The relevance of measures of subjective well-being: Why are they important?

It is important to be clear about why subjective well-being should be measured. Official statistics are produced to meet the needs of policy-makers in planning and assessing the impact of policy decisions, and to inform the general public about the state of society. Academics and the media are also important users of official statistics, contributing to a better understanding of society and informing the public and decisionmakers. The demand for official statistics is thus, ultimately, a derived demand; statistics are collected because they are of use to someone, rather than for their own sake.

The principles of official statistics generally reflect the view that information is collected only when there is good reason and for a clear purpose. The OECD framework for data quality identifies relevance as the first of the seven key dimensions of quality. Relevance implies that the value of data “is characterised by the degree to which that data serves to address the purposes for which they are sought by users” (OECD, 2003). Similarly, the United Nations Fundamental Principles of Official Statistics asserts that the role of official statistical agencies is to compile and make available “official statistics that meet the test of practical utility... to honour citizens’ entitlement to public information”.

There are sound ethical and practical reasons why official statistical agencies insist on having a clear understanding of the uses of any proposed statistical measures. Many official statistical agencies have the power to compel responses from respondents. That is, respondents are legally required to provide information when approached by a national statistical agency. The corollary of such authority is the requirement for national statistical offices to use data responsibly. From an ethical standpoint, only information that is sufficiently important to justify the intrusion into respondents’ lives should be collected. The International Statistical Institute’s Guidelines on Professional Ethics notes that:

Statisticians should be aware of the intrusive potential of some of their work. They have no

special entitlement to study all phenomena.

Over and above this ethical concern is also a practical concern. Even if compliance is legally mandated, the quality of compliance depends heavily on preserving a good relationship between respondents and the official statistical agency. This, in turn, is undermined if the statistical agency cannot articulate why the data being collected is important and how it will be used.

Official statistical agencies are also under increasing resource pressures. This takes the form of both budget cuts, which preclude collecting all the information for which there is a potential demand, and issues of response burden. Even where funding exists to collect information, official statistical agencies must be careful not to over-burden respondents and jeopardise the good will on which high-quality responses depend. Because of this, collecting measures of subjective well-being will have an opportunity cost in terms of other data that will not be collected in order to produce such measures. If subjective well-being measures are to be included in official statistics, therefore, it is essential to be clear about how they will be used.

It is also important to be clear about how subjective well-being measures will be used for purely technical reasons. The field of subjective well-being covers a wide range of different concepts and measures. Choosing which measures should be the focus of collection efforts requires knowing what the measures will be used for. Different measures of subjective well-being will be better suited to different purposes, and it is therefore important that these guidelines identify the right measures needed given the core policy- and public-uses for the data.

The intended use for measures of subjective well-being also affects judgements about the validity of such measures. No statistical measure captures the concept it is intended to measure perfectly. Whether any particular measure can be considered valid, therefore, ultimately involves a judgement about whether the quality of the measure is sufficient to support its intended use. A measure that is valid for one purpose may not be valid for other purposes. For example, a measure could provide valid information about the distribution of outcomes within a country, but be subject to significant bias due to cultural or linguistic factors. While this would be a significant limitation if the intended use of the data is to rank countries compared to each other, it is less important for purely domestic uses.

Measures of subjective well-being have a wide variety of potential uses and audiences. For the purposes of these guidelines it is useful to classify the possible uses of subjective well-being measures under a general framework. The following framework identifies four main ways in which measures of subjective well-being are used. In particular, they can:

  • Complement other outcome measures.
  • • Help better understand the drivers of subjective well-being.
  • • Support policy evaluation and cost-benefit analysis, particularly where non-market outcomes are involved.
  • • Help in identifying potential policy problems.
 
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