analysis and interpretation of descriptive statistics on subjective well-being are explored. These include the size of change over time, or difference between groups, that can be expected, as well as the risk of cultural “bias” in cross-country comparisons. The remaining two sections of the chapter deal with more detailed analyses of subjective well-being, which might be conducted by government analysts and others on the basisofmicro-datareleasedbystatisticalagencies.Section2addressesanalysesofthe drivers of subjective well-being. This includes the relationship between subjective well-being and other important well-being outcomes, such as income and health, as well as the use of subjective well-being data to inform the appraisal, design and evaluation of policy options. Section 3 addresses subjective well-being data as an input for other analyses. First, it considers the use of subjective well-being as an explanatory variable for other outcomes, and then focuses on the potential use of subjective well-being data in cost-benefit analysis. Section 1 will be of most direct interest to large-scale data producers, such as national statistical agencies, as it concerns the kinds of outputs and analyses that they are most likely to report for a wide range of audiences. Sections 2 and 3 provide a sense of the broader uses of subjective well-being data – which are essential to consider when planning its measurement (as set out in Chapter 3, an approach to Measuring subjective well-being). Analyses of drivers, for example, require consideration of the co-variates to be collected alongside subjective well-being data, and ideally call for data from which causal inferences can be drawn. The potential risk of measurement error, and the various biases that may be present in the data, are also major themes throughout the chapter. However, as the relevance of measurement errors depends on the intended usage of the data (Frey and Stutzer, 2002), the chapter is organised around data uses, rather than around these sources of error. Key interpretive issues for each type of analysis are summarised in Table 4.1. 180 OECD GUIDELINES ON MEASURING SUBJECTIVE WELL-BEING © OECD 2013 4. OUTPUT AND ANALYSIS OF SUBJECTIVE WELL-BEING MEASURES Table 4.1. Summarising possible uses of subjective well-being data Data use What Why Who Key interpretive issues 1) Complementing Core measures/headline To know if the changes affecting society Governments (central, i) What size of difference existing measures indicators used to examine: have an impact on subjective well-being. regional, local). between groups or over of well-being i) National trends over time. To identify vulnerable groups and areas Wider public. time can be expected? ii) Distribution of outcomes of suffering Public, private and third sector ii) What alternative across different groups – highlighting where key drivers organisations. explanations should be within society. of subjective well-being may lie – and where Researchers interested considered for observed iii) Distribution of outcomes there may be opportunities for policy in country-level drivers of differences? across countries. interventions. national well-being. iii) What is the role of culture Includes indicators of central To conduct international benchmarking, Individuals and organisations and cultural bias tendency or “level”, as well as assist in the interpretation of national data, – e.g. making decisions about in cross-country distribution, and the relative and identify where countries may be able where to live and work. comparisons? rate of rise or decline over time. to learn from others’ experiences. 2) Better understanding Analyses based on national To improve our understanding of well-being Governments. i) What size of impact can be the drivers of subjective and international micro-data, overall, by examining the relationship Researchers. expected? well-being with subjective well-being used between subjective well-being, Individuals wanting better ii) How can the impacts as the dependent variable, to: life circumstances, and other important information to support of different drivers be i) Examine the relationship well-being outcomes. decision-making. compared? between subjective To highlight areas of policy with the greatest Employers wanting well-being and potential to improve subjective well-being, to understand and improve other important life and the life events/circumstances most employee well-being. circumstances, likely to put subjective well-being at risk. such as income and health. To assist in government decision-making ii) Inform policy options processes, including the allocation appraisal, design of resources and the design elements and evaluation. of policies. iii) Inform policy trade-offs. To inform the public and employers about the likely drivers of individual subjective well-being, providing better information for individual and organisational decision-making. 3) Subjective well-being Micro-data on subjective To better understand how subjective Researchers. i) The sensitivity of subjective as an input for other well-being, used as an input well-being can contribute to other Governments. well-being data analyses, particularly for other analyses, including: well-being outcomes and shed light Individuals wanting better to non-market goods. cost-benefit analysis i) As an explanatory variable on human decision-making processes, information to support ii) Measurement error and its for other elements including the various biases that may be decision-making. impact on valuations. of well-being or behaviour. present. Employers wanting iii) Co-variates to include ii) Used to estimate the value To provide an alternative to traditional to understand and improve in regression models. of non-market goods economic approaches to estimating employee well-being. iv) Time horizons for study. and services, for the value of non-market goods, supporting the purposes of cost-benefit government (and other organisations) analyse.s in making decisions about complex social choices. 1. Using subjective well-being to complement other outcome measures Introduction Subjective well-being is an essential element of a broader and multi-dimensional concept of human well-being and can be used in the context of monitoring reports on the living conditions of different countries or sub-national units. Indicators of interest will include the overall level of subjective well-being, its rate of change over time and its distribution across different groups within society. This section is organised in three parts. The first part addresses what is meant by “measuring well-being” and briefly discusses how subjective well-being can contribute in this area. This includes outlining what subjective well-being data can add to more conventional measures and why subjective well-being might be considered an important outcome in its own right. The second part focuses on reporting measures of subjective well-being. This examines the relative merits of a number of different approaches to summarising and describing subjective well-being OECD GUIDELINES ON MEASURING SUBJECTIVE WELL-BEING © OECD 2013 181 4. OUTPUT AND ANALYSIS OF SUBJECTIVE WELL-BEING MEASURES data. The section concludes with discussion of the issues arising in analyses that aim to compare different levels
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