I think that UN manipulating it's own index is not culture wars even if the index is related to gender. Let me know if I am wrong.
Human development
The Gender Development Index (GDI), along with its more famous sibling Human Development Index (HDI) is a an index published annually by UN's agency, the United Nations Development Programme (UNDP). Whether an index is manipulated or not can be judged only against a precise definition of what the index claims to be measuring. So how do you measure human development? Whatever you do, you will never capture all nuances of the real world - you will have to simplify. The UNDP puts it this way:
The Human Development Index (HDI) was created to emphasize that people and their capabilities should be the ultimate criteria for assessing the development of a country, not economic growth alone.
So the UNDP defines the Human Development Index as a geometric mean of three dimensions represented by four indices:
| Dimension | Index |
|---|---|
| Long and healthy life | Life expectancy at birth (years) |
| Knowledge | Expected years of schooling (years) |
| Mean years of schooling (years) | |
| Decent standard of living | Gross National Income (GNI) per capita (2017 PPP$) |
Source: https://hdr.undp.org/data-center/human-development-index#/indicies/HDI
Gender Development
So far so good. Next, on it's website the Gender Development Index (GDI) is defined like this:
GDI measures gender inequalities in achievement in three basic dimensions of human development: health, measured by female and male life expectancy at birth; education, measured by female and male expected years of schooling for children and female and male mean years of schooling for adults ages 25 years and older; and command over economic resources, measured by female and male estimated earned income.
Source: https://hdr.undp.org/gender-development-index#/indicies/GDI
While in the actual report HDI it is simply defined as a ratio of female to male HDI values:
Definitions - Gender Development Index: Ratio of female to male HDI values.
Source: https://hdr.undp.org/system/files/documents/global-report-document/hdr2021-22pdf_1.pdf
Let's look, for instance, at the Gender Development Index of United Kingdom. The value 0.987 means that despite longer life and more education, in UK, females are less developed than males.
| Dimension | Index | Female value | Male value |
|---|---|---|---|
| Long and healthy life | Life expectancy at birth (years) | 82.2 | 78.7 |
| Knowledge | Expected years of schooling (years) | 17.8 | 16.8 |
| Mean years of schooling (years) | 13.4 | 13.4 | |
| Decent standard of living | Gross National Income (GNI) per capita (2017 PPP$) | 37,374 | 53,265 |
Source: https://hdr.undp.org/system/files/documents/global-report-document/hdr2021-22pdf_1.pdf
Wait, what?? What does it mean that females in UK have command over economic resources of post Soviet Estonia (GNI Estonia=38,048) while males in UK have command over economic resources of EU leader Germany (GNI Germany=54,534)?
The manipulation
The UNDP calculates separate command over economic resources for females and males, as a product of the actual Gross National Income (GNI) and two indices: female and male shares of the economically active population (the non-adjusted employment gap) and the ratio of the female to male wage in all sectors (the non-adjusted wage gap).
The UNDP provides this simple example about Mauritania:
Gross National Income per capita of Mauritania (2017 PPP $) = 5,075
| Indicator | Female value | Male value |
|---|---|---|
| Wage ratio (female/male) | 0.8 | 0.8 |
| Share of economically active population | 0.307 | 0.693 |
| Share of population | 0.51016 | 0.48984 |
| Gross national income per capita (2017 PPP $) | 2,604 | 7,650 |
According to this index, males in Mauritania enjoy the command over economic resources of Viet Nam (GNI Viet Nam=7,867) while females in Mauritania suffer the command over economic resources of Haiti (GNI Haiti=2,847).
Let's be honest here: this is total bullshit. There are two reasons why you cannot use raw employment gap and raw wage gap for calculating the command over economic resources:
Argument 1
Bread winners share income with their families. This is a no brainer. All over the world, men are expected to fulfil their gender role as a bread winer. This does not mean that they keep the pay check for themselves while their wives and children starve to death. Imagine this scenario: a poor father from India travels to Qatar where he labours in deadly conditions, so that his family can live a slightly better life. According to UNDP, he just became more developed, while the standard of living his wife is exactly zero.
Argument 2
Governments redistribute wealth. This is a no brainer too. One's command over economic resources and standard of living is not equal to ones pay check. There are social programs, pensions, public infrastructure. Even if you have never earned a pay check yourself, you can take a public transport on a public road to the next public hospital. Judging by the Tax Freedom Day, states around the world redistribute 30% to 50% of all income. And while men pay most of the taxis (obviously, they have higher wages) women receive most of the subsidies (obviously, they have lover wages). But according the UNDP, women in India (female GNI 2,277) suffer in schools and hospitals of the war-torn Rwanda, while men in India (male GNI 10,633) enjoy the infrastructure and social security of the 5-times more prosperous Turkey.
Don't get me wrong, the employment gap and pay gap are not irrelevant for the standard of living and command over economic resources. Pensions and social security schemes mostly do not respect the shared family income and as a result the partner doing less paid work - usually a women - gets lower pension, unemployment benefit etc. What's worse, the non-working partner is severely disadvantaged in case of divorce or break up. But while this has an impact on each gender's standard of living it certainly does not define 100% of that value.
Argument 3
You may argue that the command over economic resources measured by estimated earned income is some kind of proxy for all other disadvantages women face in society. But do you remember what I said in the beginning?
Whether an index is manipulated or not can be judged only against a precise definition of what the index claims to be measuring.
The HDI measures "people and their capabilities" and the GDI is a ratio of these capabilities measured separately for men and women. The economic dimension of the GDI is supposed to be standard of living or command over economic resources - neither of which can be represented by earned income alone.
The taboo
Wikipedia says: "For most countries, the earned-income gap accounts for more than 90% of the gender penalty." (I have not verified this.) This is important, because when we look at the other two dimensions it becomes clear that while men have shorter and less health lives they also increasingly fall behind in mean and expected years of schooling. Without the misrepresentation of the command over economic resources value, the index would show something very uncomfortable: that according to UN's own definition of Human Development men are the less developed gender.
PS: Is there a way to give those tables some borders and padding?
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Notes -
It is very nice of him to send money home to his wife and family. It is a good thing for women in his homeland if most men choose to do this.
But he could still decide to stop doing that at literally any moment. If his wife displeases him, if he meets someone else there, if he runs into trouble and needs the money for himself, if he acquires a drug or gambling problem, or just if he feels like it.
Yes, he has complete and total command over those economic resources.
That he chooses to spend them on his wife is nice for her, but it doesn't change who commands them.
This is not a distinction without a difference. being dependent on someone else for your ability to survive is essentially and massively different from being self-sufficient. And when an entire class of people is in that dependent position, it changes how society conceives of and treats those people, how they conceive of and treat themselves.
This is very much the type of thing the index is meant to measure.
Could he? Most countries have laws against that sort of thing, including alimony. Once they are married, he has literally signed away at least half of his own right to that money.
I looked into the Census Bureau source that this statistic is based on, and the data seems to be based off self-reports by custodial parents, it is not being based off any kind of formal tracking of child support (that method of doing things poses problems too, as it does not include payments made through unofficial channels, but I won't get into that at the moment). Here are some selected quotes:
The technical documentation, which can be found here on the Census Bureau's website, notes this, too: "All household members 15 years of age and older that are biological parents of children in the household that have an absent parent were asked detailed questions about child support and alimony." It is asking the custodial parent, the one with the child in their household, not the non-custodial parent. And looking at the questionnaire used to assess child support payment makes it very clear that the intended target of the questionnaire is the recipient, not the obligor.
Here are some more selected quotes:
I could not find an equivalent questionnaire asking the non-custodial parent what they paid.
This is not, in any way, a trivial source of bias and needs to be kept in mind when you're using these statistics, but the Census Bureau does not disclose this as being a significant limitation of the data - despite the fact that they have used this methodology for a while and despite the fact that this census data has been used for decades to drum up huge social scares around deadbeat dads with no acknowledgement of the possible bias involved.
These caveats were outlined decades ago by Sanford Braver, who states in his book "Divorced dads: shattering the myths" that to answer these questions completely accurately, respondents would have to remember twelve to twenty-four different payments over the past year. In the absence of precise information, many if not most respondents will just try to make up a best estimate, which is a circumstance that allows for an incredible amount of bias to enter into one's results - even worse when you consider that many people are deeply angry at their exes. And if the census officials come to their conclusion based on reports by custodial parents that is going to hugely distort things, the effect being that the results will come with a built-in bias against non-custodial parents.
Braver conducts a study himself where he solves this problem by asking matched sets of custodial and non-custodial parents, and unsurprisingly, custodial parents (mostly mothers) report a much lower percentage of payments made than non-custodial parents (mostly fathers). 13% of mothers report receiving nothing despite being owed support, but only 4% of fathers report paying nothing despite being obligated. When looking at the overall payment statistic, divorced mothers report receiving between two-thirds and three-quarters of what they are owed, and fathers report paying better than 90 percent of what is owed. If we were to do what the Census Bureau did and interview the non-custodial parent only, child support nonpayment is barely even a problem at all!
He states, after this, "I am certainly not arguing that interviewing only fathers is what the Census Bureau ought to have done. I don't believe that noncustodial parents' reports should be uncritically accepted as truth, either. To me, it merely points out how erroneous the present practice of accepting the mother's report as truth without qualification is. When studying something as emotionally wrenching as divorce, it's nearly impossible for people to answer without bias. Indeed, both parents' reports are likely to be biased. In the absence of trustworthy objective official data to the contrary, it seems safest to assume that noncustodial parents are probably overstating child-support payments made, and custodial parents are probably understating. Thus, the truth lies somewhere in between, and our findings can best be thought of as "bracketing" true child-support compliance. In short, we must conclude that how much child support is not being paid remains in substantial dispute, but the amount being paid by divorced fathers is almost certainly higher than most official estimates. Deadbeat divorced dads are nowhere near as numerous as the stereotype portrays".
As to the divorced dads who don't pay, Braver notes that you can’t assume that this represents wilful noncompliance - the single biggest factor relating to nonpayment is typically unemployment and when you exclude fathers who experienced a period of unemployment from consideration, the compliance rate rises dramatically.
EDIT: a small correction
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