By Hetan Shah
I was involved in some of the calls for improved measurement of wellbeing in the early 2000s. Two decades on, sometimes the debate feels like it has not moved on sufficiently from those earlier days.
The framing often continues in the vein of wellbeing v GDP measures. But I’m not sure how much value that adds these days. There has been a lot of progress on wellbeing statistics since the Millennium, as can be seen in the ‘UK Measures of National Wellbeing Dashboard’ which captures 59 measures over 10 topic areas drawing on data from across the Government Statistical Service and beyond. More generally there has been a growth in the use of subjective measures to complement objective metrics, recognising that people’s views and experiences matter (although are not a complete picture), and a much stronger set of environmental measures than existed two decades ago. We need to acknowledge how much progress has been made in filling gaps that proponents of wellbeing measures were pointing to.
Today’s debates also need to acknowledge the strained situation that UK official statistics is in. Both the National Statistician and chair of the UK Statistics Authority have recently resigned. The ONS is accused of systemic failures and is struggling to produce core economic series such as labour market statistics, price indices and retail sales data. Official statisticians contend with falling survey response rates, resource constraints, and a war for data skills and talent. The Office for Statistics Regulation’s recent report on the State of the UK Statistical System outlines many of the challenges. The ‘wellbeing measures’ debate can currently feel a bit tin-eared in not recognising the severe challenges that the statistical system currently faces in terms of resources and skills. We must contend not just with the elegant world of theory but also a practical world of trade offs: if we choose to measure X we therefore may not then have the resource to be able to measure Y.
Rather than fall back to the comfortable lines of debating of GDP v wellbeing, we should acknowledge that there are few people who argue for traditional economic metrics who think this captures the whole of people’s wellbeing, and equally there are few on the other side of the debate who think that economic measures have no contribution to make to people’s quality of life. The latter has become especially evident over the last decade as we have seen poor productivity growth leading to relatively stagnant wages, and weakened public finances leading to pressure on local authorities and public services. All of these have some relationship to our individual and societal wellbeing.
A better route that takes us beyond the unhelpful ‘wellbeing v GDP’ divide might be to talk about what is the ‘missing data’ that we see as a priority for understanding and improving people’s lives. This could range from traditional kinds of economic statistics (such as employment statistics which are currently not deemed of sufficient quality to be accredited official statistics), numbers about public services (such as social care or justice which I have raised with the Public Administration Select Committee), or data about how people feel and experience their lives (closer to the traditional concerns of those advocating for wellbeing measures). The merit of this approach is that it recognises both that many statistics relate in some way to our wellbeing, and that we need to consider what data to prioritise in a resource constrained environment. Such an approach will require arguments that could appeal to (i) how feasible it is to measure the issue at hand; (ii) how far such data cast light on or can help affect people’s quality of life; and (iii) how far they may help policymakers, researchers, business, civil society and the public to understand or improve lives. There are a plurality of conceptions of wellbeing, and a variety of things that affect people’s lives. Such debates would help bring this out more explicitly, and recognise that actually many official statistics are about wellbeing in some way (or at least someone’s theory of wellbeing).
Let us not risk getting trapped in the last war. Going beyond a framing of ‘wellbeing v GDP’ and thinking about ‘missing data’ also might allow us to be more sensitive to new challenges for statistics or different ways to collect them. These could include how we account for transactions in a digital age; issues of time use or getting a better handle on assets – all issues that Professor Diane Coyle has flagged in her latest book The Measure of Progress. A different example is our recent work at The British Academy in partnership with the Bennett Institute for Public Policy on measuring social and cultural infrastructure. This makes the case for a more place-based approach. It calls for methods which involve communities in setting the priorities about measuring the social assets that create value in their area.
I worry that sometimes the world of statistics can become a proxy battleground. Statistical debates about what to measure can be used as a way to transpose a philosophical or political argument about what we actually value in more cloaked and technocratic way. Calls for more measurement of X can be a signalling mechanism and sometimes a displacement activity for the much harder issue of taking action on X. We already know quite a lot about what improves life satisfaction, or the state of climate change. A final thought: is it time to focus more on taking action on what we already know rather than simply calling for better data?
Hetan Shah is chief executive of The British Academy. He is on Bluesky: @hetanshah.bsky.social.
This article is the fifth in PBE’s new ‘Economics to improve lives’ series that explores a question at the heart of PBE’s mission: How do we ensure that wellbeing – the quality of life experienced by individuals – is the ultimate goal of government?
We’re bringing together thinkers and commentators from across economics, policy, academia, media and civil society to challenge conventional wisdom and consider how we might build an approach to measuring economic success that puts the lived realities of people at its heart and fits the times we live in. Opinions are the author’s own.
Read previous articles in this series from Nancy Hey, Sarah Davidson, Jon Franklin, Ed Humpherson.