Indian economy

China’s Population Control Model is an Outdated and a Bad Idea for India

Hum do hamare ho do,
paas aane se mat roko.
— Indeevar, Rajesh Roshan, Amit Kumar, Sadhana Sargam and Rajesh Roshan, in Jurm (1990).

 Here’s a scene from a middle class Indian drawing room of the late 1980s and early 1990s. Four men are sitting and chatting.

“You know what India’s biggest problem is?” asks the first.

“Our population,” replies the second.

“The government should do something to control it,” says the third.

“Indeed,” affirms the fourth.

Three decades and more later, whether similar conversations continue to happen in the middle class Indian drawing rooms, I have no idea, simply because I haven’t been in one for many years. But some Indians still think in a similar fashion, that is, India has a population problem and that the government should do something to control it, like the way China did. (Okay, we might want to boycott Chinese goods but we don’t have such inhibitions when it comes to their population control policy).

In fact, one such individual, even filed a public interest litigation with the Supreme Court and as reported in the Sunday edition (December 13, 2020) of The Times of India, pleaded that “to have good health; social, economic and political justice; liberty of thoughts, expression and belief, faith and worship; and equality of status and opportunity, a population control law, based on the model of China, is urgently required.” (Ironically, the above paragraph mixes the Preamble of the Indian Constitution with the Chinese population control law). 

This is precisely the kind of lazy thinking that prevails when one forms an opinion on something and continues holding on to it, without looking at the latest data. Let’s look at this issue pointwise, in order to understand that such thinking is totally wrong.

1) There is no denying that India has a large population and that creates its own set of problems, everything from lack of employment opportunities to lack of public infrastructure. But is population control the answer to that? No. Look at the following chart, which plots the total fertility rate of India.


Source: https://data.worldbank.org/indicator/SP.DYN.TFRT.IN?locations=IN

The total fertility rate in 2018 stood at an all-time low of 2.222. This meant that on an average 1,000 Indian women have 2,222 babies during their child-bearing years. The chart has a downward slope, which means that the fertility rate has been falling over the years. This means on an average  Indian women have been bearing fewer children over the decades.

The replacement rate or the total fertility rate of women at which the population automatically replaces itself, from one generation to another, typically tends to be at 2.1. India’s fertility rate is almost at the replacement level.

As per the Sample Registration System Statistical (SRSS) Report for 2018, the total fertility rate in urban India was 1.7 and in rural India was at 2.4. Hence, urban India is already below the replacement rate.

2) The point being that the Indian population is increasing at a much slower pace than it was in the earlier decades. How has that happened?

As Hans Rosling, Ola Rosling and Anna Rosling Rönnlund write in Factfulness—Ten Reasons We’re Wrong About the World – And Why Things Are Better Than You Think:

“Parents in extreme poverty need many children… for child labour but also to have extra children in case some children die… Once parents see children survive, once the children are no longer needed for child labour, and once the women are educated and have information about and access to contraceptives, across cultures and religions both the men and the women instead start dreaming of having fewer, well-educated children.”

Hence, as the infant mortality rate falls due to a variety of reasons, from more women getting educated to a higher economic growth to urbanisation, the fertility rate comes down as well. Take a look at the following chart, which basically plots the infant mortality rate of India over a period of time. The infant mortality rate is defined as the number of children who die before turning one, per 1,000 live births.

Source: https://data.worldbank.org/indicator/SP.DYN.IMRT.IN

The infant mortality rate has fallen from 161 in 1960 to 28.3 in 2019. As more children born have survived and grown into healthy adults, parents have had fewer children. That is one clear conclusion we can draw here.

As the Roslings write: “Every generation kept in extreme poverty will produce an even larger next generation. The only proven method for curbing population growth is to eradicate extreme poverty and give people better lives, including education and contraceptives.”

India’s adult female literacy rate (% of females aged 15 and above) had stood at 25.68% in 1981. It has since gradually improved and in 2018 had stood at 65.79%. As more women have learned to read and write, the infant mortality rate and the fertility rate have both come down.

As the SRSS Report points out:

“On an average, ‘Illiterate’ women have higher levels of age-specific fertility rates than the ‘Literate’. Within the ‘Literate’ group there is a general decline in the fertility rates with the increase in the educational status both in the rural and urban areas, barring a few exceptions.”

Also, faster economic growth post 1991 has helped in bringing down poverty levels and in turn led to a lower fertility rate as well.

In 1960, the total fertility rate was at 5.906. It fell to 4.045 by 1990. By 2018, it had fallen to 2.22. Clearly, the rate of fall has been faster post 1990.

3) Now let’s talk about the China model of population control, which led to one Ashwini Upadhyay petitioning the Supreme Court, pleading that India adopt such a law as well. But before we do that let’s look at the following chart which basically plots the total fertility rate in China over the years.

Source: https://data.worldbank.org/indicator/SP.DYN.TFRT.IN?locations=IN-CN

China’s coercive one-child population control policy was launched in 1979. At that point of time, the Chinese fertility rate was 2.745. The interesting thing is that it had been falling rapidly from 1965 onwards when it had peaked at 6.385.

As Mauro F. Guillén writes in 2030: How Today’s Biggest Trends Will Collide and Reshape the Future of Everything:

“Back in 1965, the fertility rate in urban China was about 6 children per woman. By 1979, when the one-child policy came into effect, it had already declined all the way down to about 1.3 children per woman, well below the replacement level of at least 2 children per woman. Meanwhile, in rural China, fertility hovered around 7 children per woman in the mid-1960s, a number that decreased to about 3 by 1979.”

The point being that in 1979 when Chinese leaders pushed through the one-child policy the fertility rate in urban China was already at 1.3, much lower than the replacement rate. In rural China it was at 3, greater than the replacement rate of 2.1, but it was falling at a very fast rate. Hence, the decision to push through the one-child policy was not a data backed decision but basically politics.

As Guillén writes:

“The policymakers were unaware of the reality that fertility in China had been dropping precipitously since the 1960s, with most of the decrease driven by the same factors as in other parts of the world: urbanization, women’s education and labour force participation, and the growing preference for giving children greater opportunities in life as opposed to having a large number of them.”

Clearly, Upadhyay like the Chinese  before him, did not look at the Indian data before filing the public interest litigation in the Supreme Court and thus wasting the time of the Court as well as that of the government.

4) One of the impacts of the coercive one child policy in China was that parents preferred to have boys than girls. As Guillén writes: “While it was the law, the one-child policy created a gender imbalance of about 20 percent more young men than women, driven by the cultural preference for boys.”

The male-female ratio went totally out of whack. In 1982 there were 108.5 male births per 100 female births. This went up to 118.6 per female births in 2005. It has since fallen to 111.9. This has led to an intensified competition in the marriage market, with many Chinese men being unable to find brides.

As per the Sample Registration System Statistical Report for 2018, India’s sex ratio at birth was 1,000 males to 899 females. This works out to around 111 males for 100 females. Of course, like the Chinese even Indian parents have a cultural preference for a male child, who they believe will take care of them in their old age and also ensure that their family continues.

Imagine the havoc any coercive population control policy could have caused or can still cause, to the sex ratio in India.

In lieu of this fact, it was nice to see that the Modi government responded in an absolutely correct way in the Supreme Court. The health and family welfare ministry told the Court: “India is unequivocally against coercion in family planning… In fact, international experience shows that any coercion to have a certain number of children is counter-productive and leads to demographic distortion.”

Clearly, the government doesn’t want to become a victim of the law of unintended consequence where it wants to do one thing and ends up creating other problems. Kudos to that.

5) The Health and Welfare Statistics of 2019-20 project that India’s total fertility rate will be 1.93 in 2021, which will be lower than the replacement rate of 2.1. It is expected to fall further to 1.80 by 2026-2030.

Of course, a fertility rate of close to the replacement rate doesn’t mean that all states have low fertility rates. Recently, the data for  the first phase of the fifth National Family Health Survey (NFHS-5) was released. This had data for 17 states and five union territories. Among the large states, Bihar was the only state which had a total fertility rate greater than the replacement rate. The total fertility rate of the state stood at 3. (The data for other laggard states like Uttar Pradesh, Rajasthan, Madhya Pradesh etc., wasn’t released in this phase).

A look at the data from Health and Welfare Statistics of 2019-20 tells us that the poorer states which have higher infant mortality rates also have higher fertility rates, most of the times. This evidence is in line with theory.

6) States with a lower fertility rate will not see an immediate fall in population. This is primarily because of the past high fertility rate because of which more people will enter or be a part of the reproductive age group of 15-49. This is referred to as the population momentum effect.

As C Rangarajan and J K Satia wrote in a column in The Indian Express in October: “For instance, the replacement fertility level was reached in Kerala around 1990, but its annual population growth rate was 0.7 per cent in 2018, nearly 30 years later.” Nevertheless, population growth has slowed down and will continue to slow down further.

The larger point here being a growing population is a very important part of economic growth (of course, this is a necessary condition for economic growth but not a sufficient one).

As Ruchir Sharma writes in The 10 Rules of Successful Nations: “Throughout, increases in population have accounted for roughly half of economic growth… The impact of population growth on the economy is very straightforward, and very large. If more workers are entering the labour force, they boost the economy’s potential to grow, while fewer will diminish that potential.”

Many Indian states with a fertility rate lower than 2.1 will start facing the situation where fewer people will enter their workforce, in the next couple of decades. This includes Southern and the Western states. It also includes states like West Bengal, Punjab, Himachal Pradesh and Jammu and Kashmir.

Clearly, these states will need workers from other states to keep filling the gap in their working age population (something which is already happening). Also, as workers from high fertility states move to work in low fertility states, they will see an increase in their incomes. This will have an impact on their own fertility rates, which will fall.

In this scenario, states trying to reserve jobs for locals, is a bad idea in the medium to long-term, though it might work in the short-term by being politically popular. Also, states with lower fertility rates on the whole have higher per-capita incomes. Given that, locals do not always want to take on the low-end jobs. And for that, people from other states need to come in and take on those jobs.

People who move from less developed states to more developed states in India are those who are low-skilled or semi-skilled, largely. Alternatively, they have very high-level skills.

One indirect effect of a rise in migrants in any given state is that migrants spend a part of the money they earn and this leads to the overall increase in demand for goods and services within that state. It also leads to the government earning more indirect taxes.

This works well for the overall economy and the population as a whole though it may not be perceived in that way by the local population. As Abhijit Banerjee and Esther Duflo write in Good Economics for Hard Times: “ Migrants complement, rather than compete with, native labour as they are willing to perform tasks that natives are unwilling to carry out.”

To conclude, India has largely done whatever it had to stabilise its population growth, without resorting to any coercive policies (except for a short-time during the emergency). So, population growth has been slowing down for a while now and will continue to slowdown in the decades to come. In this environment, it is important to learn the right lesson from this entire issue, which is that societal level changes take time but they do happen at the end of the day, if the government keeps working towards it.

Also, going forward, it is important that young workers are allowed to move freely from one part of the country to another in search of an occupation; from the poorer parts to the better off parts.

As Rutger Bregman writes in Utopia for Realists: The Case for a Universal Basic Income: “Opening up our borders, even just a crack, is by far the most powerful weapon we have in the global fight against poverty.”

Of course, Bregman is talking in the context of international migration, with people moving from poorer countries to richer ones. But there is no reason why the same logic can’t apply to moving within the country as well.

Postscript: I just hope the Supreme Court judges are looking at the right data while listening to the PIL.

The Curious Case of India’s Two Wheeler Sales or Why Nothing is the Way It Seems

Ik yaaron bullet bhi hua lakh da,
dooja yaaron mehanga petrol ho gaya.

— Harkirat Singh Matharoo, Desi Crew and Jassimran Singh Keer in Bullet. 

I have been following  the issue of domestic two-wheeler sales on a regular basis. Two wheelers basically comprise of motorcycles, scooters and mopeds (around 6.37 lakh mopeds were sold in 2019-20).

Domestic two wheeler sales are a very important economic indicator which give us a good indication of the purchasing capacity of middle class India. Hence, it is important that they are interpreted in the correct way.

The sad part is that the mainstream media in its quest to get advertisements from automobile companies isn’t really doing that.

For the last few months we have been told that two-wheeler sales have been going up in comparison to the same month in 2019.
Take the case for November 2020. Newsreports tell us that 1.6 million units of two-wheelers  were sold during the month and this was 13.4% more than the number of two-wheelers sold during November 2019.

Not for a moment I am suggesting the media is making this data up. They are simply reporting the numbers that the Society of Indian Automobile Manufacturers (SIAM) is providing them with. SIAM is basically the lobby representing major vehicle and vehicular engine manufacturers in India.

SIAM reports the number of units of two-wheelers leaving the gates of manufacturers or factory gate shipments. In simpler words, these are units which have been sold by manufacturers to dealers across the country, who in turn will sell to the end consumers. So, the SIAM data does not represent retail sales or the sales made to the end consumer. If we look at retail sales, the real situation is revealed and the picture that emerges is not so pretty.

Let’s take a look at this issue pointwise.

1) In November 2020, as per SIAM, 1.6 million units of two-wheelers were sold.  But what were the real sales like?

The Federation of Automobile Dealers Associations (FADA) reports the number of units of two wheelers registered at the Regional Transport Offices (RTOs) across the country after they have been sold to the end consumer. Hence, the sales number reported by FADA is a better representation of sales to end consumers. It uses the government’s Vahan 4 database to report these numbers.

How many units of two-wheelers were sold in November as per FADA? 1.41 million units. This is lower than the number reported by SIAM. In fact, the difference is at 1.87 lakh units. This is the lowest difference between the SIAM and FADA numbers over the months since May 2020, when the difference was around 1.21 lakh units.

2) Take a look at the following chart. It plots the two-wheeler sales over the course of the current financial year (i.e. 2020-21), as reported by SIAM and FADA.

Source: SIAM and FADA.

As is clear from the above chart, in each month the SIAM sales numbers have been more than the FADA sales numbers. In fact, as per SIAM, a total of around 9.64 million units of two-wheelers were sold in India during this financial year. FADA puts the number at 6.19 million units, almost 36% lower. This is a difference of close to 3.45 million units.

3) What explains this difference? A small part of it stems from the fact that FADA sales numbers do not take into account sales made in the states of Andhra Pradesh, Telangana and Madhya Pradesh, which aren’t yet on the government’s Vahan 4 database, which FADA uses to publish the retail sales numbers. But retail sales in just three states can’t explain a difference of 3.45 million units between the SIAM sales number and the FADA sales number.

4) So what does this mean? This basically means that while manufacturers have been selling two-wheelers to retailers and retailers haven’t been able to sell a significant portion of what they have bought from manufacturers to the end consumer. Channel stuffing has been carried out and now the retailers have ended up with a significant amount of inventory. FADA suggests that the average inventory of two-wheelers with dealers is at 45-50 days. This is at the end of the festival season. Last year, at the end of the festival season the two-wheeler retailers had an average inventory of 35-40 days. What this means is that channel stuffing has gone up during the course of this year and last year’s problem has continued taking on an even bigger form.

5) Why has channel stuffing gone up? A possible explanation for this lies in the fact that both manufacturers and retailers stocked up in the hope of sales picking up during the festival season. In fact, the sales did pick up in November, with 1.41 million units and more (if we take three states for which FADA does not have data for), being sold at the retail level, the best during the course of this financial year. But this best wasn’t good enough to exhaust a bulk of the inventory build up that happened, given that retailers still have close to 50 days inventory.

Interestingly, if we look at the total sales of two-wheelers as per FADA during the 42-day festival season, from Navratri to Diwali, they were at 2.03 million units, 6.3% lower than last year. Clearly, when it comes to two-wheelers, the bets of both the manufacturers and retailers have turned out to be way too optimistic. The so-called revival in sales as per SIAM can be correctly interpreted as scooters and motorcycles stored in godowns of retailers, waiting to be sold.

6) So how bad is the situation? Let’s concentrate on FADA data for this, simply because it represents real consumer sales. Also, let’s ignore the months of April and May, when a lockdown to prevent the spread of the covid pandemic was in place and very little actual sales happened at the retail level. How do things look between June and November 2020, in comparison to the same period in 2019?

Around 6.04 million units were sold at the retail level between June and November 2020, which is 28% lower than the 8.38 million units sold during the same period last year. Clearly, retail sales have taken a huge beating.

Take a look at the following chart, which plots the fall in retail sales which happened in a given month this financial year vis a vis last financial year. Also, I have considered sales in October and November together simply because the festival of Diwali was in October last year and in November this year. This makes the comparison more robust.

Source: Author calculations on FADA data.

As can be seen, the fall in sales this year was at 40.92% in June. (I have ignored the April-May data because of the lockdown). The fall was at 12.62% in September. In the festival season of October-November it stood at 23.79%. This is a worrying sign.

7) A few two-wheeler manufacturers have made a lot of song and dance about their sales over the last few months. Let’s take a look at how things look for them during the months of October and November this year vis a vis last year. This is FADA data, hence, the usual disclaimer applies.

Source: Author calculations using FADA data.

As can be clearly seen from the above chart, the sales of the five largest two-wheeler companies during October and November this year, have been lower than the last year. On the whole, their sales were 2.25 million units, around a quarter lower than last year. The question is: what was the song and dance all about. Pleasing the government?

Finally, what will the future look like? Let’s take a look at this pointwise.

1) With an inventory of around 50 days at the retail level, the number of two-wheelers leaving the factories of two-wheeler manufacturers in the months to come will come down, unless retail sales improve dramatically. This has already happened in November with the difference between SIAM data and FADA data narrowing. The chances of retail sales picking up dramatically are low.

2) As far as retail sales are concerned, it will be interesting to see how the post-festival season period will play out. Clearly, the months of October and November were not as good this year as they were last year.

3) Also, it needs to be kept in mind that a good portion of the sales during June to November, would have been pent up demand or people who wanted to buy a two-wheeler during April and May, and couldn’t buy due to the lockdown. Further, a significant number of people must have bought two-wheelers over the last few months to avoid taking public transport. Has this demand exhausted? It is difficult to answer this question with total certainty, nevertheless, a significant portion of this demand must have led to purchases by now.

4) How the banks go about lending two-wheeler loans in the months to come will be interesting to watch. Thanks to a case which is currently on in the Supreme Court, banks haven’t gotten around to marking retail loans of under Rs 2 crore which have gone bad, as bad loans.

To conclude, it will be interesting to see how two-wheeler sales go in the remaining part of the year. From what data and logic currently suggests, things will continue to remain difficult this year. And that in turn suggests that the ability and the mindset of the Indian middle class to pay EMIs at this juncture will continue to remain limited.

Finally, petrol prices are on their way up.

Mannubhai motor chali pum pum pum.
— Rajendra Krishan, Laxmikant Pyarelal, Kishore Kumar, Asrani and Sikandar Khanna, in Phool Khile Hain Gulshan Gulshan.

Amitabh Kant, the Indian Middle Class and their Dream of a Benevolent Autocrat

Dekh tere sansar ki halat kya ho gayi bhagwan,
Kitna badal gaya insaan, kitna badal gaya insaan.

— Kavi Pradeep, C Ramachandra, Kavi Pradeep and IS Johar, in Nastik (1954).

Sometime in late December last year I was part of a panel deliberating on where the Indian economy is headed, at a business school in Mumbai.

Towards the end of the discussion, a fund manager sitting towards my right, offered his final reason on why the so-called India growth story was faltering. He said, India has too much democracy.

The room was full of MBA students, just the kind of audience which laps up reasons like the one offered by the fund manager. As soon as he finished speaking, I explained to the audience why the fund manager was wrong, not just because India and the world need democracy, but also from the point of view of economic growth.

Of course, that wasn’t the first time I had heard the too much democracy argument being made in the context of it holding back India’s economic growth. Over the years, I have seen, friends, family members, random acquaintances and men and women I don’t know, make this argument with panache and great confidence.

It seemed, as if, in their minds, they had a picture of this great leader who would come on a white horse, brandishing his sword, and set everything right. They wanted India to be governed by a benevolent autocrat. 

Given this, it is hardly surprising that Amitabh Kant, the CEO of the NITI Aayog, and one of central government’s top bureaucrats, said yesterday (December 8, 2020): “Tough reforms are very difficult in the Indian context, we are too much of a democracy.”

The thinking here is that given that India is a democracy, decision making takes time and effort and you can’t just push through economic reforms which can lead to economic growth. Getting things done needs a collaborative effort and hence, is deemed to be difficult. Hence, it would be great to have less democracy, making it easier for a strong leader to push economic reforms through.

Of course, the mainstream media has largely ignored Kant’s comment. But this is an important issue and needs to be discussed.

The question is where does the thinking of too much democracy come from.

Some of it is remnant from the emergency era of 1975-1977, when trains used to apparently run on time. Trains not running on time was basically a manifestation of the general frustration of dealing with the so-called Indian system.

The logic being that, with the then prime minister Indira Gandhi keeping democracy on a backseat, it essentially ensured that the system (represented by trains) actually worked well (represented by trains running on time).

In the recent years, too much democracy hurting India’s future economic prospects comes from the economic success of China. China doesn’t have democracy. The Chinese Communist Party governs the country. In fact, there is no difference between the Party and the government.

This essentially has ensured they can push economic growth without any resistance from the opposition, different sections of the society or the citizens themselves for that matter.

China is not the only example of this phenomenon. Countries like South Korea under Park Chung-hee, Taiwan under Chiang Kai-shek and Singapore under Lee Kuan Yew, made rapid economic surges under leaders who can be categorised as benevolent autocrats.

As economist Vijay Joshi said at the 15th LK Jha memorial lecture at the Reserve Bank of India, Mumbai, in December 2017:

“ Fewer than half-a-dozen of the 200-odd countries in the world have achieved super-fast and inclusive growth for two or more decades on the run, and almost all of them were autocracies during their rapid sprints.”

So, history tells us that most super-fast growing countries at different points of time have been autocracies.

Beyond this, there is the so-called India growth story which also leads to the sort of thinking which concludes that too much democracy hurts economic growth. Ravinder Kaur makes this point beautifully in Brand New Nation—Capitalist Dreams and Nationalist Designs in Twenty-First-Century India.

As she writes:

“What is dubbed a growth story in policy-business circles is essentially an enchanting fairy-tale blueprint of economic reforms along with calls of a strong political leader to implement it… After all, capital has always rooted for strong, decisive leaders and centralized governance that can ensure its swift mobility and put the nation’s resources at the disposal of investors.”

A good part of India’s corporate and non-corporate middle class buys into this kind of thinking. They look at themselves as investor-citizens.

This leads to the firm belief that autocracies lead to faster economic growth. Hence, too much democracy is bad for economic growth. Only if India had a stronger leader. QED. Or so goes the thinking.

Dear Reader, this is nothing but very lazy thinking. While, most super-fast growing countries may have been autocracies with a benevolent autocrat at the top, the real question is, are all autocracies with a benevolent autocrat at the top, or at least most of them, super-fast growing countries.

Economist William Easterly makes this point in a research paper titled Benevolent Autocrats. As he writes: “The probability that you are an autocrat IF you are a growth success is 90 percent. This probability seems to influence the discussion in favour of autocrats.”

But that is the wrong question to ask. The question that needs to be asked should be exactly opposite—if a country is governed by an autocrat what are the chances that it will be a growth success? Or as Easterly puts it: “The relevant probability is whether you are a growth success IF you are an autocrat, which is only 10 percent.”

And this is where things get interesting, if we choose to look at data. Ruchir Sharma offers this data in his book The Ten Rules of Successful Nations. Let’s look at this pointwise.

1) In the last three decades, there were 124 cases of a country growing at faster than 5% for a period of ten years. Of these, 64 growth spells came under a democratic regime and 60 under an authoritarian one. Clearly, when it comes to countries growing at a reasonable rate of growth for a period of ten years, democracies do well as well as authoritarian regimes.

2) Let’s up the cut off to an economic growth of 7% or more for a period of ten years. How does the data look in this case? Sharma looked at data of 150 countries going back to 1950. He found 43 cases where a country’s economy grew at an average rate of 7% or more for a period of ten years. Interestingly, 35 of these cases came under authoritarian governments. As mentioned earlier, super-fast growth and autocrats go together. But this just shows one side of things.

3) So, what’s the other side? While super-fast growth in a bulk of cases has happened under authoritarian regimes, so have long economic slumps or economic slowdowns.

As Sharma writes:

“Long slumps are also much more common under authoritarian rule. Since 1950, there have been 138 cases in which, over the course of a full decade, a nation posted an average annual growth rate of less than 3 percent—which feels like a recession in emerging countries. And 100 of those cases unfolded under authoritarian regimes, ranging from Ghana in the 1950s and ’60s to Saudi Arabia and Romania in the 1980s, and Nigeria in the 1990s. The critical flaw of autocracies is this tendency toward extreme, volatile outcomes.”

Also, under authoritarian regimes, economic growth can see wild swings.

So, for every China there is a Zimbabwe as well, which people forget to talk or think about. For every Singapore, there are scores of African dictators who killed thousands of people during their rule and destroyed their respective economies. Hence, while autocracies may lead to super-fast growth, they can also lead to long-term economic stagnation and huge political turmoil.

Also, evidence is clear that steady growth happens best in democracies.

As Sharma writes:

“Together, Sweden, France, Belgium, and Norway have posted only one year of growth faster than 7 percent since 1950. But over that time, these four democracies have all seen their average incomes increase five- to sixfold, to a minimum of more than $30,000, in part because they rarely suffered full years of negative growth.”

Further, if you look at the list of countries with a per-capita income of more than $10,000, all of them are democracies. China, as and when it reaches there, will be the first autocracy, which will make it an exception. An exception, which proves the rule. That is, in the  medium to long-term, democracy and economic growth go hand in hand.

At least, that’s what history and data tell us. But don’t let that come in your way of believing the good story of authoritarian regimes run by benevolent autocrats leading to fast economic growth all the time.

It must be true if you believe in it. I mean, Mr Kant surely does. And so do a whole host of middle class Indian men and women.

Rising Corporate Profits Aren’t Good News for Indian Economy

Salaam seth salaam seth kuch apne layak kaam seth,
Aap to khaayen murgh musallam apni to bus rice plate. 
­– Shaily Shailendra, Annu Mallik (now known as Anu Malik), Annu Mallik and Kawal Sharma, in Jeete Hain Shaan Se.

Corporates have reported bumper profits for the period July to September 2020.

This led a friend, who is generally unhappy with most of my writing given that he dabbles in the stock market which just keeps going up, to quip: “How are the corporates making profits if the economy is not doing well?”

This is an interesting question and needs to be addressed. Having said that, the right question to ask is, how are the corporates making profits with the economy not doing well.

Let’s look at it pointwise.

1) A newsreport published in the Business Standard on November 17, 2020, considers the results of 2,672 listed companies, including their listed subsidiaries, for the period July to September 2020. During this period, the net profit of these companies touched a record Rs 1.52 lakh crore, up by 2.5 times in comparison to the same period in 2019.

2) There is a base effect at play here, with last year’s low base making profits this year look very high. During the period July to September 2019, telecom companies faced massive losses. Their losses have come down during the period July to September 2020. Take the case of Vodafone Idea. The company reported a loss of Rs 50,000 crore last year. The loss during July to September 2020 was much lower at Rs 6,451 crore. Similarly for Airtel, the loss came down from around Rs 23,000 crore last year to Rs 776 crore this year.

These losses pulled down overall corporate profits by close to Rs 73,000 crore, during the period July to September 2019. This time around the losses of these two telecom companies were limited Rs 7,227 crore. Hence, these two companies had a disproportionate negative impact on the overall corporate profits last year. The same hasn’t happened this year and in the process has ended up pushing up the overall corporate profit growth this year.

3) Interestingly, companies have managed to report an increase in net profit despite shrinking sales. The Business Standard report referred to earlier suggests that the net sales of these companies shrunk by 5.2% during July to September 2020. This is the fifth consecutive quarter when the sales of listed companies have shrunk. Depsite shrinking sales, profits have gone up.

4) Economist Mahesh Vyas of the Centre for Monitoring Indian Economy, looked at a sample of 1,675 listed manufacturing companies. He found that their combined net profit stood at Rs 72,600 crore, despite their net sales shirking by Rs 96,100 crore.

5) The question is how have companies managed to increase their net profit, despite doing less business than last year, leading to lower revenues. There are sectoral reasons at play. Thanks to the ongoing case in the Supreme Court, the banks did not have to report bad loans as bad loans. This has led to banks setting aside lesser money to meet the losses that may arise from these bad loans. This has clearly pushed up the profit number in the banking sector.

More specifically, the companies managed to cut more costs than they saw a fall in sales and thus pushed up their net profit.  Take the case of the manufacturing sector that Vyas has considered in his analysis, while their sales shrunk by Rs 91,600 crore, their operating expenses came down by Rs 1,33,100 crore or around Rs 1.33 lakh crore. The companies managed to drive down the cost of raw materials thanks to a favourable shift in trade terms and drawing down their inventories.

6) Other than driving down raw material cost, companies have also managed to cut down on employee costs. Economist Sajjid Chinoy of JP Morgan in a column in The Indian Express writes that net profit of companies went up despite shrinking revenues because “firms aggressively cut costs, including employee compensation.” “Indeed, a sample of about 600 listed firms reveals employee costs (as a per cent of EBITDA) was the lowest in 10 quarters,” he writes further.

A survey carried out by the Mint newspaper and Bain found that half of the companies had reduced employee costs by either firing employees or cutting their salaries.

The above points explain why corporate profits have gone up disproportionately despite shrinking revenues. Let’s try and understand pointwise why this is not good for the Indian economy.

1) A major reason for raw material costs coming down is a favourable shift in trade terms. What does this mean? No company produces everything on its own. It uses inputs which are produced by other firms. In difficult times, companies are able to drive down the cost at which they purchase things from their suppliers, that is, inputs. The suppliers are other companies, which have  to drive down their costs as well, and this is how things are pushed down the hierarchy.

How do suppliers and suppliers to suppliers drive down their costs? They also try to shift the trade terms in their favour and at the same time cut employee costs, like companies have.

2) This leads to what economists call the fallacy of composition or what is good for one may not be good for many. A simple example of this is someone going to watch a cricket match. He stands up to get a better view of the game being played and he gets a better view. But then the person behind him also needs to stand up to get a better view. And so the story continues. In the end, everyone is standing and watching the match, instead of siting comfortably and enjoying it. To repeat, what is good for one, may not be good for many.

How does this apply in the current case? When companies cut down on input costs, they are obviously paying a lower amount of money to their suppliers or not buying new raw material or as much raw material as they did in the past, to increase their inventory.

By cutting down on employee costs, they are either paying a lower amount of money to their employees or simply firing them. The suppliers in turn have to cut their costs in order to continue to be profitable or lose a lower amount of money. So, the cycle continues and in the end leads to lower incomes for everyone involved.

3) This leads to what the economist John Maynard Keynes called the paradox of thrift. With incomes coming down, people spend a lower amount of money than they did before. It is worth remembering here that ultimately one man’s spending is another man’s income, leading to a further cut in spending. Even those who haven’t seen a drop in their income or been fired, cut down on their spending. They are trying to save more, given the risk of them getting fired and not being able to find another job. This is the psychology of a recession and it is totally in place right now.

4) One of the ways of measuring the size of any economy or its gross domestic product (GDP), is to add the incomes of its different constituents. This means adding up rents, wages, interest and profits. While, profits of companies have been going up, individual wages have been going down, leading to lower spending and hence, lower private consumption. This explains why despite corporate profits of listed companies increasing at a fast pace, the GDP during the period July to September 2020, contracted by 7.54%.

5) An August 2019 report in the Business Standard said that the combined net profit of companies that make up for the BSE 500 index was at 2.31% of the GDP. Other studies suggest that this figure has constantly been coming down over the years. Despite the fact that listed companies form a small part of the Indian economy, their influence on the initial GDP figure is very high.

A large part of the Indian economy is informal. The measures representing this part of the economy cannot be generated quickly. In this scenario, the statisticians assume the informal economy to be a certain size of the formal one. Corporate profits are an important input into measuring the size of the formal economy. This is something that needs to be kept in mind while looking at the economic contraction of 7.54%. .

To conclude, while corporate profits going up is good news for the companies, there are many ifs and buts, that need to be taken into account as well, and on the whole the way these profits are being generated, it’s not good news for the Indian economy.

Also, over a longer period, the only way to grow profits is by growing sales. This will start hitting the Indian corporates sooner rather than later.

Why RBI’s Monetary Policy Has Been a Bigger Flop Than Bombay Velvet

Mere paas kothi hai na car sajni,
Kadka hai tera dildar sajni.
— Rajkavi Inderjeet Singh Tulsi, Ravindra Jain, Kishore Kumar, Asha Bhonsle and Ashok Roy, in Chor Machaye Shor.

Okay, I didn’t have to wait for the Reserve Bank of India’s monetary policy declared today, to write this piece. I could have written this piece yesterday or even a month back. But then the news cycle ultimately determines the number of people who end up reading what I write, and one can’t possibly ignore that.

A few hours back, the Monetary Policy Statement was published by the RBI, after the monetary policy committee (MPC) met on 2nd, 3rd and 4th December. The MPC of the Reserve Bank of India (RBI) has the responsibility to set the repo rate, among other things. The repo rate is the interest rate at which the RBI lends to banks, and which to some extent determines the interest rates set by commercial banks for the economy as a whole.

The MPC has been driving down the repo rate since January 2019, when the rate was at 6.5%. The rate had been cut to 5.15% by February 2020, around the time the covid pandemic struck.

By May 2020, the MPC had cut the repo rate further by 115 basis points to an all-time low of 4%. One basis point is one hundredth of a percentage. The idea behind the cut was two-fold.

In the aftermath of the covid pandemic as the economic activity crashed, the tax collections of the government crashed as well, leading to a situation where the government’s borrowing requirement jumped from Rs 7.8 lakh crore to Rs 12 lakh crore.

The massive repo rate cut would help the government to borrow more at lower interest rates. The yield or the return on a ten-year government of India bond in early February was at 6.64%. Since then it has fallen to around 5.89% as of December 4. The government of India borrows by selling bonds. The money that it raises helps finance its fiscal deficit or the difference between what it earns and what it spends.

The second idea was to encourage people to borrow and spend more and businesses to borrow and expand, at lower interest rates. Take a look at the following chart. It plots the average interest at which banks have given out fresh loans over the years.

Source: Reserve Bank of India.

The data on average interest at which banks have given out fresh loans is available for a period of a little over six years, starting from September 2014 and up to October 2020. It can be seen from the above chart that the interest rates in the recent months, have been the lowest in many years. But has that led to an increase in lending by banks, that’s the question that needs to be answered?

As of October 2020, the total outstanding non-food credit of banks by economic activity, had gone up by 5.6% in comparison to October 2019. Banks give loans to the Food Corporation of India and other state procurement agencies to buy rice, wheat and a few other agricultural products directly from farmers. Once we subtract these loans out from the overall loans given by banks that leaves us with non-food credit by economic activity.

Also, it needs to be mentioned here that this is how banking data is conventionally reported, in terms of the total outstanding loans of banks.

When you compare this with how other economic data is reported, it’s different. Let’s take the example of passenger cars.

When passenger car sales are reported, what is reported is the number of cars sold during a particular month and not the total number of cars running in India at that point of time. In case of banks, precisely the opposite thing happens.

What is conventionally reported is the total outstanding loans at any point of time and not the loans given incrementally during a particular period. So, the total outstanding non-food credit of Indian banks by economic activity, as of October end 2020 stood at Rs 92.13 lakh crore. This increased by 5.6% over October 2019.

The way this data is reported does not tell us the gravity of the situation that the banks are in. That comes out when we look at just incremental loans from one year back. The way to calculate this is to take total outstanding loans as of October 2020 and subtract that from outstanding loans of banks as of October 2019. The difference is incremental loans for October 2020. Similarly, the calculation can be done for other months as well.

Let’s take a look incremental loans data over the last three years.

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As can be seen the above chart, the incremental loans every month in comparison to the same month last year, have been falling since late 2018, just a little before the RBI started cutting the repo rate. In October 2020, they stood at Rs 4.83 lakh crore, a three-year low.

What does this mean? It means that as the MPC of the RBI has gone about cutting the repo rate, the incremental loans given by banks have gone down as well. This is the exact opposite of what economists and central banks expect, that as interest rates fall, borrowing should go up.

And this has been happening from a time before the covid-pandemic struck. Covid has only accentuated this phenomenon. This also leads to the point I make often that for people to borrow more, just lower interest rates are not enough.

The main point that encourages people and businesses to borrow more is the confidence in their economic future. While the government will try and blame India’s currently economic problems totally on covid, it is worth mentioning here that India’s economic growth has seen a downward trend since March 2018. The economic growth for the period January to March 2018 had stood at 8.2% and has been falling since, leading to a lesser confidence in the economic future, both among individuals and corporates.

In fact, if we compare the situation between March 27, 2020, when covid first started spreading across India, and November 6, 2020, the total outstanding non-food credit of banks has grown by just Rs 2,221 crore (yes, you read that right, and this is not a calculation error).

During the same period, the total deposits of banks have grown by Rs 8.13 lakh crore or 6%. The incremental credit deposit ratio between March 27 and November 6, is just 0.27%. We can actually assume it be zero, given that it is so close to zero. Al these deposits have primarily been invested in government bonds.

Basically, on the whole, the banks have been unable to lend any of the deposits they have got from the beginning of this financial year. Only one part of banking is in operation. Banks are borrowing, they are not lending.

What does this tell us? It tells us that banking activity in the country has collapsed post covid, despite the RBI cutting the repo rate to an all-time low-level of 4%, where it’s 361 basis points lower than the latest rate of retail inflation of 7.61%. Other than cutting the repo rate, the RBI has also printed a lot of money and pumped it into the financial system, to drive down interest rates.

But despite that people and businesses are not borrowing. RBI’s monetary policy has been an even bigger flop than Anurag Kashyap’s Bombay Velvet, Raj Kapoor’s Mera Naam Joker and Satish Kaushik’s Roop ki Rani Choron ka Raja. (I name three different films so that readers of different generations all get the point I am trying to make here).

In the monetary policy statement released a few hours back, there is very little mention of this, other than:

“A noteworthy development is that non-food credit growth accelerated and moved into positive territory for the first time in November 2020 on a financial year basis .”

The governor’s statement has some general gyan like this:

“In response to the COVID-19 pandemic, the Reserve Bank has focused on resolution of stress among borrowers, and facilitating credit flow to the economy, while ensuring financial stability.”

No explanations have been offered on why the monetary policy has flopped. The current dispensation at India’s central bank is getting used to behaving like the current government.

It is important to understand here why monetary policy has been such a colossal flop this year. The answer lies in what the British economist John Maynard Keynes called the paradox of thrift. When a single individual saves more, it makes sense, as he prepares himself to face an emergency where he might need that money.

But when the society as a whole saves more, as it currently is, that causes a lot of damage because one’s man spending is another man’s income. As we have seen bank deposits during this financial year have gone up Rs 8.13 lakh crore or 6%. On the whole, people are cutting down on their spending and saving more for a rainy day.

The psychology of a recession at play and not just among those people who have been fired from their jobs or seen a fall in their income. It is obvious that such people are cutting down on their spending. But even those who haven’t faced any economic trouble are doing so.

They are doing so in the fear of seeing a fall in their income or losing their job and not being able to find a new one. When the individuals are cutting down on their spending, it doesn’t make much sense for businesses to borrow and expand. In fact, the overall bank lending to the industry sector has contracted by Rs 4,624 crore between October 2019 and October 2020.

Typically, in a situation like this, when the private sector is not in a position to spend, the government of the day steps in. The trouble is that the current government is not in a position to do so as tax revenues have collapsed this year. There other fears at play here as well.

In the midst of all this, Dinesh Khara, the chairman of the State Bank of India told the Business Standard, that bank lending rates “have actually bottomed”. Given that banks have barely lent anything this year, it makes me sincerely wonder what Mr Khara has been smoking. Clearly, it makes sense to avoid that.

To conclude, monetary policy should not get the kind of attention it gets in the business media, simply because, it is dead, and it has been dying for a while. The trouble is, there are one too many banking correspondents and even more central bank watchers, including me, who need to make a living.

And very few among us, are likely to ask the most basic question—why monetary policy is not working.

Le jayenge le jayenge dilwale dulhaniya le jayenge
— Rajkavi Inderjeet Singh Tulsi, Ravindra Jain, Kishore Kumar, Asha Bhonsle and Ashok Roy, in Chor Machaye Shor.