Congratulations.
A huge number of people in our country have been lifted out of poverty.
And our country is greener than ever.
Cleaner than ever.
And we are richer than ever.
You turn on the news and hear that the economy is booming, yet your savings are shrinking.
You’re told poverty is disappearing, yet millions are struggling just to get by.
You’re told forests are growing, but when you look around,
Umm, where is it happening?
That’s because we are all being officially gaslit with manipulated numbers
The latest victory parade we saw was over our GDP numbers.
Look, I am not here to be a spoilsport.
I would be happy to join the celebrations, only if it were actually true.
But me lying about the data will not improve our lives.
Yet the government seems to think so, time and time again.
But this isn't just about GDP. It is about how the Modi government has played with data
In this episode, I will take you through manipulated numbers in GDP, health surveys, forest cover and more.
Let me explain.
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I thought we should talk about GDP and why the latest numbers are not being trusted by so many people. For many reasons. Then I realised this happens so routinely. Right?
The government puts out numbers, claims a major victory. One section is celebrating without questioning.
And there is another section, sceptical.
Now the easiest thing to do is to call that section anti-national, say you don’t want to see the country progress, etc etc. You know the drill.
But the real problem is this. Over the years, and particularly under the Modi government, there have been so many questions about how economic data is collected, revised and presented that the credibility of the numbers themselves has taken a hit.
Despite what this anchor will have you believe…
The problem is not that governments revise data. That’s normal.
The problem is what happens when the methodology changes, the underlying data is weak, or the numbers don’t match what we’re seeing elsewhere in the economy.
And that’s what we’re going to look at today.
The GDP credibility crisis
Let's start with the government’s favourite headline: our record-breaking GDP growth rate.
The last few days, the debates have all been around whether we’re growing at 6% or 7%. Or if the math itself is a complete work of fiction.
Economist Prof. Arun Kumar thinks there’s a huge problem with the way we calculate GDP. In fact, he says we could be overestimating the size of our economy by almost 50%.
How do you overstate a country’s national income by 50%?
After watching and reading what the critics have alleged and what the supporters of the GDP say, I have arrived at four specific statistical tricks: let's say, problem areas.
The Moving Baseline Trick
Former Finance Secretary Subhash Chandra Garg dug into the government’s own spreadsheets and found something rather clever — move the baseline, and the numbers suddenly look a whole lot better.
Think of it like trying to show your parents a huge improvement in school:
Last year, you told your parents you scored 80 marks. This year, you get 83 marks. That’s a modest 3-mark improvement, about a 3.7% bump.
But then you brag to them that your score actually jumped by over 10%!
How?
Because behind the scenes, your teacher had revised last year’s score down to 75. It was some calculation error that got you 80 marks to begin with.
You’re calculating your growth off the hidden 75, but your parents are still comparing your new score to the 80 you originally promised them.
Subhash Garg says that is exactly what happened with our GDP data.
A year earlier, the government officially announced that quarterly GDP was ₹86 lakh crore. But when the new report came out a year later, the previous benchmark was revised down to ₹80 lakh crore.
By lowering last year's starting line behind the scenes, this year’s economy suddenly looked like a massive growth spurt on paper. Garg laid out the math plainly: if you measure today's economy against the original ₹86 lakh crore benchmark the public was actually told, real growth wasn't 7.8%.
There are many experts who have refuted Garg’s logic. Former Chief Statistician Dr. Pronab Sen defended the methodology, saying that tweaking old baselines is standard procedure.
But even he pointed to something alarming: the government’s data itself is dubious and holds low credibility.
Let’s start with the numbers that actually go into calculating GDP.
The Informal Sector Shortcut
When GDP is calculated, they don't have time to go out and check on the informal sector- that is, the street vendors, neighbourhood stores, or small textile workshops for how they are doing.
So, they take the profit reports of giant, stock-market-listed corporations and simply assume the informal sector is growing at the exact same speed. But that’s like assuming the local vegetable vendor is thriving just because Cognizant or Amazon had a record quarter. You see the flaw there.
Then there is the Double Deflation Problem:
Now, here’s where things get a little technical — but it matters.
When we calculate real GDP, we’re basically trying to answer a simple question: How much more stuff did the economy actually produce, after taking price changes out of the picture?
And this is where India does things differently from many major economies.
We don’t use what economists call “double deflation.”
Why does that matter?
Say a factory spends ₹100 on raw materials to make a product worth ₹150. Now imagine the price of that raw material shoots up to ₹130, while the final product price also rises.
If you only adjust the final selling price for inflation, but don’t separately adjust the cost of the inputs, the factory can appear to have made a much bigger “real” profit than it actually did.
And when you add up those inflated numbers across thousands of companies, GDP can end up looking stronger on paper than what’s actually happening on the factory floor.
Now, private household spending accounts for more than 60% of India’s GDP.
So you’d expect it to be growing strongly if the economy really is booming.
But it isn’t.
Writing in Frontline, Princeton economist Ashoka Mody pointed out that household consumption is growing at just around 3%.
So if 60% of your economy is barely growing, how is the whole economy suddenly growing at nearly 8%?
And this isn’t just me saying the numbers look suspicious.
Even the IMF has raised concerns about the quality of India’s national accounts data, giving it a “C” rating — the second-lowest grade.
Why should you care about some IMF grading system?
You are told they are all anti-India, right?
Because numbers only have value if people who matter trust them.
And increasingly, India’s headline GDP numbers don’t seem to match what we see elsewhere in the economy.
Look at diesel consumption. Tractor sales. Corporate revenues. Wages. Rural spending.
If GDP is growing at nearly 8%, you’d expect these indicators to be moving along with it.
But often, they aren’t.
That’s the disconnect.
I will give you a few more examples of data credibility from over the years and you make up your own mind after that.
Redefining Health Data
If a test gives you bad results, you can either fix the problem or change how the test works.
That is exactly what happened to India’s national health statistics.
When the National Family Health Survey (NFHS-5) released its findings in phases, between 2020 and 2022, it exposed an uncomfortable reality: 67% of young children and 57% of women in India were suffering from anaemia,
This was a sharp rise from previous years that made international headlines and severely embarrassed the administration.
So, what happened when the next survey (NFHS-6) rolled out in 2026? The problematic markers simply disappeared from the initial fact sheets.
In fact, TNM broke the story that 40 sensitive indicators were systematically dropped or sidelined.
All seven key anaemia breakdowns, official parameters tracking child mortality rates, sex ratio at birth, household sanitation access, and clean cooking fuel use were similarly removed.
When questions were raised over why these metrics were vanishing, the ministry cited "methodology tweaks"
It also claimed that some of these indicators were now in other reports.
But the point about having it all in one survey was so it would help India plan its future policies .
Redefining Standards: Magic Tricks in Poverty, Sanitation, and Forests
If you can't alter the math and you can't hide the survey, there's a third move: change what the words mean.
Poverty Escapes on Paper
Look at the headlines from feb 2025 declaring that India has drastically cut "multidimensional poverty." How did we achieve that? Simple. By just changing the yardstick.
Instead of looking at how much cash a family actually earns or spends on food, the government switched to something called "index metrics." In simple terms: instead of checking if you have money in your pocket, the system just checks off a list of hardware assigned to your name, like a bank account, a toilet, or a gas connection.
So, having a bank account or a government scheme card automatically gets logged as escaping poverty. Never mind if that bank account has a zero balance, the newly built toilet has no running water, and the LPG cylinder is just gathering dust because you can't afford the refill.
Who needs three meals when you have a government spreadsheet declaring you as not poor?
Swachh Bharat and Sanitation
Take the victory laps over state after state 100% "Open Defecation Free" (ODF). How did we wipe out open defecation so fast?
I wish the answer was that the govt worked overtime to change things on the ground.
But what they did was count concrete boxes on a dashboard instead of actual usage of toilets.
Let me explain what I mean.
I am not saying no work was done under the scheme. There was. But here’s the problem.
The government's own National Family Health Survey (NFHS-5) exposed the lie: in states certified as "100% ODF" like Bihar and Rajasthan, 15% to 25% of rural households still had no toilet access at all.
CAG audits found millions of toilets built without running water, forcing families to fetch water manually just to flush. Within months, these dry, drainless stalls became storage sheds for firewood, tools and dry cow dung.
That’s not all; the governments will have you believe that our forest cover has been increasing by a lot.
The Forest Cover Expansion
The official reports claiming India’s green cover is steadily expanding.
Sounds great, right? Except - the State of Forest Report pulled off this magic trick by drastically rewriting what a "forest" actually means.
Originally, official metrics tracked legally recorded government forest land or natural ecosystems. But starting in 2001, the Forest Survey shifted to a purely visual rule: any patch of land over one hectare with a canopy density above 10% was suddenly logged as a "forest," regardless of who owned it or what grew on it. Then came two massive administrative moves:
First, a 2017 amendment to the Indian Forest Act declassified bamboo on non-forest land as a "tree."
The result?
Commercial bamboo farms were logged as green cover. Then, in the 2019 State of Forest Report, the government formally integrated "Trees Outside Forests" (TOF) straight into headline growth numbers.
That meant commercial eucalyptus plantations in Andhra Pradesh, tea gardens in Wayanad, private coconut groves in Kerala, and roadside palm trees were suddenly rolled into national "forest" totals. As satellite camera resolutions upgraded, every green patch in a suburban housing society was detected and claimed as "new forest growth."
So, we clear-cut centuries-old, biodiverse natural jungles for infrastructure, replace them with monoculture timber farms, and watch the green line shoot up on a spreadsheet.
Scrubbing Mortality and Pollution Data
The urge to sanitise numbers reaches its most dangerous point when it touches human life, social cohesion, and public safety.
COVID-19 Death Tolls
During the second wave, millions of us watched crematoriums run around the clock and saw bodies floating down the Ganga. Yet official state registers reported a tiny fraction of those deaths. When the World Health Organisation (WHO) estimated India’s actual COVID death toll at nearly 4.7 million, almost ten times the official state tally, the government simply rejected their methodology and insisted its own low figures were absolute truth.
The Real-World Impact
Why should you care? Because you can’t cure a disease if you falsify the blood test.
When you manipulate baselines, reclassify tree farms as virgin jungles, and erase poverty on paper, you justify cutting the very welfare programs keeping families alive. Claim the economy is roaring at 8%, and interest rates stay high, keeping your home loan EMI painfully expensive. Cook the numbers, and serious investors walk away, killing real job growth.
Demanding honest data isn't political; it's survival. You can't pay rent, buy groceries, or feed a family with a headline percentage point.
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Produced by Akshay Lal, Script by Pooja Prasanna, Camera by Ajay R, Edit by Nikhil Sekhar ET