Beyond GDP: Measuring Welfare and Assessing Sustainability by Marc Fleurbaey and Didier Blanchet is a technical book on the profoundly important question of how we measure “the economy”. The authors are two distinguished economists/statisticians who were respectively a member and rapporteur for the Sen-Stiglitz commission appointed by the then French President to consider whether there is a better kind of metric than GDP. This is of course a subject about which there has been considerable debate over the years. Although this is a technical book, the algebra should not defeat a professional economist, and the explanations are very clear. The introduction is well worth a read by anybody interested in this debate.
The book’s concludes that we should be talking about “GDP and Beyond”, because GDP is adequate for measuring production and income. However, when it comes to the ‘beyond’, the authors convincingly show that a number of commonly-proposed alternatives have significant flaws in theoretical terms.The alternatives take one of two forms: a composite index that adjusts GDP in some way, either by subtracting some elements or weighting it with other kinds of indicator; or measuring well-being directly via surveys.
On the composite indices, the book points out that they are arbitrary and lack analytical foundations. They make implicit assumptions about substitution possibilities between their components. They aggregate together inputs, intermediate products and outcomes. There is almost no informational gain from these ‘corrected’ GDP alternatives. They are, to sum up, a dog’s breakfast.
The authors are no more impressed by measures of well-being or happiness. They disagree that happiness is the right or ultimate goal. “Taking happiness as the ultimate goal in life is far from normal and popular.” Indeed, normal views of morality tend to regard hedonism as a negative, not a positive. As for the ‘Easterlin paradox’, they note that subjective well-being indicators fail to account for the way people calibrate their expectations depending on what they are used to; it is simply implausible to think people do not have a strong preference for, say, the greater longevity normal now compared to 50 or 100 years ago, but they answer surveys in ways calibrated to their experience of how things are now. Not only is GDP not bounded, while surveys are answered on a 1-10 scale, but “People are induced to reason in relative terms when they must describe an open-ended object, their lives, on a closed scale.”
As the book points out, measuring current welfare is one thing, but measuring sustainability is another – and much harder. It is a separate challenge, although they are often merged. The reason for the intrinsic difficulty is that it isn’t possible to compare present consumption or activity to as ‘sustainable’ level without taking a view about the future – and not just one specific future but the entire possibility set taking account of uncertainties about how the world is now and how it may change as people’s behaviour and preferences change. “It is illusory to believe that all the information we need about the future is already present in current observations.”
This all sounds rather negative. If the conventionally-proposed alternatives are so flawed, and sustainability is intrinsically hard, is there any better alternative?
The book goes part way to an answer. It recommends looking at a version of ‘adjusted net savings’ to measure sustainability. This involves looking at changes in the stocks of relevant assets, whether physical, human or natural capital. The authors recommend a carefully-structured dashboard of indicators of over-consumption or dissaving, with the ‘Goldilocks’ aim of being neither too aggregated to be meaningful nor too disaggregated to be easily understood. On current social welfare, they recommend the ‘equivalent income’ of non-market activities or outputs, that is the income that would give the same utility as non-market dimensions of welfare such as health, the environment or social connection. This is a well-known bit of the economics toolkit, asking people how much they would need to give up something. This is better, the book argues, than making the a priori assumptions involved in present composite indicators. And it gives a clear metric for assessment, namely money: “Whatever one does, aggregation implies putting relative values on very different items, and doing so in monetary units is no less respectable than the apparently dimensionless valuations implicit in composite indexes.”
I think this carefully-argued book is very persuasive – this is not an easy challenge, and the analytical issues are set out here with great clarity. It did not give me a clear idea of how the preferred methods would be put into practice, but no doubt statisticians are working on this. The effort is certainly worthwhile, and after all, calculating GDP is itself a complex and time-consuming business. The one point on which I’d disagree with them is the throwaway line that GDP itself is ok and should be left alone. I certainly think we need GDP but it will itself need reconsidering as it might not be the best way to measure an increasingly intangible, service-based, economy with a huge proliferation of variety and complexity. More on that in my new book GDP: A brief and affectionate history, out early next year!