Gender Development Index (GDI): Measuring Gender Disparity

India’s Human Development Index has been climbing steadily, moving up four ranks to 130th out of 193 countries in the latest UNDP report. That sounds like good news, and it is. But an average score for the whole population can hide a very different story for half of it. This is exactly the gap the Gender Development Index was built to expose. It takes the same building blocks as the HDI, splits them by gender, and asks a simple but uncomfortable question: are women and men actually experiencing the same level of human development, or is the national average papering over a real divide?

What is the Gender Development Index? 🔗

The Gender Development Index, or GDI, is a composite index that compares human development outcomes for women against those for men within the same country. It was introduced by the United Nations Development Programme (UNDP) in the 1995 Human Development Report, alongside the Gender Empowerment Measure, as an attempt to add a gender lens to the original Human Development Index.

Like the HDI, the GDI rests on three core dimensions of well-being:

Health: measured through life expectancy at birth, calculated separately for women and men.
Education: captured through expected years of schooling for children and mean years of schooling for adults aged 25 and above, again split by gender.
Command over economic resources: estimated through earned income, which is where the biggest disparities usually show up, since women often work in unpaid or informal roles even when they are educated.

According to the official UNDP methodology, these three dimensions are used to build two separate HDI scores, one for the female population and one for the male population, using the exact same formula for both. The GDI is simply the ratio between these two scores.

How is the GDI computed? 🔗

The computation happens in two stages. First, a full Human Development Index value is worked out for women alone and for men alone, using sex-disaggregated data on life expectancy, schooling and income. Second, the female HDI is divided by the male HDI:

GDI = Female HDI ÷ Male HDI

This ratio format is what makes the GDI easy to interpret at a glance. A value of exactly 1 would mean women and men have achieved identical levels of human development. A value below 1 signals that women are behind men on these combined measures, while a value above 1 would mean men are behind women. In practice, values above 1 are uncommon and tend to appear in a handful of countries, largely because male life expectancy tends to be lower than female life expectancy almost everywhere.

India’s GDI in numbers 🔗

On the official UNDP country data page for India, the female HDI value stands at 0.582 against a male HDI value of 0.684, which works out to a GDI of 0.852. That gap of roughly 15 percentage points is not trivial. It places India in what the UNDP calls Group 5, the category reserved for countries with the largest deviation from gender parity in HDI achievements.

The five GDI groups 🔗

Because sex-disaggregated income data is patchy in many countries, the UNDP does not rank nations by their exact GDI score. Instead, it sorts them into five groups based on how far the GDI deviates from perfect parity:

Group 1: deviation of 2.5 percent or less, high equality.
Group 2: deviation of 2.5 to 5 percent, medium-high equality.
Group 3: deviation of 5 to 7.5 percent, medium equality.
Group 4: deviation of 7.5 to 10 percent, medium-low equality.
Group 5: deviation above 10 percent, low equality.

This grouping treats a gap favouring men and a gap favouring women the same way, since both represent a departure from parity. It is a deliberate design choice meant to avoid overstating precision that the underlying data cannot really support.

Why the GDI matters 🔗

The real value of the GDI lies in what it reveals once you place it next to the plain HDI. A country’s HDI can rise year after year while its internal gender gap barely moves, and the GDI is what catches that. India’s own trajectory illustrates this well. Life expectancy, schooling and income have all improved on average, yet the space between female and male HDI values has stayed wide.

Nowhere is this clearer than in the labour market. Official data from the Periodic Labour Force Survey 2023-24 shows India’s female labour force participation rate at 41.7 percent, compared to 78.8 percent for men. That is a gap of nearly 37 percentage points in who is even counted as economically active, let alone what they earn once they are working. Since income is one of the three pillars feeding into the GDI, a gap this large drags the female HDI down relative to the male HDI, regardless of how well women are doing in health or basic education.

This is precisely the kind of disparity that a single, blended HDI number would never show. A national HDI of 0.644 tells you India is a “medium human development” country. It says nothing about whether that development is shared evenly. The GDI forces that second, harder question into the conversation, and pushes policymakers to look at gender-specific interventions rather than assuming that a rising national average benefits everyone equally.

A tool for tracking policy priorities 🔗

Government bodies have started treating this seriously as a monitoring tool. A report from the Ministry of Statistics and Programme Implementation (MoSPI) discusses how gendered human development indices can be used at the state and union territory level to identify which regions need targeted reforms in health, education or economic access. This kind of sub-national breakdown matters in a country as large and diverse as India, where a state-level GDI can look very different from the national figure.

Limitations and criticisms of the GDI 🔗

No composite index escapes scrutiny, and the GDI has faced more than most. Three criticisms come up repeatedly in the academic literature.

It cannot stand alone 🔗

The GDI is a ratio, not an absolute score. A high GDI value does not automatically mean a country is doing well for women; it might simply mean that both female and male HDI values are equally low. The number only becomes meaningful when read alongside the HDI itself, and alongside the actual female and male HDI values it was built from. Reading the GDI in isolation can be genuinely misleading.

It is too closely tied to the HDI 🔗

A recurring academic critique, discussed in a review of UNDP’s gender-related indices, is that because the GDI simply recombines the HDI’s own components by gender, the gap between the two indices tends to look smaller than the lived reality of gender inequality. This creates a risk that policymakers read a modest HDI-GDI difference as reassurance, when the underlying disparities in income, unpaid labour and decision-making power may be far starker than the index suggests.

Value judgments baked into the design 🔗

Deciding which three dimensions matter, how to weight them, and how to convert raw data like income and years of schooling into a 0-to-1 scale all involve subjective choices. Two researchers with different priorities could build two defensible but different composite indices from the same raw data. This is a criticism levelled at composite indices in general, not just the GDI, but it is worth remembering every time a single number gets treated as an objective fact rather than a constructed measure.

These limitations are part of the reason the UNDP introduced the Gender Inequality Index in 2010, built around reproductive health, empowerment and labour market participation instead of simply splitting the HDI by gender. The GDI, however, has continued to be published and taught because it remains one of the most direct, intuitive ways to compare human development outcomes across genders within a single country.

Reading the GDI in context 🔗

For a student of data analysis, the GDI is a useful case study in composite index construction generally: how do you take multiple raw indicators, standardise them onto a comparable scale, and combine them into a single number that is still meaningful? The GDI shows both the strength of this approach, a compact figure that instantly flags gender disparity, and its weakness, a number that can obscure as much as it reveals if you do not dig into what feeds into it. The same tension shows up in nearly every composite social index used in policy today, from the Human Development Index itself to state-level development rankings within India.

Used carefully, alongside its component female and male HDI values, the GDI remains a genuinely useful signal. It tells you not just how a country is developing, but who that development is actually reaching.

What do you think? If a country’s GDI is close to 1 but both its female and male HDI values are low, does that count as gender equality worth celebrating? And looking at India’s labour force participation numbers, do you think the income component or the education component is doing more to widen the gender gap in the GDI right now?

References

1. https://www.undp.org/india/publications/gendering-human-development-indices-recasting-gender-development-index-and-gender-empowerment-measure-india-0
2. https://hdr.undp.org/gender-development-index
3. https://www.undp.org/india/human-development-index-india
4. https://www.pib.gov.in/PressReleasePage.aspx?PRID=2057970&reg=48&lang=2
5. https://www.mospi.gov.in/sites/default/files/publication_reports/Report%20on%20Gendering%20Human%20Development.pdf
6. https://www.sciencedirect.com/science/article/abs/pii/S0305750X99000352