Demographic Dividend or Disaster — Jobs in India
Summary
India with its massive youth population is sitting on a potential demographic gold mine. With most of the advanced economies aging fast and set to have a very high dependent population to working population ratio, India can potentially be the labour supply for the future. But will there be enough meaningful jobs for our youth? There are massive challenges and headwinds to job creation:
- There is massive skill deficit in India. We churn out lots of graduates but with poor skills. Successive Governments have not yet been successful to find a model to scale up training and skilling needed for tens of millions of Indians. India has to rapidly scale up its stock of skilled labour if it has to grab key economic opportunities.
- There are likely to be far lower manufacturing jobs for a given output.Automation and productivity have been improving tremendously in Manufacturing. The consequence might be that India may not be able to follow the trajectory of other Asian economic miracles like Japan or China. The current manufacturing superpowers are rapidly scaling automation.
- We are living in a low growth world. Advanced economies are growing slowly and aggressive policies have seen less than spectacular results. There has been a noticeable upswing in protectionist and anti-globalization forces that might dampen India’s growth prospects.
- The IT sector which was a boon for millions of graduates seeking class mobility in India (a ticket to the middle class) faces multiple challenges. The top Indian firms have not moved up the value chain and have not garnered opportunities in new technologies. Their growth is down to single digits. Hiring has slowed in recent years with 2017 seeing threats of major layoffs. The IT sector may no longer be a ticket to the middle class for most Indians.
- India has a peculiarly low Female Labour Force Participation rate and it has declined in the past 2 decades. All advanced economies and the other BRICS nations have a far higher female labour force participation rate.
- India has a massive informal economy riddles with low wages, low safeguards and protections for workers, low productivity and low scale. All economic miracles have been accompanied with a transformation of the labour force to a formal and organized employment. So far, the trend in India is worryingly in the opposite direction.
- India desperately needs an increase in financing to fund new businesses that will create jobs. But the Banking system is in terrible shape and credit growth is expected to be very slow that may dampen new firm creation unless we find new sources of financing.
- Software-driven automation might greatly polarize the job market — there will be a small portion of people with very-high paying very high-skill jobs and a large portion of people stuck in low-paying jobs. The availability of well-paying middle class jobs might be greatly reduced.
We should not fritter away opportunities like the super-majority of the current Government to enact bold reforms.
This article explores the above challenges in detail and provides some important suggestions.
Introduction
India has a median population age of 27.3 years compared to that of 35 years for China, 38 years for the United States and around 47 years for Germany and Japan. It is estimated that India has around 390 million millennials and about 440 million in the Gen-Z cohort. About 12 million people are added to the working age population every year. The world bank estimates around 200 million people will be added to the working age population between 2010 to 2030 in India.
Ageing demographics of many developed countries like Japan and countries in the EU is expected to be a major headwind in the economy. Even China’s working age population is expected to shrink rapidly (Figure 1)
Figure 1
Let us look at the projections (Figure 2) of the dependency ratio (the ratio of the dependent population to the working age population)
Figure 2
As we can see, major economies will be having very high dependency ratios… except India. India potentially sits on a massive demographic gold mine. India with its youth population could be the labour supply of the world in the future.
But then, we see a headline in the Hindu in Dec 2015 as follows:
The article begins: “Over 23 lakh candidates, including 2.22 lakh engineers and 255 Ph.D. holders have applied for 368 posts of peon in the State Secretariat. Thousands of candidates with Master’s degree in Commerce, Humanities and Sciences are also among the applicants, something which indicates the gravity of the unemployment situation in the State.”
A massive youth population without enough opportunities can turn what should be a demographic dividend into demographic disaster.
India needs to create a lot of jobs. From employment and unemployment surveys conducted by the NSSO indicate that between 2004-2012, the population in the age group of 15-59 minus students went up by 10.3 million a year. During the same period, the workforce engaged in agriculture declined by 4.4 million people a year. So, that makes a total potential workforce of 14.7 million (10.3 + 4.4) a year between 2004 to 2012. The actual jobs created during this time was only 6.5 million a year.
And it has gotten worse ever since.
The Government provides data for eight key labour-intensive sectors (Textile, Leather, Metals, Automobiles, Gems and Jewellery, Transport, IT/BPO and Handloom/Powerloom)
Figure 3
As we can see jobs in these eight sectors has dropped drastically over the years (Figure 3). Only 1.35 lakh jobs were created in these sectors in 2015. According to Government data, in IT/BPO (often a ticket for Indians to the middle class) job creation was 1.09 lakhs in 2013, 1.93 lakhs in 2014 and 0.76 lakhs in 2015. Note that at least 12 million people or 120 lakh people enter the working age population every year.
The Ministry of Labour and Employment puts the unemployment rate at 5%. But that doesn’t tell the complete story. The unemployment rate:
- Does not tell us how many people are looking for work. The same report gives the Labour force participation rate (people who are looking for work) as just 50%. That is only 50% of the working age population is looking for work. The other 50% are engaged in other activities like education or drop out to do domestic work, or just drop out of the workforce indefinitely and lose their skills. The report notes that the Labour force participation rate among women is just 23.7% (for urban women it is still a dismal 26.7%), i.e. a huge percentage of women drop out of the workforce
- Does not tell us about the quality of employment. A PHD candidate who applied for the Peon post mentioned earlier in the article, if he/she had been employed would be counted as an employed person. An engineering graduate who cannot find engineering work and ends up in a part time job would be counted as employed. Womenfolk who help with farm work for their families in villages would count as employed.
The dismal job growth has been surprising given the massive GDP growth.
Figure 4 (Google Public Data Explorer)
India’s growth has been second only to China for more than a decade and was the fastest growing economy in 2015. But the growth has not translated into employment creation as shown below.
Figure 5
The above graph (Figure 5) shows that for any meaningful employment creation, the GDP must grow at double digits, not an easy achievement. Only China has consistently grown at the level and the conditions at the time were very different (high external demand, one-party rule in China, boom part of the business cycle, lower automation etc.).
A NITI Ayog report had this to say:
“The committee also recognizes the urgent need for disruptive change; that bold reforms are the order of the day. India needs to generate 115 million non-farm jobs over the next decade, to gainfully employ its workforce and reap its demographic dividend”
- India needs to create lots of jobs (115 million non-farm jobs as mentioned above)
- India needs to create high-quality jobs. Remember that in the example where 23 lakh people applied for 368 peon jobs, if a PHD had got the job, he would be counted as employed. But that is incredibly sub-optimal. We need high quality jobs for our youth.
The Government believes that India needs to create 115 million non-farm jobs over the next decade. The data and trends we have seen thus far clearly illustrate that we are nowhere close to that number.
I believe, we are significantly underestimating the challenges to job creation.
I expect eight significant headwinds or challenges to job creation in the coming future.
Part 1 - Challenges to Job creation in India
- Massive Skill Deficit in India
The percentage of population that has acquired formal skill training is very low, by some estimates just 2%. The corresponding number is 68% in UK and 52% in US. Only 6.8% sign up for vocational training.
About 50% of the working population is still involved in Agriculture while the agriculture share of GDP is drastically declining (Figure 6).
Figure 6
In other words, Agriculture will not be able to support 263 million farm workers. A lot of them would have to move out in search of better opportunities but have few relevant skills.
Even among the ‘educated’ population, the skills picture is quite dismal. Various studies capture the skills deficit in the country. One study says that 47% graduates are unemployable. Another puts it at 80% for certain sectors. An ASSOCHAM study says 93% of management graduates are unemployable. The study also says that though 97% of graduates aspire for a job in IT and core engineering, only around 19% are employable in IT and around 7% are employable in core engineering.
By any measure, there is a major skills gap in the country. And time is running out.
In 2009, the previous Government set an (probably too) ambitious target of skilling 500 million people by 2022 (including many would enter the working age population later on).
The subsequent Government took on the mantle from the previous Government and set up a Ministry of Skill Development with the same target of 500 million.
But recently, the Government seems to have abandoned the target, saying, “It will be demand driven than supply driven”.
The official outcomes are not clearly known. In 2014-15, around 7.5 million people were trained against a target of 10.5 million. The next year around 11 million were trained. It is not clear how many of those trained are in jobs.
The NSDC (National Skill Development Corporation) website says around 37% of those (it) trained are placed in jobs (Figure 9)
Figure 9
We need to do much better, if we want to grab opportunities like China did. In India had a net enrollment of 5.5 million a year. China had 90 million.
By any measure, India faces a monumental task in skilling its population.
2. Far Fewer Manufacturing Jobs
Are there simply enough well-paying jobs for all Indians? Historically, for fast developing (and now advanced) countries and recently China, Manufacturing was seen as a ticket to the middle class. There were abundant jobs in manufacturing which lifted many people out of poverty.
The Government’s Make in India initiative puts Manufacturing front and center. Some of the key points in its vision document are as follows (emphasis mine):
- An increase in manufacturing sector growth to 12-14% per annum over the medium term.
- An increase in the share of manufacturing in the country’s Gross Domestic Product from 16% to 25% by 2022.
- To create 100 million additional jobs by 2022 in manufacturing sector.
- Creation of appropriate skill sets among rural migrants and the urban poor for inclusive growth.
- An increase in domestic value addition and technological depth in manufacturing.
- Enhancing the global competitiveness of the Indian manufacturing sector.
- Ensuring sustainability of growth, particularly with regard to environment.
The share of manufacturing in the country’s GDP increases when nations industrialize and then falls later taking a U-turn (as people have more money and invest it in services which becomes more important and expensive). Manufacturing as percentage of GDP has declined in almost all advanced economies as shown below (Figure 10).
Figure 10
China’s manufacturing share to GDP is also declining gradually (Figure 11).
Figure 11
The current share of manufacturing in India is about 17% of GDP. India if it industrializes strongly may probably increase manufacturing as % of GDP to the Government’s target of 25%. But there is a catch.
Will India be able to create 100 million additional manufacturing jobs while doing so?
Let us take some optimistic growth projections. GDP was 2.074 trillion dollars in 2015. Let us take a 7% growth in 2016 and 2017 and let us take a very optimistic 10% growth for each year till 2022. The GDP would be 3.82 trillion dollars. Let us say manufacturing makes 25% of GDP as targeted. The manufacturing output would be about 0.95 trillion dollars. Will this be able to create 100 million additional jobs?
For reference let us see the manufacturing output vs. employment for a country like United States.
Figure 12
The manufacturing employment stood at around 11.8 million people for about 1.8 trillion dollar of manufacturing output (Figure 12).
This has been the story of manufacturing over the past several decades. There has been tremendous productivity and automation in manufacturing. Notice something bizarre in the above graph? For all the regular election campaign rhetoric in the US about how manufacturing jobs are lost to China, manufacturing output has tremendously increased but automation and machines have replaced workers (Figure 13) and (Figure 14)
Figure 13
Figure 14
What about China? The same story repeats there (Figure 15).
Figure 15
Manufacturers have mostly increased capital and equipment rather than workers in their factories as shown below (Figure 16).
Figure 16
Even China is moving from labour intensive methods to capital intensive methods.
Its robot density (number of robots per 10000 workers) was lesser than the global average (Figure 17).
Figure 17
But it has been going on a robot buying binge for a few years and is the world’s biggest buyer of industrial robots. The Government is actively subsidizing this transformation through its Made in China 2025 initiative. Underline that - the Chinese Government is subsidizing automation! The Guangdong province is offering $137 billion in subsidies to about 2000 local companies that are looking to automate their plants. The Zhejiang province of China replaced nearly 2 million workers between 2013 and 2015. The city of Dongguan has replaced 87000 workers. One of the companies in that city - Changying Precision Technology Company replaced 90% of humans with robots - it now has 60 employees compared to the earlier 650. Its output has increased 160% and defect rate has decreased from 25% to 5%.
If India has to become a manufacturing powerhouse, then Indian manufacturers must also go about the same capital-intensive rather than labour-intensive methods. Otherwise, our industry may not be very competitive. The only jobs that have increased in manufacturing in the US are the high-skilled ones as shown below (Figure 18). The rest would sooner or later be replaced by machines.
Figure 18
And as we can see, the number of high skilled jobs added are very few.
Bottomline? The present and future of manufacturing is automation. There may be higher output but fewer manufacturing jobs. It is therefore a big challenge to create 100 million additional manufacturing jobs as envisioned by the Make in India initiative.
3. Lower External Demand
A key major headwind is likely to be the low external demand that we are continuing to witness post the 2008 recession. World economy is growing at a far slower pace than anticipated. A robust external demand is critical for production and in turn jobs.
More worryingly, even after the developed countries have had the lowest interest rates possibly in recorded world history (Figure 19), growth hasn’t picked up enough.
Figure 19
As the following graph shows (Figure 20), growth has been reduced to a trickle across the advanced and richer economies.
Figure 20
And if you measure recovery in terms of jobs, the recovery in the West from 2008 recession has taken far longer than the previous recessions as shown below. It took about 75 months to return to pre-recession employment - far longer than the previous recessions (Figure 21).
Figure 21
The low growth is not just due to the 2008 recession. Even without the financial crisis, growth would have fallen short of expectations (in the graph, No financial crisis scenario vs. CBO Projection) - (Figure 22)
Figure 22
That may be because of some fundamental structural reasons. One of them might be very high inequality. When there is high inequality, there can be lower demand (a person with $1 million income will consume far less than 100 people with $10,000 income because of decreasing marginal utility). The median incomes in the west have stagnated. For example, in the United States, median incomes have stayed flat since the 1970s (Figure 23)
Figure 23
There is no clear policy consensus in the West on how to tackle these problems and how to accelerate growth.
But the implications are clear. Low demand from the West can put a drag on growth in India and in turn on job creation.
China is a clear cut example of this. China produces a lot more supply than the actual demand. Its capacity utilization rates present a dire picture (Figure 24).
Figure 24
I have mapped China’s Debt-GDP ratio and the growth rate since 2007 (Figure 25).
Figure 25 (Sources here, here and here)
From 2014 to 2017, the growth rate has remained flat whereas the Debt-to-GDP ratio has increased from 236% to a whopping 304%.
China has to take on massive debt to keep maintaining its growth rate and is highly unsustainable.
Moody’s has recently downgraded China’s sovereign credit rating for the first time in almost 30 years.
India’s hopes of its economy growing in double digits would unfortunately be very dependent on the world economy which may not grow faster.
And for good employment creation, we may need such a growth rate because as we saw earlier, for some reason, employment creation in India is much lesser than the GDP growth rate.
4. Lower Hiring and Threats to the IT Sector
The importance of India’s IT sector cannot be overstated. The industry estimated at $150 billion employs around 3.5 million to 4 million people.
Mckinsey notes in 2016 “It (the Indian IT Sector) created almost 50 percent of all organized jobs in the past five years in India, that one sector”.
For many, the job in IT is a key ticket to the middle class.
But the IT sector will be facing challenges:
1. The IT services business model of charging billable hours for headcount might be disrupted in face of greater automation. The cost arbitrage may not be a significant value proposition going forward. In that case, the Indian IT firms will be facing a greater number of competitors selling piece-meal best-in-class solutions.
The IT sector growth has slowed down markedly over the past few years posting growth in the single digits recently (Figure 26).
Figure 26
2. Lower demand. Most of the revenue for top Indian IT firms come from banking clients in US and Europe. Their IT/BPO spending growth has decreased (Figure 27). The traditional application development business is growing relatively slowly.
Figure 27
3. The Indian IT firms have not yet successfully moved up the value chain. For example, their ‘Digital’ business offerings have far less revenue per employee compared to a company like Accenture and is not much different from their traditional lines of business (Figure 28). Below are the figures for 2015.
Figure 28
For example, the revenue per employee in the digital business of TCS was $48,780 whereas for Accenture it was more than 4 times that amount. The traditional businesses for TCS netted around $48500. So the digital business was not a significantly higher margin business.
The revenue per employee has decreased recently at the Indian IT firms as shown below (Figure 29).
Figure 29
4. Tighter immigration rules are expected from US which contributes to more than 50% of revenues for the top firms. This will mean companies may have to step up local hiring (in client countries).
In fact, Infosys has already announced plans to do the same.
Figure 30 (headline here)
Reuters reports — “India-based IT services firm Infosys Ltd plans to hire 10,000 U.S. workers in the next two years and open four technology centers in the United States, starting with a center this August in Indiana, the home state of U.S. Vice President Mike Pence.”
Hiring higher cost talent in client countries would mean Infosys margins would take a hit and they may have to trim the Indian workforce.
As mentioned earlier, the Indian IT firms so far have not been very successful in moving up the value chain. The efforts to move up the value chain also seem to be sub-optimal. Indian IT firms have notoriously stayed away from making critical acquisitions in new technologies like AI, IoT, Blockchain etc. that would boost their offerings. TCS for example except for a minor acquisition of a fellow subsidiary of its parent company (Computational Research Laboratories Ltd.) has not made acquisitions in new technologies. All of their acquisitions have been in their traditional business (Figure 31).
Figure 31
This despite TCS and Infosys sitting on piles of cash for a long time.
Figure 32 (headline here)
Recently both TCS and Infosys have decided to spend a significant amount of money in buying back shares rather than invest in critical acquisitions.
Figure 33 (headline here)
Figure 34 (headline here)
The headcount growth in top Indian IT has been decreasing since 2013 as shown below (Figure 35).
Figure 35
The IT firms have stepped up layoffs this year (Figure 36).
Figure 36
An aggressive activist investor Elliot Management has acquired a significant stake in Cognizant Technology Solutions which employs hundreds of thousands in India. In their letter to the management, the following were their key suggestions for operational improvements — almost all of which pointed to reducing the workforce. (emphasis mine)
“Cognizant’s delivery organization currently operates below industry benchmarks. One important factor is the Company’s maintenance of a deeper bench of unbillable trainees relative to peers, particularly onsite where costs are much higher. This carrying of excess bench capacity is an increasingly unnecessary drag in a maturing world with decelerating growth and fewer greenfield opportunities.”
“…There is an opportunity to streamline the sales function through an optimization of the complex matrix structure and selected selling roles, reduction of non-selling resources, and clarification of P&L responsibilities”
“…We have identified an opportunity to trim function sizes, specifically HR and Finance. Our analysis has revealed opportunities to improve management spans of control, eliminate redundancy throughout the organization and increase the level of process optimization.”
The composition of the workforce has also changed. Employees with higher experience make up a bigger part of the workforce which means higher costs for the companies. Below is the example of Infosys (Figure 37).
Figure 37
To protect the margins, they may need to cut down the workforce unless a lot of these mid-level employees can be reskilled.
Note that we have touched very less on the subject of automation in Indian IT jobs which is a big threat.
Figure 38 (headline here)
Bottomline — The Indian IT sector faces serious challenges and is struggling to find new growth drivers and in moving up the value chain. They have also stepped up trimming redundant workforce. Automation may displace a lot of workers who are involved in repetitive data entry and low level data analytics jobs. I’m afraid going forward, there will be fewer tickets to the middle class through an IT job.
India may become a hub for high end tech jobs but so far very few efforts have been made in that direction by the companies or by the educational institutions.
5. Low Female Labour Force Participation
The next major headwind to job creation is the unusually low female labour force participation — the number of women officially looking for jobs. As mentioned earlier, the official female labour force participation (FLFP) declared by the Government is only 23.7% and even in Urban areas, the FLFP is a poor 26.7%. This contrasts with a 75% labour force participation rate for men.
Claudia Goldin, a star labour economist famously hypothesized that the FLFP usually takes a U-shaped curve. When the overwhelming population is employed in agriculture, women have no other choice but to work. The FLFP is high. As incomes increase and employment share of agriculture decreases, women drop out of undesirable farm work as the household incomes increase. This brings down the FLFP. After this phase, more women get educated and go to college and take up well paying jobs again increasing the FLFP.
But in India, the problem seems to be peculiar.
The following graph (Figure 39) shows the trends in FLFP from UNDP in some developed countries and in the BRICS nations. The data is the relative labour force participation — (number of females looking for work) divided by (number of males looking for work).
Figure 39 (Source here)
We can see that India is peculiar in its low FLFP rate (for more than 2 decades). China started with a very high FLFP. And the two BRICS countries that had a low FLFP of less than 0.6 (Brazil and South Africa) have posted significant improvements. India’s female to male labour force participation has actually decreased over time.
The low relative rate is remarkable for another reason. India has made tremendous progress in enrollments across different stages of education. The following (Figure 40) is the number of females enrolled per hundred males.
Figure 40
The drop out rates are actually higher for boys than for girls in certain stages of education like primary education.
But the high enrollment has not translated into equal number of jobs for men and women. The reasons could be many, early marriage being one of them (though this trend is on a decline). High unorganized and informal employment characterized by lack of rules and contracts, lack of safety measures and highly irregular wages can also be holding women back. But these are problems that would take its own time to be corrected. And if the female labour force participation rate does not start making a steep U, we would be looking at a lot of wasted potential and productivity and household earning power.
6. Low Productivity, Low Firm Creation and Low Quality Jobs
India has a huge informal economy. The informal economy is plagued with low wages, no or unenforced labour contracts, low scale and low productivity. There is even a dearth of data on the informal economy.
The Government’s Labour Bureau in its Fourth Employment and Unemployment survey (2013–2014) made the following estimates:
“At all India level, 49.5 per cent persons are estimated to be self employed under the Usual Principal Status Approach followed by 30.9 per cent as casual labour. Only 16.5 per cent were (regular) wage/salary earners and the rest 3.0 per cent covered contract workers.”
“…In about 78 per cent of households, there is no (regular) wage/salary earning members”
India has a very low 2.24 people employed per establishment according to the 6th economic census. What is surprising is the people employed per establishment has gone down post liberalization (Figure 42)
Figure 42
More than 95% of establishments have between 1–5 employees. Only 1.37% of establishments had greater than 10 employees! This number was 3% in 1990 (Figure 43)
Figure 43
This data probably may not reveal much. If we take United States for example, 90% of firms have less than 20 employees (Figure 44).
Figure 44
But the small establishments with 1–5 employees employed 69% of the non-agricultural workforce whereas in 1990 they employed a lesser number (54%) of the workforce (Figure 45).
Figure 45
Establishments with >10 employees provided 37% of employment in 1990 whereas they provide just 21% of the employment in 2013. In contrast, in the United States, firms with >500+ employees provided about 50% of the employment (Figure 46). Firms with >20 employees provided with 80% of the employment (note that a lot of the <20 employees firms can be high tech and high productivity startups).
Figure 46
Unless we increase the share of formal employment, there will be very low productivity, low wages and low quality work.
Firm creation and more importantly creation of high productivity firms must drastically increase. It must be easy to start a business (India is ranked a dismal 130 in the World Bank’s ease of doing business). Much has been written about the reforms needed and I won’t rehash them here. But the trends are clearly worrying and we are not moving in the right direction with respect to the formal economy.
And this scenario can be improved only by new firm creation, stronger institutions, intellectual property rights, a vibrant capital market, removing unnecessary regulations etc.
7. Terrible shape of Indian Banking System and expected slow growth of Credit
A healthy credit market and credit growth is needed to finance India’s growth and firm creation which in turn creates jobs. But bad incentives and moral hazards seem to be rampant in India’s credit markets to say the least. Bad structuring of debt and malfeasance ends up in bad loans which slows down credit growth in the future.
India has the worst ratio of Non-Performing Loans to Gross Loans in Asia according to IMF (Figure 47) . Note that this does not take into account restructured loans.
Figure 47
The above data is for 2015. It has likely gotten even worse. Bad loans soared to 7.7 Lakh crores in FY 17. Private banks were at fault too. Bad loans at private banks increased 70% to around Rs. 85000 crores.
Public sector banks make up 70% of the banking system. According to McKinsey, the total stressed assets of of public sector banks stood at Rs. 8.53 lakh crores. But the combined net worth of of these banks were only Rs. 5.69 lakh crores! For Public plus Private banking sector, the total stressed assets were Rs. 9.6 lakh crores which is higher than the total sector’s net worth of Rs. 9.24 lakh crores.
The past bad lending may be coming home to roost. India’s bank credit growth in FY 17 was the slowest in 60 years. Loan demand from industrial sector (accounts for almost 40% of non-food credit) is at historical lows. (Figure 49)
Figure 49
The Interest coverage ratio (i.e. ratio of Operating income to Interest expense — in other words the amount of income available to pay interest) of Indian companies have dropped sharply as shown below (Figure 50). About 41% of companies have an interest coverage ratio <1 (Figure 51). That is, they don’t earn enough even to pay the interest expense.
Figure 50
Figure 51
Note the steep rise in firms having ICR <1 from 17% in Q1 2013 to 41% in Q3 2016.
Even Large-cap listed companies are seeing a dramatically falling Interest Coverage Ratio (Figure 52)
Figure 52
In other words, a lot of companies may end up not paying back the loans.
And banks have been continuing to make bad loans in the past six years. A Mint analysis shows that for firms with a median ICR < 1 between 2011 and 2016, the debt increase was Rs. 2.85 trillion. What was the total bank credit increase in that period to industry? Rs.7.65 trillion. That is one out of every three rupees in that period was unsustainable. Quoting Mint below (emphasis mine):
To be sure, it doesn’t mean that banks have been responsible for the total increase in debt of these financially weak firms since debt profiles of companies include corporate bonds, commercial papers, external commercial borrowings and other instruments.
Still, it does indicate that they are partly responsible for letting companies accumulate debt despite insufficient cash flows. For the top eight stressed accounts in the banking system, which are either under S4A or other bad loan resolution schemes, total debt doubled over five years even as ICRs crashed.
A large part of the debt given out to weaker companies, experts point out, were purely working capital loans that were used by such companies to often pay interest on their old debt. The net result, though, was that the overall debt of these companies kept rising, leading to unsustainable debt increases.
How did we even get here? It is worth quoting from Raghuram Rajan’s excellent speech in June 2016, ‘Why bad loans have been made’ (emphasis mine):
I will argue that the slowdown in credit growth has been largely because of stress in the public sector banking and not because of high interest rates.
…There are two sources of distressed loans — the fundamentals of the borrower not being good, and the ability of the lender to collect being weak. Both are at work in the current distress.
…Why have bad loans been made? A number of these loans were made in 2007–2008. Economic growth was strong and the possibilities limitless. Deposit growth in public sector banks was rapid, and a number of infrastructure projects such as power plants had been completed on time and within budget. It is at such times that banks make mistakes. They extrapolate past growth and performance to the future. So they are willing to accept higher leverage in projects, and less promoter equity. Indeed, sometimes banks signed up to lend based on project reports by the promoter’s investment bank, without doing their own due diligence. One promoter told me about how he was pursued then by banks waving checkbooks, asking him to name the amount he wanted. This is the historic phenomenon of irrational exuberance, common across countries at such a phase in the cycle.
…sensible lending means careful assessment up front of project prospects, which I have argued may have been marred by irrational exuberance or excessive dependence on evaluations by others. Deficiencies in evaluation can be somewhat compensated for by careful post-lending monitoring, including careful documentation and perfection of collateral, as well as ensuring assets backing promoter guarantees are registered and tracked. Unfortunately, too many projects were left weakly monitored, even as costs increased. Banks may have expected the lead bank to exercise adequate due diligence, but this did not always happen. Moreover, as a project went into distress, private banks were sometimes more agile in securing their positions with additional collateral from the promoter, or getting repaid, even while public sector banks continued supporting projects with fresh loans. Promoters astutely stopped infusing equity, and sometimes even stopped putting in effort, knowing the project was unlikely to repay given the debt overhang.
The process for collection, despite laws like SARFAESI intended to speed up secured debt collection, has been prolonged and costly, especially when banks face large, well-connected promoters. The government has proposed reforms to the judicial process, including speeding up the functioning of the Debt Recovery Tribunals, which should make it easier for banks to collect, but those legislative reforms are before Parliament. Knowing that banks would find it hard to collect, some promoters encouraged them to “double-up” by expanding the scale of the project, even though the initial scale was unable to service debt. Of course, the unscrupulous among the promoters continued to divert money from the expanded lending, increasing the size of the problem on bank balance sheets.
…The inefficient loan recovery system then gives promoters tremendous power over lenders. Not only can they play one lender off against another by threatening to divert payments to the favored bank, they can also refuse to pay unless the lender brings in more money, especially if the lender fears the loan becoming a Non-Performing Asset. Sometimes promoters can offer miserly one-time settlements (OTS) knowing that the system will ensure the banks can collect even secured loans only after years. Effectively, loans in such a system become implicit equity, with a tough promoter enjoying the upside in good times, and forcing banks to absorb losses in bad times, even while he holds on to his equity.
…Unfortunately, the incentives built into the public sector banking system have made it more difficult for public sector bank executives to follow these principles (I should add that some private sector bank executives have also not been immune on occasion). The short tenure of managers means they are unwilling to recognize losses immediately, and more willing to postpone them into the future for their successors to deal with. Such distorted incentives lead to overlending to or “ever-greening” unviable projects. Unfortunately, also, the taint of NPA immediately makes them reluctant to lend to a project even if it is viable, for fear that the investigative agencies will not buy their rationale for lending. The absence of sound and well documented loan evaluation and monitoring practices by banks makes such an outcome more likely. So excessive lending to bad projects and too little lending to viable ones can coexist.
Indeed India has one of the highest Debt-to-Equity ratios in Emerging markets (Figure 53) as this chart (from 2014)
Figure 53
Let us not even get started on the potential lakhs of crores of farm loan waivers further increasing moral hazards in the credit system.
We are not sure how much of this bad lending is malfeasance in sanctioning bad loans and how much is over-optimism or bad structuring. Either way, unless we fix our banking and credit system and tap new sources of financing, there is going to be very slow growth in financing new businesses that will hurt firm creation and in turn hurt job creation.
8. Threat of Software-driven Automation of Middle-Class Jobs
“We are being afflicted with a new disease of which some readers may not yet have heard the name, but of which they will hear a great deal in the years to come — namely, technological unemployment. This means unemployment due to our discovery of means of economizing the use of labor outrunning the pace at which we can find new uses for labor.” — John Maynard Keynes in Economic Possibilities of our Grandchildren (1930)
Carl Benedikt Frey and Michael Osborne of Oxford University in the now famous and highly cited paper, ‘The Future of Employment: How susceptible are jobs to computerization?’ (2013) predict that 47% of jobs are at risk of being automated. Economists Erik Brynjolfsson and Andrew McAfee in the book, The Second Machine Age and Martin Ford in the book, Rise of the Robots paint a dire picture of jobs being automated away. They say that not only ‘routine and non-cognitive’ jobs are being automated but also high paying white-collar jobs, the ‘non-routine cognitive’ jobs are in danger of being automated (real estate agents, loan officers, credit analysts, paralegals etc.) and they document examples where such capabilities are being improved.
Machine Learning and AI have made a lot of headlines over the past two years — AI can beat the best Go player in the world. AI can bluff its way into beating top Poker pros; AI has become better than humans at image recognition and speech recognition; AI performs better than doctors at diagnosing lung cancers; AI can arguably make a loan assessment better than human loan officers;
Economists Marteen Goos and Alan Manning propose a ‘job polarization’ hypothesis or ‘the lovely and lousy jobs’ hypothesis. After studying the UK labour market for years, they predict that technological change, especially related to information technology will increasingly lead to a scenario where only two types of jobs exist — very high-paying and very high-skilled jobs (lovely jobs) and low-paying low-skilled jobs (lousy jobs). They hypothesize that well-paying middle-class jobs will be automated by technology.
I agree with the hypothesis. Many professions with intervention from technology have become incredibly scalable. Take the example of a loan officer or an insurance agent. It is a decent paying middle class job. But given enough data about a customer, an algorithm can better make a decision whether to provide a loan to a borrower or what premium to charge a customer. And it can do it at incredible scale, possibly making loan decisions for millions of customers in a single day (whereas loan officers can process 100 applications a day?). A teacher (lecturer) can lecture to probably 100 students at once in a classroom? With the internet, a single teacher who is highly demanded by students can reach millions of students at once. Such decent-paying jobs might be eliminated (though to be noted that technology will ensure cheaper loans and far cheaper education in the above examples). But paradoxically it is difficult for machines to automate very low-paying jobs (like picking garbage or cutting onions). A number of prominent economists have come to the same conclusion. Erik Brynjolfsson and Andrew McAfee (mentioned above) write about it in their book, The Second Machine Age. Tyler Cowen comes to the same conclusion in his book, Average is Over.
The United States Government towards the end of 2016 released a report, “Artificial Intelligence, Automation and the Economy”. The report touches on the uncertainty of jobs in the future in the face of automation.
In recent years, machines have surpassed humans in the performance of certain tasks related to intelligence, such as aspects of image recognition. Experts forecast that rapid progress in the field of specialized artificial intelligence will continue. Although it is unlikely that machines will exhibit broadly-applicable intelligence comparable to or exceeding that of humans in the next 20 years, it is to be expected that machines will continue to reach and exceed human performance on more and more tasks…
AI-driven automation will continue to create wealth and expand the American economy in the coming years, but, while many will benefit, that growth will not be costless and will be accompanied by changes in the skills that workers need to succeed in the economy, and structural changes in the economy. Aggressive policy action will be needed to help Americans who are disadvantaged by these changes and to ensure that the enormous benefits of AI and automation are developed by and available to all.
AI should be welcomed for its potential economic benefits. Those economic benefits, however, will not necessarily be evenly distributed across society. For example, the 19th century was characterized by technological change that raised the productivity of lower-skilled workers relative to that of higher-skilled workers… In contrast, technological change tended to work in a different direction throughout the late 20th century. The advent of computers and the Internet raised the relative productivity of higher skilled workers.
Today, it may be challenging to predict exactly which jobs will be most immediately affected by AI-driven automation. Because AI is not a single technology, but rather a collection of technologies that are applied to specific tasks, the effects of AI will be felt unevenly through the economy. Some tasks will be more easily automated than others, and some jobs will be affected more than others — both negatively and positively. Some jobs may be automated away, while for others, AI-driven automation will make many workers more productive and increase demand for certain skills. Finally, new jobs are likely to be directly created in areas such as the development and supervision of AI as well as indirectly created in a range of areas throughout the economy as higher incomes lead to expanded demand.
AI, though, may allow machines to operate without humans to such a degree that they fundamentally change the nature of production and work. It may be that the question is no longer which segment of the population will technology complement, but whether the new technology will complement many humans at all, or if AI will substitute completely for much of human work. The skills in which humans have maintained a comparative advantage are likely to erode over time as AI and new technologies become more sophisticated. Some of this is evident today as AI becomes more capable at tasks such as language processing, translation, basic writing, or even music composition
AI-driven technological change could lead to even larger disparities in income between capital owners and labor. For example, Brynjolfsson and McAfee argue that current trends in the labor market, such as declining wages in the face of rising productivity, are indicative of a more drastic change in the distribution of economic benefits to come. Rather than everyone receiving at least some of the benefit, the vast majority of that value will go to a very small portion of the population: “superstar-biased technological change.” Superstar-biased technological change is somewhat similar to skill-biased technological change, but the benefits of technology accrue to an even smaller portion of society than just the highly-skilled workers. The winner-take-most and winner-take-all nature of the information technology market means that the fortunate few are likely to emerge as victors of the market. This would exacerbate the current trend in the rising fraction of total income going to the top 0.01 percent
In theory, AI-driven automation might involve more than temporary disruptions in labor markets and drastically reduce the need for workers.
Software driven Automation can greatly reduce the available well-paying jobs and can put incredible wage-pressure on these jobs.
To recap and summarize the challenges discussed thus far:
- There is massive skill deficit in India. We churn out lots of graduates but with poor skills. Successive Governments have not yet been successful to find a model to scale up training and skilling needed for tens of millions of Indians. India has to rapidly scale up its stock of skilled labour if it has to grab key economic opportunities.
- There are likely to be far lower manufacturing jobs for a given output. Automation and productivity has been improving tremendously in Manufacturing. The consequence might be that India may not be able to follow the trajectory of other Asian economic miracles like Japan or China. The current manufacturing superpowers are rapidly scaling automation.
- We are living in a low growth world. Advanced economies are growing slowly and aggressive policies have seen less than spectacular results. There has been a noticeable upswing in protectionist and anti-globalization forces that might dampen India’s growth prospects.
- The IT sector which was a boon for millions of graduates seeking class mobility in India (a ticket to the middle class) faces multiple challenges. The top Indian firms have not moved up the value chain and have not garnered opportunities in new technologies. Their growth is down to single digits. Hiring has slowed in recent years with 2017 seeing threats of major layoffs. The IT sector may no longer be a ticket to the middle class for most Indians.
- India has a peculiarly low Female Labour Force Participation rate and it has declined in the past 2 decades. All advanced economies and the other BRICS nations have a far higher female labour force participation rate.
- India has a massive informal economy riddles with low wages, low safeguards and protections for workers, low productivity and low scale. All economic miracles have been accompanied with a transformation of the labour force to a formal and organized employment. So far, the trend in India is worryingly in the opposite direction.
- India desperately needs an increase in financing to fund new businesses that will create jobs. But the Banking system is in terrible shape and credit growth is expected to be very slow that may dampen new firm creation unless we find new sources of financing.
- Software-driven automation might greatly polarize the job market — there will be a small portion of people with very-high paying very high-skill jobs and a large portion of people stuck in low-paying jobs. The availability of well-paying middle class jobs might be greatly reduced.
Lack of (quality) jobs combined with fast rising prices is a ticking time bomb waiting to explode. (At the risk of sounding alarming) Lack of jobs creates its own second order effects like high social unrest, depression, lack of faith in institutions, high crime etc. We are in danger of creating a ‘lost generation’
India needs jobs and fast
Part 2 — Suggestions — The Difficult, Grinding and Long-Term Answers
There are no easy, short term, magic wand solutions to the jobs problem. How are jobs really created?
- Entrepreneurs tinker, experiment and create products and solutions
- Some of these solutions use the right combination of technology and business model to solve a problem for customers.
- They get funds or financing from friends, family or investors to serve many customers.
- They hire employees to expand the market and scale solutions to many customers.
- Some of these companies become big and hire tens of thousands of employees.
- Workers/employees take home a healthy part of the wealth created as wages and their wealth is further increased by the problems solved and prices lowered by different companies
- New entrepreneurs attack the incumbent companies or create solutions for unserved markets. In both cases, they reach more customers and create more jobs.
Rinse and Repeat. This process has to continue for affordable solutions to be created for different needs and wants of people and jobs to be created as a consequence.
The following are the preconditions for the above process of job creation:
- Entrepreneurs have the ability/skill to come up with solutions that are affordable to many people
- There are no unnecessary regulations that prevent entrepreneurs from forming companies and taking their solutions to the market.
- There is a skilled workforce that can be hired by entrepreneurs to improve solutions and scale
- There is an active, competent, competitive and non-corrupt financing and credit industry that funds new businesses and entrepreneurs
- There are strong institutions that protect property rights, intellectual property rights and enforces relevant rules, laws and regulations that are geared towards promoting innovation and encouraged problem solving.
- The Government ensures that it does not favour particular companies and does not picks winners and losers
- There is an underlying effective ‘infrastructure’ that raises productivity and that enables innovators and entrepreneurs to quickly build and scale solutions. Roger Martin describes three such infrastructures:
Physical Infrastructure — the shared, built resources that meaningfully enable and advance our standard of living. Examples are Transportation System (Roads, Bridges, Railways etc.), Internet, Bank Accounts, Electricity, Health systems etc.
Transactional Infrastructure — the set of rules, decision-making institutions and mechanisms that allow a society to exchange goods and services. Examples are legal systems that are fast and fair, voting systems, corporate governance rules, capital markets and rules and standards that reinforce trust in these capital markets, consumer protection rules, labour laws, environmental regulations etc.
Knowledge Infrastructure — the complex set of systems that allow fluid transfer of knowledge, values and culture. Eg. Schools and Universities
In my opinion, we cannot short-circuit the above pre-conditions. The answer to create well-paying jobs would be to checkmark ‘All of the above’. Ensuring the above pre-conditions is a long term multi-year project that needs strong focus and commitment from society and Government and has no short answers but these need to be prioritized as soon as possible.
There are some clear opportunities that we should not fritter away, like the current Government’s super majority that it can use to bring about foundational reforms that will yield long term rewards.
Here are a few of my suggestions.
1. Increase and Overhaul Government Spending on Education and…
The Government of India spends Rs. 79,685 crores on education (Rs. 46,356 crores on primary education and Rs. 33,329 crores on the rest). The world average for Government spending on education is 4.7%. India spends around 4% on education. Brazil and South Africa spend around 6% of GDP. The United States spends around 5.4% of GDP. (source: World Bank data).
Therefore, India spends lesser than the world average. This spending ratio would be even worse, if we take into account the massive youth population difference between the different countries. Ideally we should be spending much more than the world average.
Should we increase spending on Education?
In my opinion, the more important question to ask is how we spend that money. How much money currently spent is wasted? How effective is the current spending? What outcomes are we getting for the current spending? Are we spending money on the right things?
As noted earlier, the enrollment numbers have increased. For example, we have only 3.1% of children not enrolled in a school. (source for following four figures here)
Figure 54
But overall the education outcomes have gradually become worse than a decade earlier. The Annual Status of Education Report (ASER) over the years reveal this.
The percentage of children in Standard V who can read a standard II level text has decreased from 59% in 2007 to 48% in 2016. Think about that. Less than half the students in Class V can read a Class II level text.
Figure 55
The percentage of children in Standard V who can division has reduced from 42% to 26%.
Figure 56
Only 25% of children in Standard V can read English sentences.
Figure 57
We are not only getting bad outcomes, we are consistently getting worse outcomes year on year.
Many times, governments do not just spend money inefficiently, they sometimes don’t spend at all! The Government collects 3% Educational Cess on the tax payable or tax due (2% for primary education and 1% for secondary and higher education).
According to a report in 2015, it was estimated that Rs. 77,000 crores of Education Cess collected was lying idle (Figure 58)!
Figure 58
The CAG report in 2015 notes:
“The Secondary and Higher Education Cess (SHEC) was introduced in the Finance Act, 2007 to fulfil the commitment of secondary and higher education. Scrutiny of the Union Finance Accounts for the period 2006–15 showed that a total collection of SHEC of ` 64,228 crore had been made. However, unlike the creation of PSK (Parambarik Shiksha Kosh) in the case of primary/elementary education cess, neither a fund was designated to deposit the proceeds of SHEC thereto nor schemes identified on which the cess proceeds were to be spent. Consequently, the commitment of furthering secondary and higher education as envisaged in the Finance Act was not transparently ascertainable from the Union Accounts. Thus, the possibility of the diversion of funds for purposes not mandated under the Finance Act cannot be ruled out.”
Figure 59
And more and more schools (primarily public schools) are becoming inefficient. About one-third of ‘schools’ have less than 50 students in them (highly underutilized). (Figure 59)
The state of school education has been dismal. About 65% of the students are enrolled in public schools (Figure 60).
Note: compiled by Geeta Kingdon for 20 states
Figure 60
But as shown above, this is a declining number. Parents of students are voting with their feet and wallets by preferring private schools vs. public schools. Between 2010–11 and 2015–16, student enrollment in Government schools in 20 states fell by 13 million while enrollment in private schools in these states increased by 17.5 million. More and more parents are willing to pay a fee to go to private schools while in public schools they can study for free until the age of 14.
And it is estimated that about 71 million students (26% of all students) attend private tuition classes primarily to augment their learning with the prime reason being augmenting their basic learning highlighting the state of education.
Karthik Muralidharan of UC San Diego and Venkatesh Sundararaman of World Bank conducted a rigorous two and a half year experiment in Andhra Pradesh on outcomes from Private and Public schools. They randomly selected students and provided them with a voucher to attend private schools. They found no difference between test scores in private and public schools but the cost of private schools was only one-third the cost of public schools.
They further note:
“The main operating difference between private and public schools in this setting is that private schools pay substantially lower teacher salaries (less than a sixth of that paid to public school teachers), and hire teachers who are younger, less educated, and much less likely to have professional teaching credentials. However, private schools hire more teachers, have smaller class sizes, and have a much lower rate of multi-grade teaching than public schools. Using official data and data collected during unannounced visits to schools, we find that private schools have a longer school day, a longer school year, lower teacher absence, higher teaching activity, and better school hygiene. We find no significant change in household spending or in time spent doing homework among voucher-winning students, suggesting that the impact of school choice on test scores (if any) is likely to be due to changes in school as opposed to household factors.”
So, with the same (dismal) outcomes, private schools take one-third the cost to produce an unit of education compared to public schools.
There is no question that the Government must substantially increase its spending on education. To put things in perspective, just two states Maharashtra and Uttar Pradesh have allocated Rs. 70,000 crores for Farm Loan waivers. The TSR Subramanian committee tasked with preparing a new education policy for India has recommended the outlay for education to be raised to 6% of GDP “without further loss of time”. It has also asked for the mid-day meal scheme to be extended to cover students of secondary schools. The total central budget for education is Rs. 78,000 crores.
But the Government must rethink the way it spends its money. With the mass implementation of Aadhar cards, welfare fraud is likely to be minimal. The Government can target pincodes where poverty is prevalent and provide Direct Cash Transfers for the purpose of education. Direct cash transfers (conditional transfers if necessary) will empower the poor to choose among private education service providers. It will also drastically reduce the leakages in education spending (and corruption) and reduce wasteful spending.
Similarly, conditional direct cash transfers can be given to youth to be used with skill development service providers.
But real transformational change cannot happen without the next suggestion…
2. …unbundle Education
Currently, Education (world over) is structured in a very rigid and inflexible manner. For example, the number of years for a typical education is very rigid.
(Figure 61)
Also, there is rigidity in knowledge and certification. For example:
- There are regulations that sometimes mandate maximum pupil-teacher ratio
- The college that imparts knowledge to the student also certifies
- There are regulations around the curriculum a student or college imparts to students
and so on…
A lot of these rules and regulations regarding curriculum, knowledge and certification are:
- Relics of a bygone industrial age and haven’t changed in years to reflect current and future economy and current skill sets needed.
- Do not have any strong fundamental theory or insight for the way it currently is
- One-size fits all approaches that commoditizes students
- Allows for no intervention of technology and hence no improvements in cost and scale
- Allows for no significant experiments and hence no significant improvements in the method of education
India must lead the way in pioneering the Unbundling and Transformation of Education.
If I take technical education for example, the following form the components of a technical education, what I call the Education Bundle.
Figure 62
Note that all of the above are done by the same university that I enroll in.
This leads to tremendous rigidities:
- A student can opt only for a fixed curriculum determined by the university
- If the university mandates a four year time frame for completion, a student cannot complete his education and receive credentialing within (say) two years even if she is fully qualified to and has completed all the requirements.
- The student cannot choose one part of the bundle. If a student just wants to use only lecturing, that won’t be possible. The student must opt for the entire bundle. The student cannot opt out of the bundle as well. If the student does not use the sprawling sports facilities, she cannot opt out of paying for it. The student must pay for the entire bundle.
Instead we must unbundle Education.
Figure 63
Unbundling can allow for great outcomes in Education. An example scenario as follows:
Figure 64
Unbundling education will greatly reduce costs because of the following:
- It allows certain components of the Education Bundle to scale because of technology. Lecturing and Curriculum will greatly scale. One teacher (the best in her subject) can arguably reach millions of students.
- Certification is not contingent on spending years in college. There will be one service provider who can crack the problem of certification who can assess a student however and wherever he/she gets her knowledge from. This is very crucial. This will greatly eliminate the artificial constraint on number of ‘degrees’ handed out by prestigious institutions and will greatly reduce costs to the student.
- Students need not wait four years to complete (say) a technical education. This creates right incentives. The earlier the student masters the program/skills, the earlier she can be certified and hence the lower will be her costs.
- There will be an explosion in variety in curriculum. Imagine a 1000 different topics. The student can tailor her own ‘playlist’ that fits her goals and expectations of the market. For example, a student can choose a course about business innovation + a course about environmental science + a course about tail risks. Or a course in 3D printing + Jewellery making + Entrepreneurship.
- Education NPAs are at an all time high. Reduced costs will bring down the potential debt of students.
The standardization of education — the system we currently have is insanely unfair to students, is expensive and creates unnecessary artificial scarcity. Only with a non-standardized form of education and where many components scale because of technology, high quality education can be affordable to most students in India and India can have a very skilled workforce.
There is no time. The costs of the present ‘artificial scarcity’ standardized model is increasing drastically (Figure 65).
Figure 65
3. Reforms to encourage Firm Creation
India needs high quality and innovative companies that solve difficult problems and in the process create high quality, well paying jobs.
There are four key elements of a pro-innovation policy by the Government to boost firm creation:
a. Ease of Firm Creation and Doing Business
It must be easier to start companies. India has a dismal rank of 130 in World Bank’s Ease of Doing Business. The breakup of the components is interesting (Figure 66).
Figure 66
Some components have gotten better like ‘Getting electricity’ but other components need a lot of work. The Government though has been working in the right direction on a number of them like ‘Resolving Insolvency’ and ‘Enforcing Contracts’. It remains to be seen when we will be able to see good results. For example, in India it takes 26 days to start a business whereas in New Zealand it takes only half a day!
Improvements on these parameters would kick-start a virtuous cycle of financing, firm creation and job creation. I expect this would also gradually bring in many of the high-skilled Indians currently working abroad back to India (11 of the 87 billion-dollar tech startups in United States was founded by Indian immigrants).
We should want our world-class IIT students to start companies in India by making it easy to start businesses in India. After all, relative to the total spending on higher education in India, the Government spends a fortune on IITs and NITs as shown below (Figure 67). We should ensure they start companies here and create jobs here in India.
Figure 67
b. Entrepreneurship Visas
In a low-growth world, India offers a large market with many problems unsolved with many problems having a very unique context. A lot of these problems have to be solved through technology. India must fast track ‘entrepreneurship visas’ to tech firms and startups abroad combined with ease of starting businesses. Countries like United States, China, Japan and South Korea have far higher talent when it comes to new technologies like AI, Machine Learning and Robotics (a substantial number of them being Indian immigrants themselves; More than 130,000 students went to US schools in 2015). We need to tap this talent to solve problems in India and in the process create jobs.
c. Stronger Consumer Protection Laws
The other side of the coin of allowing businesses to be founded easily are having robust consumer protection laws. All the countries at the top of the list of Ease of Doing Business have robust consumer protection laws with strong redressal systems.
d. Ensure a healthy Banking system
As mentioned earlier, India’s banking sector is in deep trouble. India needs to reform its banking system, clean up the banking balance sheets and remove bad incentives and moral hazards and restore healthy credit growth. To quote Raghuram Rajan:
Given, however, that public sector banks are much bigger than private sector banks, private sector banks cannot substitute fully for the slowdown in public sector bank credit. We absolutely need to get public sector banks back into lending to industry and infrastructure, else credit and growth will suffer as the economy picks up.
4. Encourage Business models in Education and Skill Development that align incentives of service providers and students (customers)
Currently, the incentives of Education and Skill Development service providers and students are not aligned. Governments have been distorting the market for education by providing easy access to education loans which increases demand and shoots up prices of education. The service providers can provide extremely low quality education and skill development and still get paid by students and worse still, the students are on hook for the debt incurred if any (banks in Tamil Nadu alone have given an estimated Rs. 16,381 crores of which Rs. 1875 crores are deemed non-performing assets). Students cannot ask for a refund from the service providers if they don’t get a job or end up getting low quality jobs.
We must encourage business models that align incentives of service providers and students. In other words, service providers must succeed only if students succeed. Government must fast track approval of service providers with such business models.
Below is one such business model of ‘study first, pay later’. (Figure 68)
Figure 68
The above model can be applied to both Education and Skill Development Service Providers. The model greatly aligns incentives of service providers and students:
- Service providers get paid only when students get a job. Or else they are not paid.
- Service providers automatically have a high incentive to invest in good curriculum and good teaching and also partner with companies to provide the skill development they need.
- Students don’t incur debt. If they don’t get a job, they don’t pay.
- The service providers takes the risk of the downside (student doesn’t get a job) but also participates in the upside (student gets a very well paid job in which case service provider gets paid very well).
But a precondition for such models to be successful is the flexibility of service providers as mentioned in ‘Unbundling Education’ before.
5. Prepare for the ‘Peak Jobs’ scenario
By ‘Peak Jobs’, I mean a scenario where enough well-paying jobs for everybody is structurally impossible to achieve. As mentioned earlier, software-driven automation might greatly reduce the availability of well-paying middle-class jobs. There maybe very few very high-paying jobs and few or many low-paying jobs. There may not be be a great need for extensive human labour in the production process.
The only solution in such a scenario is to rethink alternative approaches for resource allocation other than the ‘wages for jobs’ model. We may need to massively rethink, redesign and greatly increase welfare and redistribution. Some solutions are vigorously being proposed and debated like UBI (Universal Basic Income) where everyone gets a fixed income every month regardless of the employment status. The Government must actively pursue these discussions.
That is the end of this long post! The above suggestions may not be enough but the challenges and headwinds mentioned definitely exist. We need to be aware of them and solve for it lest we end up with Demographic Disaster.
