By Richard Heys
As an economist working in government, I was once described as being akin to a plumber, sorting out the metaphorical piping on a particularly knotty policy question. Economists often describe themselves as using a range of techniques akin to having a ‘tool-box’ from which to pick. However, using the ‘right tool’ for the right job is normally a good start: Using the ‘wrong tool’ normally doesn’t lead to the best results. The work of our paper, as well as its predecessor and successors in the future, is to add an array of simple tools suited to different circumstances which economists in government, academia, the private sector, and elsewhere can use alongside the Gross Domestic Product (GDP) hammer.
This is pretty much the challenge around GDP – that as a measure of economic output centred on the market economy it is a hugely reliable tool and does its job better than any other conceivable metric. GDP has a long back-series, so one can look at previous comparable events and use these to predict what might happen now. It can be broken down into more granular data. It is published frequently. One can compare between countries to understand relative performance. It is timely, with monthly data and preliminary estimates calculated just 45 days after the end of each month. And finally, it is accurate and being comprehensive in terms of being a good measure of the concept it is targeting.
But as a measure of ‘welfare’ it isn’t really suitable. There have always been critics of GDP, and a variety of reasons why they have felt the need to criticise it, and a big part of that is related to what it excludes. Whilst national accountants will say in relation to GDP that there is ‘for everything a place, and a place for everything’, this is part of the problem: what if the place for something of increasing relevance is outside the national accounts and the scope of GDP? This is a growing challenge given the pace of change in the economy and society, and as much as national accountants may argue that GDP shouldn’t be used when it is the ‘wrong tool’, in a world where it is the ‘only tool’ it is important to recognise that as statistical producers we may not be giving data users much choice. The importance of this was summarised powerfully by Joseph Stiglitz as part of the Report by the Commission on the Measurement of Economic Performance and Social Progress (2010), which propelled the ‘Beyond GDP’ agenda to the forefront of international debates;
What we measure affects what we do. If we have the wrong metrics, we will strive for the wrong things.
At its heart, this debate comes down to the fact that when thinking about the economy there are ultimately two aspects of interest: there is a need to understand the size and composition of the economy as a whole, and a need to understand what is happening at the innovative frontier and driving change. This reveals two key issues:
Firstly, to measure an economy on a consistent basis, to be able to compare across time and between countries, one must have consistent rules, consistently applied, which define what is in scope and what is not. Now those consistent rules must be agreed internationally, otherwise any country could choose to make itself look more successful by including more of what it is good at and less of what it is not. That agreement can take a long time, and given those rules need to apply to the poorest as well as the richest countries, it would not be fair to re-write them every year as changes can be expensive to implement. This is why the international national accounts community is governed by the System of National Accounts 2008, and is currently debating changes which may be included in 2025 for countries to apply from 2027 onwards.
But this takes us to our second key point: in a fast-moving world, a rulebook written 13 years ago may no longer meet need, especially at the innovative frontier. A simple example: the 2008 System of National Accounts mentions the word ‘digital’ precisely and only twice; both times referring to digital cameras, a product which is now rarely seen, having been almost completely replaced by cameras integrated into smartphones. The pace of change in the most innovative parts of the economy have completely outpaced our ability to keep up, particularly when many countries face either constrained budgets or real data collection challenges.
So if it just isn’t possible for GDP to both be constantly up to date and to be widely consistent across geography and time, one has to make a choice between the two. The international community has generally sought a compromise by maintaining the rule book for long periods of time, then implementing one large set of changes each generation: leading to the last three manual revisions being dated 1968, 1993 and 2008: the manual has only been revised twice in the last 53 years.
So, if the GDP hammer isn’t going to be the ‘right tool’, then maybe it is time to invent the screwdriver. This takes us to a path frequently walked: many groups, individuals, commissions and reviews over the years have considered alternative measures; whether they be single measures, like GDP, or more complex dashboards containing a variety of data sources. Our contribution aims to achieve several things:
- We want to use pre-existing data as much as possible, so the new measures can be produced on a consistent basis with GDP, and other national statistics around natural capital and other measures, and in this area, it is worth saying that the ONS is one of the strongest statistics bodies in the world. We publish high quality data on a range of key measures which this project has been able to recycle at minimal extra cost, demonstrating the value in that original investment.
- We want to use existing, international agreed frameworks and methodologies centred around national accounting methods as far as possible, effectively widening the range of activity by loosening the production boundary. Where this isn’t possible, we use methodologies and data which would be readily available in countries outside the UK. Again, where much of this data has been produced via ‘satellite accounts’ using methods agreed to deliver consistency to the national accounts we are able to move quickly and with certainty we won’t be double-counting or missing key components.
- We want to reflect the wider range of factors which impact economic welfare by bringing unpaid household production and flows of benefit arising from the environment into the picture to reflect that increasingly we don’t only derive economic value from what we purchase and consume. As increasing numbers of parents and guardians have had to take up childcare responsibilities during the pandemic, this “work” isn’t included in GDP. As pollution and emissions fell, and the value of parks and open spaces became even more evident to many, these were also excluded. And whilst GDP will account for changes in the number of children in school, the impact on their examination results is also excluded.
- Finally, we want to recognise the importance of capital, in all its forms. We both have a wider understanding of capital and the impact of different types of capital have both on production and, particularly through environmental degradation, on the planet.
So, what does that give us in terms of results. At the headline level, our new measure (called augmented NNDI) noticeably outperforms GDP and other market metrics over the period.
Breaking this down, we can see the key driver of this difference is unpaid household production. It isn’t unusual in a recession for us to do more work in the home – cook meals rather than purchase them in restaurants, look after children rather than use childcare, do DIY rather than hire a painter-decorator. But what is unusual is that once the economy started to recover, we didn’t revert to buying these services, such that growth of these services exceeded 15%, and is now almost as large as the market economy.
Secondly, despite carbon emissions falling over the past decade, the degradation of the atmosphere (as a natural capital) from these emissions has increased. According to the methodology applied in this work, this can be attributed to the emissions being produced into a warmer world over time, with the result that the marginal cost of each unit of carbon has increased and outweighed the impact of reduced emissions: the cost has gone up faster than the volume has fallen; which if we are correct is a worrying and highly pertinent result.
So, in conclusion, is this new measure perfect? Is it the right tool for understanding changes in welfare? We consider it is a better tool than GDP for measuring welfare, with a long-term consistent time series, utilising standard methodologies which allow us to compare with other data-series, but there is still work to do. The eagle-eyed will have spotted there is no account taken of human capital. To do this we need to do further work to create a Human capital satellite account framework, fully incorporating stocks and flows. We also need to capture the impact of free digital services on household production and a fuller set of natural capital service flows.
Does that mean we advocate this measure as a replacement for GDP? No: there is, and will always be a place for GDP in economic decision-making. Just because one has a screwdriver doesn’t mean you are going to throw away your hammer. Nevertheless, having a wider measure to complement GDP has to be an improvement, providing a fuller, richer picture of economic welfare that builds upon, rather than rebuilds, national accounts.
So what happens next? We plan to further develop this work, and are keen to receive feedback. We also need to update our analysis with the forthcoming Blue Book 2021 dataset. We want to particularly explore integrating human capital. Finally, we plan to develop a Total Capital Stock publication, and explore the potential to update this data annually.
Read the full ESCoE Discussion Paper here.
Richard Heys is Deputy Chief Economist at ONS.
ESCoE blogs are published to further debate. Any views expressed are solely those of the author(s) and so cannot be taken to represent those of the ESCoE, its partner institutions or the Office for National Statistics.