Macroeconomy

RBI Gives a Covid Spin to Cash Touching Pre-Demonetisation Levels

We live in an era of narratives. Politicians create them. Corporates create them. Social activists create them. Commentators, public intellectuals, economists and analysts also create them. And there are days when we are even lying to ourselves in our heads and creating narratives for ourselves.

In all this, it is hardly surprising that the Reserve Bank of India (RBI), with Shaktikanta Das at its helm, has also padded up and gotten into the business of narratives and spin. Before I explain this in detail, let me give you some background to this piece.

In November 2016, the central government demonetised Rs 500 and Rs 1,000 notes. The citizens had to deposit these notes into their bank accounts. The result was that 86% of the currency by value suddenly went out of the financial system.

Paper money has different uses, but its main use is as a medium of exchange. It basically facilitates the process of buying and selling. Of course, if people want to, the process of exchange can be carried out through other means like issuing a cheque, making a demand draft, carrying out a money transfer or even paying money digitally.

But India back in 2016 was a country which believed in operating in cash. When the cash went out of the system, the economic transactions especially in the informal sector took a beating. The gravity of the situation never really came out fully, except perhaps anecdotally, given that the government data collection for the informal part of the economic system was and continues to remain abysmal. I guess, which is why it is called an informal sector in the first place.

Between November 2016 and now, I have closely tracked the total amount currency in circulation gradually increasing. Of course, as the economy expands, the currency in circulation is bound to go up. In order to take care of this, the data that needs to be tracked is the currency in circulation divided by the gross domestic product (GDP), expressed as a percentage. (I will refer to this as cash in the system). The GDP is the measure of the size of any economy. The cash in the system basically adjusts for the size of the economy.

My contention over the years has been that the cash in the system will eventually rise to touch the pre-demonetisation level. Earlier this year, in April 2020, writing in the Mint, I had said: “The cash in the system [as of March 2020] works out to 12% of GDP.” I had made this calculation on the basis of the currency in circulation as of March 27 and the GDP forecast for 2019-20 (up until then, the actual GDP numbers were yet to come in).

A formal confirmation of this came yesterday with the RBI  releasing its annual report. In the annual report, the RBI says: “The currency-GDP ratio increased to its pre-demonetisation level of 12.0 per cent in 2019- 20 from 11.3 per cent a year ago, indicating the rise in cash-intensity in the economy in response to the pandemic [emphasis added].” The currency in circulation constitutes of cash with banks and cash with the public.

Before analysing this statement, let’s look at the following figure, which plots the currency in circulation to the GDP ratio or the cash in the system, over the years.

Cash in the System


Source: Reserve Bank of India.

In March 2017, a few months after demonetisation was carried out and after the whole country had queued up to deposit the demonetised Rs 500 and Rs 1,000 notes into their bank accounts, the cash in the system fell to 8.7% of the GDP.

The reason for this was very straightforward; the government and the RBI couldn’t replace the cash in the system at the same pace as they had taken it out. There were all kinds of problems, including banks having to reset ATM trays in order to take care of the smaller size of the new notes.

As of March 2020, the cash in the system is back to 12% of the GDP, which is at an almost similar level of 12.1% of the GDP as of March 2016, before demonetisation was carried out. The RBI feels this has happened because there has been a dash for cash in light of the spread of the covid-19 pandemic. People hoarded on to more cash than they normally do and this led to a faster rise in the cash in the system than it normally would have.

The point to be remembered here is that we are talking cash in the system as of March 2020 and not August 2020. At that point of time, people had just started to take covid-19 seriously. Let’s take a look at the monthly increase/decrease in currency in circulation during the course of 2019-20.

Changes in currency in circulation


Source: Author calculations on data from Reserve Bank of India.

It is very obvious from the above chart that at Rs 99,040 crore, the maximum monthly increase in cash in the system during the year, happened in March 2020. Does this then imply that there was a dash for cash as the fear of the pandemic spread? In order to say this with surety we will have to look at weekly increase in cash levels in the system during the course of March 2020.

Dash for Cash?


Source: Author calculations on Reserve Bank of India data.

India went into a physical lockdown starting March 24, 2020. It is only around then that most of the country realised the gravity of the pandemic. This can be seen by increase in cash in the system in the week ending March 27. This implies a higher than normal increase in currency with public with a higher withdrawal of money from the banking system than would have been the case if all was well.

But the bulk of the increased withdrawals in March had happened before March 20. Close to 62% of the withdrawals in March (at Rs 61,354 crore) had happened before March 20. Interestingly, up until then the fear of the pandemic hadn’t really spread. This weakens the entire dash for cash argument.

Let’s say if things had gone on normally then it is safe to say that the increase cash in the system in March would have been around 80-85% of what it eventually got to. At this level of increase, the cash in the system as of March end would have been around 11.95% of the GDP, which is not significantly different from 12.03% of the GDP, it eventually came to. The RBI’s dash for cash argument hangs on a few basis points.

Even if assume, that increase in the cash in the system in March 2020 was at around 60% of the actual number, the cash in the system would have worked out to 11.84% of the GDP, which is slightly lower than 12.03% of the GDP. And even at 11.84% of the GDP, the cash in the system would have been higher than where it was as of March 2019, and would have continued to go up, as it has since November 2016. This is the more important point.

While India of November 2016 was a country which believed in operating in cash, so is the India of March 2020. Yes, digital transactions have gone up along the way and that’s a good thing. But that could have happened anyway without putting the country through the trouble that demonetisation did.

Also, it is time we realised that people don’t store their black money in cash. In fact, data from a White Paper on black money published in May 2012 showed that around 4.9% of the total undisclosed income admitted to during search and seizure operations between 2006 and 2012 was held in the form of cash. Cracking down on black money is much more complicated operation than just cracking down on cash in the system.

Further, societies with more cash aren’t necessarily more corrupt. If that was the case Japan with a cash in the system of around 20% of the GDP would be more corrupt than India. On the flip side, Nigeria which has a cash in the system comparable to that of Norway, wouldn’t be a country as corrupt as it is. The government needs to make peace with this fact.

To conclude, I think one reason the RBI might have resorted to this spin and is trying to create a narrative, lies in the fact that when demonetisation was carried out, the current RBI governor Shaktikanta Das was the finance secretary.

My guess is that a part of Das still wants to justify demonetisation as a good thing and show it by telling the nation that the cash in the system rose to the pre-demo level simply because of the Covid-19 pandemic, something that wouldn’t have happened otherwise.

But as I showed above that is a very weak argument. It is time the RBI sang a different tune on this front and moved a dash for cash to Das for cash.

Why HDFC Finds Homes to Be More Affordable, When They Clearly Aren’t

Summary: HDFC is getting better home loan customers that doesn’t mean homes have become more affordable. HDFC’s conclusion of homes becoming more affordable is an excellent example of survivorship bias.

Before I start writing this, I have a confession to make. I have written about this issue before, around five years back. But given that things haven’t really changed since then, it is a good time to write about it again. Hence, to all my regular readers who have been following me over the years and might have read this earlier, sincere apologies in advance.

Home loans in India are given by two kinds of institutions – banks and housing finance companies (HFCs). Among the HFCs, Housing Development Finance Corporation (HDFC) has been a pioneer in the area of home loans.

The company regularly publishes an investor presentation along with every quarterly result.

I am not sure for how long the company has been doing this, but its website has these presentations going as far back as March 2013, a little over seven years. Since then, the company has had a slide in its investor presentation which talks about the improved affordability of owning a home in India. Usually, it is the eight or the ninth slide in the presentation (sometimes, but very rarely tenth).

This is the slide in the latest presentation for the period April to June 2020.

Improved affordability of homes

Source: HDFC Investor Presentation, June 30, 2020.

Let’s look at the chart between 2000 and 2020, the last two decades. The home loan market in the country before that was too small and evolving and hence, prone to extreme results. So, it makes sense to ignore that data.

What does the chart tell us? It tells us that affordability of homes in the country has gone up over the years. The chart defines affordability as home price divided by the annual income of the individual buying the home.

In 2020, the average home price has stood at around Rs 50 lakh. Against this, the average annual income of the individual buying the home stands at around Rs 15 lakh. Given this, the affordability factor is at 3.3 (Rs 50 lakh divided by Rs 15 lakh).

Hence, the average individual in 2020 is buying a home which is priced at 3.3 times his annual income. (Please keep in mind that the property prices are represented on the left-axis and the annual income is represented on the right axis).

As can be seen from the chart, the affordability factor at 3.3 is the lowest in twenty years. Hence, affordability of homes has gone up. QED.

The trouble is, this goes totally against what we see, hear and feel all around us. Real estate companies have lakhs of unsold homes with absolutely no takers. They have thousands of crore of unpaid loans. The banks and non-banking finance companies (NBFCs) have restructured these loans over the years and not recognized them as bad loans in the process, with more than a little help from the Reserve Bank of India (RBI). Bad loans are loans which haven’t been repaid for a period of 90 days or more.

Further, investors who bought real estate over the years have been finding it difficult to sell it. Indeed, if homes had become more affordable, this wouldn’t have been the case. Real estate companies would have been able to sell homes and repay the loans they have taken from banks and NBFCs. And the RBI wouldn’t have to intervene.

So, what is it that HDFC can see that we can’t? Before I get around to answering this question, let me tell you a little story. During the Second World War, the British Royal Air Force (RAF) had a peculiar problem.

It wanted to attach heavy plating to its airplanes in order to protect them from gunfire from the German anti-aircraft guns as well as fighter planes. The trouble was that these plates were heavy and hence, had to be attached strategically at points where bullets fired by the German guns were most likely to hit. The British couldn’t plate the entire plane or even large parts of it.

The good part was that they had historical data regarding which parts of the plane did the German bullets actually hit. And this is where things got interesting. As Jordan Ellenberg writes in How Not to Be Wrong: The Hidden Maths of Everyday Life: “The damage [of the bullets] wasn’t uniformly distributed across the aircraft. There were more bullet holes in the fuselage, not so many in the engines.”

So, historical data was available and hence, the decision should have turned out to be a very easy one. The plates needed to be attached around the plane’s fuselage. But this logic was missing something very basic. The German bullets should have been hitting the engines of airplanes more regularly than the historical evidence suggested, simply because the engine “is a point of total vulnerability”.

A statistician named Abraham Wald realised where the problem was. As Ellenberg writes: “The armour, said Wald, doesn’t go where bullet holes are. It goes where bullet holes aren’t: on the engines. Wald’s insight was simply to ask: where are the missing holes? The ones that would have been all over the engine casing, if the damage had been spread equally all over the plane. The missing bullet holes were on the missing planes. The reason planes were coming back with fewer hits to the engine is that planes that got hit in the engine weren’t coming back.” They simply crashed.

This is what is called survivorship bias or the data that remains and then we make a decision based on it.

As Gary Smith writes in Standard Deviations: Flawed Assumptions Tortured Data and Other Ways to Lie With Statistics: “Wald…had the insight to recognize that these data suffered from survivor bias…Instead of reinforcing the locations with the most holes, they should reinforce the locations with no holes.”

Wald’s recommendations were implemented and ended up saving many planes which would have otherwise gone down. (On a different note, both the books from which I have quoted above, are excellent books on how not to use data, especially useful if you are in the business of torturing data to make it say what you want ).

If you are still scratching your head and wondering what does this Second World War story have to do with HDFC finding homes more affordable, allow me to explain. Like the British before Wald came in with his explanation, HDFC is also looking at the data it has and not the overall data.

Look at the left-hand of the corner of the chart, it says based on customer data. The analysis is based on HDFC’s own historical customer data. When HDFC talks about an average home price of Rs 50 lakh and an income of Rs 15 lakh, it is basically talking about the set of people who have approached the HFC for a loan and gotten one. Hence, HDFC’s conclusion of better affordability is drawn from the sample it has access to.

But does this really mean that affordability has improved? Or does it mean that the quality of HDFC’s customers has improved over the years? The customers that HDFC is giving a home loan to are ones who can afford to buy homes. The HFC clearly has no idea about people who want to buy homes but simply do not have the financial resources to do so.

They don’t show up as a part of any sample, hence, the evidence on them is at best anecdotal. These people are like planes whose engines were hit and hence, they did not make it back to their base, in the Second World War. And like there was no data on the planes which got hit and didn’t make it back, there is no data on these people as well. Basically, HDFC’s data and conclusion are victims of the survivorship bias

In fact, HDFC’s investor presentation has always carried another interesting slide on low penetration of home loans in India. The following chart is from the latest presentation.


Home loans as a percentage of GDP

Source: HDFC Investor Presentation, June 30, 2020.

Total home loans outstanding given by both banks and HFCs in 2020 stands at 10% of the GDP (On a slightly different note, the ratio of homes loans given by banks to home loans given by HFCs is 64:36). In March 2014, the total outstanding home loans in India had stood at 9% of the GDP. If homes indeed were affordable this ratio would have gone up faster.

To conclude, it’s time that HDFC remove this misleading slide from its investor presentation or at least say that the affordability has improved for its customers and not for the country as a whole.

Why income tax is not going to be abolished anytime soon

Dr Subramanian Swamy has time and again suggested that personal income tax should be abolished. The logic is that this will put more money in the hands of people, and they will go out there and spend a lot of it, and this will benefit businesses and the overall economy.

What the government will lose out on the direct tax front, it is likely to make up from indirect taxes like goods and services tax, as people consume more. Companies will earn more and as a result pay a higher corporate income tax.

So, clearly there is economic logic to what Dr Swamy has been suggesting over the years. But the fact of the matter is that no government will have the balls to take a decision like this.

Take a look at the following chart.


Source: Author calculations on data sourced from www.cga.nic.in and www.indiabudget.nic.in

The chart plots personal income tax as a proportion of total gross taxes collected by the central government. In the last ten years, this has gone up. In 2019-20, the last financial year, the total personal income tax collected formed 23% of the overall taxes collected by the central government.

Other than personal income tax, the central government collects central goods and services tax, corporate income tax, union excise duty and customs duty, as well. These taxes form a bulk of the taxes collected by the central government.

In 2020-21, the central government hopes to collect a total of Rs 6,25,000 crore as personal income tax. This is around 26% of the total taxes that the government expects to collect in the year.

Of course, this estimate was made before covid-19 struck. Nevertheless, irrespective of that what it tells us is that the government during 2020-21 hoped to collect more personal income tax as a proportion of overall taxes than it has ever done before.

If the government does away with individual income tax as Dr Swamy has suggested over the years and as many income taxpayers have come to wholeheartedly want, it loses nearly a fourth of its tax revenue immediately.

As mentioned earlier in the piece, this will mean a windfall for individual income taxpayers. As they spend a part of this money, the government will earn taxes in other forms. At least that’s what the theory suggests. The government can also sell a lot of assets (its shares in public sector enterprises and land) that it owns to make up for the elimination of personal income tax.

And that’s where the trouble is. No government in its right mind will give up on a fourth of its tax revenues, just in the hope of making up for it through other ways.

Also, it is worth remembering that the salaried pay a major portion of individual income tax. It is easy to tax salaried income. And anything that is easy to tax, no government is going to give up on. And finally, what happens to all the taxmen if personal income tax is done away with? So, clearly there is no incentive for the government to do away with personal income tax.

Hence, hoping that the government will abolish personal income tax is at best a pipe dream. It’s not going to happen.