Indian economy

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.

So, the 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.

India, China and the Quest for Atmanirbharta

Atmanirbharta has been the hot political and economic buzzword in India for quite a while now. It means self-reliance in English. Or as the finance minister Nirmala Sitharaman put it in her budget speech:

“Atmanirbharta is not a new idea. Ancient India was largely self reliant, and equally, a business epicentre of the world. Atmanirbhar Bharat is an expression of 130 crores Indians who have full confidence in their capabilities and skills.”

In economic terms it essentially refers to import substitution, which India practiced for almost four decades, after independence, where the idea was to make everything in the country rather than import it.

In political terms, the narrative is directed towards China and our import dependence on the Middle Kingdom. In the recent past, our political tensions with our largest neighbour have escalated and we are trying to hurt it economically by producing more at home, and not importing as much from it as we had done in the past. Also, we have banned many Chinese apps.

The question is where are we going with atmanirbharta. Let’s take a look at the following chart, which plots the total amount of goods imported from China during the period April to January, over the years.

Source: Centre for Monitoring Indian Economy.

The goods imports from China during the current financial year have been the lowest between 2016-17 and 2020-21, at $51.92 billion. Nevertheless, a simple presentation of goods imports doesn’t take into account the fact that India’s goods imports during April 2020 to January 2021 have fallen by 23.1% to $340.9 billion. They stood at $443.22 during April 2019 to January 2020. This fall shows a lack of consumer demand, which has crashed during the course of the year, with the spread of the covid pandemic.

Let’s look at the next chart, which plots what proportion of India’s goods imports came from China, during the period April to January of a financial year, over the years.

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

During April 2020 to January 2021, the proportion of imports coming from China stood at 15.23%. This is the highest in the period considered. Hence, while economic and political narrative maybe moving towards atmanirbharta, the data clearly shows something else. Our dependence on China for goods imports continues, like it was in the past.

There is one more way we can look at data. While we don’t have the full year’s data for 2020-21, we do have that for the years gone by. Hence, we take a look at proportion of full-year imports coming from China, in the next chart.

Source: Centre for Monitoring Indian Economy.
*April 2020 to January 2021.

The above chart makes for a very interesting read. In 1991-92, India barely imported anything from China. Just 0.11% came from China. In the nearly three decades that have followed, the imports from China have exploded. This just shows the rise of Chinese productivity year on year, in comparison to that of India. The proportion of imports coming from China peaked at 16.4% in 2017-18, fell for the next two years, and have risen again this year.

What is the reason for this marginally increased dependence in 2020-21? Ananth Krishnan writing in his terrific book India’s China Challenge – A Journey Through China’s Rise and What It Means for India, quotes Amitendu Palit, an economist at the National University of Singapore, in this context.

As Palit says: “If you look at critical medical supplies, which India has been importing for frontline healthcare workers in the Covid-19 battle, most of these come from China, which is one of the top sources, but, on the other hand, there isn’t a very widely diversified source of countries from which India can actually import these either.”

The larger point here is that China has now become central to many global supply chains and hence, it won’t be easy for India to lower its dependence on China dramatically as far as imports of goods is concerned.

In fact, one area where India has managed to reduce its dependence on China in the last five years, is telecom instruments, as they are categorised in the imports data. Given that the use of landline phones has come down over the years, the category  primarily includes mobile handsets.

Take a look at the following chart. It plots the value of the telecom instruments (read mobile handsets) imported from China, over the years.

 Source: Centre for Monitoring Indian Economy.
*April 2020 to January 2021.

As can be seen, the value of the instruments imported from China has come down over the years, though the 2020-21 full year imports are likely to end up being higher than those in 2019-20. In 2017-18, import of telecom instruments formed a little over a fifth of our imports from China. This fell to 8.67% in 2019-20 and has increased to 10.48% in the current financial year.

To make companies manufacture mobile phones in India, the government has been imposing duties/tarrifs on various goods that go into making of a mobile phone. The idea is to make imports from China expensive and in the process, force companies to manufacture phones in India.

In fact, this strategy has been borrowed from China. As Matthew C Klein and Michael Pettis write in Trade Wars and Class Wars: “Import substitution has succeeded thanks in part to Chinese government policies that have systematically encouraged Chinese businesses to substitute foreign production for domestic production, even when this has raised costs for Chinese consumers.” Of course, unlike India, China does not need to impose duties/tariffs to “direct domestic demand towards domestic production”.

As Klein and Pettis point out: “Executives can simply be told to pick Chinese suppliers over foreign ones… The result is that, unlike many other countries, imports have become less and less important to the Chinese economy since the mid 2000s.”

Also, given that Indian productivity is worse than that of the Chinese, manufacturing in India, comes with a cost. While, mobile handset prices barely rose between 2015 and 2019, the same hasn’t been the case in 2020, when they rose by 7%. Clearly, the cost of atmanirbharta on the mobile handsets front is being borne by the Indian consumer. As I keep saying, there is no free lunch, someone has got to bear the cost.

The government has also come up with the production linked incentive (PLI) scheme in order to help manufacturing companies in India. As Sitharaman said in the budget speech:

“Our manufacturing companies need to become an integral part of global supply chains, possess core competence and cutting-edge technology. To achieve all of the above, PLI schemes to create manufacturing global champions for an Atmanirbhar Bharat have been announced for 13 sectors. For this, the government has committed nearly Rs 1.97 lakh crores, over 5 years starting FY 2021-22. This initiative will help bring scale and size in key sectors, create and nurture global champions and provide jobs to our youth.”

There are multiple problems with this approach. The first being that the government is trying to pick winners. This entire approach smells of how things used to happen before the economic reforms of 1991, with the bureaucrats deciding what businesses should be doing.

Also, this comes at a time when prime minister Narendra Modi has been critical of IAS officers. As he said in February: “Just because somebody is an IAS officer, he is running fertiliser and chemical factories to airlines.” The same babu is now expected to run an incentive scheme for big business.

India’s biggest success stories over the last three decades, software, pharma and automobiles, happened despite the government, and not because of it. So, the idea still should be to make things easier for smaller businesses to grow bigger, which is something that happened beautifully in the IT sector. (This is not to say that the government didn’t help. It did. But it largely didn’t meddle).

In fact, while we think of China as a country with big companies that wasn’t always the case. China’s initial growth in the 1980s and up until the mid 1990s was through the growth of millions of Township and Village Enterprises (TVEs). This is a fact that seems to have been forgotten.

Big companies growing bigger can create some jobs, but not the number of jobs that India requires. As data from the Centre for Monitoring Indian Economy shows, in the last five years India has added 11.77 crore individuals to the working age population.

This means that around 19.76 lakh individuals have crossed the age of 15 on an average every month, over the last five years. Of course, not all of them are looking for jobs but a good chunk are. Even if we assume that around 40% of them are looking for jobs, we end up with around one crore people looking for jobs every year.

Such a huge number of jobs can only be created by small businesses growing bigger and not by big businesses growing bigger, which can only possibly be the icing on the cake.

As an OECD (Organisation for Economic Co-operation and Development) research paper points out:

“SMEs (small- and medium-sized enterprises) account for 60 to 70 per cent of jobs in most OECD countries, with a particularly large share in Italy and Japan, and a relatively smaller share in the United States. Throughout, they also account for a disproportionately large share of new jobs, especially in those countries which have displayed a strong employment record, including the United States and the Netherlands. Some evidence points also to the importance of age, rather than size, in job creation: young firms generate more than their share of employment.”’

In fact, given the obsession the current government has had with scale and formalisation of the economy, small businesses have been hurt through a mind-numbing move like demonetisation and a half-baked goods and services tax.

Further, the globalisation game itself might be changing. While, we might want companies based out of India to become a part of global supply chains, it is worth remembering here that the strategy worked at a certain point of time.

As Krishnan writes:

“China was able to recognize and exploit the opportunities just as global production chains were forming through the opening of the early 1990s… The infrastructure it was able to create through the 1990s enabled ‘a unique and probably unrepeatable combination of low developing country labour costs and good, almost rich country infrastructure.'”

Also, the supply chains that are already in place are not going to shut down and move to India, just because India is now offering incentives. As Apple CEO Tim Cook said in 2017: “The popular conception is that companies come to China because of low labour cost… The reason is because of the skill, and the quantity of skill in one location and the type of skill it is.”

India clearly has a skills problem. A little more than a fifth of Indian graduates are unemployed, and at the same time when companies advertise for personnel, they can’t seem to find enough of them who meet the right criteria. Multiple surveys have found Indian graduates and engineers to be simply unemployable. This is not something that can be set right overnight.

The corporates, not surprisingly, have welcomed the scheme, given that the government is offering “a recurring cash subsidy computed as a fixed percentage of the manufactured sales turnover.” Hence, they clearly have an incentive to do so. In fact, lobbying has already started on this front.

Take the case of the PLI scheme in the electronics and mobile manufacturing, which has been touted as a success, after attracting investments of over Rs 11,000 crore in 2020. As an editorial in The Hindu Business Line points out, the beneficiaries are already asking for a rollover, “citing land acquisition delays, lack of skilled workforce and demand issues post Covid.”

Also, as has been seen in India in the past, once a subsidy is introduced into the government’s budget, it rarely goes away.

Finally, lest I be accused of looking at only negatives (honestly, please go to news.google.com and enter PLI scheme, you will only get positive stories to read), one positive thing could come out of the scheme.

As Palit told Krishnan in the context of China: “When we look at value chains today, let’s say in a post Covid-19 situation, the emphasis on the part of businesses is to make these chains shorter, more resilient, more durable, and locate them closer to demand markets… This is where we often overlook the importance of China. It continues to remain a major source of final demand.” And given this shifting supply chains out of China will be difficult.

This applies to India as well. Given India’s size, it will continue to have a huge source of consumer demand in the years to come. This should encourage companies looking for stable supply chains to have their manufacturing bases in India to cater to its domestic market. And this is where PLI can work its magic.

As Neeraj Bansal of KPMG put it in a recent writeup:

“From raw materials to critical components, the COVID-19 pandemic exposed the reliance of country’s key sectors on a few markets for fulfilling their manufacturing and sourcing requirements. To put things in perspective, India depends on a single market for 70 per cent of its API consumption needs, 85 per cent of smartphone components imports and 75 per cent of television components imports. As global supply chains were swiftly and effectively dismantled as one country after another went into lockdown in 2020, efforts toward bolstering domestic manufacturing gained momentum.”

Nevertheless, there is a corollary to this. As more and more people get vaccinated and the world moves on and goes back to doing things that it always has, this narrative of having manufacturing facilities closer to the demand markets, will keep getting weaker. Hence, India has a couple of years to cash in on it.

Of course, whether India emerges as a country where the products are assembled or major value addition takes place, remains to be seen. Also, prices will go up. Make in India will come at a cost.

Revealing the Real Picture Behind India’s Unemployment Problem

BA Kiya, MBA Kiya, 
Lagta Hai Sab Kuch Aiwen Kiya 
— With due apologies to Sampooran Singh Kalra.

The rate of unemployment as of February 2021 stood at 6.9%. This doesn’t sound very high. But the calculation of this figure misses out on a very important nuance. 

Those who follow me on Twitter know that I go by the moniker of Shikshit Berozgar (or educated unemployed). This is basically a joke I crack on myself on not being gainfully employed with a corporate, in the traditional sense of the term.

Nevertheless, on a more serious note, unemployment is a very serious problem in India. In fact, in the recent past, #modi_rojgar_do has been a top Twitter trend. This gives me a reason to look into this economic and social illness which impacts the society at large and the youth in particular, very badly. Of course, nothing is what it seems, which is why it is important to go into details.

I will use unemployment data published by the Centre for Monitoring Indian Economy, which has now been available for a period of five years, hence, will give us a decent long-term trend.

Let’s first look at the unemployment rate over the last five years, starting from January 2016 onward.

Source: Centre for Monitoring Indian Economy.

What does the chart tell us? The unemployment rate has varied quite a bit between January 2016 and February 2021. As of February 2021, the rate of unemployment stood at 6.9%.  Hence, things have improved from April 2020, when the unemployment rate hit a high of 23.52% and nearly one-fourth of the labour force was unemployed. This was when the lockdown enforced by the government was at its peak.

Nonetheless, the unemployment rate is still very high in comparison to the low of 3.37%, which was achieved in July 2017. It needs to be mentioned here that the Goods and Services Tax (GST) came into effect from July 1, 2017 and has been responsible for increased formalisation of the Indian economy. Hence, many informal businesses have been shut down. Formal businesses tend to be more mechanised and hence, employ fewer people, can be one possible explanation for the higher unemployment.

Moving forward if we were to read only the above chart, we are likely to come to the conclusion that the negative economic impact of the covid pandemic and the general slowdown in the Indian economy, over the years, are gone. But there is some nuance we are missing out on here.

While I have shared the unemployment rate in the above chart, I haven’t told you how the term unemployment is defined. 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. At the risk of repetition, 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.

It will soon become clear why have I gone into such detail trying to explain what being unemployed exactly means. First let’s take a look at the following chart, which plots the labour participation rate.

Source: Centre for Monitoring Indian Economy.

In fact, this chart is at the heart of the issue of Indian unemployment. As can be seen from it, the labour participation rate has been falling over the years. It was at a peak of 48.47% in May 2016 and fell to a low of 35.57% in April 2020. In February 2021, it stood at 40.5%.

Now what does this mean? 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.

What has happened in the last five years? Let’s take the case of May 2016. In May 2016, the population greater than 15 years or what is referred to as working-age population, stood at 94.58 crore. Of this, 45.84 crore individuals formed the labour force, which means they were either employed or were unemployed and actively looking for a job. Hence, labour participation rate, which is the ratio of the labour force to the population greater than 15 years of age, was at 48.47%.

Now what’s the scene in February 2021? The population greater than 15 years stood at 105.80 crore. The labour force stood at 42.85 crore. This implies a labour participation rate of 40.5%.

In simple English, in February 2021, a smaller proportion the working age population is working or is unemployed and looking for a job, than was the case in May 2016.

The working age population, between May 2016 and February 2021, has gone up from 94.58 crore to 105.8 crore, this implies an increase of 11.22 crore.

Nevertheless, the number of people employed or unemployed and looking for a job, that is the total labour force, has fallen from 45.84 crore to 42.85 crore, or by 2.99 crore.

So, the working age population has increased by 11.22 crore between May 2016 and February 2021, but the total labour force as such has fallen by 2.99 crore. This is India’s real unemployment problem, which isn’t reflected in the unemployment rate, and needs a lot more digging.

What is happening here? A very small proportion of the population is studying more and some may also be retiring early. But that hardly explains the scale of this problem. The explanation lies in the fact that more people are simply dropping out of the labour force, because they are not able to find jobs over a period of time and hence, are not actively looking for jobs anymore.

Let’s look at how the situation has changed 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 workforce has shrunk by 1.39 crore.

Clearly, covid has only accentuated the larger unemployment trend India was already going through. In a sense, many jobs have simply been destroyed, leading to people dropping out of the workforce and in the process, making the overall unemployment number look much better than it actually is.

In the conventional definition of unemployment, individuals who are not actively looking for a job and drop out of the workforce, do not get counted, but ultimately, they are also not gainfully employed. And that’s where the problem lies and explains hashtags like #modi_rojgar_do.

If you still haven’t got it, let me share a very simple example. Let’s say the labour force has 100 individuals. The working age population of people above 15 years of age comprises 200 individuals. Hence, the labour participation rate is 50%. Let’s further assume that the unemployment rate is 10%. This means that 10 individuals are unemployed (10% of 100) and are actively looking for a job.

These individuals do not get a job for a while and let’s further assume that four of them stop actively looking for a job. Given this, the labour force size will fall to 96 (100 minus 4). Those categorised as unemployed will fall to six (10 minus 4). The rate of unemployment will fall to 6.25% (6 expressed as a percentage of 96).

So, the rate of unemployment will come down from 10% to 6.25%, nevertheless, the number of people without jobs will continue to remain at 10. The labour participation rate will come down to 48% (96 expressed as a percentage of 200), from the earlier 50%.  This is how the maths will work out.  This is precisely what is happening in India, of course, at a much larger level.

Now let’s take a look at the unemployment rate and labour participation rate among the youth, that is those aged between 20 and 29. This is where things get very interesting.

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

As can be seen from the above chart, the unemployment among youth, which was always on the higher side, has gone even higher, in the last five years. It peaked at 40.41% in April 2020, and in February 2021, was still at a very high rate of 25.68%.

What this means is that one in every four Indian youths is unemployed and is actively looking for a job. And that is clearly bad news. The situation has deteriorated over the last five years.

Now let’s take a look at the labour participation rate among youth.

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

As is the overall trend, the labour force participation rate among youth has come down dramatically over the years. It peaked at 53.18% in May 2016 and in February 2021, it stood at 45.42%. Of course, one explanation for this is lies in youth spending more years in college. Nevertheless, the broader explanation for this lies in youth dropping out of the labour force given their inability to find a job. Also, even those who are in college are actively looking for a job. Or sometimes college is just an excuse to postpone actively looking for a job. These are points that need to be remembered.

What explains this situation? One reason for this lies in the fact that the investment to gross domestic product (GDP) has fallen over the years from a high of 34.31% of the GDP in 2011-12 and is expected to be at 30.91% in 2020-21. Hence, with a lower investment in the economy, fewer jobs are being created.

Over the last few years, the government has made attempts at formalizing the economy through a harebrained measure like demonetization and a half-baked measure like goods and services tax.

As an August 2018 Mint Street Memo published by the Reserve Bank of India points out:

“The MSME ( micro, small and medium enterprises) sector has witnessed two major recent shocks, viz., demonetisation and introduction of goods and services tax (GST). For instance, contractual labour in both the wearing apparel and gems and jewellery sectors reportedly suffered as payments from employers became constrained after demonetisation (RBI, 2017). Similarly, the introduction of GST led to increase in compliance costs and other operating costs for MSMEs as most of them were brought into the tax net.”

This has hit jobs badly as well.

It needs to be understood here that many employees of MSMEs that shut down did not come under the income tax slab. Nevertheless, whenever they make a purchase as a consumer, they do pay some form of indirect tax. This is a point those celebrating the increasing formalisation of the economy, seem to miss out on.

Let’s take a look at a few more trends, starting with female labour participation rate.


Source: Centre for Monitoring Indian Economy.

This is a very disturbing chart. The female labour participation rate has crashed to just 10.89%. In urban India, it was at 6.56% in February. This means more and more women are getting educated but are not working in salaried jobs. In fact, this is a trend that started before 2014 and it has only accentuated since then. As per surveys carried out by the Labour Bureau, the female labour participation rate in 2012-13 and 2013-14 stood at 25% and 28.7%.

Economists have struggled to come up with an explanation for this. 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. This needs more research, and I will write about it in detail in the days to come.

Another interesting trend is the unemployment rate depending on the education level. The following chart plots the unemployment rate by level of education for February 2021.

Source: Centre for Monitoring Indian Economy.

While I have only shared data for February 2021, this is a trend that has played out over the years.

World over there is a wage premium for education, which means, the more educated you are, the higher your income is likely to be. That might be the case in India as well, but along with that we have another very interesting phenomenon.

The rate of unemployment increases with the number of years of education, with one in every five graduates being unemployed. The fact many graduates are unemployed again explains the popularity of trends like #modi_rojgar_do. The graduates have the time, the energy and the internet bandwidth, to get such an important issue to trend.

The larger explanation for this lies in the fact that graduates tend to wait for that good job, which never really comes. That is a choice that the less educated don’t make.

Let’s now look at a chart which plots the rate of unemployment across different age brackets, for the month of February 2021.

Source: Centre for Monitoring Indian Economy.

The rate of unemployment is highest at the younger ages and as one ages, it comes down dramatically.

The high rate of unemployment for the ages between 15-19 can be explained by the fact that more individuals now spend time in school and go to college. But what about rates beyond that bracket?

The interesting thing is that rate of unemployment in the age category 25-29 stood at 11.53% in February 2021. For the age group, 30-34, it was at only 1.32%. While I have only shared data for February 2021, this is a trend that has played out over the years.

What’s happening here? It seems this is a problem that isn’t just peculiar to India and is prevalent in other parts of the world, including South Africa, Egypt and countries in the Middle East.

A part of the problem, like most disappointments in life, is a mismatch of expectations that the unemployed youth have, and the situation as it prevails.

As Abhijit Banerjee and Esther Duflo write in Good Economics for Hard Times:

“They [i.e. the youth] were told that if they studied hard they would get a good job, meaning mostly a desk job or a teaching job. This was closer to the truth in their parents’ generation than it is today… The growth in government jobs slowed and eventually stopped in the face of budgetary pressures.”

In fact, in the Indian case, the pace of creation of government jobs has slowed down over the years. As far as central public sector enterprises (CPSEs) are concerned, the total number of employees has gone down over the years.

Take a look at the following table.

Employment at CPSEs


Source: Public Sector Enterprises Survey 2018-19.

The number of employees in 2009-10 had stood at 14.90 lakh. It has fallen to 10.33 lakh in 2018-19. This is largely true of the government as a whole. But the fascination for a government job still remains strong and there is an economic incentive for it as well.

As can be seen from the above table, while the number of jobs in CPSEs has come down, the emoluments have gone up. In 2009-10, it stood at Rs 5.89 lakh. In 2018-19, it had jumped to Rs 14.78 lakh. And this is just the emoluments. There are other things that come with a government job, employment guarantee for life, access to good medical facilities, pension in many cases, and so on.

This explains why every few months we get stories in the media about graduates, engineers, post graduates and even PhDs, applying for low-level government jobs like that of peons, sweepers etc.

As Banerjee and Duflo write:

“There are small fraction of jobs that are much more attractive than the rest, for the reasons having nothing to do with productivity. The best example are government jobs… In the poorest countries, public-sector workers earn more than double the average wage in the private sector. And this is not counting generous health and pension benefits.”

What this ensures is that many individuals spend the best part of their youth preparing and writing exams to get into a government job. As Banerjee and Duflo write: “These young people are mostly waiting for jobs they will not get… If the government jobs stopped being quite so desirable, the economy would gain many years of productive labour.”

But given that there are very few government jobs going around at the end of the day, the futility of it all, ultimately hits individuals who cannot see a world beyond a government job. What this basically means is that as people age, they eventually do start working, once their overall expectations fall in line with what is on offer.

So, other than the fact that there aren’t enough jobs going around for anyone, the love of a government job also seems to hold people back.

To conclude, you won’t get to read this anywhere in the mainstream media. Hence, it is very important that you continue supporting my work.

PS: This is not to say that all was well before 2014. It clearly wasn’t. As the Report on Employment-Unemployment Survey of 2013-14 points out: “Full employment was available to only 63.4 per cent of self-employed persons, the figure being as low as 42.1 among ‘casual’ workers.” The government has done away with the publishing of this report, since then. Such big structural problems don’t manifest overnight. If not tackled on a war footing, they only get worse with time and which is what seems to have happened.

Bihar’s APMC Story Does Not Inspire Much Confidence

This is the third piece in the agriculture reform series. You can read the first two pieces here and here. While this piece stands on its own, for a better context on the overall issue, it makes sense to read the two pieces published earlier, before reading this piece.

Chintan Patel and Vivek Kaul

The Farmers’ Produce Trade and Commerce (Promotion and Facilitation) Act 2020 became a law on September 27, 2020. It is one of the three farm laws passed by the Modi government that has been met by stiff opposition from farmers. The law supposedly creates a mechanism allowing the farmers to sell their farm produce outside the Agriculture Produce Market Committees (APMCs).

As we pointed out in an earlier article, the fate of the APMCs or mandis, under the new laws is a topic of much debate. Proponents of the bill claim that allowing farm trade outside the APMCs will encourage competition and help farmers get better prices for their produce. The idea being that there will be more competition for agriculture produce and in the process, farmers will make more money. QED.

Farmer organizations opposing the bill argue that unregulated transactions outside the APMCs will actually result in a price squeeze for the farmers, given the asymmetry or the huge difference of negotiating power between the individual farmer and corporate-backed buyers. As is often the case, both sides can lay claim to a logically coherent argument backed by economic theory. So, which argument has higher odds of manifestation?

When the future is uncertain, the past is often a reliable guide. Using that rationale, it is instructive to look deeper at the Bihar experience vis-a-vis APMC markets. Bihar had done away with APMC markets in 2006. But before we get into the specifics, let’s zoom out a little and take a look at the bigger picture first.

Bihar’s Backdrop

Bihar is India’s poorest state. Given below are tables that chart the per capita income of India’s richest and poorer states.

Source: https://statisticstimes.com/economy/india/indian-states-gdp-per-capita.php

Source: https://statisticstimes.com/economy/india/indian-states-gdp-per-capita.php

As the above tables show, Bihar has the lowest per capita income in the country. It is about 18 percent of the income of Haryana and less than 10 percent of the income of Goa. Ironically, Bihar is endowed with abundant natural resources, especially fertile soil and groundwater, and yet it continues to remain one of the poorest states in the country.

The state has a population of 11.52 crore (2016), with a very high population density of 1,218 per square km as compared to the national average of 396 per square km. It is largely an agrarian rural economy with approximately 88.5 percent rural population out of which 74 percent of the workforce is reliant on the agriculture sector for a livelihood as per the 2011 Census.

Even accounting for shifts in the economy away from agriculture and migration out of rural areas since the last Census, the poverty in Bihar is closely linked to state of its farmers.

The high population density is clearly reflected in the land holding pattern in Bihar. Compared to other states, Bihar has highly fragmented landholdings. As the same piece of land has got divided among more and more family members over the generations, the average holding has fallen dramatically. Even though quite a few migrate to the cities, they still keep their farmland. This also stems from the fact that selling agricultural land in India is not easy.

As the table below indicates, marginal holdings of less than one hectare (around 2.47 acres) constituted about 91.2 percent of all land parcels in 2015-16, compared to the national average of 68.5 percent. Additionally, 97 percent of all holdings are  less than 2 hectares in Bihar. This high skew towards small land holdings is an important statistic, as agricultural marketing policies affect small and marginal farmers differently from those with larger holdings.

Land holdings in Bihar.

APMC Abolishment in Bihar

In 2006, the Nitish Kumar state government made the decision to abolish its state-level APMC Act allowing private players to directly purchase agricultural produce from farmers. Under the erstwhile Bihar APMC Act, both farmers and buyers would pay 1 percent of the sale price to municipal bodies. After the APMCs were abolished, the government introduced Primary Agriculture Credit Societies (PACS). PACS are panchayat level cooperatives with farmer members that fulfil 3 roles in Bihar.

1) Help farmers borrow money for buying farm equipment, farming inputs such as seeds, fertilizers, etc., or to tide through losses. PACS in turn are given credit by cooperative banks which are funded by the state government.

2) A one-stop shop for high-quality seeds, fertilisers, and other inputs.

3) Most importantly, PACS are responsible for procurement of grains particularly rice-paddy and wheat from the farmers at the government-announced minimum support price (MSP). Thus, PACS act as an intermediary between the farmers and the eventual purchasers of wheat and rice – which can be any of the following; Food Corporation of India (FCI), state procurement agencies or private mills, for that matter. For other produce (other than rice and wheat), farmers interact directly with private traders.

Upon procurement of the crop, especially in the case of paddy, it goes to the Bihar State Food and Civil Supplies Corporation, and then on to the Food Corporation of India, who direct it to the Public Distribution System or ration shops as they are more popularly known. The payment is expected to reach the farmer within 48 hours of selling the crop at PACS.

It should be noted that PACS exist nationwide and have long been a part of the cooperative banking system in India, formed to provide credit to rural areas. Bihar however is unique in that it expanded the scope of PACS to b) and c) above. As we shall see later in the article, PACS have not been able to deliver effectively on these objectives.

The deregulation of agriculture market transactions in Bihar in 2006 shares significant similarities with the Farmers’ Produce Trade and Commerce (Promotion and Facilitation) Act 2020 . Although the central law does not call for the closure of state APMCs or creation of PACS-like entities, the core idea of deregulating agriculture trade outside of APMCs is the same.

Thus, there is merit in examining the outcomes of what has happened in Bihar over the last decade and a half,  to form expectations from the new law.

Several leaders of the Bhartiya Janata Party including prime minister Narendra Modi  and other supporters  of the new laws have touted Bihar’s abolition of APMCs to make their case. At the same time, critics have invoked Bihar as a cautionary tale of deregulating agriculture market.   So, the same scenario is being presented to suit diametrically opposite arguments.

What gives? As is often the case, the truth lies somewhere in between two extremes.

Prices

The bane of Indian agriculture is the price difference between the first transaction – what the farmer gets for a commodity, and the last transaction – what you and I pay for the same commodity.  Any changes to agricultural markets like the abolition of APMCs in Bihar needs be assessed against its impact on prices.

The government recognizes the importance of collecting data on prices. Each year, the Ministry of Agriculture and Farmers Welfare publishes data on farm gate prices based on data received from the state governments “to facilitate fine-tuning of agriculture policies aimed at farmer welfare”  .

The average wholesale price of a commodity (e.g. wheat, rice, etc.) at which the farmer sells to a trader at the village site during the specified marketing period after the harvest of each commodity, is termed as the Farm Harvest Price (FHP) for each commodity.  The next few charts track both the FHP and MSP of four commodities (paddy, wheat, maize, and ragi) from 2000- 2017. The central government announces MSPs for 23 agricultural crops during the course of any year, but primarily buys only rice and wheat directly from farmers.

Source:  https://eands.dacnet.nic.in/

The above chart shows that for rice paddy, the MSP has always been higher than the FHP. From 2001-02 to 2006-07, the average difference between MSP and FHP was around 26 percent. This basically means that  the FHP was 26 percent lower than the MSP on an average. From 2006-07 to 2014-15, the average difference reduced to around 18 percent. 2015-16, onwards the difference has inched up to around 24 percent, for the last two years for which the data is available.

                                                                            Source:  https://eands.dacnet.nic.in/

For wheat, the difference between MSP and FHP has been less stark than that for rice paddy.  From 2001-02 to 2006-07, the average difference between MSP and FHP for wheat was around 7 percent. From 2006-07 to 2014-15, the average difference barely moved up to  around 8 percent . However, for the last two years 2015 to 2017, for which data is available, the difference has spiked to around 17 percent.

Source:  https://eands.dacnet.nic.in/

For maize too, the difference between MSP and FHP has been less stark than for paddy but higher than that of wheat.  From 2001-2 to 2006-07, the average difference between MSP and FHP for wheat was around 19 percent. From 2006-07 to 2014-15, the average difference reduced to around 12 percent . However, for the last two years 2015 to 2017, the difference has spiked to around 18 percent.

Source:  https://eands.dacnet.nic.in/

Finally, for ragi, the difference between MSP and FHP has been quite high and has kept increasing.  From 2001-02 to 2006-07, the average difference between MSP and FHP for ragi was around 26 percent. From 2006-07 to 2014-15, the average difference increased to around 31 percent. Finally, for the last two years, 2015 to 2017, the difference has increased to around 37 percent.

The following table summarises the data from the above four charts.

Price Trends Summary
Source:  https://eands.dacnet.nic.in/

What can we infer from the above charts. Let’s take a look pointwise.

1)  The span from 2001 to 2017 can be divided into three periods : 2001-06, 2007-13, and 2015-17. Farm prices improved for paddy in the second period (around 18 percent lower than the MSP)  compared to the first period (around 25 percent lower than the MSP). Of course, they were lower than the MSP during both the periods.

Similarly maize prices improved in the second period (around 12 percent lower than the MSP) from the first period (around 19 percent lower than the MSP). Of course, they were lower than the MSP during both the periods.

For wheat, difference between the farm prices relative to MSP stood at 7 percent during the first period and at 8 percent during the second period. Hence, the difference increased though marginally.

Rice, wheat and maize are the three major cereals produced in Bihar and make up for 80 percent of the cropping area. The difference in prices between the FHP and the MSP, largely came down in the seven year period after the removal of the state level APMC Act. This finding weakens the argument that market deregulation will necessarily lead to lower prices, even though the farmers did not get the MSP.

2) As can be seen from the above table, starting in 2015, difference between FHP and MSP has increased for all the four commodities. Let’s take the case of maize. Between 2007 and 2014, the difference had stood at around 12 percent. It has since jumped to around 18 percent, almost back to pre-2006 levels.

A similar trend can be seen for the other three crops as well.

The official government data is only available till 2017, but this divergence between FHP and MSP is also reported in recent articles discussing the farmer situation in Bihar.

An article from People’s Archive of Rural India on Feb 20, 2021  reports  that “In 2019, a farmer sold his stock of raw paddy at the rate of Rs. 1,100 per quintal – this was 39 percent less than the MSP (minimum support price) of Rs. 1,815 at that time”.
Another article from December 2020 reports that “Paddy has sold for Rs 900-1,000 a quintal in Bihar, almost half the Rs 1,868 fixed by the Centre as MSP”.

The farm prices at which farmers sell continue to be depressed compared to the MSPs and given that difference has only increased in recent years, weakens the argument forwarded by supporters of the new farm laws which extrapolates deregulation to improved price realization for farmers. Economic theory doesn’t always fall in line with things actually happening on the ground.

A key underlying rationale behind dismantling of the APMCs in Bihar was that it would lead to an increase in the number of buyers in the marketplace. A similar argument is also being made in the case of the new farm laws. However, that is not how things have worked out, in markets across Bihar.

In fact, anecdotal evidence from newsreports emanating from Bihar suggests that sales to private traders are often distress sales since farmers don’t have access to a sizeable pool of local buyers .

A 2019 paper by the National Council of Economic Research makes a similar observation: “Despite the abolition of the Agricultural Produce Market Committee (APMC) Act in 2006, private investment in the creation of new markets and strengthening of facilities in the existing ones did not take place in Bihar, leading to low market density. Further, the participation of government agencies in procurement and the scale of procurement of grains continue to be low. Thus, farmers are left to the mercy of traders who unscrupulously fix lower prices for agricultural produce that they buy from farmers..”

Of course, there are other reasons that push farmers to make these distress sales such as a deficient transport network, poor storage facilities, and lack of capital. All of these are exacerbated for small and marginal farmers who form the bulk of agriculturists in Bihar. Given these harsh conditions, it is unsurprising that farmers are unhappy with the present system.

The disillusionment of the Bihar farmer can also be understood looking at incomes of farmers, because ultimately the proof is in the pudding.

Income of Farmers in Bihar

 Source: Study on Agricultural Diagnostics for the State of Bihar in India, 2019 report by NCAER

                                   
The above chart shows that while the net income of farmers in Bihar rose from 2007 to 2010, nevertheless, it has been declining continuously since 2010, up to the point we have data for. The declining income is explained by a rise in costs of agriculture inputs (seeds, power, labour, fertilizers, cost of finance, etc.) without a commensurate increase in sales revenue. The net income per hectare farmed, has moved alarmingly towards zero.

Government procurement of foodgrains 

Farm prices and farmer incomes are significantly affected by the level of government procurement of foodgrains in Bihar. The Central Government extends price support to paddy and wheat through the Food Corporation of India (FCI) and state procurement agencies across the country.

As per this policy, state governments are supposed to purchase paddy and wheat (conforming to certain specifications) from farmers at the declared MSP. Farmers have the option to sell their produce to private traders if they can get better prices in the open market. The objective of foodgrains procurement by government agencies is to ensure that farmers get remunerative prices for their produce and do not have to resort to distress sale. The central government accepts the responsibility to fund the procurement operations.

The next two tables give a breakdown of foodgrain procurement in the recent few years for major rice and wheat producing states.

State wise FCI Procurement of rice-paddy 
Source: Food Corporation of India.

State wise FCI procurement of wheat

Source: Food Corporation of India.

Procurement of paddy in Bihar is around 20 percent of the state’s total production, and that of wheat is almost negligible (less than 1 percent). Compare this to Punjab and Haryana, where procurement levels for paddy are over 80 percent and that of wheat are over 60 percent. This is primarily because of historical reasons, in order to promote the green revolution in the states.

This is one of the reasons for the disparity of wealth between Bihar and the other states. Since government buys paddy and wheat at MSP rates, low levels of government procurement in Bihar negatively impact the FHP for wheat and paddy, and in the process farmer incomes.

If the government purchased 100 percent (hypothetically speaking) of the paddy grown in the state, the FHP for paddy would more than likely be the same as the MSP. At 2016-17 prices, that would mean the farmer would get Rs 1,510 per quintal instead of Rs 1,147 per quintal for paddy – an increase of around 32 percent or Rs 363 per quintal. This additional revenue would directly pass-through as added income for farmers. This explains why procurement at MSP rates is a pressing demand by farmers during any policy debates on improving farmer incomes.

Low procurement of foodgrains by the state of Bihar can be attributed to two main reasons: a) inadequate funding by the state and b) Poorly functioning PACS.

There are several deficiencies in how PACS operate including restrictive registration requirements which limit who can sell to PACS, limited windows of procurement, sub-optimal timing of procurement, rejection of crop by the PACS due to excessive moisture content, and excessive delays in payment.  In fact, the number of PACS  in Bihar has declined by over 82 percent, from 9,035 in 2015-16 to 1,619 in 2019-20.

While the specific problems of PACS are less relevant to the national debate on the farm bills, they point to an important fact. The success or failure of market deregulation is highly dependent on the alternate systems that emerge in that environment, which will be unique for each state. Hence, the “vocal for local” mantra should also be applied when implementing policy solutions that strengthen federalism over a one solution-fits-all approach.

Conclusions

1) The so-called opening up of the agriculture market in Bihar to private players has not fundamentally altered the state of the Bihari farmer. The data on farm prices and farmer incomes is mixed after dismantling the APMCs. The difference between FHP and MSP for commodities like paddy and maize did decrease after APMCs were abolished, but those gains have reversed since 2015. The lived experience of farmers as reported by ground reports and the data on farmer incomes and prices paint a grim picture.

2) The PACS created by the state government for procuring food-grains have proven to be inefficient and non-responsive to farmer needs.

3) The government procurement at MSP continues to be a key contributing factor in improving FHPs and farmer incomes. This underlines why MSPs continue to be a key issue for farmers protesting the new farm laws.

4) The Bihar experiment is pertinent to the 2020 Farm Laws, but extrapolating the outcomes in Bihar to the current farm law debate needs some nuance. The data can be presented selectively, both by opponents and proponents of the farm laws to further their argument. But based on the analysis presented here, it is clear that deregulating agriculture markets in Bihar, did not cause prices to crash, though the difference with the MSPs has risen in the recent years. Neither did it usher in a wave of private buyers vying for agriculture produce, buoying up farmer incomes and prosperity in its wake.

It must be noted that the total output of an agrarian economy is affected by a host of factors including crop yield (how much crop is produced per unit area), land usage (how much area is used for cropping), cropping patterns (choice of high-value vs low-value agricultural produce), and prices . Of these, only prices are affected by the new law.

The other factors are influenced by variables such as irrigation, power availability, fertilizer usage, seed quality, rainfall, weather events, mechanization, among others. In a 2017 paper on agriculture in Bihar, the authors identify the following factors as drivers of agricultural growth. These are, irrigation, flood protection, energy for agriculture, roads, procurement system and agriculture markets.

While government policy has a role to play in shaping some of these variables, Bihar’s APMC abolishment law in 2006 and the central laws in 2020, are limited to procurement and agriculture markets. Thus, commentary correlating the abolishment of APMCs in 2006 with changes in macroeconomic metrics in Bihar such as total agricultural output or agricultural growth is disingenuous.

PS: Such a detailed data dive takes a lot of time and effort and you won’t see it anywhere in the mainstream media. Given this, our work needs your constant financial support. 

Please support Vivek’s work. 

You Have Heard the Good News About GDP, Here’s the Slightly Better News

The gross domestic product (GDP) figures for the period October to December 2020 were declared earlier in the day today. GDP is a measure of economic size of a country.

The good news is that the Indian economy is back on the growth path. It grew by 0.41% during the period. While the growth rate itself isn’t great, it comes on the back of six months of a covid led economic contraction. And that’s clearly good news.

But this bit most of you who follow the economy closely on the social media, must have already heard by now. So, let me give you some better news than this good news.

The Indian GDP is measured in two ways. One way is by adding up private consumption expenditure (the money you and I spend buying up things), government expenditure, investment and net exports (exports minus imports). If we leave government expenditure out of the GDP, what remains is the non-government GDP, which forms a bulk of the GDP. In the October to December period, it formed around 90.3% of the GDP.

For the GDP to grow on a sustainable basis, this part needs to grow. Given that the government is a small part of the Indian economy, it can only create so much growth by spending more and more money.

The non-government part of the GDP grew by 0.58% during October to December 2020, after contracting significantly during the first six months of the financial year.

What this tells us is that the private part of the economy recovered quite a bit during the period without the government trying to pump up economic growth. The government expenditure during the period was down by 1.13%. This is the slightly better news I was talking about.

The private consumption expenditure, which forms a major part of the non-government part of the GDP contracted by 2.37%, after having contracted much more, during the first six months of the financial year. This tells us that the consumers are gradually coming back to the market even though some apprehension still prevails. This apprehension is probably more towards going out and spending money in the services part of the economy.

The other important part of non-government GDP is investment. It grew by 2.56% during October to December, which is the best in a year’s time. For jobs to be created, this growth needs to be sustained in the months to come.

The other way of looking at size of the economy is to add up the value added by the various sectors. Of this, the services sector, from hotels to real estate to banking to trade to broadcasting to transport to public administration, form nearly half of the economy. And if economy has to get back on track, it is these sectors that need to get back on track. The services sector grew by 0.98% during the period, though this was better than the contraction seen during the first six months of the year.

Agriculture was the standout sector and it grew by 3.92% during the period. In fact, October to December is the biggest period for agriculture during the year and the sector has done well during its biggest quarter. On the other hand, manufacturing grew by 1.65%.

What this tells us is that the economy is gradually coming back to where it was before covid. It is worth remembering here that even before covid the Indian economic growth was slowing down. All in all, the real challenge for the Indian economy will start in the second half of the 2021-22, once the base effects of the covid led economic contraction are over. As I have said in the past, the economic growth rate during the first half of 2021-22 will go through the roof, but that will be more because of base effect than anything else.

Nonetheless, even with this recovery during the second half of the financial year, the Indian economic growth is expected to contract by 8% during 2020-21. This figure has been revised upwards. The Indian GDP was earlier expected to contract by 7.7% during the year.

The main reason for this lies in the revision of the government expenditure expected during the year. As per the first advanced estimate of the GDP for 2020-21 published in early January, the government expenditure for 2020-21 was expected to be at Rs 17.48 lakh crore. In the second advanced estimate published today, it has been revised to Rs 15.87 lakh crore, a cut of 9.2%.

From the looks of it, the central government is trying to cut down on the targeted fiscal deficit of Rs 18.49 lakh crore for 2020-21. Fiscal deficit is the difference between what a government earns and what it spends.