This blog is based on an article in the Journal of Social Policy by Arun Advani, Tahnee Ooms and Andy Summers. Click here to access the article.
During the decade of austerity that characterised the 2010s, successive UK Chancellors reassured voters that we were ‘all in it together’. They were bolstered by official income statistics showing that key indicators of economic inequality – the Gini coefficient and top income shares – had barely shifted during this period. As Channel 4’s fact-checker website summarised in 2016: ‘Despite the rhetoric from the opposition benches, the official statistics do not support the view that income inequality has worsened since David Cameron became Prime Minister’.
But it is always wise to maintain a healthy scepticism of statistics – in particular an awareness of what they may conceal as well as reveal. As Richard Titmuss asked in 1962, responding to statistics showing how inequality had fallen in post-war Britain:
To what extent and in what respects do these statistics represent reality? How faithfully do they depict the changing constituents of income and wealth, and changes in rewards and ways of spending, giving and saving? … How valid are the concepts and the data in relation to the uses to which they are put?
Sixty years on, our research set out to identify the gaps in the UK’s current income statistics and assess how these have impacted our understanding of economic inequality over the past two decades. Our focus was on incomes from wealth – in particular investment incomes and capital gains – whilst acknowledging that the measurement of other types of income (for example, social security benefits) are also in need of further research.
Our findings show that the problem of missing incomes from wealth remains very much at large. Two key findings are particularly striking. First, by comparing survey data with tax data, we show that in aggregate 70% of all investment income was missing from the survey data used to compile official statistics for 2017. Whilst the ONS’s new ‘top incomes adjustment’ now goes some way to correcting this problem, we estimate that 44% remains missing even afterthis correction, indicating that underestimation of investment income is still a major problem.
Second, we also find that the exclusion of taxable capital gains from the definition of ‘fiscal’ income used in the new top incomes adjustment has seriously distorted official statistics on top-end inequality. Once capital gains are included, we find that top income shares did increase during the austerity period of the 2010s, contrary to the established narrative on which successive Chancellors relied. In other words, inequality had not abated, but just taken a different form – one which official statistics failed to capture.
What policy lessons can we learn from these findings? The most obvious is the need to implement further reforms to official income statistics to fill existing gaps in coverage. But our article also raises more far-reaching implications for the interaction between measurement and policymaking.
First, we hypothesise several mechanisms by which the underestimation of incomes from wealth may have contributed to their current favourable tax treatment. Second, we also emphasise the importance of considering this relationship in reverse: existing policies can constrain what is measured in the first place, and risk skewing the conclusions that policymakers and other researchers draw from available statistics. This concern is of growing importance in an era when administrative data is being used more and more widely in social policy research.
None of this is intended to detract from the welcome process of transformation currently being rolled out by the UK’s official statisticians, leveraging new data sources and methods to improve our understanding of economic inequality, as well as other key social indicators. To be sure, a lot of progress has been made. However, there remains a lot to do. In the meantime, it is important that researchers and policymakers alike remain vigilant about the limitations of the data that they are using.
About the authors
Arun Advani is Assistant Professor at the University of Warwick.
Tahnee Ooms is a Visiting Fellow at the London School of Economics.
Andy Summers is Associate Professor at the London School of Economics.
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