Do it yourself: Unemployment

Showing posts with label Unemployment. Show all posts

Tuesday, April 22, 2025

Focus on affordability quotient not inflation

The rate of Consumer Price Inflation (CPI) in India dropped to 3.34% in the month of March; below the lower bound (4%) of the regulator’s (RBI) target band of 4% to 6%. It is definitely a significant development insofar as the monetary policy consideration, macroeconomic stability, and consumer confidence are concerned.

If this trend sustains, it would pave the path for further easing in the monetary policy; improve the fiscal outlook; improve the outlook for debt and currency markets; aid corporate profitability and encourage fresh investment flows. In this sense, it is certainly good news for the investors in Indian financial markets in the near-term.

However, in my view, a low inflation rate does not help a large section of the Indian population much. A low inflation rate only implies a slower rise in the price level as compared to the prices in the base period. It offers no relief to the people who are already finding the existing prices of the essential goods and services unaffordable. A slower rise, not matched by a similar rise in wage level, just makes the living conditions even more challenging.

Apples at Rs300/kg and Mangoes @Rs180/kg are unaffordable for many middle-class households, even though their annual inflation rate may be close to zero.

Over the past two decades, nominal wage growth has often lagged or barely matched CPI inflation, especially for informal and unskilled workers. This has led to stagnant or declining real wages, exacerbating affordability challenges.

This trend, juxtaposed with poor new job creation, implies a further squeeze on the struggling middle class of India. The growth rate of private consumption, which constitutes approximately 60% of India’s GDP, will decelerate. Household savings which have cushioned the fiscal balance since independence, will erode even faster. A significant section of middle-class households may slither into a debt trap. Investment rate will deteriorate. The economy will get stuck in a vicious cycle of poor savings rate-low investment rate-lower economic growth-lower household income growth-poor savings rate.

Wage dynamics in India

As per the latest Annual Report (2023-24) of the periodic Labour Force Survey (PLFS):

· Labour Force Participation Rate (Ratio of workers employed and willing to work to the total population) in India is ~46%. The worker population ratio (WPR) is slightly lower at ~43%.

· Of the total Worker population (WP), 58% workers are self-employed (39% work on their own account and 19% family members helping these own account workers). Only 22% of WP is employed in a regular salaried job. ~20% of WP is casual workers.

· Regular wage workers (22% of WP) earn on average Rs700/day wage. Self employed workers earn on an average Rs463/day wage. Casual workers earn on an average Rs433/day wage.

· About 90% of WP is employed in the informal sector, with mostly undefined social security and poor job guarantee.

· Job creation has been a persistent challenge. The PLFS data shows unemployment rates hovering around 6–8% from 2017–2023, with youth unemployment (15–29 years) exceeding 15%. Formal job growth has been sluggish, with only ~10% of the workforce in organized sectors. The IT and services sectors, traditional middle-class job engines, face slowdowns due to automation and global competition.

· In the past decade or so, wages of the regular salaried employees have risen at 3.7% CAGR; while casual and self-employed have experienced 2-3% CAGR in their earnings. CPI index in the 2013-2025 period has risen at 5.5% CAGR. The affordability quotient of middle classes has obviously diminished.

It is pertinent to note that “Nominal wages grew faster (6–10%) in the 2000s due to MGNREGA and economic growth but slowed to 2–4% post-2015, lagging inflation.

Implications of diminishing affordability quotient

The combination of stagnant real wages and poor job creation has put a squeeze on middle-class disposable income, reducing their ability to consume and save. This is particularly acute for the lower middle class, who lack the financial cushion of wealthier households.

· Private Final Consumption Expenditure (PFCE) accounts for ~60% of India’s GDP. PFCE registered a growth rate of 6–7% in the 2000s and early 2010s. In the past five years PFCE growth rate has slowed to 4–5% due to economic shocks like demonetization, GST implementation, and the COVID-19 pandemic. Recent trends are indicating a recovery in consumption, with PFCE growth projected at 5–6% for FY25, driven by rural demand and government transfers. However, urban middle-class consumption continues to remain subdued.

Stagnant real incomes and high absolute prices (e.g., food, fuel, education) have adversely affected the discretionary consumption (e.g., durable goods, travel) of households. For example, automobile sales, a proxy for middle-class spending, grew only 2–3% annually post-COVID, reflecting affordability challenges.

· Household savings have been quintessential to India’s fiscal stability, financing investment, fiscal deficit and cushioning the current account deficit. Gross household savings averaged 20–25% of GDP in the 2000s but have since declined to 17–19%. Financial savings (e.g., bank deposits, mutual funds) have fallen from 10–12% of GDP in the early 2010s to ~7% in 2022–2023.

A sustained decline in household savings reduces the pool of domestic capital available for investment, increasing reliance on foreign inflows or government borrowing. This is straining India’s fiscal balance and public investment. Erosion of savings is also making middle-class households vulnerable to economic shocks.

· Household debt in India has risen steadily, from ~10% of GDP in the early 2000s to 40% by 2023. Retail loans (e.g., housing, personal, credit card debt) grew at 15–20% annually post-2015, far outpacing income growth. Middle-class households are increasingly relying on debt for housing, education, and consumption (e.g., EMIs for durables).

If real incomes stagnate and job creation lags, households may struggle to service debt, especially with rising interest rates. A debt trap would further erode savings, reduce consumption, and increase financial instability, as households divert income to debt repayment. This could also strain the banking sector, reducing credit availability for investment.

· Gross Fixed Capital Formation (GFCF), a measure of investment, averaged 30–32% of GDP in the 2000s and has fallen below 30% by 2024. In particular, corporate capex has remained slow, despite a variety of government incentives. Declining household savings has on one hand reduced the available domestic capital pool for investment; while on the other hand poor demand growth visibility is also discouraging new capacity building in many areas.

· Declining household savings has adversely affected bank deposits, constraining credit for small and medium enterprises (SMEs), a key investment driver. RBI data shows SME credit growth slowing to 10–12% from a high of 18-20%.

Conclusion

While low CPI is welcome, it does not address affordability issues. It is critical to not lose focus on managing the price situation and improve the affordability quotient of households. The urgency of implementing structural reforms cannot be emphasized more at this point in time.

Massive efforts and pragmatism are needed in the areas of agricultural productivity enhancements, education & skilling of workers, improving women workforce participation rate, making education, housing and healthcare costs affordable for households. A strong wage indexation mechanism could also help improve the affordability quotient.

Thursday, December 5, 2024

Status of households’ quality of life

The National Sample Survey Organization (NSSO) released results of the Comprehensive Annual Modular Survey 2022-2023 a few weeks ago. The survey made many interesting findings. Some of the key findings could be listed as follows:

Primary school enrollments: Among persons of age group 6 to 10 years, about 90.5% in rural areas and 89.2% in urban areas are currently enrolled in primary education.

25% of rural children and 20% of urban children who never enrolled in school, did it because they were not interested in studies. Another major reason for non-enrollment was “parents not interested in sending them to school”.

Among persons aged 15-24 years, around 97.8% of males and 95.9% of females are able to read and write short simple statements in their everyday life with understanding and are also able to perform simple arithmetic calculations.

Secondary education: In urban areas, only 56.6% persons of age 25 years and above have some secondary education. Whereas, in rural areas, this ratio is much lower at 30.4%.

Only about one third of all graduates were science and technology graduates.

Financial inclusion: Around 94.6% of adults have an account individually or jointly in any bank/other financial institution or with mobile money service providers at all-India level. More adults in rural areas have bank accounts as compared to the urban areas.

Digital access and skills: About 94.2% of rural households and about 97.1% of urban households possess telephone and/or mobile phones. About 59.8% of people above the age of 15years have access to the internet.

Among persons aged 15-24 years, around 78.4% reported the execution skill of ‘sending messages (e.g., e-mail, messaging service, SMS) with attached files (e.g., documents, pictures, video)’. In the same age group, around 83.6% of males and 72.7% of females reported execution of the above skill.

About 38% of people were able to perform online banking transactions. (30% in rural areas and 40% in urban areas). Only 17% in rural areas and 37.7% female in urban areas were however able to make an online banking transaction.

Access to Transportation: Around 93.7%t of the urban population has convenient access to low-capacity public transport within 500 meters from the place of living.

About 94% of the rural population has access to an all-weather road within 2kms from the place of their residence.

Cost of healthcare: The average medical expenditure per household on hospitalization during a year is Rs 4,496 in rural areas and Rs 6,877 in urban areas whereas the average out-of-pocket monthly medical expenditure per household on non-hospitalization during is Rs 545 in rural areas and Rs621 in urban areas.

Out of the average medical expenditure, about 91% in rural areas and 76% in urban areas was borne by the households. This implies public healthcare services in rural areas are much worse as compared to the urban areas.

Clean cooking fuel: About 63% of households use clean cooking fuel. The proportion is much less in rural areas (49%) as compared to urban areas (93%).

Unemployment: Around one fourth of the youth in the 15-29 years age group reported to be not in education, employment, or training. The ratio was highest in rural females (over 46%).

Indebtedness: Around 18.3% of adults have some outstanding loan. Rural adults are more likely to have a loan than an urban male. Male indebtedness is much higher as compared to the female indebtedness.

Wednesday, August 28, 2024

Employment- Gender gap and skill mismatch remain alarming

The latest Periodic Labor Force Survey (PLFS), released on 16 August 2024 by the National Statistical office (NSO), provides some useful insights into the current employment conditions in the country. The following are some of the key observations from the Survey report.

The Good

· The employment conditions have improved during 1QFY25. The WPR-U improved for all ages and both genders. The Youth WPR-U improved from 39.3% (1QFY24) to 40.8% (1QFY25). For all workers, WPR-U improved 38.4% to 39.3% during this period.

· The LFPR-U male workers improved from 57.2% in (1QFY24) to 58.9% in (1QFY25) for youth (15-29yrs) and from 73.5% to 74.7% for all workers above 15yrs of age.

· Self-employed female workers increased in urban areas from 39.2% to 40% while the number of self-employed male workers in urban areas increased from 39.5% to 40%.

· Unemployment rate in urban areas has reduced marginally from 6.7% (1QFY24) to 6.6% (1QFY25).

The Bad

· The percentage of regular wage/salaried employees fell marginally from 49.2% in 1QFY24 to 49% in 1QFY25. There was a corresponding increase in the own account and self-employed workers.

· The employment in the secondary sector (manufacturing, mining etc.) was lower in 1QFY25. More people were employed in the tertiary sector. Worker employed in the secondary sector reduced from 33.1% in 1QFY24 to 32.1% in 1QFY25.

· The employment for female workers in “household enterprise helper” category also witnessed decline. Female employed in this sector reduced from 11.9% in 1QFY24 to 11.4% in 1QFY25.

· The proportion of female workers declined both in agriculture and secondary sectors.

The Ugly

· LFPR-U for female workers remains very low at 18.2% (1QFY25) vs 54.7% for males; even though it has shown improvement from 16.8% in vs 54.1% in 1QFY24. Even for Young females (15-29yr age) it remains materially lower at 16.4% (vs 50.2% for males).

· Youth (15-29yr) unemployment in urban areas remains very high at 16.8% (23% for young females); even though it came down from 17.6% a year ago.

· J&K (29.8%), Odisha (28%), Rajsathan (25.5%) and Assam (23.9%) had the worst youth unemployment in the country in 1QFY25. For young female workers unemployment Himachal (41.6%), Kerala (41.9%), Jharkhand (40.6%) and J&K (52.7%) were the worst state.

Conclusion

The huge gender gap in the labor force continues to be a cause of serious concern. Female workers, especially young (15-29yr) females, are getting much fewer employment opportunities. The gender gap in the workforce is persisting at alarming levels and does not augur well for the acceleration in the growth rate. If we juxtapose this data with the education statistics, we find the bridging of the education gap between male and female population has not resulted in equal opportunity for females in employment.

Another cause of concern is that the unemployment remains materially higher amongst the young workers (16.8%) as compared to overall unemployment level in urban areas (6.6%). The reason could be multifold like unemployability (skill mismatch and/or sub-standard education), reducing employment intensity of GDP, and poor employment growth in manufacturing sector. Nonetheless, it substantially diminishes the demographic dividend for the Indian economy.

Persistently, high ratio of self-employed and casual labor (over 40%), inter alia, indicates (i) lower employment elasticity in the organized sector and (ii) skill mismatch.

Wednesday, July 31, 2024

The capex “nudge”

Capital expenditure (capex) has been one of the primary focus areas of the government in the past one decade. As per the Economic Survey 2024, “The focus of capex has been broad-based. Spending in sectors such as road transport and highways, railways, defense services, and telecommunications delivers higher and longer impetuses to growth by addressing logistical bottlenecks and expanding productive capacities. Government capex has also begun to crowd in private investment, as discussed earlier in this chapter. Additionally, the Government continues to disburse grants-in-aid for the creation of capital assets to the states, thereby incentivizing them to increase their productive spending.”

Accordingly, “capex” has emerged as an important driver of growth, as indicated in its rising share of nominal GDP. As per the provisional actual (PA) figures for the FY24, capex for FY24 stood at ₹9.5 lakh crore, an increase of 28.2 per cent on a YoY basis, and was 2.8 times the level of FY20.

However, despite the sharp rise in the government capex in building the enabling infrastructure and incentivizing enterprises, the private capex has not responded adequately. Lamenting the private entrepreneurs, the Economic Survey stated, “while it remains the government’s responsibility to facilitate the development of infrastructure and address logistical challenges, it is incumbent upon the private sector to take forward the momentum in capital formation on its own and in partnership with the Government. Between FY19 and FY23, the share of private non-financial corporations in overall GFCF increased only by 0.8 percentage points from 34.1 per cent to 34.9 per cent. This was mostly driven by their fast-increasing share in the additional stock of dwellings, other buildings and structures. Their share in addition to the capital stock in terms of machinery and equipment, started growing robustly only since FY22, a trend that needs to be sustained on the strength of their improving bottom-line and balance sheets in order to generate high-quality jobs.”

In the recently concluded general elections, lack of adequate job generation emerged as one of the key agenda points. The experts have held the prevalence of high unemployment rates amongst educated youth as one of the factors responsible for below par performance of the BJP.

Obviously, the government is concerned about the employment situation. The problem is that commitment to fiscal discipline and structural reform in the public sector may not permit the government to create many new employment opportunities in the public sector. The employment generation would thus be the responsibility of the private sector.

In the recent budget for FY25, the government announced some measures to encourage private enterprises to invest in building new manufacturing capacities and generate employment for the youth entering the job market. The budget adopts a carrot and stick approach for that. On one hand, it provides support for hiring more fresher employees and skill them, and on the other hand it makes outflow of funds from companies difficult. After dividends, now buybacks are also made tax inefficient. The idea seems to “encourage” companies to invest in growing their businesses and reward shareholders through share price appreciation only. Abolition of Angel Tax on startups is also a measure to encourage more new businesses to be set up and offer employment opportunities.

How much of these efforts will yield in terms of new employment and growth is to be seen, but the intent seems clear.

Tuesday, March 5, 2024

Cognitive dissonance- 4

Continuing from last week

The development of Artificial Intelligence (AI) is still in the early stages. How many more job losses shall we witness in the coming years due to automation?

Last week, one of the popular viral videos on Indian social media was about the views of Mr. Rahul Gandhi, Lok Sabha MP, and Mr. K. Annamalai, Tamil Nadu State President of BJP, on the challenges of artificial intelligence (AI). In the video, Mr. Annamalai is seen eloquently explaining the challenges of AI to young students, while Mr. Gandhi is seen doing some whataboutery to hide his lack of proper understanding.

Discussing the matter with many people who chose to forward the video to me, I found that the key reason for their forwarding this video is to show Mr. Gandhi in a poor light and not bother about the challenges of AI. They deliberately chose to ignore that both Mr. Gandhi Mr. Annamalai may not be in a position to make policies, at least for the next five years; whereas Chief Ministers of the largest populated and most industrialized states in India, and even some of the top leadership of the country, may be equally lacking in understanding about the challenges of AI, as Mr. Gandhi. Many of these may even fail to spell Artificial Intelligence correctly. That ought to be an issue these people should be worrying about and discussing.

Until a few months ago, India’s IT minister rejected the threat of AI to jobs in India as “nonsense”. Recently he reluctantly acknowledged that “AI may result in automating some routine jobs but will also result in job creation in various data science, data curation, etc.” This is in total contrast to what the global IT leaders believe. For example, Elon Musk insists AI will get humans to a point where “no job is needed.”

In a recent famous interview with Trucker Carlson, President Vladimir Putin expressed fears that the developments in AI and genetics could potentially be a threat to humanity as a whole in the future. He said, “When there arises an understanding that the boundless and uncontrolled development of artificial intelligence or genetics or some other modern trends, cannot be stopped, that these researches will still exist just as it was impossible to hide gunpowder from humanity... when humanity feels a threat to itself, to humanity as a whole, then, it seems to me, there will come a period to negotiate at the inter-state level on how we will regulate this.”

Notwithstanding the state of denial by politicians, the campus recruitment by Indian IT companies in FY24 was just 75000, the lowest since 2002.

The Viking expansion during the 8^th – 11^th centuries reshaped the history, culture, and commerce of the world, by laying the ground for global colonial imperialism. It was aided by the first industrial revolution (1760-1820). The Second Industrial Revolution (1870-1914) redrew the contours of global strategic balance. The atomic attack on Hiroshima and Nagasaki (1945) established a new world order that was dominated by trade and commerce rather than military power. The development of Artificial Intelligence is a similar event in world history. It has the potential to redefine how people procreate, live, think, work, interact, transact, entertain, and die. AI could pose a much bigger threat than nuclear weapons; and could be a bigger service to humanity than any medicine or healthcare procedure.

Confining the discussion on AI to job losses would be beyond ridiculous.

On a lighter note, let me share a recent anecdote. An acquaintance (56-year-old) was running a 110-seater call center in Delhi for 24yrs. He had to shut the operations as his major clients automated their processes. He has converted the facility into a stock market jobbing facility by retraining all 110 operators. He is making 2x more money than the best years of call center business. Employees are also taking home 25-50% more. He told me, “Let Nvidia and Musk do whatever. We will make money trading their stocks. If we cannot compete with Nvidia, and Microsoft, we will own them!”

The point is that unemployment due to AI is a worry only for those who refuse to adapt, retrain, and reskill. For others AI is a major opportunity to move to higher orbits. The real damage due to AI could happen in social, personal, and emotional spheres.

Thursday, February 29, 2024

Cognitive dissonance- 3

Continuing from yesterday.

If the job crisis is so severe, why is the incumbent government so popular, especially among the youth?

The incumbent prime minister, reportedly, enjoys the highest rating amongst the popular leaders of the world. In particular, he is very popular amongst the youth and women in India.

India faces one of the worst youth unemployment rates globally. Indian homemakers are facing serious challenges in managing their household budgets due to inflation. According to the World Bank, the youth unemployment rate in India could be comparable to war-torn economies like Syria, Yemen, Lebanon etc. The unemployment rate and household inflation have worsened or failed to improve in the past 10 years.

The question thus arises, why is the incumbent government still popular amongst youth and women?

I have discussed this aspect with numerous common people, like myself, nationwide over the past couple of years. My conclusion is as follows:

(a) Contrary to common perception, the incumbent government is not very popular with the people. It is the Prime Minister who is popular, not his team or the administration. A majority of people defend the prime minister, arguing that he sincerely wants to make life of the people better, but the administration is corrupt and not supporting him fully.

(b) A majority of the prime minister’s supporters believe that he is a divine incarnation and he could only salvage them from their misery and distress.

(c) The popularity of the incumbent government and the prime minister is significantly higher in West and North India, as compared to South and East India. He is also relatively less popular in the states where there are strong local leaders.

(d) The lower middle-class youth is increasingly becoming kind of masochist. They appear to be comfortable with their pain and misery, so long as their neighbors are more miserable and are in deeper pain.

(e) Above all, the welfare schemes of the government have benefitted poor households. The campaign to promote these schemes is very strong and effective, strengthening the connection between beneficiaries and the prime Minister.

(f) Overindulgence with social media is making youth delusional.

(g) Partisan reporting by electronic media has affected the judgment of gullible households to a material extent.

(h) The lack of a visible opposition leader with a pan-India appeal, and the lack of any competition from within the BJP to the prime minister’s supremacy, are helping the prime

Wednesday, June 28, 2023

Chosen the wrong template

Continuing from Tuesday (Nine years of continuity and low growth), I must say one key area of sub-optimal by the incumbent NDA-2 government is management of human resources. Despite massive public campaigns, the investment in education, skill developments, and employment generation opportunities have been found lacking. Meager budget allocations have been made for capacity building in the areas of education and skill development. In fact, the capital expenditure budget was sharply cut for school & higher education and skill development in the union budget for FY24. A meager sum of Rs99.2cr was allocated towards capital expenditure on skill development.

The successive governments in India have been consistently ignoring the fact that the global community has always valued resource rich nations and expected them to behave in a responsible manner to preserve the global order.

· The capital rich western world is expected to help the poor and starved of the world. The world looks forward to funding technological advancement, preservation of cultural heritage, assisting global growth and development. Even after taking full cognizance of the blemished legacy of imperialism and suppression, I believe that financially rich communities have worked for the betterment of human life by funding technological innovation, life science research & development, productivity enhancement, and development assistance to the economically underprivileged world.

· Similarly, nations rich in natural resources like minerals etc. have been expected to prospect and exploit these resources in optimum manner to assist the sustenance and growth of the global economy. For example, in spite of frequent allegations of cartelization and supply manipulation, OPEC has been mostly successful in maintaining petroleum market equilibrium.

The point is that since India now possesses the largest pool of prospective workers for the world, it is our responsibility to prospect, grow, and develop this resource for the benefit of the global community! This becomes even more pertinent in the context of the current global financial conditions. In places like Europe and Japan the root cause of the crisis could be traced to the aging demographic profile. China is also likely to join the club soon. Under the circumstances it is the responsibility of India to provide educated, skilled and trained workforce to the global economy.

A number of research papers and surveys have shown that (a) Child and mother nutrition level in India is sub-standard consequently child mortality rates are poor; (b) higher and professional education standards are extremely poor consequently a large number of Indian graduates are unemployable even in routine jobs; (c) There is acute shortage of competent scientists to scale up research and development (R&T) activities to make Indian businesses competitive at global stage.

The consequences are low proportion of labor force and even lower labor force participation; especially in case of female workers. As I highlighted last week (see here), for urban females in India, labor force participation rate is a dismal 18%. Even for young females (15-29yrs of age) it remains materially lower at19.3% (vs 57.6% for males). Youth unemployment in urban areas is very high at 17.3% (22.9% for young females). In some states like Assam (41.7%). Himachal (49%), Kerala (42.8%), Rajasthan (43%), and J&K (59.3%) urban unemployment rate amongst young female workers is running at over 40%.

It is cause of grave concern that the unemployment remains materially higher amongst the young workers (17.3%) as compared to overall unemployment level in urban areas (6.8%). The reasons for this may include unemployability (skill mismatch and/or sub-standard education), reducing employment intensity of GDP, and poor employment growth in manufacturing sector. Besides, persistently, high ratio of self-employed and casual labor, inter alia, indicates (i) lower employment elasticity in the organized sector and (ii) skill mismatch.

Unfortunately, the results of the latest (7^th) Economic census launched in 2019 are not yet released, so we will have to rely on the outcome of 6^th economic census (2013-14) for the sake of argument sake. Anecdotally, I can vouch that the trend has not reversed in the past one decade. In fact, the conditions are more likely to have deteriorated, if we consider the latest Annual Survey of Industries (2019-20).

As per the 6^th Economic Census, there were 58.5mn business establishments (excluding public administration, crop production & plantation, defense and compulsory social service activities) operating in the country. Of these ~96% establishments were privately owned while just ~4% were government owned. These establishments employ 131.29mn people (52% in rural areas and 48% in urban areas).

· Out of total ~58mn establishments about ~72% were Own Account establishments (meaning with no hired worker). These Self Owned Establishments (SOEs) grew 56% during 2005-2013. About 63mn people (48% of total employed people) are employed in these SOEs.

· The government or public sector employs only 7% people. 79% of people work in proprietary establishments. Organized private and cooperative sector employs 14% people.

· About 36% of business establishments were operated from the home of the Self Owner, while another ~18% operated from outside the home without any fixed structure.

· Retail trade (~35%) and Manufacturing (~23%) were dominant non-agricultural activities.

A June 2014 working paper released by RBI, concluded that aggregate employment elasticity (change in employment due to economic growth) of Indian growth has fallen considerably in the post 1991 period. In this period for every 10 per cent change in real GDP, there had been about 1.8-2 per cent change in employment. The current statistics are even poor.

Moreover, elasticity varies considerably across sectors. While agriculture has witnessed negative elasticity, services including construction have generally been employment intensive. Manufacturing employment elasticity has hovered in the range 0.29-0.33.

Within manufacturing, the employment elasticity for organized manufacturing sector based on various estimates seems to be higher, in the range 0.42-0.57 for 2000s and it has risen over the previous two decades. Given the huge productivity and wage differentials between organized and unorganized sectors, greater employment generation in organized manufacturing is crucial as it has larger multiplier effects.

The working paper suggests that going forward, it is the relative cost of capital vis-à-vis labour and the nature of investment demand that will determine to what extent growth would be job-creating. Increased capital to labour ratio in the organized sector for a labour abundant country like India is a concern that has been well-highlighted. If India has to meet the demographic dividend challenge, focus should be on industries where employment elasticity is higher. Roughly, in India over 10 million people would need a job every year for the next 15 years. Finding productive jobs for such huge numbers is a big challenge, and clearly the answer lies in stepping up growth, and importantly, stepping up the employment intensity of growth.

In this context, the findings of the latest Annual Survey of Industries (ASI-2020) are noteworthy.

As per the ASI-2020, the addition of net new manufacturing units in India has been very low. Moreover, the factories have become more relatively capital intensive. The average fixed capital per factory increased 43% from Rs12.78cr in ASI-2013 to Rs18.33cr in ASI-2020 (a part of higher amount could be attributable to cost inflation); but the number of employees per factory increased only 17% from 56 to 66. Net value-add per factory in operation increased ~27% in this period from Rs4.82cr to Rs6.11cr. This barely covers the inflation.

The worst part is that only ~6.6% operational factories were located in the most populous state (Uttar Pradesh); while Tamil Nadu accounted for ~16% of total operational factories.

Three trends could be reasonably deciphered from this Survey:

1. In the past 10yrs the capital-intensive large industries have grown at the expense of labor intensive MSME and household sector industries.

2. The employment intensity of the Indian manufacturing sector continues to decline. The employment intensity of the agriculture sector is already negative. These are the areas where over 70% of the workforce is employed or seeking employment.

3. The government incentive schemes to promote industrial growth (e.g., PLI) are yet to show any meaningful impact. Some recent reports indicate that against a total budget outlay of Rs 1.97 trillion, so far only Rs29bn have been disbursed under 14 PLI schemes.

In conclusion, the solution for the unemployment problem in India lies in promotion of cottage and MSME units and not fancy large manufacturing plants. The government’s focus should be on skilling youth and enabling the setup of high-quality cottage and MSME sector that could become ancillary to large OEMs in India and abroad. The development of the Auto industry during the 1990s and 2000 is the classic template that should have been adopted for overall industrial growth. Unfortunately, it does not seem to be the case so far.

Wednesday, June 21, 2023

Employment- Gender gap and skill mismatch alarming

The latest Periodic Labor Force Survey (PLFS), released three weeks ago by the National Statistical office (NSO), provides some very useful insights into the current employment conditions in the country. The following are some of the key observations from the Survey report.

Key definitions

The Worker Population Ratio (WPR-U): Percentage of potential workers, i.e., the population aged between 15-60yr of age, in urban areas.

The Worker Population Ratio (WPR-R): Percentage of potential workers, i.e., the population aged between 15-60yr of age, in rural areas.

Youth WPR-U: Worker Population Ratio for population aged between 15-29yr in urban areas.

Youth WPR-R: Worker Population Ratio for population aged between 15-29yr in rural areas.

The Labor Force Participation Rate (LFPR-U) is defined as the percentage of population offering or willing to work in urban areas, whether currently employed or unemployed.

The Labor Force Participation Rate (LFPR-R) is defined as the percentage of population offering or willing to work in rural areas, whether currently employed or unemployed.

The Worker-U: Person in the labor force currently employed in urban areas.

The Worker-R: Person in the labor force currently employed in rural areas.

The Good

· The employment conditions have improved during FY23. The WPR-U improved by almost 150to 200bps for all ages and both genders. The Youth WPR-U improved from 30.5% (4QFY22) to 32.6% (4QFY23). For all workers, WPR-U improved 43.4% to 45.2% during this period.

· The LFPR-U improved from 38.2% in (4QFY22) to 39.4% in (4QFY23) for youth and from 37.2% to 38.11% for all workers.

· Self-employed female workers increased in urban areas from 35.3% to 38.5% while the number of self-employed male workers in urban areas reduced from 40.4% to 39.7%.

· Unemployment rate in urban areas has reduced from 8.2% (4QFY22) to 6.8% (4QFY23).

The Bad

· The percentage of “own account workers” in urban areas reduced by 40bps from 33.1% (4QFY22) to 32.7% (4QFy23).

· The percentage of regular wage/salary workers increased marginally from 48.3% (4QFY22) to 48.9% (4QFY23); however, the female regular wage workers in urban areas reduced sharply from 56.7% to 54.2% during the same period. More females were employed as helpers in household enterprises 10.2% in 4QFY22 to 11.7% in 4QFY23.

· The proportion of female workers increased from 8% to 9.3% in the agriculture sector while it declined both in secondary and tertiary sectors. While it was the opposite for male workers.

The Ugly

· LFPR-U for female workers remains very low at 18% (4QFY23) vs 57.3% for males; even though it has shown improvement from 16.2% in 4QFY22. Even for Young females (15-29yr age) it remains materially lower at19.3% (vs 57.6% for males).

· Youth unemployment in urban areas remains very high at 17.3% (22.9% for young females); even though it came down from 20.2% a year ago.

· Assam (41.7%). Himachal (49%), Kerala (42.8%), Rajasthan (43%), and J&K (59.3%) had the worst urban unemployment rate amongst young female workers. Only Delhi (9.9%) and Gujarat (9.7%) had an urban unemployment rate less than 10% for young female workers.

Conclusion

The huge gender gap in the labor force is a cause of serious concern. Female workers, especially young (15-29yr) females, are getting much fewer employment opportunities. The gender gap in the workforce is alarming and does not augur well for the acceleration in the growth rate. If we juxtapose this data with the education statistics, we find that bridging the education gap between male and female population has not resulted in equal opportunity for females in employment.

Another cause of concern is that the unemployment remains materially higher amongst the young workers (17.3%) as compared to overall unemployment level in urban areas (6.8%). The reason could be multifold like unemployability (skill mismatch and/or sub-standard education), reducing employment intensity of GDP, and poor employment growth in manufacturing sector. Nonetheless, it substantially diminishes the demographic dividend for the Indian economy.

Persistently, high ratio of self-employed and casual labor, inter alia, indicates (i) lower employment elasticity in the organized sector and (ii) skill mismatch.

Thursday, March 16, 2023

Beyond ‘statistics’

Recently, the growth in per capita GDP of India has been in the news. The government statistics claim that per capita income of India has almost doubled in the past nine years. This claim has generated intense discussion over the economic performance of the incumbent government; especially relative to the previous UPA government (2004-2014).

Without getting into a political argument and keeping the statistics aside for a while; I would like the popular debate to take the following into consideration:

· The last census of India was done in 2011. Therefore all “per capita” data points are using an estimated number of the population. There is a possibility that the actual number could be different from the estimates.

· In the past twelve years there have been significant changes in the socio-economic and demographic structure of the country. The youth population has increased materially. Millions of professionals (engineers, doctors, management & accounting professionals etc.) and other graduates have passed out of colleges and millions have dropped out of colleges. Not all of these are fully or partially employed.

Besides, demonetization of high value currency (2016), implementation of GST (2017), and Covid-19 pandemic (2020) accelerated the trends towards formalization the economy and digitalization of trade and commerce stressing millions of the micro and small businesses (mostly self-owned) and migrant laborers.

The rise in inequalities and dispersion of income and wealth must be factored while using “per capita” data to measure the welfare, quality of life and purchasing power of the bottom 75% of the population.

· Traditionally, the primary sources of data on the workforce and employment have been the (i) decennial population census and (ii) nationwide quinquennial surveys on employment and unemployment by the erstwhile NSSO under the Ministry of Statistics and Programme Implementation. The latest Census data is available for the year 2011. Similarly, the quinquennium NSSO data on employment and unemployment is available up to the year 2011–12 only.

From 2017-18 National Statistical Office (NSO) of MoSPI started publishing Periodic Labour Force Survey (PLFS). PLFS data is published annually for both rural and urban and the total population; and quarterly for the urban households.

For the purposes of PLFS, the Labour force includes persons aged 15-60yrs who were either working (or employed) or those available for work (or unemployed). Some persons in the labour force may be abstaining from work for various reasons. Subtracting that number from the labour force gives the number of actual workers. These workers are further categorised as persons who are engaged in any activity as self-employed or regular wage/salaried and casual labour. The difference between the labour force and the workforce gives the number of unemployed persons.

As per the latest data NSO PLFS available (FY21), India has a low labour force participation rate of 41.6%. The rate is lower for urban labour force (38.9%) vs Rural labour force (42.7%); and for female workers (25.1%) vs male workers (57.5%). In urban India the female labour participation rate is dismal 18.6% vs still poor but higher 27.7% for rural female workers.

Clearly, (i) the data availability and quality is of not very high quality; (ii) employment conditions cannot be termed as good; and (iii) India is wasting the demographic dividend.

· Unlike other developed economies, we could not create enough unskilled and semi-skilled jobs in the manufacturing and construction sector during the transition of economy from agrarian to industrial. In fact, unlike the US and Europe, we jumped from agriculture to services mostly skipping the industrial part. Now we are trying to fill the gap by encouraging manufacturing. However, the unfortunate part is that manufacturing is no longer labor intensive now. It is not feasible to transit a large number of unskilled or semi-skilled agriculture workers to industry or even construction. Consequently, there remains massive disguised unemployment in agriculture.

At the same time we do not have enough highly skilled people needed for globally competitive manufacturing. The corrective action to encourage manufacturing is thus not working well, at least so far.

The only feasible way to correct the occupational structure of the country is to focus on accelerated development of the agriculture sector and make the farm workers more productive.

Thursday, June 2, 2022

State of economy – no scope for complacency

The latest data published by the National Statistical Office (NSO confirms that India’s economic activity in FY22 has reached the pre pandemic levels of FY20. The Real Gross Domestic Product (GDP at FY12 prices), private consumption, government consumption, and gross investments in FY22 were at a marginally higher level than FY20. The exports and Imports in FY22 were more than 10% higher than FY20.

The Real GDP in FY22 grew 8.7% vs a contraction of 6.6% in FY21, and a growth of 4% in FY20. The growth in Real GDP in 4QFY22 was much slower at 4.1%.

Media and government officials have reported the growth numbers in a context of their own liking. Some have taken pride in India achieving the fastest growth rate amongst the larger global economies. Some have expressed relief that the Indian economy has recovered fully from the pandemic impact and attained the pre pandemic level of economic activity. Some celebrated this as a “V” shape recovery of the economy. Some expressed concern over slower growth in 4QFY22 and poor growth outlook for FY23. Many global agencies have downgraded their estimates of FY23 growth for India.

In my view, comparing India’s growth trajectory to global peers is meaningless, as the socio-economic profile of India (particularly demography and people living below poverty line) may be very different from the developed or even developing economies like China. A fair comparison, if at all needed, would be to compare with the growth rate of those economies when they had similar demographics and poverty levels; adjusted for the available resources (financial, human, and other natural resources) for future growth.

Our competition is with ourselves only

Also, it is important to note that this 8.7% number is a purely statistical phenomenon that is impacted by the base effect. Since the growth in FY21 was a negative number (-6.6%), the FY22 growth is statistically looking stronger. There is no denying that the Indian economy has shown resilience. The government has been able to limit the impact of the pandemic to a material extent. But a better way to look at growth would be to compare it with the “Required growth Rate” (RGR) to achieve full employment and eliminate poverty in, say, the next two decades. The RGR must also account for the costs to be incurred over the next couple of decades for improving the sustainable quotient of the economy, and achieving the sustainable development goals (SDGs).

Urgent need to exploit the demographic dividend

The demographic profile of India warrants extreme urgency in accelerating the growth rate to RGR. As per the latest available Periodic Labour Force Survey (PLFS 2018), almost one third of skilled youth in the country are unemployed. The rate of unemployment amongst skilled female workers is even higher. The situation is widely believed to have worsened in the past three years due to the pandemic.

My experience indicates that if a college graduate does not get employed in accordance with his/her skill level within 2yrs of graduating, the probability of his remaining underemployed for life increases manifold. It is therefore important that India achieves RGR urgently so that 8 to 12 million youth who are joining the workforce every year get employed appropriately. Else, we will continue to lose the benefits of demographic dividend, which has been one of the primary factors in many countries graduating to the middle class of wealthy economic status.

Focus on long term growth trajectory

Rather than focusing on quarterly numbers that may be materially impacted by some non-recurring factors (Drought, flood, lockdown, monetary or fiscal action etc.) it is important that we focus on the long term growth trajectory of the economy. For example, a 5yr CAGR of real GDP may be a better indicator of sustainable growth potential of the economy. This long term growth rate may adequately account for the sustainable level of economic activity and capacity building for the future growth.

The long term growth (LTG) trajectory (5yr GDP CAGR) has been declining since the global financial crisis (GFC 2008). It had shown some signs of improving in FY15-FY19, but the pandemic has pushed it down again. The economy had a LTG of 9% in FY08, which declined to 7% - 7.5% during FY13-FY19. The present LTG is less than 4%; and the Indian economy is expected to regain even the 6% LTG trajectory not before FY27.

For record, the LTG during the past 8yrs (FY15-FY22) is 5.2%.

Obviously, the economy has some serious challenges to surmount, and there is no scope for any complacency.