The Uncounted

Alex Cobham

• Publisher: Polity
• Year: 2020
• ISBN:
  9781509536030
• Edition: 1
• Topic: Economics
• Subtopic: Economic Policy
• Index: Economics

What we count matters - and in a world where policies and decisions are underpinned by numbers, statistics and data, if you're not counted, you don't count. Alex Cobham argues that systematic gaps in economic and demographic data not only lead us to understate a wide range of damaging inequalities, but also to actively exacerbate them. He shows how, in statistics ranging from electoral registers to household surveys and census data, people from disadvantaged groups, such as indigenous populations, women, and disabled people, are consistently underrepresented. This further marginalizes them, reducing everything from their political power to their weight in public spending decisions. Meanwhile, corporations and the ultra-rich seek ever greater complexity and opacity in their financial affairs - and when their wealth goes untallied, it means they can avoid regulation and taxation. This brilliantly researched book shows how what we do and don't count is not a neutral or 'technical' question: the numbers that rule our world are skewed by raw politics. Cobham forensically lays bare how these issues strike at the heart of our democracy, entrenching inequality and injustice – and outlines what we can do about it.

Part I
Uncounted and Excluded: The Unpeople Hidden at the Bottom

As we embark on this great collective journey, we pledge that no one will be left behind.

Recognizing that the dignity of the human person is fundamental, we wish to see the Goals and targets met for all nations and peoples and for all segments of society. And we will endeavour to reach the furthest behind first.

UN Sustainable Development Goals¹

Would it not be a great satisfaction for the King to know every year in precise terms the number of his subjects, in full and in detail, including all the personal effects, riches and poverty of each house; that of the nobility of the sword and of the clerics of all kinds, of the nobility of the robe, of Catholics and members of other religions, each individual with the places they inhabit? Would it not be a great pleasure, but also a useful and necessary pleasure, to be able himself and from his cabinet to cover in an hour the present and the past of a great kingdom of which he is the chief, and to be able to know by himself and with certainty its greatness, its riches and its strength? This could be done in an orderly fashion, in full and in detail, by means of well-drawn maps, both general and particular, that could be added to the tables of counting which, repeated once every year, would show him precisely and clearly his gains and his losses, the increase or decline of his Estate, the increase or decrease of his peoples, and that of the livestock which are the foundation of men’s subsistence and of trade. And the comparison of the old counts with the new would enable him to judge soundly the changes occurring in the provinces …

Marquis de Vauban, proposing an annual census to Louis XIV of France in 1686²

Notes

1. 1. UN SDGs, finalized text for adoption (1 August 2015), p. 3.
2. 2. Sébastien le Prestre Vauban, 1686, Méthode générale et facile pour fair le dénombrement des peuples, Paris: Imprimerie de la Veuve d’Antoine Chrestien (printed on demand, 2019, Chapitre.com). With many thanks to Dr Julia Prest for her valuable assistance with the translation.

1
Development’s Data Problem

What we measure affects what we do; and if our measurements are flawed, decisions may be distorted … [I]f our metrics of performance are flawed, so too may be the inferences that we draw.

The Stiglitz–Sen–Fitoussi Report (2009)¹

This chapter summarizes several decades of shifts in development thinking and the associated indicators, from GDP to UN development goals. Those indicators have great power – including the power to embed massive biases in development policy and in the progress made.

Everyone knows that development has a data problem. However, different people understand that statement to mean quite different things. For some, ‘development’ is the study of poor countries, and the data problem is that those countries aren’t good enough at generating the data needed to study them. For others, ‘development’ is the process by which poor countries and poor people stop being so poor, and the data problem is about having the information to improve that process.

But these ideas of development are themselves problematic: the notion that some countries (or people) have developed, or are developed; while others are developing, or yet to develop. Increasingly, we think of ‘development’ as shorthand for the whole subject of how human beings live on this planet, the ways in which we as a species organize ourselves from the local to the global, to provide the greatest opportunities for each person in current and future generations to live a good life.

A good life might be considered as one in which people have a degree of power in various spheres: the personal (in which empowerment implies that people enjoy a level of health, education and mental well-being, along with decent work and leisure conditions); the economic (a broadly secure level of income, and freedom from extreme inequality); the political (political freedom and political security, i.e. freedom from political violence or instability); and the social (community well-being, social relations and environmental conditions including environmental security, i.e. freedom from environmental fluctuations).² On this view, poverty is a lack of power – and so is fundamentally political, rather than (say) strictly financial, and necessarily complex and multifaceted.

The data problem for development, understood in these terms, is grave. Typically, we lack sufficient data in countries at all levels of per capita income to ensure that these aspects of a decent life are met. Moreover, the weaknesses of data are not consistent but discriminatory. The data to determine political representation (‘who decides’) and to inform policy prioritization (‘what people get’) tends, as we will see, to exclude further precisely the people and groups who are already marginalized. Development’s data problem reflects a mixture of genuine absences of quantification, deliberate manipulation and bias – in both the collection and the use of data. Those weaknesses, together, are consistently disempowering of marginalized people and groups – effectively deepening their experiences of poverty and inequalities.

Counting is crucial to understanding development. But if we seek to understand development only by what is already counted, we lock in the underlying inequalities. This is to make the same mistake as the drunk who searches for their keys under the lamppost despite having dropped them at the dark end of the street, simply because it is the only place they can see. The emergence and maintenance of effective states, and their capacity to promote and support human progress, depend upon the numbers available and selected. At the same time, differences in development thought have implications for the type of counting that is prioritized, and therefore for the numbers that are available.

If the history of development thought is simplified to a series of evolutionary steps in counting, then in each stage we see that mainstream aims have become more nuanced and more relevant to the lived experience of populations. Inevitably, this greater nuance has driven better counting (that is, better measurement of a population’s lived experience). However, the causality runs in both directions because at the same time, better measurement has revealed important realities that have in turn informed different mainstream priorities.

‘Development’ has itself developed, from the longstanding preoccupation in which economic growth, or the rate of increase in countries’ GDP, was the dominant metric of success. The Commission on the Measurement of Economic Performance and Social Progress (the ‘Stiglitz–Sen–Fitoussi Report’ quoted above) was primarily focused on rejecting GDP as a meaningful metric of progress, but GDP remains disproportionately salient, along with the simple average of economic activity per person, GDP per capita, as a basis to track and compare countries’ development.

GDP: Global Data Problem

GDP poses problems both because of what it does not aim to count, and because of how it fails to count even on its own terms. The most egregious issues, in terms of what GDP does not aim to count, are two. One is the absence of any reflection at all that economic output may come at a planetary cost. If activity is less than totally sustainable, pursuing increases in a measure of total activity may prove to be the ultimate in pyrrhic victories – quite literally. The other is the failure to count unpaid activities – in general, and in particular. In general, because if only what’s counted counts, then the dominance of GDP must bear some responsibility for the trend of which it forms a part, towards narrow economic evaluation, and the devaluing of other human outputs including cultural public goods. And in particular, because GDP is a gender-biased measure of a reality that is itself already deeply, structurally unequal.³

Women’s participation in the labour force globally is estimated to be 26 percentage points lower than that of men. Women also earn less for their participation: 24 per cent less on average, globally. These facts alone would mean that GDP reflects a disproportionately male scale of economic activity – even on top of the inequalities that give rise to the facts in the first place. But it is the additional features of women’s economic oppression that make GDP especially, almost perfectly biased as a single measure of ‘progress’.

Women’s participation in the labour force occurs disproportionately in a sector that is largely or completely excluded from GDP statistics: subsiste...

Table of contents

• Cover
• Front Matter
• Preface
• Abbreviations
• Introduction
• Part I Uncounted and Excluded: The Unpeople Hidden at the Bottom
• Part II Uncounted and Illicit: The Unmoney Hiding at the Top
• Part III The Uncounted Manifesto
• Index
• End User License Agreement