The Benefits of a Single Measure of Wellbeing in Policy-making
The appeal of a single measure of wellbeing that policies orient around is partially the associated benefits of simplicity and accountability: it makes for a simple story of what policy-making is all about, whether local or national, and it allows others to challenge policies based on the science of wellbeing and statistics on actual outcomes. It thus fits a vision of policy-making that is ‘enlightened and rational’ in the sense of being oriented towards a clear goal that can be debated and improved over time.
If one accepts that vision of policy-making as something to move towards, the main question is whether there is a candidate measure of wellbeing that has the minimum characteristics one needs to use it in policy-making: it should be easy to collect and analyse, provide definitive answers on what needs to be done in order to improve it (and what not to do), and it is acceptable to politicians and the general public. This is the vision advocated in this book, and we make the argument that life satisfaction is the measure of wellbeing that most appropriately ticks all these boxes.
Yet, many think differently. So in this section, we discuss alternative visions of policy- making, which leads to an appreciation of other wellbeing measures and other roles of these measures.
One alternative scenario is a policy world in which there is little capacity to understand the many linkages between policies and where there is little capacity for continuous experimentation and learning. This is the reality in many developing countries, for example, and inside many institutions within developed countries where there is very limited capacity to gradually optimize on the basis of a whole apparatus of measurement and reflection.
The experience of Bhutan is quite instructive in this regard. Its monarchy was invested in the notion of ‘Gross National Happiness (GNH)’ from the 1970s onwards, but there were few university-trained civil servants in Bhutan, which has a population of just under a million and which is highly dispersed and quite diverse. Not until 2007 was there an actual attempt at measuring happiness, and even currently there is little in terms of organized learning about happiness within its small civil service. Bhutan simply lacks the general expertise and resources to implement the sophisticated policy systems which operate in richer and far larger countries.
What this primarily meant was that happiness-promoting policies were arrived at in a discretionary and autocratic way, with the small political elite of Bhutan simply enacting what it believed to be good for happiness, such as restricting tourism so as not to introduce cultural change and pressure on environmental resources arising due to tourism.
Many other countries in the world have a similar combination of a political desire to, in principle, improve the wellbeing of the population, but quite limited capacity to independently fine-tune local institutions based on sophisticated measurement and experimentation.
In this section, we introduce three of the most prevalent alternative approaches to wellbeing policy-making: (1) aspirational wellbeing decision systems, (2) wellbeing dashboard systems, and (3) policy-domain-specific wellbeing systems. The perspective that gives allows us to reflect on the approach in this book, i.e. the pros and cons of a system that openly accepts a particular measure of wellbeing as decisive for policy trade-offs. We call such a decisive measure an apex-measure and a system that openly accepts such a measure an apex-measure-based system.
Aspirational Wellbeing Decision Systems: The Case of Bhutan
An aspirational wellbeing decision system is one wherein the policy elites have openly and seriously accepted that the goal of government is the wellbeing of the population, but where there is no actual measurement of wellbeing or real attempt at integrating scientific insights on wellbeing into policy-making.
To some degree, many countries in the world have been aspirational on wellbeing for many decades without incorporating scientific insights on wellbeing. The United States is a perfect example of this, with a constitution that for over two hundred and fifty years has advocated an inalienable right to the pursuit of happiness. Yet, the United States has no institutional mechanism to adopt insights on happiness into actual policy-making. There is no happiness accounting unit in Congress, or even a happiness advisory group informing the president about how the country fares in terms of the happiness of the population. Its constitutional advocacy of happiness has remained aspirational for over two hundred and fifty years, at least when it comes to federal government.
Probably the best-known long-standing commitment to wellbeing by a government comes from Bhutan, where the fourth King of Bhutan, King Jigme Singye Wangchuck, declared in 1972: ‘Gross National Happiness is more important than Gross Domestic Product.’12 This declaration was not mere idle talk either, as the religion of the country, Vajrayana Buddhism, has an explicit role for religious leaders in catering for the happiness of the population, for example through happiness-oriented meditation practices.
Making the population happier through meditation by dedicated priests ‘beaming out’ happiness to others is an actual policy, though it obviously does not fit within modern scientific ideas of how people affect each other. Yet, within the belief system of the majority religion of Bhutan, it is a serious proposition that particular types of meditation are the way to make others happy. It thus fits our definition of an aspirational wellbeing decision system: serious but without the application of science. As said before, there was no actual attempt in Bhutan to measure the wellbeing of the population until its first survey in 2007. Currently, it has a dashboard-measure of wellbeing (the GNH index) that is purportedly used as a checklist in policy-making.
It is important not to over-romanticize Bhutan: it has a population of less than a million, its life expectancy is about sixty-eight years, its GDP per capita is not even 10 per cent of that of the United Kingdom, and it has experienced internal unrest in recent decades, especially when it comes to the expulsion and marginalization of the Lhotshampa community, many of whom had arrived in the nineteenth century (Aris, 1979; Meier and Chakrabarti, 2016). Still, Bhutan exemplifies a natural trajectory in wellbeing policy-making: from aspirational, to some kind of explicit measurement and gradual adoption into policy processes, perhaps eventually to an apex-measure-based system.
Like Bhutan, many other countries have formally adopted some notion of wellbeing as its goal and even mandated it in laws. This includes France, where its Senate in 2015 passed the ‘Sas Act’ mandating the government to inform the country every year of its progress in ten areas, including subjective wellbeing (see table 3.1 in Durand (2018), for example). Part of the ambition was to have new initiatives evaluated in terms of their likely effect on wellbeing. Similar aspirations and initiatives have been taken in Australia, Ecuador, India (Andhra Pradesh), Italy, New Zealand, and many other countries and regions during the past decades. Mariano Rojas (2020) called this the first wave of wellbeing policy-thinking.
Ecuador is a good example of how limited and transient some of these aspirational initiatives have been. In 2013, Ecuador instituted a ‘State Secretary for the Presidential Initiative for the Construction of a Society of Good Life’. This position holder had no budget, no measurement apparatus, and no political power to do much else than appear frequently on
conferences and talk about the direction towards which the country should go in terms of wellbeing policies. When an opposing political party came into power four years later, the position was axed.
Wellbeing Dashboard Systems
There are literally hundreds of wellbeing dashboards and associated indices in the world, including both government-sponsored dashboards and privately sponsored ones. Government-sponsored dashboards include, for example, the International Well-being Index, the Global Youth Well-being Index, the OECD Better Life Index, or the Bhutan Gross National Happiness Index. Privately sponsored dashboards include the Sainsbury’s Living Well Index or the Lloyds Bank Happiness Index. There is even a Salvation Army one. A report by the New Zealand Treasury nicely summarizes many of the best-known ones (King et al., 2018).
To discuss their general properties and uses, let us discuss two in greater depth: the Bhutan Gross National Happiness Index and the OECD Better Life Index, which was adopted in a slightly altered format by New Zealand in its 2020 wellbeing budget.
The Bhutan Gross National Happiness Index is best summarized by its official diagram (see Figure 4.1).
One can see that it involves nine policy domains, each including two to four actual indicators. We do not comment here about the actual indicators that supposedly measure elements such as ‘knowledge’ or ‘family’, as the inherent issues with these kinds of ‘representative variables’ will be discussed later in the context of the OECD Better Life Index. For now, let us assume that there are reasonable indicators to capture most of what is meant by these nine policy domains.
Life Satisfaction as an Apex-measure of Wellbeing
1.The New Zealand Treasury institutionally owned the wellbeing framework and advised other ministries what to implement in regard to wellbeing.
2.Spending ministries were instructed to choose the indicators in the index they thought their policies addressed, encouraging them to say how much their proposed and current policies contribute to those indicators.
3.Individual ministries were not required to work out how their policies affected the other indicators in the index, though in individual cases the Treasury negotiated with those ministries as to whether and how they should handle and report likely ‘spillovers’ of their policies to other policy domains.
4.There was approximately a 2 per cent discretionary budget which was spent on things that were advertised as core wellbeing: suicide prevention, mental health, and child wellbeing.
5.To a large extent, the announced new policies were reassessed and relabelled existing policies, including many long-standing ones, such as on economic growth.
It thus seems to be the case that the wellbeing budget in New Zealand combined a relabelling of existing policies with some discretionary spending in the direction of social relationships and mental health, as well as an evolving administrative system to induce spending ministries and organizations to start thinking about particular spillovers.
One should not think of this description as a critique at all, but rather as a reflection of the huge challenges involved in truly getting a machinery as complex as a civil service to move from its previous preoccupations to a wellbeing orientation. It simply takes time and the road inevitably involves aspirations, window dressing, ad hoc processes, and only a gradual adoption of new insights. One should not expect anything different but acknowledge that a reorientation of a civil service is an evolutionary process, not a revolutionary one. This, by the way, has its advantages because it makes policies dependable and credible: precisely because they cannot be changed wholesale from one decade to the next, the general population and the private sector have trust in many government programmes, like primary school education.
What to make of these indices and dashboards then? Given the discussions above surrounding wellbeing dashboard systems, it becomes difficult to ascertain whether this or
that index of wellbeing, which invariably combines dozens of indicators, ‘truly measures wellbeing’. Such indices are not used, or even usable, for practical policy-making, so their role is not really to measure ‘the quality of life of the population’. Rather, the goal of wellbeing dashboard systems is to make particular groups of indicators quickly available and visible in one place.
In that light, very different questions arise regarding indices: do they combine the policy domains where there is a lot of improvement to make in the countries using them? Are the indicators involved leading the decision-making systems to perverse incentives, and if so, should they be taken seriously? Do the frameworks around these indices lead users to look in the most promising areas for wellbeing improvements? And in those cases whereby they are just window-dressing and designed to make the funders feel useful, are they cheap forms of window dressing that have little negative effects?