#
Did you know that Parsi's in Mumbai, instead of being left at the Tower of Silence after
#
they die, are now cremated?
#
Because a cow fell sick in the early 1990s.
#
Did you know that the smog in Delhi is caused by something that farmers in Punjab do and
#
that there's no way to stop them?
#
Did you know that there wasn't one gas tragedy in Ghopal, but three?
#
One of them was seen, but two were unseen.
#
Did you know that many well-intentioned government policies hurt the people they're supposed
#
Why was demonetization a bad idea?
#
How should GST have been implemented?
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Why are all our politicians so corrupt when not all of them are bad people?
#
I'm Amit Verma and in my weekly podcast, The Seen and the Unseen, I take a shot at
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answering all these questions and many more.
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I aim to go beyond the seen and show you the unseen effects of public policy and private
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I speak to experts on economics, political philosophy, cognitive neuroscience and constitutional
#
law so that the insights can blow not only my mind, but also yours.
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The Seen and the Unseen releases every Monday.
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So do check out the archives and follow the show at seenunseen.in.
#
You can also subscribe to The Seen and the Unseen on whatever podcast app you happen
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Most of us are very impressed by numbers.
#
Show me a chart and I'll think, hey, that looks authoritative.
#
This person knows what she is talking about.
#
In most cases, you can say any nonsense you want and put some numbers besides it and boom,
#
the common person, someone like me who doesn't have a degree in statistics all the time to
#
do his own research, will swallow whatever you're saying.
#
And sometimes it seems that you can actually prove anything with numbers.
#
That's where the old saying comes from.
#
If you torture the data hard enough, it will confess to anything.
#
It is true that lies can be cloaked in fancy figures, but they can also be unmasked using
#
And in a democracy, it's a vital task of the citizen to question all the data that a government
#
Welcome to The Seen and the Unseen, our weekly podcast on economics, politics and behavioral
#
Please welcome your host, Amit Barma.
#
Welcome to The Seen and the Unseen.
#
Today's episode deals with how the government uses and misuses data to do what my good friend
#
Vivek Khol calls optics management.
#
Vivek is my guest on the show today.
#
But before I ask him to elaborate on this, a quick commercial break.
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If this happens to be the only podcast you listen to, well, you need to listen to some
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Check out the ones from IVM Podcasts who co-produced the show with me.
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Go to ivmpodcasts.com or download the IVM app and you'll find a host of great Indian
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podcasts that cover every subject you could think of.
#
From the magazine I edit, Pragati, I think, pragati.com, there is the Pragati podcast
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hosted by Hamsini Hariharan and Pawan Srinath.
#
There is a brilliant Hindi podcast, Puliya Baazi, hosted by Pranay Kutaswamy and Saurabh
#
And apart from these policy podcasts, IVM has shows that cover music, films, finance,
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sports, sci-fi, tech and the LGBT community all under one roof or rather all in one app.
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So download the IVM Podcasts app today.
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Vivek Khol, welcome to the Scene in the Unseen.
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Thanks Samit for having me over.
#
Vivek, you said you wanted to start by reading out a quote and you wanted me to guess who
#
So this is basically, you know, Greek philosopher called Plato from his book called The Republic
#
in which he says, our first business is to supervise the production of stories and choose
#
only those we think suitable and reject the rest.
#
We shall persuade mothers and nurses to tell our chosen stories to their children and by
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means of them to mold their minds and characters rather than their bodies.
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The greater part of the stories current today, we shall have to reject.
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Are you sure this is Plato and not someone in India today?
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So basically, you know, all the good things have already been written.
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I mean, it's just that we tend to realize them over and over again.
#
And this is exactly how, you know, governments tend to cherry pick data in order to project
#
a story that they want to project, which you know, the short phrase for it is optics management.
#
And you know, there's a lot happening in the country and if the government, for example,
#
Prime Minister Modi came to power in 2014 with a lot of promises, we'll do this, we'll
#
But ultimately, the story of what's happening with the economy is a very complex one.
#
There are many parts to the economy.
#
There are many kinds of numbers and a lot of it does come down to presentation.
#
But where is the truth?
#
And what can we learn from the sort of data that the government presents?
#
So, I mean, this question deserves a book.
#
But are you writing a book on this?
#
But, you know, the short answer is to sort of look for as much data as possible and then
#
try forming an opinion and by data, I mean, not just government data, but there is a lot
#
of other real time economic indicators which sort of come out right from two wheeler sales
#
to cement sales and so on and so forth, which tell you, which give you a broad direction
#
of which rather a broad idea of which direction the economy is headed in.
#
Also, I don't think it's fair to sort of analyze the economy on one parameter.
#
I mean, you obviously have to look at different things and how the economy is doing on those
#
But as you rightly said, it's like, you know, one of my editors used to say, you think of
#
So before you sort of write a piece in journalism, this is a standard operating procedure because,
#
you know, you have 600, 700 words to express yourself.
#
So before you write, you have to think of the headline first.
#
So when you're thinking of the headline first, you're already deciding on the slant that
#
And when you've already decided on the slant that you want to take, you go looking for
#
data that justifies that slant.
#
That's very insightful because what it sort of indicates is that then your journalism
#
So if you think of the headline first, you're thinking of the market first instead of.
#
So you're not really chasing the truth per se.
#
You're chasing the story that you think will get traction from the audience.
#
No, that would be like, I mean, that is also true.
#
So what I'm basically trying to say is that, you know, everything cannot be expressed in
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400, 500, 600 words and not by everyone.
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I mean, there are people who can do that, but everybody can't.
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The second thing, the problem is that, you know, every piece that is published and irrespective
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of whether it's published in a magazine or on a digital media or in a newspaper needs
#
Now, the moment you need a headline, you have to take a slant.
#
You cannot be like the economy is doing well, but it is also not doing well.
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That is not a, that doesn't work.
#
So there's a lot of a problem with the way the media is structured.
#
That reminds me of what Harry Truman once said, that show me, give me a one-handed economist
#
because all his economists would say on the one hand, this on the other hand.
#
I mean, that is also true, but that's more at a macro level.
#
I'm talking about a very, you know, I mean, I'm talking about at a micro level as to what
#
Because these days, you know, whenever I try to be objective, what happens is, you know,
#
the length of the piece goes from 600 to 1200 words and it is very difficult to give a headline
#
and when you can't give a headline, I mean, when you give a sort of a, you know, nondescript
#
balanced sort of headline in the, you know, day and age of clickbait journalism, it just
#
doesn't work because people want simple stories.
#
They don't want stories.
#
Nobody likes the idea of, but you know, as you said, on the other hand, yeah, yeah, exactly.
#
So, so there is a, I mean, it's, it's, I mean, there is a truth out there, but it is a lot
#
more nuanced than, you know, you, most people think it is so.
#
And nobody really wants to read a headline which says something like, um, Modi's time
#
as prime minister has been both positive and negative, which is actually where it is in
#
the sense that, uh, I mean, like, I mean, I was writing a piece yesterday on, I mean,
#
just on the economic side of his performance and I mean, given the fact that I criticize
#
him a lot, but on the whole, he, you know, his performance on the economic front has
#
been a little, you know, as a little better than average.
#
But then if you look at how governments in the past have done, that is typically how
#
most Indian governments are because most Indian governments are not really bothered about
#
the economy in the way that they should be.
#
I'd say that it's, uh, his performance has been pretty much par for the course and what
#
you would expect from any government of any party, except for the two big bang disasters
#
of demonetization and the GST implementation, which is very useful, which is what, you know,
#
I also mean most of, you know, what I wrote was what you say now.
#
So, uh, but then, I mean, if you say that it doesn't work, I mean, in order to make
#
it work, you would have to say Modi has failed or you'll have to say something like, oh,
#
he's been, you know, God's gift to mankind because what has also happened is, you know,
#
because of the social media and the way it is, the thinking now has become very binary.
#
I mean, this is something, I guess, you know, people keep discussing on your show.
#
So you are either with us or you're against us.
#
So it's, it's very difficult to.
#
No, in fact, whenever I'm discussing politics with someone, one question I ask, like if
#
he's against Modi, one question I'll ask is, can you name a few good things he's done
#
or something good about him?
#
And equally, if they are for say Kejriwal, I'll ask him that, can you name a few bad
#
things that he's done or that you're against?
#
And typically you find that no, it's all black and it's all white and it's tribal.
#
You know, what happens is, and I mean, I briefly went through that phase it's one is it's easy
#
to sort of write, talk about stuff after you've already, you know, thought of the headline
#
first night and over a period of time, you just get caught on to it in such a way that
#
it becomes difficult to get out of it.
#
I mean, it's, it's like, I mean, you start believing in the whole thing.
#
So we're not really discussing journalism in this episode, but what you said is fairly
#
interesting and we're both journalists.
#
So I'll explore this a bit further till we get back to the subject of the episode.
#
When you write a story, typically when you pick up a story, do you already have in your
#
mind broadly what the thrust or the headline is?
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Not always, not always.
#
In fact, what I do these days is I have a working headline, which is very like I was
#
to give you a very simple example.
#
Today I wrote something on basically what has happened is that the cabinet has passed
#
an ordinance, which essentially will categorize home buyers as financial creditors in case
#
of, you know, real estate companies who have defaulted on their loans.
#
So basically long story short, I just had a working headline.
#
And then as I wrote, you know, a headline evolved and, and then I gave that headline,
#
but that always, I mean, it doesn't always happen like that.
#
I mean, sometimes you are already sure as to what you want, like, I mean, I was writing
#
a piece on Punjab national bank yesterday, or rather day before yesterday, and I was
#
already sure that, you know, this is a bank which really should not be in the business
#
Because you've written about it enough and you know, all of that.
#
Anyway, I should tell listeners that we are recording this on the 24th of May, so it's
#
going to be released a little bit later, but just to give you a context.
#
So don't get surprised as to why are we talking about archaic stuff, you know.
#
Well, I mean, it'll be 10 days old by the time it's...
#
No, 10 days is a long time these days on its own.
#
And I guess it's okay for an opinion writer who's writing an opinion piece to already
#
have a headline in his head because he knows the slant, but if you're a reporter or if
#
you're writing features, then perhaps it's not always such a good thing.
#
So as you know, one of my ex bosses used to say is, if you're writing a feature story,
#
two is a trend and then you get two people to say what you want them to say.
#
And then, you know, just to sort of balance it out, you get a third guy to say something
#
which the first two guys haven't said.
#
So I mean, so it's like having said that and then sort of, yeah, it's like, it's, it's
#
the structure, I mean, I guess, and you know, the good part is that as journalism moves
#
from paper to the digital media, people who want to sort of get rid of these structural
#
inefficiencies, they can do that.
#
It's just that the audience also needs to evolve and the audience will evolve if enough
#
people sort of are doing that.
#
I mean, they're not thinking of the headline first.
#
So head on over to prakati at thinkprakati.com and that advertisement out of the way.
#
Let's sort of move back to the subject for today.
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When it comes to economic journalism, you've been writing the most insightful pieces that
#
I've read in the last few years.
#
And a lot of your recent ones have examined the government's claims where the government
#
has claimed XYZ using a certain amount of data and you've shown why that is cherry picking
#
of data or in some cases is the wrong data entirely.
#
And you sort of deconstructed that.
#
Let's start by talking about what both of us did an episode on and we agree is the most
#
burning issue of our times, which is the jobs crisis.
#
The government has recently on multiple occasions, in fact, recently come out and said that, hey,
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People say that there are, you know, India's producing 12 million jobs a year and where
#
are the new jobs being, like 12 million people are coming into the workforce every year,
#
where are the new jobs and blah, blah, blah.
#
And the government has handled that by on the one hand, Arvind Panagariya, ex head of
#
NITI Aayog saying that that number is false is seven and a half million.
#
And on the other hand, Rajiv Kumar saying that who's in our current head of the NITI
#
Aayog saying that, hey, we are producing all these jobs and you've done two separate stories
#
rebutting these two gentlemen.
#
So give us some details.
#
So basically, you know, let's start with the Arvind Panagariya thing because that's a little
#
So Mr. Panagariya, as you said, was the vice chairman of the NITI Aayog till he sort of
#
decided to cut his losses and go back to Columbia.
#
And by the way, he's blocked me on Twitter.
#
He's blocked me on Twitter as well.
#
It's just a badge of honor we should wear with pride.
#
Actually, you know, you have all these people saying, saying on Twitter, followed by the
#
We are blocked by, we should say blocked by Arvind Panagariya.
#
So anyway, so he had this piece in the Times of India on the edit page of Times of India
#
where he challenged this data point of one million Indians entering the workforce every
#
Now, first, it is important every month, okay, not every year.
#
So which means 12 million a year.
#
So first, it is important to understand where this data has come from.
#
So this data is largely, you know, it was there in the 12th five year plan for one.
#
There are other researchers who have come up with similar data.
#
It was also a part of this document called some inputs into the draft educational policy
#
or something like that.
#
So there are multiple occasions on which various government documents at various points of
#
time, you know, have said that around a million Indians are entering the workforce every year,
#
So Mr. Panagariya essentially challenged it by using projections from a report published
#
by the National Population Commission.
#
Now, as per this report, in 2016, the number of Indians over the age of 15 or more was
#
essentially equal to 929 million, okay.
#
In 2021, the estimate suggests the number of Indians of 15 years or more would be 1003
#
So which essentially means that between the period 2026 and 2021, around 74 million people
#
have crossed the age of 15.
#
So the moment you cross the age of 15, you become a part of, you can become a part of
#
So if five or a period of five years, 74 million people have been added, one year average would
#
Now not all of these 15 million are looking for a job because some of them sort of continue
#
to study in case of women, many of them are married off and, you know, are not allowed
#
So if you adjust for that, I mean, you adjust for that using something known as the labor
#
force participation rate.
#
And there are two methods to calculate that.
#
And so the labor force participation rate is around, you know, is this as per one method
#
is 50% as per another method is 52.4%.
#
So if you use these two data points, you essentially come to the conclusion that around anywhere
#
between 7.5 to 7.8 million Indians enter the workforce every year.
#
And this is much lower than the 12 million number, which has been bandied around for
#
Now the problem was, I mean, it sounds very logical.
#
The problem was that Mr. Panagariya was using a projection, which was made in 2006.
#
So in 2018, now that would have been okay if between 2006 and 2018, no other projections
#
But I sort of, you know, got curious because and it's a funny thing that I was in Noida
#
that day and it was late in the night and I got very curious as to, you know, why would
#
anyone in 2018 choose a data point from 2006.
#
So I went looking and I found a more recent projection in a report called Youth in India,
#
which was published in 2017 by the Central Statistics Office, okay, which is as kosher
#
as very solid it can get, right.
#
And so they had basically as per their projections and I'm just reading that out.
#
So in 2011, the number of Indians who were 15 years or more was 838 million and by 2021,
#
this was expected to go up to 1031 million.
#
So the difference is 193 million.
#
So over a period of 10 years, 193 million Indians will enter the workforce.
#
So which if you sort of, now, as I said, not all of them, I mean, look forward because
#
some of them continue to study, some are married off, but you use the same formula for labor
#
I use this exactly, you know, the numbers that Mr. Panagari had used 50% and 52.4% because
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these rates are from a report which was published in 2016.
#
So it's like not something which was, you know, 15 years old and it's fair enough to
#
use the same methodology, but better data to show that the man is wrong.
#
So if you sort of do the math, so 193 million over a period of 10 years works out to 19.3
#
million a year and at 50%, it works out around 9.7 million at 52.4%.
#
It works out around 10.11 million.
#
So roughly around 10 million.
#
So 10 million, obviously it's closer to 12 than to 7.5, but it's, it's, it's almost
#
33% more than 7 and a half million.
#
So the question again, you know, comes back to the fact that, you know, why would someone
#
like Arvind Panagari, who was the former head of NITI IO use 2006 data and not 2017 data?
#
I mean, when you make such an obvious schoolboy error, you know, it's either incompetence
#
or dishonesty and one doesn't know, we shouldn't speculate, but there's no third explanation.
#
And the other thing is, you know, I mean, I would have been fine if he would have used
#
both the, that would also, because see, these are not, you know, nobody's like sitting there
#
counting, you know, this year, so many Indians entered the workforce.
#
I mean, it is an estimate at the end of the day and estimates will vary.
#
So he could have easily sort of use that data and then use this data also to say that, however,
#
you know, more recent, you know, projection seems to suggest this, but the problem there
#
would have been, he wouldn't have had a headline as we sort of talked about.
#
So he was not chasing the truth.
#
He was chasing a narrative and whatever data he could get in service of the narrative.
#
Think of the headline first.
#
But you know, I want to keep you on that piece that you wrote in Panagari because another
#
very insightful point to me that you mentioned is that of course it's a great tragedy that
#
so few of our women come into the workforce, but that changes.
#
Tell us about the conditions under which that changes and whether it applies to India.
#
Basically, so if you, if you look at the labor force participation rate of women, as I said,
#
So as per one method, it's 23.7 as per another method is 27.4, which basically means one
#
in four women, you know, are a part of India's labor force.
#
And this number is higher in rural India than in our own India, which is something that
#
people really don't know.
#
I mean, I find it very, I mean, I, I mean, I don't think there's a greater need for
#
the women to work in rural India.
#
No, obviously in rural India, you know, women are a very important part of farming.
#
So, but in our own India, I think, you know, the possible explanation for this is the moment,
#
you know, the man in the family sort of makes a little more money.
#
He doesn't want, you know, the woman to work.
#
And all the data, as cliched as it may sound, and all the data from this, I assume would
#
relate to the formal sector, which is, no, I mean, this is as how it is, or I mean, it
#
It includes everything.
#
So, and the funny thing is the labor force participation rate for women has been falling
#
since Nariga was launched.
#
And I mean, economists really, you know, have not been able to come up with an explanation
#
I mean, whether it's a data error or…
#
Having said that, if you look at the experience in, you know, countries like China and South
#
Korea, which were very close to, you know, where India was in the 60s and the 70s and
#
I mean, China and India were more or less at a similar position.
#
And so, as more and more women got educated, the labor force participation rate for women
#
really, you know, went up and it was, you know…
#
And you pointed out that it's inversely correlation to the fertility rate.
#
As the fertility rate comes down, the labor force participation of women goes up.
#
So, fertility rate comes down when the mortality rate comes down, when, you know, the number
#
of children dying before the age of one comes down.
#
And that comes down when women get educated because they know how to read.
#
And when you know how to read, you're in a better position to take care of your child.
#
And more prosperity and so on because poorer people tend to have more kids.
#
I mean, that's just a fact everywhere.
#
So basically, the experience from other countries seems to suggest that as women earn more,
#
they enter the workforce and the participation rate for women can be in the high 60 percent.
#
I mean, so even if India reaches, let's say, you know, we are at 25 percent now, I mean,
#
even if we sort of go to 35-40 percent, you will have more women…
#
And that will make a massive difference if you have that many…
#
I mean, the thing is, obviously, if all of them can find jobs, it will make a massive
#
difference to the economy, to the general well-being of the economy.
#
So, that means the labor force participation numbers you mentioned earlier, which Mr. Panagari
#
had assumed and you took them 50 point something percent and 52 point something percent, they
#
should go up over time as a fertility rate comes down.
#
I mean, there is no reason because, I mean, that is the global experience.
#
But in the last few years, after Nariga was launched, the rate seems to have come down.
#
I mean, I really don't have an explanation for it.
#
But if you look at the global trend, there is no real reason as to why these numbers
#
And these numbers growing up, of course, isn't… going up is, of course, an awesome sign.
#
Let's move on to the other side of the jobs crisis.
#
Here we had Panagari saying that, no, no, there isn't actually that much demand for
#
jobs and that's been overstated and we just discussed how we cherry pick data to make
#
The other side of it is Rajiv Kumar, who was his replacement at Nityayog, making a claim
#
that actually we are producing a hell of a lot of jobs.
#
Tell me a bit about that.
#
So, one of the good things that has happened is that the Employees Provident Fund Organization
#
is now going to regularly publish the addition to the number of EPF subscribers.
#
And the first, you know, I mean, the data point was recently released.
#
And as per that, between September 2017 and February 2018, a period of six months, 31.1
#
lakh subscribers were added to the Employees Provident Fund.
#
Now, this data point was immediately used by Rajiv Kumar, who is the current vice chairman
#
of the Nityayog and he claimed on Twitter that on a pro-rata basis, this implies the
#
creation of 62.2 lakh jobs in 2017-18, Cassandra should please give up.
#
So he basically, you know, we had data for a period of six months, September to February,
#
he doubled it and, you know, he came up with, you know, double the number.
#
Now there are, there's a basic problem with this, you know, with this argument.
#
And the basic problem is that, you know, organizations are supposed to sort of become a part of the
#
EPF when the number of employees reaches 20 or more.
#
So the moment, you know, an organization joins sort of, you know, becomes a part of the Employees
#
Provident Fund, it is probably, it has had 19 employees till then, and then one more
#
So you have 20 employees and you become a part of the EPF.
#
Now that does not mean that 20 jobs are being created.
#
The data will reflect 20 new jobs.
#
Which is, so there is no, I mean, this data does not adjust for this anomaly.
#
And the funny thing is that Mr. Kumar said the same thing, you know, to the Financial
#
Express having tweeted what he had.
#
So I'll just read out what he had told the Financial Express.
#
One has to be careful in estimating addition to jobs.
#
What happens is that companies start to contribute to the EPFO when their headcount increases
#
So all 20 workers come into the EPF picture in one go, while it is not that all 20 were
#
not there with jobs earlier.
#
So the point is, you know, Mr. Kumar is contradicting himself.
#
Obviously, you know, he said one thing on Twitter and he said entirely another thing
#
on the Financial Express.
#
And my suspicion would be, correct me if I'm wrong, and maybe we don't know, but my
#
suspicion would be that the entirely sensible thing that he said to the Financial Express
#
would be said long before.
#
And now that he's part of the government, in a sense, he is mocking the Cassandra.
#
So let me just, I have it open here.
#
Oh, so he actually, okay.
#
So, I mean, so obviously the only explanation for this is that, you know, he probably, I
#
mean, nobody reads the Financial Express.
#
So he said the thing that, you know, his bosses wanted to hear on Twitter.
#
And then he said the right thing to the Financial Express.
#
You said the truth by mistake.
#
So yeah, so that's the thing.
#
The second interesting point here is, and this is again, you know, if you look at all
#
the estimates of how big the formal sector in India is vis-a-vis the informal sector.
#
So there are multiple estimates.
#
Some estimates say that the informal sector is 90% of the economy.
#
Some others say that the informal sector is two thirds of the economy and there are other
#
So if the formal sector is creating 62.2 lakh jobs in a year, it means the informal sector
#
is creating close to six crore jobs in a year.
#
I mean, if the informal sector is creating six crore jobs in a year, then India does
#
not have a jobs crisis.
#
And then it should, again, if so many jobs are being created, it should be visible in
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The economy should be booming.
#
So if you look at the rate of economic growth, it's been the slowest in four years, 17, 18.
#
In 2017, 18, the private consumption growth has been slowest in five years in 2017, 18.
#
If you look at the investment data, the total value of projects scrapped or dropped in 2017
#
reached an all time high level.
#
The drop between 16, 17 and 17, 18 was 60%.
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This is as per center for monitoring Indian economy.
#
They offer another data point where they say as far as projects completed are concerned,
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they dropped 34% in value terms.
#
So where are these jobs being created?
#
I mean, ultimately, I mean, we all know.
#
In the geo-wise publicity department, we go back to the argument that, you know, everyone's
#
selling pakoras basically.
#
So I mean, that is the only possible explanation.
#
You had another in your article, you'd mentioned another, I was just coming to that.
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This is a slightly complicated point.
#
So I mean, I'll take it gradually.
#
Now, as I said, you know, between September, 2017 and February, 2018, 31.1 lakh subscribers
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were added to the Employees Proud and Fund.
#
Now, if you look at slightly more long-term data between March, 2017 and April, 2018,
#
you realize that only 12 lakh subscribers were added to the EPFO, right?
#
So you have, so, you know, between September and February, 31.1 lakh were added.
#
But between March, 2017 and April, 2018, only 12 lakh were added.
#
So I guess one explanation for this is that people probably lost jobs.
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They stopped paying, you know, their monthly subscriptions to the EPFO.
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I mean, this is something only the government should be able to explain.
#
But there is a clear anomaly here.
#
So obviously, you know, this data has been published for the first time.
#
And I would say that instead of just giving the additions, it is also important to give
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the total number of subscribers at that point of time.
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And this total number of subscribers should essentially be people who have paid the last
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You know, whatever, I mean, the last 12 installments or whatever you might call it, investments.
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Actually, who have essentially contributed to the EPF for the last 12 months.
#
That would give us, you know, a lot better picture than just giving us, you know, one
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addition number and then everyone playing around with it.
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And another event that kind of complicates this, which you mentioned in your article
#
was a government offering amnesty to firms that hadn't had EPFO.
#
So that also sort of pushed up the number.
#
I mean, there are people, there are firms who should have been on EPFO and they were
#
But that's a good thing.
#
There's a breakdown and, but then again, that doesn't add to jobs.
#
I mean, the argument isn't whether it's a good or a bad thing, but it's something that
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would have made the numbers go up artificially and it wouldn't have been new jobs, merely
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new people coming into the EPF fold.
#
So basically, you know, more people coming into the formal economy.
#
Yeah, which is overall a good thing.
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But as far as the data is concerned, it's artificially inflated.
#
Yeah, really different.
#
So I want to move on from jobs now on to various other areas of the economy where the government
#
recently has been slightly economical with the truth, but before that, let's take a quick
#
It's been another great week on IVM Podcasts, and if you're not following us on social media,
#
We're at IVM Podcasts on Twitter, Facebook, Instagram, et cetera, et cetera.
#
On our latest episodes of The Scene and the Unseen, Amit Verma is joined by author and
#
columnist Vivek Paul to decode how the government uses and misuses data for optics management.
#
On Puliyabazi, Pranay and Saurav talked to authors Nikda Poonam about her new book, Dreamers.
#
On Football Total, we have Azeem Banatwala as a guest with Saru, Bharu and Kumar discussing
#
the end of the UEFA Champions League.
#
And on Who's Your Mommy, Veda talks about mothers and how they cope with their constant sleep
#
As I said, it's been a great week, and please try and listen to as many of these shows as
#
And now on to your show.
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Welcome back to The Scene and the Unseen, I'm Amit Verma, and I'm talking with my good
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friend Vivek Kaul, the data detective, as we discuss the various shenanigans that the
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government of India has got up to with data, which is not a trivial subject because to
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live in a healthy democracy, it's essential that citizens always question what the government
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And it's hard to do so because most of us are data illiterate and the government throws
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so much data at us, but worry not, India is fortunate we have Vivek Kaul with us.
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Vivek, before the break in the first half of the show, we spoke about the jobs crisis
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and you demystified a lot of the data thrown at us by Mr. Panagariya and Mr. Kumar.
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What's the next subject you want to tackle?
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So there's this whole hangama happening around how the government is collecting more taxes
#
And it's a very funny thing because obviously as the economy grows, any government would
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not collect more taxes.
#
So what you need to look at are not direct taxes collected in the absolute sense of the
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term, but direct taxes collected as a proportion of the size of the economy.
#
So the proportion, the size of the economy is essentially the gross domestic product
#
So in 2017-18, the government of India, the direct tax collection was 5.94% of the GDP.
#
Now this was more than the taxes collected in 2016-17, which were at 5.6%.
#
Now before the Modi government came to power in 2013-14, the direct taxes to GDP ratio
#
was 5.62% and the collection over the next three years was lower than this number.
#
In 2017-18, it improved to 5.94% of the GDP, which was a jump of around 34 basis points.
#
So the moment you deflate the direct taxes number with the GDP number, you suddenly realize
#
that the jump has not been as huge as claimed.
#
I mean, if you look at in absolute terms, direct taxes have gone up by around 17-18%.
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There has also been increase in what the government calls the tax base.
#
So this is essentially people who are filing returns.
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But then as we've discussed in the past, filing returns and paying taxes are two very different
#
So when you file returns and don't pay taxes, the government does not benefit your chartered
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So even though the tax base is going up, it has not led to a proportionate increase in
#
So the argument offered here again is that, okay, right now these people are not paying,
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but in the years to come, as their income goes up, they'll start to pay.
#
Now the problem with that argument is that in the years to come, as their income goes
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up and as the inflation goes up, the minimum exemption limit will also have to go up.
#
I mean, it's but natural, that's how, you know, it's always been the case.
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And it's the right thing to do as well.
#
The other thing that people don't talk about is that in 2007-8 and 2008-9, the direct taxes
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to GDP ratio was 6.3% and 5.93% respectively, which is, you know, one number is greater
#
than the direct taxes collection in the last year and one number is almost similar.
#
Now what happened back then?
#
What had happened back then was that, you know, the stock market was rallying and obviously
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the government ended up collecting a lot of tax from the stock market in the form of securities
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transaction tax and in the form of short-term capital gains.
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My contention is that a similar thing could have happened in 2017-18 as well.
#
I mean, the data for, you know, STT and short-term capital gains is not available in public domain.
#
So if it was available in public domain, we could have sort of figured out as to, you
#
know, how much tax is coming from STT and short-term capital gain and then sort of arrived
#
at the, you know, whether demonetization has had an impact or not.
#
What has also happened is that, you know, refunds have been delayed.
#
So if, you know, the moment you delay refunds, your collection, the net direct tax number
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So once you factor in all these things, you realize that, you know, again, it's a very
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strong case of optics management.
#
And also besides the refunds being delayed, one thing that you mentioned in your piece
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was that companies were asked to deposit TDS early.
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And that also, that was a report in the economic times and yes.
#
And that also said they were doing these various jogas to kind of get taxes up in the short
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Essentially to bump up the DTC number.
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And what I'd say is the issue here that you're talking about is whether they were accurate
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The issue is not necessarily whether direct taxes going up are desirable or not because
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In the context of our discussion, it's completely irrelevant.
#
We're just discussing that, okay, are they being truthful with whatever their claims
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And if they are claiming X, did they do any short term jogas like being slow on giving
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refunds or making companies deposit TDS early to inflate the numbers so that the optics
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management, as you put it, works well?
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So this is about direct tax data.
#
You know, another very insightful piece you wrote in business standard, if I'm not mistaken
#
is about another, I don't know whether one would call it dishonesty, but the way they
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manage the optics of the budget and in particular the subsidies time bomb.
#
So this is something that, and you cannot just blame the Modi government.
#
It started with Mr. Pichai Dambaram.
#
And so essentially, you know, you need to understand the fact that the government accounting
#
works on cash systems, which basically means that revenue is accounted for when the money
#
comes in and, you know, expenditure is accounted for when the money goes out.
#
Typically in case when companies account, that is based on the accrual system wherein
#
if a sale is made, you know, it is booked as revenue irrespective of the fact whether,
#
you know, the customer, whoever the thing has been sold to has paid for it or not.
#
So that is a basic difference.
#
So essentially what the governments tend to do is they tend to postpone the payment of
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So there are largely three kinds of subsidies, food, fertilizer and petroleum.
#
And these are made by these government agencies like the food corporation of India and they
#
have to take the money from the government.
#
So basically what happens is, so let's say, you know, the food corporation of India buys
#
rice and wheat primarily from farmers and they pay them an X rate, 14 rupees a kg, 15
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I don't remember the exact number, but somewhere along those lines.
#
And then they sell those, that rice and wheat to the public distribution system at a price
#
of two to three rupees a kg.
#
And then there is also the cost of moving that grain around.
#
So the government has to compensate the food corporation of India for that difference.
#
Now, what it tends to do is that the government does not pay on time.
#
So let's say, you know, some amount of subsidy was due in 2017-18, it wouldn't have been
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It will be paid in 2018-19.
#
So the moment they don't pay it in 2017-18, they don't have to account for it as an expenditure
#
because simply because it's a cash accounting.
#
So I'll ask a layman question, clarify this.
#
If this was a private company, the moment that even if they didn't pay, that would still
#
Because it's been incurred.
#
But in case of the government, it's not on the books.
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Not on the books because the government is not incurring the expenditure itself.
#
There is an agency which incurs the expenditure.
#
So I'll give you some numbers.
#
As of 2017-18, and this is data from the Comptroller and Auditor General, the total subsidies outstanding
#
were 2,19,774 crore, of this FCI was owed 2,04,376 crore.
#
Now what happens is the natural question that one may ask now is that how does FCI function?
#
If you know, such a huge amount of money is not paid to an organization, I mean, how does
#
it continue to function?
#
So the FCI essentially continues to function because it keeps borrowing and banks are happy
#
to lend to FCI because FCI is basically the government.
#
So typically what happens is that when FCI borrows, it has to pay interest on that borrowing.
#
So that interest also gets added on to the subsidy burden.
#
And listeners should know that all of you and me and Vivek are paying this interest.
#
I mean, because in some form or the other, I mean, we are paying for it in the form of
#
high petrol and diesel prices for one.
#
So essentially, an estimate made by the CAG suggests that between 2011 and 2016, the Food
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Corporation of India paid an interest of more than 35,000 crore on all the money they had
#
borrowed because the government had not paid them on time.
#
And the government is not paying them on time.
#
So it can do this accounting trick of saying that, hey, we've kept the fiscal deficit
#
We're not spending so much.
#
So this basically started during the Chidambaram era.
#
And back then, I think the number was around 100,000 crore.
#
And over the last four years, it sort of doubled and reached around 2,920,000 crores.
#
And you described this as a subsidies time bomb.
#
Is it going to explode?
#
What's going to happen?
#
I mean, it's a time bomb, yes.
#
Every year, they'll kick it down the road.
#
So the government, essentially, the government fiscal deficit is basically upon this scheme,
#
It keeps running because the government issues bonds and a new set of investors keeps coming
#
In fact, there was a great demand on Twitter that I asked you about Ponzi schemes.
#
But that is a separate...
#
That's a separate episode.
#
And I haven't written on Ponzi schemes for a while, so I'll have to read up and...
#
Though he has written a book which you must read called India's Big Government.
#
And what is that, if not a Ponzi scheme?
#
So I guess, yeah, and that sort of...
#
Because the government at the end of the day is a Ponzi scheme, so they can continue.
#
And I mean, so there are other ways.
#
I mean, you look at the fact that the amount of money, I think 20, 21% of the deposits
#
that the banks collect have to compulsorily be invested in government securities.
#
Of the insurance companies, they have to sort of compulsorily invest money in government
#
So the government in its own way has ensured that the demand for the debt that it issues
#
I mean, the term that economists use for it in the Western world is financial repression.
#
And in India, because we are so used to the idea of financing the government as citizens,
#
we don't even realize it.
#
This is another fascinating subject and all the listeners of the show who are fans of
#
Vivek Kaul, I'd urge you to go to Twitter, find them at kaul underscore vivek and bombard
#
the guy insisting that he write these two books, one on how government is a Ponzi scheme
#
and two on how government uses data.
#
Moving on now to general questions.
#
You know, you're an experienced financial journalist and you have an eye for numbers
#
and you're trained to figure all this stuff out.
#
But what does a citizen do?
#
I'm not really trained.
#
You're sort of self-taught.
#
You're an autodidact data detective.
#
Autodidact data detective.
#
There's a lot of D in there.
#
It sounds like one of those syndromes, you know, which you don't know of.
#
But to get back to my question, what is a citizen, what is a concerned citizen to do
#
to keep a government accountable as far as the truth is concerned?
#
It's tricky, you know, in the, you know, daily life, living, you know, making an earning
#
and, you know, getting to office and coming back.
#
So I guess the only thing you can do is to try and read a wide variety of people given,
#
I mean, and to be, you know, not trust everything that arrives on WhatsApp and, you know, just
#
follow a few, you know, people on the social media and try reading them out.
#
I mean, I don't think there is...
#
See, unless people sort of go looking for knowledge and try understanding things, it's
#
And you cannot blame them given the fact that life is difficult.
#
There is only so much time, there are pressures from the family, you know, there are bosses
#
Everyone's not as lucky as, you know, I am to, you know, who gets the time and gets paid
#
And I think what I'll clarify and I'm sure you'll agree with me and as Plato's quote
#
in fact pointed out, is that this is something that is embedded in human nature and in the
#
way governments function.
#
So this is not particularly about this specific government.
#
I mean, we tend to like stories.
#
So I'll give you a very interesting example, I mean, something that happened today.
#
De Williers retired yesterday.
#
I mean, out of the blue.
#
Now that's a different thing.
#
So now suddenly you have this WhatsApp forward going around, which says that, you know, De
#
Williers was a champion hockey player, a champion tennis player, a champion rugby player, champion
#
golf player at the school level.
#
Now it's, it's very difficult to sort of believe that one guy could have been, you know, good
#
at so many sports, right.
#
And so I just sort of Googled and I realized that this is some fake news, which has been
#
going around for a while now and De Williers has clarified that all this is wrong.
#
And he said that the only sports that he played for a year was hockey in his school or college
#
or something like that.
#
Now so, so one guy who had sent it to me and I told him this and his immediate response
#
was ki, arey kya hua, kamse kem padhne me toh achha lagta hai na.
#
So it's, it's inspiring.
#
My response would have been ki Vivek, tu government ke nahi usko breaker ye toh rahe nahi de.
#
I feel, I feel like you just told me Santa Claus doesn't exist.
#
So I mean, if you look at AB De Williers, I mean, he's done enough on the cricket field
#
itself to be categorized as a legend, but we are a storytelling species.
#
So, so, so people love this, you know, here's this guy.
#
So in fact, if, if you remember correctly, there used to be the same sort of stories
#
going around for John T. Rhodes also, but John T. Rhodes apparently was a great hockey
#
He was, he was, he would have easily made it into the South African hockey team as a
#
center forward if he had not chosen to sort of play cricket.
#
But cricket was, you know, paid, no, I think hockey in South Africa, when he used to be
#
around was played at an amateur level.
#
And thank goodness for that because so many hours of pleasure.
#
So, you know, you can understand one guy being good at two sports, one guy got some six,
#
So apparently Bal Narendra when he was a young lad was good, excellent at a lot of sports.
#
Now we're getting into tricky territory.
#
Let's, let's, let's, I could produce a lot of data on that by the way, but let's end
#
Vivek, thanks so much for coming on the show.
#
As always, I learned to not talk to you.
#
If you enjoyed listening to this episode, go to the page of this episode on either scene
#
unseen.ie and our thinkpragati.com and there are links to all the articles by Vivek called
#
that I mentioned in there.
#
So do check out all those articles.
#
Also I'd urge you to go to your nearest bookstore offline or online and buy the easy money trilogy
#
The easy money trilogy has recently been released by HarperCollins and it's looking really snazzy
#
So this is not just a random plug I'm doing.
#
It's a great book by a very fine writer.
#
In fact, it's your duty as a citizen of this great democracy to read and follow Vivek call.
#
And it's also your duty to read and follow me.
#
So you can find me on Twitter at Amit Verma, A-M-I-T-V-A-R-M-A, thank you for listening.
#
He bends down to test the warm water for his bath.
#
He comes here to quench his thirst for a hot shower and some podcasts.
#
You can witness how he enjoys having other people talk about cool stuff in his bathroom.
#
Indeed, it helps him with his loneliness.
#
You can find more of his PCs on IVMPodcast.com, your one stop destination where you can check
#
out the coolest Indian podcasts.
