मन के अंदर की मन की बात

कल से शिक्षित बेरोज़गारी का दसवां साल शुरू होने वाला है

जब ये सब शुरू हुआ था तब नहीं सोचा था कि नौकरी से ज़्यादा वर्ष शिक्षित बेरोगज़ारी में गुज़रेंगे. शायद मिडिल क्लास होने कि वजह से एक छोटी सी नौकरी की तलबगारी बनी हुई थी.

पर नौ साल वर्क फ्रॉम होम करने के बाद जो भी थोड़ी बहुत फीलिंग थी नौकरी की तरफ, वो पूरी तरह से ख़तम हो चुकी है. या फिर ये कहना चाहिए कि हम नौकरी करने के लायक रह ही नहीं गए है. प्रबंधन का प्रबंधन करना हमारे बस की बात नहीं है.

दुनिया भर के मैनेजमेंट गुरु entrepreneurship पर मोटी मोटी किताबें लिखते हैं, पर कोई ये नहीं बताता कि एक अच्छी नौकरी में, बॉस के ईगो और सहकर्मियों की असुरक्षाओं को सँभालते हुए, और इन्फ्लेशन से कम इन्क्रीमेंट पर ज़्यादा ध्यान नहीं देते हुए, ईमानदार कैसे बना रहा जाए?

खैर, हमें कौन सा हर महीने EMI देना है कि इन चीज़ों की चिंता की जाए, न ही बच्चों को पढ़वाना है या उनकी शादी के लिए पैसे जमा करने हैं. आपको ये सब करना है, इसलिए, बने रहिये. पिच पर नज़र बनाये रखिये और विकेट बचाये रखिये. कोई भी कभी भी आपकी तरफ गूगली फेंक सकता है, इसलिए उनकी कलाइयों पर ध्यान बनाये रखिये.

समय बहुत कठिन चल रहा है. पहले तो न्यूज़ मीडिया की हालत ख़राब है और ऐसी ख़राब हालत में गेम पूरी तरह से बदल चुका है. हम जैसे अदना लोगों को भी अब नेटफ्लिक्स इत्यादि के साथ compete करना पड़ रहा है.

compete, शायद सही शब्द नहीं है यहाँ पर, पर कहने का मतलब ये है कि लोगों के पास अब भी उतना ही समय है जितना पहले था, पर अब करने को ज़्यादा चीज़ें हैं और वो भी फ़ोन पर. और फ़ोन पर अगर आप गेम ऑफ़ थ्रोन्स से लेकर मिर्ज़ापुर देख सकते हैं, या फिर paaarti हो रही है वाला मीम बना सकते हैं, फिर आप हमारे लिखे को पढ़ने की मगज़मारी क्यों करेंगे. शायद हम भी नहीं करते.

सच बोलिये तो हमने भी न्यूज़ मीडिया को पढ़ना तो लगभग बंद ही कर दिया है. पर हमारी वजहें कुछ अलग हैं.

माओत्से तुंग के ‘परमानेंट रेवोल्यूशन’ का भारतीय रूप हर सुबह उठकर नहीं देखा जाता. जिन चीज़ों पर बातें होनी चाहिए उन पर बात हो ही नहीं रही, और जिन चीज़ों का कोई मतलब नहीं है, उन पर फलसफे जड़े जा रहे हैं.

खैर, अच्छी बात ये है कि हमने बच्चे नहीं पैदा किये हैं और जिन्होंने किये हैं वो तो व्हॉट्सऐप पर मस्त हैं. इसलिए सब चिल कर रहे हैं, बुत बनकर बैठे हैं. जो बात दिख ही नहीं रही, वो समझ में कैसे आएगी!

प्लान बी ये है कि अगर शिक्षित बेरोज़गारी नहीं चलती रही तो फिर क्राइम फिक्शन लिखेंगे और इन किताबों में उन सभी लोगों का, जिनका असल ज़िन्दगी में गला दबाने का मन किया था, उनको एक-एक करके मारेंगे.

कम से कम मन की दुनिया में मन की बात करने की आज़ादी अब भी बनी हुई है.

और शायद इस मन के अंदर की मन की बात में, आप भी हों. तैयार रहिएगा. बुत बनकर मत बैठे रहिएगा.

On Homes and Home Loans

Yesterday evening I had gone to meet a cousin who lives in the Western suburbs of Mumbai. All along the way, there were billboards of Kotak Mahindra Bank advertising its home loans, which are available at an interest rate of 6.65%.

While the interest rate of 6.65% comes with terms and conditions, such low interest rates have rarely been seen before. It is possible to get a home loan these days at an interest rate of 7%.

A few things have happened because of these low rates. There have been scores of stories in the media citing surveys where everyone from women to HNIs to NRIs to millennials seem to want to buy a house and they want to do it right here and right now. 

Of course, these surveys have been carried out by real estate consultants, whose very survival depends on the real estate sector doing well. Incentives as they say.

Low interest rates on home loans also have led to stories in the media suggesting that this is best time to buy a house. The other thing that has happened is that analysts have been recommending stocks of home finance companies (HFCs).

The logic being that at lower interest rates people will take on more home loans. This will help the loan book of HFCs grow, making them good investment bets. How easy all this sounds? But is it?

All this stems from the flawed assumption that people borrow more at lower interest rates and live happily ever after. Let’s see if that is true or not.

Take a look at the following graph. It plots the increase in home loans outstanding during the period April to January, over the years.

 Source: Author calculations on data from Centre for Monitoring Indian Economy.

What does the above graph tell us? It tells us that despite very low home loan interest rates, the increase in home loans given by banks between April 2020 to January 2021, stood at Rs 78,577 crore. This was around half of the increase of Rs 1,56,362 crore between April 2019 to January 2020.

Even between April 2018 and January 2019, the increase stood at Rs 1,46,227 crore. Clearly, people borrowed much more when interest rates were higher. Hence, the logic that people borrow more when interest rates are lower, basically goes for a toss.

In fact, the increase between April 2020 to January 2021, was the second lowest in six years in absolute terms. The lowest increase of Rs 74,837 crore was between April 2016 to January 2017. This period included demonetisation when banks had more or less stopped doing everything else and concentrated on taking back the demonetised notes from the public.

If we look at the period between April 2016 to October 2016, before demonetisation happened, the increase in home loans had stood at Rs 64,501 crore. Clearly the disbursal of home loans slowed down in the post demonetisation months.

There is another point that needs to be made here. Other than banks, HFCs or home finance companies, also give out home loans. Typically, banks give out two-thirds of the home loans and HFCs, the remaining third. Nevertheless, the last couple of years haven’t been good for a few HFCs. This has meant that some of the business of home loans has moved from HFCs to banks.

Once we take these factors into account then we can conclude that the increase in home loans during this financial year, has been the worst in six years. And this despite the extremely low interest rates. In percentage terms, the increase in outstanding home loans during this financial year has stood at 5.97%, the lowest in six years, and the only time the increase has been less than 10%. 

Why is that the case? For economists and analysts, the interest rate is the most important parameter that people look at while taking a home loan, nevertheless, a little bit of common sense tells us that this isn’t the case.

Let’s try and understand this through an example. As per HDFC, India’s largest HFC, their average home loan size is Rs 28.5 lakh. Their average loan to value ratio at the time of giving the loan is 70%. This basically means that HDFC on an average gives up to 70% of the price of the home as a home loan.

This basically means that the average price of a home in the books of HDFC against which they give a home loan, stands at Rs 40.7 lakh (Rs 28.5 lakh divided by 70%). Let’s round this to Rs 41 lakh, for the sake of convenience.

What does this mean? It means that in order to buy a home, other than taking on a loan of the buyer first needs to make sure that he has savings of around Rs 12.5 lakh (Rs 41 lakh minus Rs 28.5 lakh) to make the downpayment on the home loan. Even if the money is available, he or she needs to make sure that they are in a position to spend that money.

This is not where it ends. In many parts of the country a portion of the real estate transaction is still carried out in black. Money needs to be available for that. Further, a stamp duty needs to be paid to the state government. Then there is the cost of moving into a new house (everything from transport to perhaps new furniture).

Once we factor these things into account, we can conclude that the home loan forms around 50-60% of the overall cost of buying a house. Further, in a time like present, any individual thinking of buying a house will have to weigh the decision against the possibility of losing their job or facing a drop in income in their line of work.

Now let’s consider the average home loan of Rs 28.5 lakh. At 7% interest and a tenure of 20 years, the EMI on this amounts to Rs 22,096. At 9%, the EMI would have worked out to Rs 25,642. Hence, the EMI is Rs 3,546 lower.

So, yes, the EMI is lower. But what will the buyer first look at? The lower EMI or the ability to be able to pay the lower EMI and be able to continue paying it in the days to come. Of course, the buyer will look at his ability to pay the EMI and be able to continue paying it. Also, it needs to be remembered that the interest rate on the home loan is a floating one, and can rise in the years to come.

Hence, this decision will be based on the confidence that the buyer has in his or her own economic future. This is not something that can be measured at an aggregate system level and varies from buyer to buyer. The point being that everything that is important cannot necessarily be measured in numerical terms.

Having said that, the confidence in the economic future will be currently low, with many individuals losing their jobs or seeing their friends, relatives and acquaintances lose jobs. Hence, other than losing a job, there is also the fear of losing the job. There has also been a drop in their income or in some cases small businesses have been shutdown. 

Also, whether it is the best time to buy a house or not, like most things in personal finance, it depends on your finances and more importantly your mental makeup of what you want from life. If you want to settle in life and make your parents and relatives happy, and have the money to do so, then now is as good a time as any to buy a home.

Please keep this in mind at every point of time in life when some expert tells you that this is the best time to do this or the best time to do that.

So, right now if you think you have enough money and enough confidence to keep paying the EMI, and want a home to live in, then please go ahead and buy one. Also, make sure that you have enough savings to pay the EMI for at least six months to a year, even without your main source of income.

To conclude, buying a home is not just about low interest rates. There are several other factors, which people who are in the business of selling real estate, seem to conveniently forget about.

Then there are surveys in which a high proportion of people end up saying they want to buy a home to live in. Of course, they do. But just wanting to do something doesn’t add to demand. I mean, I want to buy a house in central Mumbai, but I also know that ain’t going to happen. My finances don’t allow it.

Vehicle Scrapping Policy is Half-Baked and More About Feeding a Constant Narrative

Late last week the central government announced the vehicle scrapping policy (VSP). As the Minister for Road Transport and Highways, Nitin Gadkari, put it in the Parliament, the aim of the VSP is to create “an eco-system for phasing out of unfit and polluting vehicles”.

So how will this be put into action? Using the public private partnership (PPP) model involving the state governments, private sector and the automobile companies, the central government plans to promote the setting up of automated fitness centres (AFCs). 

These AFCs will issue vehicle fitness certificates to private vehicles and commercial vehicles based on emission tests, braking, safety equipment among many other tests which are as per the Central Motor Vehicle Rules, 1989.”

A commercial vehicle which is 15 years old and fails the vehicle fitness test will be declared an end of life vehicle and scrapped. Similarly, a private vehicle which is 20 years old and fails the vehicle fitness test will be declared to be an end of life vehicle and scrapped. Further, if owners don’t renew the registration certificate, their vehicle may be declared as an end of life vehicle and scrapped.

In order to disincentivise commercial vehicle owners who own vehicles which are 15 years old, from continuing to use them, even if they clear the vehicle fitness test, the fee for the fitness certificate and the fitness test will be set on the higher side. For private vehicle owners with vehicles which are 15 years old, the re-registration fee will be set on the higher side.

The point being that if you have a private vehicle which is 20 years old or perhaps even older, the government wants you to stop using the vehicle and buy a new one, irrespective of what state it is in. For commercial vehicles, the same logic applies for vehicles which are at least 15 years old.

And the expectation is this will lead to lower pollution, newer cars, safer pedestrians, more spending, more investment and more jobs. QED.

The minister expects additional investments of Rs 10,000 crore and 35,000 job opportunities to be created because of this.

It will also lead to banks and non-banking finance companies (NBFCs) giving out more loans. Of course, given that the auto industry and the auto-ancillary industry use a lot of contract workers, one could possibly argue that this could lead to more work opportunities for them as well. 

The question is how will things really play out? Let’s try and understand that in some detail.

Economics is basically the study of incentives and second order effects. The trouble is that politicians and policy makers don’t keep this in mind while designing policy, particularly the second order effects of what they are proposing.

Let’s try and understand this pointwise.

1) There are a total of 1.02 crore vehicles, both commercial and private, which fall under the defined category of older vehicles. Even if a small proportion of these vehicles are scrapped they will generate a huge amount of non-biodegradable waste.

What plans do we have to handle all this waste coming our way? As the press release announcing the policy pointed out: “Efforts are also being made to set up Integrated Scrapping Facilities across India.” Even while taking into account that this policy will be implemented over the next few years, this sounds too much like work in progress than definitive economic policy. One needs a lot more clarity on this front. 

2) As a way to get the scheme going, the government first plans to scrap its older vehicles. As the press release announcing the plan puts it: “It is being proposed that all vehicles of the Central Government, State Government, Municipal Corporation, Panchayats, State Transport Undertakings, Public Sector Undertakings and autonomous bodies with the Union and State Governments may be de-registered and scrapped after 15 years from the date of registration.” This is supposed to be implemented from April 1, 2022 onwards, or little over a year from now.

Why have this blanket policy at a time when governments, in particular state governments, are already short of money? Why not look at the fitness of vehicles and then decide? If at all, vehicles of the central government and the public sector enterprises tend to be decently maintained.

3) Also, the assumption here is that only older vehicles cause pollution. The manufacturing of newer vehicles needs electricity. Most electricity in India is generated by burning coal, which causes pollution. Steel goes into the making of vehicles. The process of making of steel, releases carbon dioxide into the atmosphere. That causes pollution as well. The same is true of plastic and pretty much everything else which goes into the making of vehicles. Hence, every new vehicle that is produced has a carbon footprint. 

Of course, all this pollution doesn’t show up in cities where most private vehicles are driven and tends to be well distributed across the country. But shouldn’t a policy that has lower pollution as one of its key points, take this basic factor into account as well? Further, we need to consider the fact that many older private vehicles are not constantly in use. 

4) As I have explained earlier, the government wants private and commercial vehicle owners to buy new cars. Of course, as and when this happens, the automobile companies are supposed to benefit. This explains why companies have come out in favour of this policy (or even otherwise, when do Indian businessmen ever disagree with the government). But this doesn’t take a very basic factor into account.

Whatever we might like to say about the new India and such things, we are a poor country at the end of the day. And covid has only made things even more difficult by pushing many more people into poverty, as health bills have mounted, incomes have crashed and small businesses have gone bust.

Hence, assuming that people will go out and buy new vehicles if the older vehicles are scrapped or because re-registration is made more expensive, is just looking at first order effects of policy, in the same way that economists tend to believe that lower interest rates always push up consumption. 

Private vehicle owners who are not heavy users of their vehicles, might just prefer to use Uber or Ola or even the metro infrastructure coming up across India’s major cities. (This reminds me of a time when the government kept telling us that slower automobile sales were primarily because of Uber and Ola).

Further, owners might financially not be in a position to buy a new vehicle. Already, the trucking industry has spoken up against the idea.

Also, even if owners buy a new vehicle, they might cut consumption on something else given that there is only so much money going around. Hence, net-net, the impact on the overall economy may not be much.

The trouble is that the costs of second order effects are not so obvious and straightforward, whereas the supposed benefits are easy to convey in a simplistic way. And politicians love stuff which they can convey in a simplistic way.

5) Kitna deti hai (how much does it give?), goes a Maruti advertisement, telling us that Indians are price conscious value for money consumers. And there is nothing wrong with this, given that an automobile is probably the second most expensive thing we buy during our lifetime. So, while the idea that old polluting vehicles need to be discarded is a noble one, what is in it for the consumer?

This is what the government is planning. a) The owner will be paid 4-6% of the showroom price of a new vehicle, when his old vehicle is scrapped. b) The state governments may be advised to offer a road- tax rebate of up to 25% for personal vehicles and up to 15% for commercial vehicles. c) The vehicle manufacturers are also advised to provide a discount of 5% on purchase of new vehicle against the scrapping certificate. d) The road transport minister has requested the finance minister and states to give a concession in goods and services tax (GST) on purchase of new vehicles.

There are too many ifs and buts in the above paragraph. As usual, the government seems to be in a hurry to announce and implement a policy. As I have said in the past a massive cut in GST on automobiles will encourage buying. What the government will lose out on per unit of sales, it is more than likely to make up for through volumes. 

One understands that the road transport minister cannot ensure all of this on his own, which is why it is important that the government spends some time in discussing and figuring out how to design and implement policy. Also, it is important to carry out small experiments in union territories, before announcing policies which need to be implemented across the length and the breadth of the country.

As Vijay Kelkar and Ajay Shah write In Service of the Republic

“The safe strategy in public policy is to incrementally evolve—making small moves, obtaining feedback from the empirical evidence, and refining policy work in response to evidence.”

But the trouble is that small moves involve a lot of time, effort and thinking, which is very difficult for a government which believes in constant action and constantly creating new narratives to keep people busy and happy. The narrative also feeds into the idea that the government is trying to do new things. 

6) Take a look at what happened to two-wheeler sales in 2019-20 (This is before covid struck). Sales fell by nearly 18% year on year to 17.42 million units, as the price went up due to various reasons. Hence, India is a very price sensitive market and the point is that there has to be a huge benefit involved in buying a new vehicle in a tough economic environment.

While the notion of pollution control is a noble one, it is not something which is going to get people to go out and buy new vehicles, unless it is very clear what is in it for them. Ultimately, if you want people at large to behave in a certain way, the right incentive should be on offer, something this half-baked policy, like the policy to encourage electric vehicles before it, lacks.

To conclude, one does wonder, what were they doing all these years, given that the policy has been on the anvil for a while now. 

Women Are Bearing the Brunt of India’s Unemployment Problem

This piece is an extension of a piece on unemployment I wrote sometime back. Nevertheless, you don’t have to read that piece in order to make sense of this.

Honestly, this is probably the most disturbing data driven piece that I have ever written, despite the fact that I started writing on the issue of unemployment more than half a decade back, when it wasn’t very fashionable to do so.

The brunt of India’s unemployment problem is being borne by women. This is not to say that the men are having an easy time. They aren’t, given that many more men enter the labour force than women.

Nevertheless, the proportion of women who are employed and get paid was low to start with, and it has become even lower over the years. This, at a time, when more and more women are going to school and college.

As the All India Survey of Higher Education for 2018-19 points out: “Total enrolment in higher education has been estimated to be 3.74 crore with 1.92 crore male and 1.82 crore female. Females constitute 48.6% of the total enrolment.” But all this education isn’t helping them find paid employment.

Let’s start with the unemployment rate for men and women. The following chart plots this data since January 2016.

Source: Centre for Monitoring Indian Economy.

The above chart tells us several interesting things.

1) The unemployment rate for women is significantly higher than that of men. In February 2021, the unemployment for women stood at 12.39% whereas for men it stood at 6.23%.

2) The unemployment rate for women in February 2021 is much lower than it was in January 2016, when Centre for Monitoring Indian Economy (CMIE) published the unemployment data for the first time. Have things improved? Keep reading to know the answer.

3) The peak unemployment rate for women during covid was 29.22% as of April 2020. The rate has fallen since to 12.39%, as of February 2021. Again, have things improved?

In order to answer the questions raised above, we need to understand how unemployment is defined. (For those who have read the earlier piece I wrote on unemployment, the next few paragraphs may seem like a repetition, which they are. I have repeated these paragraphs, simply because it is important for every piece to stand on its own, so that first time readers can also read and understand it easily).

A person is categorised as unemployed “because of a lack of job and where such a person is actively looking for a job”. The word to mark here is actively. Hence, a person can be categorised as unemployed only if he doesn’t have a job and is searching for one.

As the Centre for Monitoring Indian Economy (CMIE) puts it, a person categorised as unemployed, “should be unemployed on the date of the survey, should be actively looking for a job in the 100 hundred days (approximately three months) preceding the date of the survey and should be willing to take up the job if a job is found.”

They further point out: “A person is considered to be actively looking for a job if such a person has contacted potential employers for jobs, contacted employment agencies, placement agencies, appeared for job interviews, responded to job advertisements, online employment sites, made applications, submitted resumes to potential employers or reached out to family members, friends, teachers to look for jobs from them.”

To put it in short, waiting for a job offer to come, is not considered as actively looking for a job.

Let’s move on and plot the next two charts, the labour participation rate for men and women.

Source: Centre for Monitoring Indian Economy.

Source: Centre for Monitoring Indian Economy.

Before we interpret these charts, we first need to define what labour participation rate is. Labour participation rate is the ratio of the labour force to the population greater than 15 years of age. And what is the labour force? As per CMIE, labour force consists of persons who are of 15 years of age or more, and are employed, or are unemployed and are actively looking for a job.

Now we are in a position to interpret the above two charts. Let’s do that pointwise.

1) The labour participation rate for women is miniscule on the whole. In February 2021, it stood at 9.42%. What does this mean? It means that a very small proportion of women over the age of 15, are employed and get paid for it or are unemployed and are actively looking for. a job. And the tragic part is that this rate is falling. It was at 17.7% in May 2016. Since then it nearly halved.

2) The labour participation rate of men is considerably higher. It was 67.82% in February 2021, even though it has been falling. Hence, two in three men over the age of 15, are employed and are getting paid for it, or are unemployed and actively looking for a job. For women, this ratio is less than one in ten. That’s the difference between the two sexes and it’s huge. 

3) Urban women are in a much worse position on this front. The labour participation rate for urban women stood at 6.56% in February 2021. The rate had peaked at 16.58% in August 2016 and has been falling ever since. What does this mean? It means that it is more difficult for a woman to be employed and get paid, if she is in urban India than in comparison to rural India.

Also, the dramatic fall in the rate since August 2016, tells us that once a woman loses a job or a source of income, it is very difficult for her to get it back. And finally, very few women in urban India are stepping out of their homes to go to work and get paid for it. This has only increased post the spread of covid. The labour participation rate for women was 9.92% in January 2020. It’s not at 6.56%.

4) Now comes the worst part. Between January 2016 and February 2021, the number of women greater than 15 years of age has gone up by 5.41 crore to 49.49 crore. Hence, the number of women who have entered the working age population has gone up by 12.26% (5.41 crore expressed as a percentage of 49.49 crore). On the other hand, the female labour force, has shrunk by 2.75 crore to 4.66 crore. In January 2016, it was at 7.41 crore. This is a collapse of 37% (2.75 crore expressed as a percentage of 7.41 crore).

Let me just repeat this again. While the working age population for women over the last five years has gone up by 12.26%, the female labour force has collapsed by 37.11%. This also explains the fall in unemployment rate for women, given that much fewer women are actively looking for a job. Many women who haven’t been able to find jobs, have stopped actively looking and simply dropped out of the labour force.

Economists have struggled to come up with an explanation for this phenomenon. One possible explanation lies in the fact that the number of jobs available haven’t grown at the pace that could accommodate the new individuals, both men and women, entering the workforce. Hence, in a patriarchal society, men in deciding positions, have offered jobs to other men, forcing women who have searched and not found jobs to stop actively looking for a job and drop out of the labour force altogether.

5) Let’s take a look at the overall population. The working age population, between January 2016 and February 2021, has gone up from 93.85 crore to 105.8 crore, this implies an increase of 11.95 crore. Nevertheless, the number of people employed or unemployed and looking for a job, that is the total labour force, has fallen from 44.76 crore to 42.85 crore, or by 1.91 crore.

Sothe working age population has increased by 11.95 crore between May 2016 and February 2021, but the total labour force as such has fallen by 1.91 crore. What does this really mean?

While, the total labour force has shrunk by 1.91 crore, 2.75 crore women have dropped out of it. This basically means that the number of men in the labour force has gone up.

Hence, the brunt of India’s unemployment problem is being borne by women. Women who lose their jobs find it difficult to find a new one and over a period of time simply drop out of the labour force. Many women who enter the labour force and actively look for jobs, are unable to find one and eventually stop searching and drop out of the labour force.

Given that chances of men finding a job are higher, they continue to look for a job and the situation is not as bad as it is for women. Between January 2016 and February 2021, number of men who crossed the age of 15 and entered the working age population, increased by 6.54 crore to 56.30 crore.

During the same time, the number of men entering the labour force (that is either they were employed or were unemployed and actively looking for a job) increased by 83.62 lakh to 38.19 crore. Hence, in this case of men, the labour force at least hasn’t shrunk.

6) Given that more and more women are dropping out of the labour force, it makes it easier for the men who don’t drop out of the labour force to find a job, from the opportunities that come up. (I am using the word easier here and not easy. Kindly appreciate the difference between the two).

7) Urban women are likely to be more educated, but their labour participation rate is very low. Hence, what that means is that they are unable to utilise their education to work and earn money in the process.

8) Now let’s take a look at how things have been post-covid.  In January 2020, before covid had struck, the working age population had  stood at 103.13 crore. By February 2021, this had jumped to 105.8 crore, a jump of 2.67 crore. Meanwhile, the labour force as of January 2020 stood at 44.24 crore. It has since shrunk to 42.85 crore, by 1.39 crore. So, post-covid, the working age population has gone up by 2.67 crore, but the labour force has shrunk by 1.39 crore.

How have the women done on this front? The working age population post covid for women has gone up by 92.23 lakh whereas the labour force has shrunk by 78.03 lakh. Again, more women have dropped out of the labour force than men, given that the labour force has shrunk overall by 1.39 crore. Also, do keep in mind that the fact that a lower number and proportion of women enter the labour force in the first place.

To conclude, the world celebrated the international women’s day a few days back (on March 8). On that day, the corporates and the government institutions talked about the importance of the women who worked for them. The social media influencers talked about women. Many women talked about what it means for them to be a woman.

But almost none of them talked about one of the most important issues at hand, the fact that Indian women are bearing the brunt of India’s unemployment problem.

If you are reading this(man or woman) please share it with your friends and family. The first step towards solving any problem is knowing and acknowledging that it exists.

On Confidence

Around mid-November 2020, I spoke to a bunch of macroeconomics students at IIM Ahmedabad on data in economics. After I had spoken, one of the questions asked was how can we use data to say things with absolute certainty (or something along similar lines).

My simple straightforward answer to the question was that we can’t. Over the years, economists had ended up portraying their subject as a science simply because it has a lot of mathematical equations built into it. But macroeconomics was always more of an art. Hence, we could say things with a reasonable amount of confidence, but never with total confidence.

I don’t think the student was convinced about what I said. And I don’t blame him for it because in the world that he lives in, economists, investors, analysts, politicians and just about everyone speaking to the world at large, is saying things with total confidence.

Let’s take the case of economists. Their economic growth forecasts are made to the precision of a single decimal point.

If we talk about investors, they forecast a stock market index reaching a particular level in a certain amount of time, with total confidence.

Analysts forecast the price of a stock or a commodity reaching a certain level at a certain point of time.

And let’s leave politicians out of this. Untangling their confidence levels will take a book.

The trouble is all this confidence comes in a world that keeps rapidly changing, where if we stick to our ideas all the time, we will largely turn out to be wrong.

As Dan Gardner writes in Future Babble—Why Expert Predictions Fail and Why Believe Them Anyway:

“The simple truth is no one really knows, and no one will know until the future becomes the present. The only thing we can say with confidence is that when that time comes, there will be experts who are sure they know what the future holds and people who pay far too much attention to them.”

And people pay far too much attention to experts who predict/forecast/comment confidently simply because confidence convinces. The audience is looking for a buy in and nothing helps get that more than the confidence of the expert talking.

Also, in these days of the social media, many a time we are simply looking for a confirmation of something that we already believe in. If the expert ends up saying something along those lines, he tends to become our go to man. Our echo chambers are really small.

Let’s take the case of the investor Rakesh Jhunjhunwala, a man known to make confident bold statements when it comes to the Indian economy and the stock market. He recently forecast that India will overtake China in the next 25 years. As he put it: “You may call me a fool… but I can tell you one thing – India will overtake China in the next 25 years.”

The media and the investors as usual lapped it up, without putting that simple question to him: How?

The Indian gross domestic product (GDP) in 2019 was at $2.94 trillion. And that of China was at $11.54 trillion (World Bank data, 2010 constant US dollars). What this means is that if Chinese GDP stagnates at its current level for the next 25 years, India still needs to grow at 5.62% every year for the next 25 years to get where China currently is.

So, the chances of something like this happening are minimal, given the current state of things. But Mr Jhunjhunwala might know something that ordinary mortals like you and I, probably don’t.

The funny thing is that the Big Bull, as the media likes to call him, has made similar such forecasts in the past, which have gone horribly wrong. In October 2007, he had forecast that the Sensex will touch 50,000 points in the next six to seven years.

And he is not the only one making such forecasts. In June 2014, the domestic brokerage Karvy had forecast that the Sensex will touch 1,00,000 points by December 2020.

People making a living out of the stock market (or any other market for that matter) have an incentive in saying that future will be better than the present is. Many analysts make a living by simply doing this on the business news TV channels, on a regular basis.

The media looking for bold headlines to run, laps it up. And the investors who are more like sheep ready to be slaughtered, follow the sheep in front of them.

In fact, the trick is to make bold bigger forecasts and not small ones. I mean, if you currently forecast that Sensex is going to touch 55,000 points this year, no one is going to pay interest. But if you say Sensex is going to cross 1,00,000 points by 2023 or 2024, everyone is going to sit up and take interest.

An excellent example of this is Jhunjhunwala’s 2014 forecast on the stock market index Nifty touching 1,25,000 points by 2030.

Of course, if he turns out to be right, everyone will be dazzled by the forecast he had made. If he turns out to be wrong, no one will remember. Did you remember that Karvy had forecast the Sensex touching 1,00,000 points by December 2020? That’s how the game is played.

Big investors are trying to drive up stock prices, so that their investment portfolios can also gain in the process, which is why they publicly need to be seen as being confident.

A similar game is now played on the social media where traders claim to have generated a humongous amount of return in a short period of time. Of course, there is no way to verify this, except believing him or her.

This is accompanied by other confident predictions of how the future is going to be. The idea is to sell some training programme that they are offering. And no one is going to buy a training programme from a trader who doesn’t sound confident.

For the economists, the game is a little different. They tend to treat their pet theories as gospel. So, an economist who believes in free markets will keep parroting the free market line on everything.

As Scott Galloway writes in his excellent book Post Corona—From Crisis to Opportunity:

“The libertarian argument… is that…regulation and redistribution is inefficient, that left to its own devices the market will regulate itself. If people value clean rivers, the argument goes, they won’t buy cars from companies that pollute. But history and human nature shows that this does not work.”

An excellent example of this is the river Ganga in India, which people keep polluting despite the fact that at the same time they look it as a holy river.

Galloway offers a few more examples. “Nobody wants to see children working eighteen hours a day in a clothing factory, but at the H&M outlet, the $10 T-shirt is an unmissable bargain… Nobody wants to die in a hotel fire, but after a long day of meetings, we aren’t going to inspect the sprinkler system before checking in.” The point being that some sort of regulation is necessary.

There is economic theory and then there is how things play out in real life. As Adam Grant writes in Think Again—The Power of Knowing What You Don’t Know: “In theory confidence and competence go hand in hand. In practice, they often diverge.”

Other than continuing to believe in their pet theories, there is one more reason for economists to portray confidence. Over the years, they have sold their subject as a science, if not to others, at least to themselves in their heads. I mean the first step before convincing anyone else is to convince oneself first.

Hence, the economic growth figure is forecast to the precision of one decimal point. I have always wondered about how economic growth, which is something very complex and is impacted by so many factors, can be forecast in such a precise way.

Now, this is not to say that the forecasting economic growth is not important. It is very important, simply because without that governments and corporations won’t be able to plan for the future.

Without knowing the economic growth number for the next year, a government wouldn’t be able to forecast its fiscal deficit or the difference between what it earns and what it spends expressed as a percentage of the country’s GDP. Without forecasting the fiscal deficit, the government wouldn’t know what kind of money it has to borrow in order to meet this gap. Without the government knowing the government’s borrowing target, the country’s central bank won’t be able to set the country’s monetary policy. And so on.

Nevertheless, the world would be a much better place if the economists started forecasting in ranges. Like, in 2020-21, the Indian economy is likely to contract by 8-10% or even 8-9%, rather than saying something as specific like the Indian economy is likely to contract by 8.3%.  In this scenario, the governments could also forecast a range when it comes to their fiscal deficit.

As John Maynard Keynes is said to have supposedly remarked: “It is better to be roughly right than precisely wrong.”

Hence, forecasting ranges and pointing towards the right direction is more important than being extremely precise about the economic growth.

As Tom Bergin writes in Free Lunch Thinking—How Economics Ruins the Economy:

“If economic models or theories can point us in the right direction and give us a reasonable estimate of the scale of a force or impact, they’re helpful. For example, if consumers are building up levels of personal debt that will require ever-rising house prices and wages to sustain – think the United States in 2006 –economists don’t need to tell us exactly how much a drop in GDP this situation will likely result in. If they can simply show the risks are unsustainable and material, this can prompt and inform government action and protect society.”

I learnt this the hard way. In 2013, when I first started writing about real estate, looking at the situation at hand, I started predicting a real estate bust very confidently. In the years to come, I turned out to be partly right, with parts of the country seeing a substantial fall in prices.

But the deep state of Indian real estate (the bankers, the builders and the politicians) essentially ensured that a real bust never really came. Of course, having learnt from this, now I point out more towards the perils of owning real estate at a price you cannot really afford because that is point people looking to buy a house to live in, essentially need to understand.

Also, one can more confidently say that the real estate sector will continue to remain moribund in the days to come, than confidently predict a bust. As far as investors are concerned, the real estate story has been over for a while.

Sometimes the confidence of economists comes from the prevailing narrative. As Daniel Acemoglu and James A Robinson write in Why Nations Fail – The Origins of Power, Prosperity and Poverty:  

“The most widely used university textbook in economics, written by Nobel Prize-winner Paul Samuelson, repeatedly predicted the coming economic dominance of the Soviet Union. In the 1961 edition, Samuelson predicted that Soviet national income would overtake that of the United States possibly by 1984, but probably by 1997. In the 1980 edition, there was little change in the analysis, though the two dates were delayed to 2002 and 2012.”

Of course nothing of this sort happened, and the Soviet Union broke up in December 1991. But those were the days, and the narrative framed around the success of the Soviet style of economics, driven by its Five-Year Plans, was very popular. Samuelson was not the only one to be seduced by it. In fact, an entire generation was.

Interestingly, the economist Phillip Tetlock has carried out extensive research on experts and their predictions. Gardner, from whose book I have quoted above, documents this in Future Babble.

As he writes:

“Tetlock recruited 284 experts— political scientists, economists, and journalists—whose jobs involve commenting or giving advice on political or economic trends…Over many years, Tetlock and his team peppered the experts with questions. In all, they collected an astonishing 27,450 judgments about the future.”

It turned out that the expert predictions were no more accurate than random guesses. As Gardner writes: “Experts who did particularly badly… were not comfortable with complexity and uncertainty. They sought to “reduce the problem to some core theoretical theme.” This means that they had this one big idea and they stuck to it, without trying to realign their view to the new information coming in.

An excellent example of this is all the gold bulls who came out of the woodwork post the financial crisis of 2008. They talked about gold reaching very high price levels (The highest I encountered was $55,000 per ounce).

As a journalist I interviewed many such individuals and the confidence they had in their forecasts was amazing. In that round, gold didn’t even touch $2,000 per ounce. But the audience lapped the interviews I did. Why? Because these experts exuded confidence in their interviews, even though they eventually turned out to be wrong.

In 2012, when I turned into a freelance writer, I exuded the same confidence on gold while writing about it. And when the prices actually started to fall, it sort of struck at a core belief I had developed over the years and it took me a couple of years to get around to the whole thing.

As Grant writes: “When a core belief is questioned… we tend to shut down rather than open up. It’s as if there’s a miniature dictator living inside our heads, controlling the flow of facts to our minds.” This is referred to as totalitarian ego and a decade later I can see this ego among many bitcoin experts, whenever one questions the entire idea of bitcoin as money, and that has me worried.

Now getting back to Gardner and Tetlcok. Experts who did better than the average of the group that Tetlock had recruited had no template or no big idea. They tried to synthesise information from multiple sources.

As Tetlock writes: “Most of all, these experts were comfortable seeing the world as complex and uncertain—so comfortable that they tended to doubt the ability of anyone to predict the future. That resulted in a paradox: The experts who were more accurate than others tended to be much less confident that they were right.”

This explains why most business TV news anchors, podcasters, YouTuber, social media influencers, etc., who are popular, sound very confident. They believe in this one big idea, which sounds sensible to people, irrespective of whether it is right in the real world or not, and they keep hammering it over and over again, to their audience.

It also explains why guys who are normally right about things aren’t really popular with the media or the public at large. This is simply because they are not totally confident about what they are saying. They have their ifs and buts built into what they say and are constantly revising the information in their heads. And as and when they feel like it, they are ready to revise their views as well. This constant revision comes across as lack of confidence to the world at large. Tetlock called such experts foxes and experts who believed in that one big thing as hedgehogs.

The categorisations were from an essay written by political philosopher Isaiah Berlin, in which Berlin had recalled a small part of an ancient Greek poem. “The fox knows many things… but the hedgehog knows one big thing.” After knowing this, it is easy to figure out who is a fox and who is a hedgehog.

As Gardner writes:

“If you hear a hedgehog make a long-term prediction, it is almost certainly wrong. Treat it with great skepticism. That may seem like obscure advice, but take a look at the television panels, magazines, books, newspapers, and blogs where predictions flourish. The sort of expert typically found there is the sort who is confident, clear, and dramatic. The sort who delivers quality sound bites and compelling stories. The sort who doesn’t bother with complications, caveats, and uncertainties. The sort who has One Big Idea.”

Hence, the kind of expert found in the media is the kind of expert who is more likely to be wrong. One of the key findings that emerged from Tetlock’s data was: “The bigger the media profile of an expert, the less accurate his predictions are.”

In a world filled with confident forecasts, this is a very important point that needs to be kept in mind. If we really need to make sense of the world we are in, we need to figure out who the foxes are and follow them, however mentally disconcerting it might be. The hedgehogs need to be discarded.