Should we continue to use Gross Domestic Product (GDP) as the key measure of economic and societal progress? Or should we supplement it with measures that reflect broader aspects of society, including unpaid work, use and abuse of the environment, and the use of intangible data assets?
This debate has been going on throughout the history of GDP. It has been given renewed prominence since 2008, when Professors Stiglitz, Sen and Fitoussi published their report on the Measurement of Economic Performance and Social Progress. Their report remains a very clear articulation of the issues.
Recent contributions to the debate
While acknowledging the continued relevance of the Stiglitz/Sen/Fitoussi report, I’ve been struck by two recent contributions to this debate. First, Jon Franklin’s PBE article sets out the parameters of this debate clearly and comprehensively. In particular, he highlights what GDP is and does, and crucially what it does not do, and therefore what alternative measures can contribute.
Second, I chaired a session at the Economic Statistics Centre of Excellence (ESCoE) conference at Kings College London on the future of GDP and alternative measures. It had an excellent panel: Dame Diane Coyle, author of GDP, A Brief But Affectionate History and The Measure of Progress: Counting What Really Matters; Richard Heys, Acting Chief Economist of the Office for National Statistics (ONS); and Chris Giles, Economics Commentator at the Financial Times. This panel avoided the tendency of people on panels to all agree politely with one another. Instead, three distinct views came across:
- Diane’s view was that GDP fails, even on its own terms, to measure the current economy, with its unpaid digital labour and reliance on intangible assets – and that’s before we consider the absence of unpaid work and consumption of environmental resources.
- Richard argued that GDP’s integrated framework makes it powerful, and that recent changes (under the new System of National Accounts) improve it, but that we need complementary measures to capture the full picture of economic wellbeing; and
- Chris put forward the position that we should be very wary about amending or supplementing the GDP measure with new concepts.
More on this session in an upcoming OSR blog.
Usefulness
There’s not much I can add on the technical and conceptual level to either Jon’s masterly article or to the debate at the ESCoE conference.
Instead, I can share a couple of reflections as a statistics regulator about the usefulness of GDP and its alternatives for decision-making.
First is the question of usefulness. As a statistics regulator, we always start by considering what statistics are used for. We recognise they are only meaningful insofar as they meet the needs of users. So, it follows that when considering GDP and alternatives to GDP, we should consider how they would be used, by whom and for what purpose.
For GDP this is fairly clear. As Jon’s essay points out, “GDP is an indicator of the potential tax base and helps identify whether government can afford spending commitments”. And he adds that “it is far easier for government to administer a tax on the sales of goods like clothing than it is on the hypothetical value of housework or volunteering.”
So, it’s often thought that a decision-usefulness criterion should be applied to any alternatives – if we want to measure something different, like wellbeing, we should be clear how these new measures will be useful for particular decisions.
But I’m a bit suspicious if the test is usefulness solely for policy decisions. I’m not sure we should seek better measurement simply because it creates better central policy. I think better knowledge of economic and social wellbeing is worth having; it is a legitimate use in its own right. It’s like history: do we read history because it provides us with actionable insights about decisions we have to make now? Well, maybe. But I think most people are like me – interested in history because it is just interesting.
Knowledge is its own end goal; it doesn’t need a utilitarian purpose to justify itself. Or in the arid conceptual language of economics – knowledge is not an intermediate output that feeds into some other final consumption good (called a ‘policy decision’). Knowledge is a final consumption unit in its own right. (They know a thing or two about sucking the life out of something, these economists, don’t they?)
Decision usefulness also sets a difficult bar for any alternative measure. It implies a neat input-output relationship between statistical evidence and policy decisions. The reality is that so much goes into decisions, that it is not a mechanical relationship between the input of the measure and the output of a policy decision.
And focusing on a broader metric of social progress, like wellbeing, actually serves a range of uses that go well beyond the narrow usefulness to central policy makers who decide on monetary and fiscal policy. For example, PBE’s work with individual charities very often assesses the impact of a charity’s interventions in terms of the increases in wellbeing the charitable activity secures for a group of beneficiaries or a community. These direct wellbeing benefits have a lot of value, at least as much as appraisal approaches which seek to monetise the value of activities using standard assumptions (eg about the monetary value of time saved).
So the thing I would want to see the debate explore is not so much the technical merits of different approaches, but the use cases – recognising that use can be as much about enriching knowledge at multiple levels of society as it is about informing macroeconomic decisions.
Relevance to the public
The second reflection concerns public engagement. This again is a crucial factor in our considerations as a statistics regulator. Are the statistics conveyed in a way that is likely to be accessible and meaningful to users?
As Diane Coyle said in a recent article on the role of evidence in a polarised political landscape, analysts should shift the focus of their attention from trying to influence policy decision makers, to focusing on direct engagement with the public as opinion-formers in their own right.
This is where alternative measures may have a clear potential win. GDP can be hard to explain in simple terms. It can feel technical or alienating, as demonstrated by the famous quote from a citizen at a public event: “That’s your bloody GDP” illustrates (I explore the meanings of this quote in an essay based on another ESCOE event). And some of the technical aspects of GDP may seem counter-intuitive to non-economists – like the significant imputation of the value of housing to owner-occupiers using rents on equivalent properties as a proxy.
Some alternative measures can reproduce these communication challenges. Measures of inclusive wealth, which supplement GDP measures with a broader range of monetised estimates, are conceptually rigorous. But they may be hard to convey in simple and accessible terms. Similarly, the enthusiasm for dashboards which bring together a wide range of metrics may add comprehensiveness but not insight.
I am keener on more direct measures like Carnegie UK’s Life in the UK index, or PBE’s Low wellbeing in the UK report 2024. They have the potential to provide a more direct and accessible measure of what life is like, and what the implications of this are for society.
This question of accessibility constitutes an important test. If alternatives to GDP just create a more complex landscape, or are hard to explain, then they fail the test of public accessibility, and may just complicate the landscape of measures without much benefit. Jon makes a similar point when he says “This challenge is largely one of communication and PR, not a technical one. How can wellbeing measures, or indicators of sustainability for that matter, be translated into something that has both technical credibility and immediately accessible appeal? If we want to go “beyond GDP” we will need to go beyond the comfort zones of researchers and get creative about how these issues are communicated.”
A way forward
This debate has some time to run; we feel far from reaching a consensus. My contribution to it, as statistics regulator, is simple and somewhat humble. It is, in summary, this: the case for supplementing GDP shouldn’t seek to emulate GDP’s apparent decision usefulness as a macro tool. Instead, measures should seek to create a clearer and more accessible picture for public knowledge and understanding. Focus on these questions, and we might make some progress in moving this debate forwards.
This article is the second 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.