Uncounted: Power, inequalities and the post-2015 data revolution

Data: Facts and statistics collected together for reference or analysis

Revolution: A forcible overthrow of a government or social order, in favour of a new system

– Oxford English Dictionary

Just published: a special double issue of the journal Development on African inequalities, including my (open access) guest editorial setting out the thesis of ‘Uncounted’ – how power and inequality are intimately related to who and what go uncounted, from tax evasion in the 1% to the systematic exclusion of women and girls, from the corrupting influence of illicit financial flows to the marginalisation of people living with learning disabilities…

Guest Editorial: Uncounted: Power, inequalities and the post-2015 data revolution

Development (2014) 57(3–4), 320–337. doi:10.1057/dev.2015.28

People and groups go uncounted for reasons of power: those without power are further marginalized by their exclusion from statistics, while elites and criminals resist the counting of their incomes and wealth. As a result, the pattern of counting can both reflect and exacerbate existing inequalities. The global framework set by the Sustainable Development Goals will be more ambitious, in terms of both the counting and the challenging of inequalities, than anything that has gone before. This article explores the likely obstacles, and the unaddressed weaknesses in the agreed framework, and suggests a number of measures to strengthen the eventual challenge to inequalities, including by the promotion of tax justice measures.

Keywords: inequality; data; household surveys; SDGs; tax; uncounted

 

While the whole edition just came out, it is technically the 2014 volume. The majority of the papers are drawn from the Pan-African Conference on Tackling Inequalities in the Context of Structural Transformation held in Accra that year, and include some cracking contributions – not least important papers on gender inequality, sustainability and disabilities, as well as broader pieces on the economics and politics of inequality. Check out the full table of contents.

Power in the darkness, uncounted

Is ‘girl-centred development’ harmful fantasy?

Has the worm finally turned on the promotion of ‘girl-centred development’ in terms of claimed macroeconomic benefits? Daphne Jayasinghe posted on aspects of this yesterday; and the academic literature is pointing the same way.

The Journal of International Development has just published a paper by Cynthia Caron and Shelby Margolin, Rescuing Girls, Investing in Girls: A Critique of Development Fantasies.

The authors analyse “three girl-centred campaigns [and find that they] identify and diagnose girls’ problems and prescribe solutions that not only circumscribe girls’ futures, but are also counterproductive.”

From SciDevNet’s handy summary:

These campaigns do not recognise girls as individuals, each with specific abilities and personal aspirations, but rather assume that all girls want to be educated, raise families and become wage earners,” write Cynthia Caron and Shelby Margolin, two development scholars at Clark University in the United States…

The authors say these programmes support a “development fantasy”, promoting education as a way to “invest in girls” and increase their economic value. The campaigns aim to further economic growth under the guise of girl empowerment, say Caron and Margolin, perpetuating what they see as a “failed development narrative that economic growth inevitably leads to an equitable future for all”.

Has the worm turned? Let’s hope so. The need for a genuine focus on women’s empowerment is far too great for it to be pushed down the channel of fantasy.

Here’s the full abstract:

The girl child increasingly is at the centre of development programming. We draw on Slavoj Žižek’s notion of fantasy to show how and, more importantly, why girl-centred initiatives reproduce the shortcomings of women and gender-focused programmes before them. Through an analysis of three girl-centred campaigns, we illustrate how experts identify and diagnose girls’ problems and prescribe solutions that not only circumscribe girls’ futures, but are also counterproductive. We argue that even as campaigns try to integrate lessons learned from earlier gender and development initiatives, the critical reflection that a Žižekian approach promotes would better enable development actors to reformulate campaigns and fundamental campaign assumptions.

Versions of the same thinking are clearly now influencing some of the campaigns that have been critiqued too – take for example Katrine Marçal’s piece in the 2015 State of the World’s Girls report:

Girls and women are not an untapped economic resource in the world; their work is the invisible structure that keeps societies and economies together.

Things are shifting.

Time for a gendered data revolution

Too many of the big numbers on gender inequality count the cost for GDP – rather than the costs imposed on women. Daphne Jayasinghe, Women’s Rights Policy Adviser at ActionAid UK, calls time. 

Counting gender inequality – which big numbers?

It seems that when it comes to measuring the scale of women’s economic inequality, big numbers really count. Last month the McKinsey Global Institute published its finding that labour market gender inequality represents a $12 tn loss in global GDP. The IMF, the World Economic Forum, the OECD and others have described the “double dividends” of increasing numbers of women in the labour market thereby increasing GDP growth rates .

This analysis makes a striking, headline grabbing argument but what is the purpose? In spite of 1 in 3 women suffering violence and a gender pay gap as high as 30% in some countries, it seems that world leaders and decision makers need more convincing on the value of gender equality.

The fashion therefore is to promote women’s rights in relation to financial returns to the economy. To highlight the growth potential for economies of more women in the labour market, regardless of the exploitative or dangerous conditions they may be working in.

This analysis neglects the fact that neoliberal growth models rely on underpaid women workers as well as a workforce that is fed, clothed and brought up by the invisible cadre of unpaid women carers. Gender inequalities in the home and work place are by no means an inconvenience to global capitalism, they are a precondition for its success.

Counting the costs to women

ActionAid took steps to attach a big number to this debate which challenges this contradiction and measures losses to women themselves. We estimate that women globally could be USD$17 trillion better off each year if their pay and access to jobs were equal to that of men (USD$9 trillion in developing countris). We argue that women’s cheap labour and unpaid work is effectively subsidising the economy by this staggering amount – a result of gender discrimination and women’s economic inequality.

AAid gender gap2

An analysis of this problem that makes a growth potential argument for gender equality neglects the role that economic policies can play in exacerbating inequalities.  An assessment of the benefits of economic justice to women themselves and the economic drivers of inequality is vital.

Analysis of the legal gender barriers to the economy exist in the World Bank’s Women, business and the law project. In contrast, an understanding of the underlying but more pervasive social norms governing gender inequality is constrained by data shortages. For example, less than half of all countries measure unpaid care using time-use surveys.

Talkin bout a revolution

The Sustainable Development Goals agreed last month present an opportunity to improve gender data particularly since addressing discriminatory social norms and institutions has become a new development priority and features strongly across the goal on gender (SDG5) targets. Investments in countries’ capacity to gather data and attention to strong indicators to track the progress of achieving goals are imperative.

Such a gendered data revolution may help move the debate on women’s economic empowerment along from assessing what women could do for the economy towards what they are already doing – often with little recognition or reward.

Ask not what women could do for the economy – ask what they are already doing. 

 

Framing and social construction: A UK proposal, post-election

[A long post, building to an Uncounted proposal on UK inequalities monitoring and data.]

Last week’s UK election produced a majority for the centre-right Conservatives – a majority of parliamentary seats, that is, albeit with 36.9% of votes.

Framing a victory

The winning framing seems to have been one of Conservative economic competence, set against two claimed threats from change:

  • a ‘coalition of chaos’ featuring Labour and the Scottish National Party (despite the 2010-2015 Conservative-Liberal Democrat coalition having set something of a modern precedent in UK politics, and both Labour and the SNP having explicitly ruled out a coalition); and
  • a return to Labour’s crisis-inducing economic incompetence (despite a fairly broad expert and academic consensus that Labour’s economic policy before and through the crisis was pretty reasonable; and that the the 2010 coalition’s austerity measures, largely abandoned in 2012, were a triumph of ideology over economic commonsense, with predictable macroeconomic and human costs).

Much has been written, and much more will be, on the reasons for the framing success – including the breadth of media support for a Conservative victory, and not unrelated, the ‘mediamacro myths‘ per Simon Wren-Lewis that ensured popular perceptions of economic (mis)management remained far adrift of expert analyses.

Lost in construction?

The campaign featured more heat than light on the impacts of austerity, and the related inequalities. Everyone said they’d reduce tax avoidance, some said they’d reduce tax evasion, but there was barely a specific policy proposal among the lot.

OBR 2015 chart 4B receipts in deficit reductionNobody mentioned that the 2010 UK government had been the only major economy to cut tax during austerity – so that spending cuts were, uniquely, greater than the deficit reduction that was achieved.

In terms of either broad inequalities (e.g. income and wealth), or specific ones facing marginalised groups such as people living with disabilities, the campaign featured little in the way of detailed discussion.

Marginalisation in (as?) policy design

Jim Coe has written a typically thought-provoking piece on the challenges facing broadly progressive activists in the UK now.

Jim looks at a model of four groups in terms of (i) their respective power and (ii) the extent to which they are ‘socially constructed’ as deserving policy support or not:

Coe power matrix

  • Advantaged groups – such as small businesses, or homeowners – are treated with respect and perfectly placed to receive policy benefits.
  • Contender groups – such as some in big business (bankers etc) – are not seen so positively. But, because they are powerful, they can gain hidden benefits whilst resisting attempts to impose policy sanctions.
  • Dependents – groups who require some kind of support, students, workers on low pay – are seen generally positively but lack political power. They may be viewed as ‘good people’ but the support offered will often be inadequate, and they lack the influence to make enhanced claims.
  • ‘Deviants’ both lack power and are negatively perceived. The list of groups who fall in this category seems to be ever-growing. Criminals, drug users, and, increasingly, many migrant groups, and families in poverty, etc. etc. Few speak on their behalf and policy makers are reluctant to be seen providing ‘good things to bad people’.

Jim’s post is well worth reading, as he builds from here to discuss the ways in which positions can be self-reinforcing over time, and what the strategies may improve the prospects for reversal or resistance in particular aspects. I want to make a comment and a proposal.

Austerity and uncounting

There is presumably always pressure, in the model above, to squeeze those in the low power group deemed deserving of policy support, into the undeserving group: in the model’s terminology, to see dependents increasingly as deviants.

In the context of a commitment to austerity – whether economically sensible or not – there is a specific need to reduce the total of policy support, potentially giving rise to a political climate which sets those with power (more) strongly against those without.

CWR disabled cutsIn the UK the growth in abuse directed at people living with disabilities, including learning disabilities, is a particularly damning feature of this trend – along with the disproportionate cuts in benefits applied. The rise of explicitly anti-immigrant positions across the major political parties is another.

A flipside of this that one might expect to see is a (quiet) reduction in the fiscal contribution of those with power – perhaps explaining the UK’s real reduction in tax revenues, though not necessarily why the UK is an international outlier in this regard.

The incoming government has committed to sharper cuts than it managed in the previous parliament: with a similar revenue trajectory, the risk is of a significant worsening in inequalities, and the weakening more generally of the state’s capacity to deliver support to ‘dependent’ groups.

Finally, Jim’s model provides one more way of thinking about the phenomenon of Uncounted (the importance of power for being counted, and vice versa).

This last parliament has seen some fairly striking uncounting – none more so than the decision to stop collecting statistics on the deaths of those receiving certain benefits, but the continuing failure to implement fully the government’s own review recommendations about statistics on lives and deaths of people living with learning disabilities should not be overlooked either.

Failing to count bad group outcomes represents a substantial worsening of the inequalities faced – but often a politically beneficial one for governments.

A modest proposal

Without getting into party political issues of leadership direction, are there reasonable measures that would support greater accountability to limit damaging inequalities in the current parliament, and promote greater attention to these issues in future political debate?

The one that springs to mind is simply to track the data – its existence or otherwise, and its values where it does exist – on each of the major inequalities in the UK.

The high-level group that David Cameron co-chaired on the post-2015 successor to the Millennium Development Goals was absolutely clear on the importance of disaggregated data to ensure that all groups and people benefit:

The suggested targets are bold, yet practical. Like the MDGs, they would not be binding, but should be monitored closely. The indicators that track them should be disaggregated to ensure no one is left behind and targets should only be considered ‘achieved’ if they are met for all relevant income and social groups. We recommend that any new goals should be accompanied by an independent and rigorous monitoring system, with regular opportunities to report on progress and shortcomings at a high political level. We also call for a data revolution for sustainable development, with a new international initiative to improve the quality of statistics and information available to citizens.

My pie in the sky is that groups like the Resolution Foundation, Centre for Welfare Reform, #JusticeforLB, National Institute of Economic and Social Research, UK Women’s Budget Group and others, might collaborate to ensure the following:

  1. A baseline of available UK data on a full range of aspects of human development, fully disaggregated as Cameron’s panel demanded, showing levels of inequalities and also gaps in data, as at 7 May 2015; and
  2. A tracking and ongoing analysis of changes in that data and its availability over the course of the current parliament (and ideally beyond).

Naturally, this would be a fully open data pie in the sky, and ideally one or more groups like Open Knowledge Foundation would play a role too.

Immigrant life and death in Europe, uncounted

Just as immigrants to Europe are often undocumented, so too their deaths. The UK’s Institute of Race Relations has published a study looking at the known cases in recent years, and it makes for terrible reading from the title onwards: ‘Unwanted, unnoticed: An audit of 160 asylum and immigration-related deaths in Europe’.

Aside from the typically harrowing detail of each case, the study puts together an overview of the main patterns.

How can people be uncounted up to the point, even, of their death? Out of 160 cases, not even the cause of death is known for 32 people. Not. Even. For 43 people, even the basic information of nationality remains unknown.

Table 2 shows the main factors where these are known.

IRR uncounted migrant death 2015 tab2

These findings aren’t only important because, well, people died. As the authors put it:

If there is no publicly accessible record of deaths, how can states be held accountable?

The report calls to mind the CIPOLD review in the UK: the Confidential Inquiry into the premature deaths of people with learning disabilities. Through tracing individual stories of lives and deaths, the study created a set of baseline results that remain the best we have – including:

  • men with learning disabilities die, on average, 13 years younger than men in the general population; and
  • women with learning disabilities die, on average, 20 years younger than women in the general population. (Intersecting inequalities, anyone?)

These differences are not, to be clear, just a direct result of learning disabilities. They reflect society’s treatment of people who live with learning disabilities. The report finds, for example, that 37% of deaths would have been potentially avoidable if good quality healthcare had been provided (and see Chris Hatton’s powerful comment on discrimination by health specialists).

There’s an earlier post here on how the problem of being uncounted with learning disabilities hasn’t been addressed in the UK since CIPOLD, and despite various high-profile scandals.

Not always, but often, an important part of not counting is not caring. And all the more so when the uncounted is a particular group. The phenomenon of Uncounted is not a technical one, but a profoundly political one.

Back to migrants in Europe. Uncounted, from beginning:

IRR uncounted migrant death 2015 tab1To end:

IRR uncounted migrant death 2015 tab3

Link to the full study.

Transgender Reporting and Human Rights

I’m delighted to host this guest post from Fran Luke, full-time parent, un- and underemployed musician and teacher.

“Ignorance is the parent of fear.” Moby Dick, Herman Melville     

I am not a subject matter expert.  I do not pretend to be, nor have I ever had any intention of becoming one.  I would much prefer to be playing with my children, writing music, improving and performing on my instruments, or even working at a job that allows me to adequately care for my family.  That said, I have located and read as much reporting as I can find regarding Transgender Human Rights issues, globally.  I’ve read a good many other reports, as well, but this is personal.

After being advised by a member of an NGO advocating, I guess, for people ‘like me’ that the ‘time was not yet right’ to pursue Trans* rights at the UN level, I felt the need to learn more.

When our leadership spends more time speaking about the tie or dress they wore to a White House function, or how great it is our Trans* children can now die in endless war, it’s time to look elsewhere.

The argument for which group is the most marginalized should never be entered into.  It is pointless.  It’s always an issue of class and perceived degrees of humanity.

Transgender reporting

With regard to documentation, who is included or not, and policy, I’ll start with the UN.  It’s my understanding population data is provided at the national level.  This from a brief discussion with Anne-B Albrectsen at UNFPA, “We work to make sure that all countries disaggregate data as much as possible. Nationally owned data is best”.

Can data collected at the national level, perhaps the easiest way to get data into the system, accurately reflect conditions of marginalized sectors?  Would it not often be the policies of those in power that keep marginalized communities where they are?  The issues of the Rohingya and question of citizenship come first to mind.

There is not a great deal of reporting on the issues of Transgender human rights, but there is some.  Rather than begin by referencing reports from LGBTI advocacy organizations, I thought it more appropriate to start with recommendations and reports from agencies within the UN.

UN-counted?

After being treated at times like an uncomfortable joke at some UN initiatives that invited civil society discourse, I thought I’d start with their own recommendations.  These recommendations never seem to make it to the mainstream discussions of Human Rights, or the General Assembly for that matter.

Here is a list of recommendations from the 2013 UNDP Discussion Paper, ‘Transgender Health and Human Rights’:

undp dec2013 trans rights recs

Some of the recommendations from the 2012 UNDP report ‘Transgender Persons, Human Rights and HIV vulnerability in Asia and the Pacific’ include; having Trans* people as research partners, documenting and understanding Trans* vulnerability, promoting transgender rights and culture, making equality legislation work better.

The first of eleven recommendations relates directly to counting:

undp dec2012 hiv trans rec1

UNDP’s 2010 Issues Brief, ‘Hijras/Transgender Women in India: HIV, Human Rights and Social Exclusion’, includes the following recommendations:

undp 2010 hijras recs5-8

Finally, these are the concluding thoughts from the UN-Women briefing paper, ‘The Transgender Question in India; Policy and Budgetary Priorities’:

unwomen trans india conc

Where next?

One question to consider is why this type of analysis has failed to penetrate more deeply into UN and national-level policy discussions.

Another is whether there are risks from being counted – whether invisibility does not sometimes provide a type of protection.   The discussion, and struggle for the realization of Universal Human Rights for any segment of society can never be put off for political expedience.  If the goal is truly a crosscutting, transformative human rights agenda, then we must start by recognizing our shared humanity.  The cost of silence is, and has been far too great.

Night is Another Country - culture of silence

[From The Night is Another Country,  RedLac Trans and the International HIV/AIDS Alliance.]

We know some information at least is there, provided as shown in these instances by the agencies or organizations that do not appear to bring it into the mainstream.  So, who does the counting and decides what to count?  I’ll end here with a quote from Dr. Martin Luther King: 

Cowardice asks the question – is it safe?
Expediency asks the question – is it politic?
Vanity asks the question – is it popular?
But conscience asks the question – is it right?
And there comes a time when one must take a position
that is neither safe, nor politic, nor popular;
but one must take it because it is right.

 

Selected Resources

Links

$17 trillion: ActionAid counting the gender (employment) gap

AAid gender employment fig1

Here are four big bullets from ActionAid UK’s new report, ‘Close the gap!’:

  • Women earn 15% less than men on average. If women’s wage were raised to the level of men’s wages in all developing countries, with all else held equal, women would earn $2 trillion more.
  • Women’s participation is 37% lower than men’s. Raising women’s participation to equal that of men, all else held equal, would see women earn $6 trillion more.
  • Addressing both the wage gap and participation gap simultaneously in this way would see women earn $9 trillion more.
  • Extending the analysis to rich countries generates a global total gap of nearly $17 trillion.

Congratulations are due – it’s an enormously important issue and these are striking findings, so I hope it gets serious attention. [Disclosure: I commented on an early draft of the quantitative analysis.]

How good are the numbers? (Uncounting ahoy)

The methodology is fairly straightforward, and clearly set out in the report. If there’s a weakness, and there is, it’s in the data. ActionAid are commendably straightforward about this too:

Pay gaps and ratio of male to average wage taken from ILO data. There are many missing values. We fill the pay gaps using regional medians…

Inevitably given the extent of missing values, some of the extrapolations of pay gaps verge on the heroic. I’d judge the methodology to be reasonable in the data context, but make no mistake – the data context is shocking. Meanwhile,

Labour share data are taken from a [2012] working paper

I’ve no reason at all to doubt the quality of these data, but how can it be that there is no better source than these multi-year averages calculated by a single IDPM researcher a couple of years ago? The report quite rightly highlights the gender implications of the failure to count unpaid work, and to this can be added the pretty desperate state of counting of paid work.

Normally I would insert some blather here about post-2015 and reasons to be cheerful, but ba’ hairs I’m having a bad day. Talk to me about the data revolution when you’ve decided who’ll be first up against the wall. It seems we’re really talking about incremental data reforms. Either way, serious improvements in gender disaggregation are urgently needed.

Some progress will certainly come via the Sustainable Development Goals, but let’s not kid ourselves. The Open Working Group SDG proposal includes:

8.5 by 2030 achieve full and productive employment and decent work for all women and men, including for young people and persons with disabilities, and equal pay for work of equal value

That should do it, right? Maybe. Remember the current failure of counting is the end-product of 15 years of the Millennium Development Goals – which included this more prominent target:

Target 1.B: Achieve full and productive employment and decent work for all, including women and young people

Still, I suppose the MDGs didn’t include a data revolution so this time is bound to be different. Right?

Three points of caution

  • Presentation. One issue to mention is the possibility that the number take a life of its own, as these numbers can, and ends up being presented as the cost of sex discrimination in employment. It’s not this – because there’s no reason to think that $17 trillion of extra employment will suddenly come into being if the world was fairer, so a good part of this would likely come instead from reduced male employment earnings. The $17 trillion reflects the estimated scale, in currency terms, of the sex gap in employment in developing countries.
  • Economics above the rest? While it makes sense in advocacy terms to go for a big number (that may be why you’re reading this post, for example), it’s unfortunate if it adds to the sense that only economic arguments matter. As the report makes clear elsewhere (in the bits that won’t make any headlines), the deeper dignity and empowerment dimensions are much more important and complex.
  • Inequality reinforced? A related point is that the nature of the calculation reinforces a different aspect of inequality. Consider two economies of the same size with the same gender participation gap but where the average wage in one is twice as big as in the other. The methodology will value the gap in the first as also being twice as big as the other. Now that seems unhelpful, on the face of it, if we would broadly think that the two economies and their respective gaps are of equal importance. In fact, we might think that the gap in the lower-income country is more important, since it is more likely to imply poverty for those on the wrong end.

To give a sense of how important this potential problem is within the overall calculation, compare the developing country and advanced country totals. In particular, note that the wage gap in rich countries is nearly twice that in developing countries. We certainly shouldn’t downplay the sale of the problem in rich countries, and I’m glad ActionAid have made the analysis global rather than giving the impression it’s only a developing world problem. But at the same time, measuring in dollar terms may overstate the relative importance of the problem in high-income settings; when the human costs in lower-income contexts may be equal or greater.

AAid gender employment table1