At the start of 2020, the Office for National Statistics (ONS) released a statement saying that it had persistently underestimated the extent of income inequality in the UK. According to the ONS, income inequality—as measured by the Gini coefficient—was at least 2.4 percentage points higher than official figures suggested when taking into account income from capital gains.

This weekend, the Resolution Foundation released a report demonstrating that our measures of wealth inequality suffer from a similar problem. The Missing Billions argues that the Wealth and Assets Survey, used by the ONS to measure wealth inequality, struggles to account for many of the assets held by the wealthiest in society. By merging information from the WAS with information from the Sunday Times Rich List, the Resolution Foundation finds that the top 1% is almost £800 billion wealthier than previous estimates suggested.

How do we keep failing to accurately measure wealth and income inequality? One thing worth noting is that these measurement errors cannot be put down to any peculiar failings of the UK’s Office for National Statistics.

A 2016 study from the OECD found that income inequality in Canada was higher than previously thought, largely because high earners underreport their incomes in household surveys. Last year, Canadian researchers used the same methods as the Resolution Foundation—combining national statistics with information from Canada’s Rich People List—to show that the wealth held by the top 1% was CA$3 trillion higher than previous estimates suggested.

A recent study in Germany also found that both wealth and income inequality in the country are higher than previously thought. In Germany, the richest 1% own 35% of the total wealth, rather than 22% as previous estimates had suggested; and the country’s Gini coefficient is 0.81, rather than 0.78. And last year, a study in Norway also used new methods to show that, while statisticians previously thought that the top 1% earned 9% of all income, they really take home 20%.

Similar studies demonstrating systematic underreporting of wealth and income inequality can be found for many other rich countries. The wealthy seem consistently to understate their wealth and income in self-reporting surveys.

But there are other issues too. First, at the very top of the income spectrum wealth and income are highly fungible: it can be hard to differentiate income from wealth and wealth from income. Depending on the tax treatment of different forms of income and wealth, the very richest can decide how to receive their income to minimise their tax burden. A business owner, for example, might decide to remunerate themselves through dividends rather than by paying themselves a wage.

Second, and relatedly, the wealthier have a greater ability and incentive to avoid and evade tax, so any system that attempts to measure inequality using tax data is likely to understate the extent of the problem. In 2017, researchers studied the data found in the leaked HSBC files and the Panama papers and showed that all over the world the wealthiest were far more likely to avoid or evade tax than the less well-off, and that this was likely substantially skewing inequality statistics downwards.

It is notable that none of the studies mentioned above fully accounted for every one of these three problems. The problem of underreporting in surveys can be addressed through an analysis of tax records, but these methods cannot account for what is likely to be the most significant culprit in our consistent underestimation of wealth and income inequality: tax avoidance.

Some of the largest and most powerful financial institutions in the world generate a significant portion of their income from supporting clients to avoid tax, which requires a huge amount of secrecy and subterfuge. These institutions would not give in to demands for full transparency without a significant fight – a fight that most governments are unwilling to wage.

Statistics can be a powerful tool for demonstrating the dramatic inequalities generated by capitalism and the Left can and should rely on them where rigorous data exists. But the problems of measurement that researchers have discovered in recent years are not coincidental; they show that measuring economic outcomes is not a neutral endeavour, but one that is inflected by power relations.

Our inability properly to measure inequality is a symptom of a much deeper problem. The production of knowledge in capitalist societies is always geared towards the interests of the ruling class.

The governance of populations—what Foucault called ‘biopolitics’—is intimately linked with attempts to observe and measure those populations; and the methodological tools used for this measurement and observation are themselves designed for very particular purposes. Under neoliberalism, measures of inequality are not designed to serve as the basis for a critique of capitalism; they’re designed to support the efforts of capitalist states to control their domestic populations and economies.

Higher income inequality, as is now well-known, leads to a whole host of social pathologies—from higher rates of violent crime, to lower reported levels of trust in dominant social institutions—all of which makes governing harder. And it is a central tenet of Keynesian economics that higher levels of inequality constrain aggregate demand and therefore output.

The real root of inequality under capitalism is, of course, the dispossession of the working class. The social relations that underpin capitalism naturally generate extremely high levels of inequality, tempered only by the actions of governments seeking to stabilise the system. While statistics can bear this point out—often very powerfully—socialists shouldn’t need them to understand that the system is far more unequal than we are encouraged to believe.