Gender Development Index (GDI): Analysing Interstate Profiles in India

We often talk about development, but what does it truly mean? For decades, we measured a country’s progress by its economic output, its GDP. But a rising tide doesn’t automatically lift all boats-and as we’ve learned, it certainly doesn’t lift them equally. What if a country is getting richer, but half of its population is being left behind? This isn’t just a hypothetical question. It’s a reality that economists and policymakers had to confront. To get a clearer picture, we needed a new tool, one that could look inside our development numbers and ask a critical question: how are women faring compared to men?

What is the gender development index (GDI)? 🔗

Enter the Gender Development Index, or GDI. You’ll often see it mentioned in reports by the United Nations Development Programme (UNDP). Think of it this way: if the Human Development Index (HDI) measures a country’s overall achievements in health, education, and standard of living, the GDI measures the *gender gap* in those same achievements. It’s essentially a ratio of the female HDI to the male HDI. A GDI of 1.000 would mean perfect gender equality in these basic dimensions. A lower score means women are at a disadvantage.

The GDI became a critical tool for what’s known as a rights-based development approach. It shifted the conversation from “are we growing?” to “is our growth fair?” The findings from the GDI were stark and universal: it revealed that no country in the world, not even the most developed ones, treats its women as well as its men. This simple, powerful metric exposed the invisible barriers and systemic disadvantages holding women back, providing the data needed to demand change.

A mirror to India’s states: GDI profiles 🔗

This new lens was particularly revolutionary for a country as vast and diverse as India. Applying the GDI framework here allowed researchers and policymakers to move beyond a single national average and start ranking individual Indian states. The results were a wake-up call. They exposed deep development inequities that were often hidden by data that was only focused on economic output.

This state-level analysis revealed that high economic growth in some states did not translate into high gender development. For instance, states that were otherwise considered prosperous, like Punjab and Haryana, showed significant gender gaps. The data highlighted troubling realities in these regions, as well as in states like Bihar and Rajasthan, where women faced compounded disadvantages in health, education, and economic command.

This kind of granular data is not just academic. It means that in a particular state, a girl might have a lower life expectancy, fewer years of schooling, and far less control over economic resources than a boy living in the same household. It gives policymakers a map showing exactly where interventions are needed most.

The services sector boom: A tide that lifts all boats? 🔗

In the last few decades, India’s economy has been famously propelled by its booming services sector-think IT, communication, finance, and tourism. This growth created millions of new jobs and a new, upwardly mobile middle class. On the surface, this looks like a huge win for everyone. But when we apply a gender lens, a more complicated story emerges. Has this services boom been a true force for gender equality? The research on trade in services and its impact on gender employment suggests we should be cautious.

Supporting subtopic: The literacy link and the stubborn wage gap 🔗

The good news is that female literacy and education have a clear, positive impact. Studies show that as more women gain an education, the wage disparity between genders tends to shrink. This is a powerful argument for investing in girls’ education. However, the story doesn’t end there. A significant wage gap remains, even among graduates.

Imagine two colleagues, Priya and Rahul, who both graduated from the same business school with the same degree. They get hired at the same multinational IT services firm. You would expect them to earn the same salary, right? Yet, studies on India’s services sector show that, on average, Priya is likely to be paid less. One analysis found that in India’s major services exporting sectors, women would earn 20% more if they were paid the same as men with identical qualifications. This gap isn’t about skill or education; it’s about a persistent bias that devalues work done by women.

Supporting subtopic: Who gets the new jobs? 🔗

Beyond pay, there’s the question of access. While the growth in services exports *does* create new employment opportunities for women, these benefits are disproportionately enjoyed by men. It’s like a new highway is built, but one group gets a multi-lane expressway while the other gets a narrow service road. Data has shown that in the boom years, only about 30-40% of the new jobs created by this growth went to women. The remaining 60-70% went to men, widening the economic participation gap even as the sector itself expanded.

Digging deeper: Where exactly are the jobs? 🔗

To understand *why* this is happening, we need to look even deeper into the economic plumbing. Economists use a tool called a Social Accounting Matrix (SAM) to do this. A SAM is like a highly detailed, 3D map of the entire economy. It doesn’t just show what a sector produces; it shows who it buys from, who it sells to, and, most importantly, who it employs-broken down by gender, skill level, and region.

Using this map, we can calculate something called an “employment multiplier.” This answers a fascinating question: “If exports in one sector (like tourism) go up by 1 crore, how many new jobs are created in the *entire* economy as a result, and who gets them?” The answers reveal the hidden wiring of gender inequality.

Supporting subtopic: Different paths for men and women 🔗

An analysis of a SAM for India (from 2003-04) provided a clear picture of this divergence. It found that the employment multiplier from a rise in services exports was highest for men in sectors like communication and tourism. These were, and still are, high-growth, high-visibility sectors.

Where was the multiplier highest for women? In a broad category called “other services.” This often includes sectors like education, health, and personal care services, which are traditionally lower-paying and less secure, often reflecting an extension of women’s perceived domestic roles into the formal economy.

Supporting subtopic: The high-tech gap and the call for action 🔗

The most pronounced gender differential was found in high-tech sectors like communication. This is where the story comes full circle. The reason for this gap, the analysis suggests, is women’s lower access to the specific education and technology required for these jobs. This isn’t just about a basic degree; it’s about access to digital literacy, advanced technical training, and the professional networks that lead to high-paying tech jobs.

This is where the barriers become painfully clear. Even when women are present in the services sector, they can be held back by a “digital divide,” a disproportionate burden of unpaid care work at home, and social norms that may discourage them from taking jobs that require late hours or travel.

This analysis is more than just data; it’s a direct call for targeted policy intervention. It shows us that simply growing the services sector is not enough. We need policies that actively dismantle these barriers. This could mean investing in STEM education and digital literacy programs specifically for girls, creating safer transport and workplace environments, and implementing policies that support childcare and fairly distribute unpaid work. The GDI and SAM analyses don’t just show us the problem; they point us directly toward the solutions.

What do you think? Given the data, what do you believe is the single biggest barrier holding women back in India’s high-tech service sectors? What kind of ‘targeted policy intervention’ do you think would be most effective in your community?

References

1. https://www.undp.org/india/human-development-index-india
2. https://www.mospi.gov.in/sites/default/files/publication_reports/Report%20on%20Gendering%20Human%20Development.pdf
3. https://www.cepweb.org/services-trade-and-the-gender-wage-gap-the-case-of-india/
4. https://blogs.worldbank.org/en/trade/toppling-barriers-indian-womens-participation-trade