Do we really listen to expert advice?

There’s no point telling somebody who grows more desperate as each bill falls due that the overall economic situation is improving or to take a broader, longer-term view. If what the expert says has little or no relation to what people feel or can see all around them, it’s inevitable that they stop believing the experts and the politicians they advise, and look for answers elsewhere. President Sarkozy of France recognised this, and in 2008 convened the Commission on the Measurement of Economic Performance and Social Progress, the so-called Stiglitz-Sen-Fitoussi Commission.

The traditional approach to measuring an economy and well-being relies heavily on GDP. But GDP’s inventor, Simon Kuznets warned against this. He stressed that GDP is a measure of output, not of well-being. “It measures everything in short, except that which makes life worthwhile” as Robert F. Kennedy famously remarked. Kuznets and Kennedy also pointed out that GDP has nothing to say about the consequences of environmental degradation.

The OECD-hosted High Level Group on the Measurement of Economic Performance and Social Progress (HLEG) was created to pursue the work of the Stiglitz-Sen-Fitoussi Commission, whose final report was published in 2009 (Stiglitz et al. 2009). In a double volume of findings published at the end of last year – Beyond GDP: Measuring What Counts for Economic and Social Performanceand For Good Measure: Advancing Research on Well-being Metrics Beyond GDP (Stiglitz et al. 2018a, 2018b) – the HLEG argues that we need to develop datasets and tools to examine the factors that determine what matters for people and the places in which they live. The production of goods and services in the market economy – something which GDP does try to capture – is of course a major influence, but even in the limited domain of the market, GDP doesn’t reflect much that is important. The most used economic indicators concentrate on averages, and give little or no information on well-being at a more detailed level, for instance how income is distributed among households. Once conclusion of the HLEG is then that we need more granular data that capture all components of income and wealth and how they are related to each other. We also need to complete and render more timely the datasets we do have, both by integrating administrative and other types of data (such as from surveys) that already exist, and redesigning national accounts to incorporate distributional aspects.

It is often easier to measure outcomes than the factors that contributed to producing those outcomes. The Group devoted considerable efforts to circumstances outside the control of individuals, such as ethnicity or gender, that can have a significant impact on inequality and opportunities. The HLEG also looked at factors, such as trust, that can be both a cause and consequence of both well-being and market income. The evidence shows that subjective well-being is influenced by trust, while countries with higher levels of trust tend to have higher income.

An important determinant of well-being is security, and as in many of the domains considered by the HLEG, there are important interactions between objective measures (such as the risk that an individual falls into poverty) and subjective metrics.

Economic insecurity today is only one of the risks individuals face. Other risks are those affecting people’s future well-being. The Group considered how to better measure the resources needed to ensure economic, environmental and social sustainability and the extent to which we are approaching (if not trespassing) critical “tipping points” and planetary boundaries. The HLEG discussed the new metrics and tools that would be required to analyse the complex interactions between the economy, the environment and social conditions.

Misleading statistics result in misguided policies. If governments think the economy is well on the road to recovery because that’s what GDP suggests, they might not take the strong policy measures needed to resuscitate the economy that they would take with metrics that inform on whether most of the population still feels in recession. If they do not have metrics on the extent of people’s economic insecurity, they may not take measures to bolster the safety net and social protection; they might even set about stripping away some social programmes.

One reason the Great Recession morphed into a social and political crisis is that relying on GDP not only gave a false picture of the overall state of well-being, it contributed to the decline of trust in governments and experts, as people saw that their own situation was not improving despite the claim by the experts, based on certain official figures, that a recovery was underway. If we had had better metrics, including better measures of increases in people’s economic insecurity, we might have realised that the downturn was deeper than the GDP statistics indicated. And if that had been the case, perhaps governments would have responded more strongly to mitigate the negative impacts of the crisis.

The HLEG sets statisticians a challenge: find the right balance between a comprehensive set of metrics that embraces a full account of what is occurring and a simpler and less complete set of metrics that are more comprehensible. In other words, a set of indicators that is broad enough to reflect what matters in people’s lives, but narrow enough to be readily understood by policymakers and the public. But having the right set of indicators is just the beginning. They need to be anchored in policy. If we want people to trust us, we have to show them evidence that is at least as good as the evidence of their own eyes. And we need to act on this evidence, designing policies that improve their lives. In this way we can close the gap between experts and ordinary people that are at the root of today’s political crisis.