Employment in India-from dividend to disaster?
As the 2019 election season approaches, we have seen much debate around the topic of jobs. We’ve had much mud slinging done over data around jobs with even some members of the NSC resigning apparently in protest against the government not publishing the data. The best estimates show that India is generating about 5 million jobs at this point.(http://www.iimb.ac.in/sites/default/files/Payroll%20in%20India-detailed_0.pdf)There are other reports that show that India is actually shedding jobs. (https://www.livemint.com/Politics/sYBQOalLczD2rlAqE0xoWL/Forget-job-growth-employment-in-India-fell-between-2014-and.html)
Whichever one we choose to see and accounting for inconsistencies in reports there is no running away from the fact that India needs to create jobs in a hurry. Sounds alarmist? Read ahead to know the whys and the wherefores of our demographic dividend waiting to turn to disaster.
By the year 2030, every working individual in India will support 2 other people in addition to himself/herself! India will need to provide employment opportunities for 120 million people . That translates to about 10 million new jobs starting this year.
Unmasking the jargon :
Most conversations on employment tend to discuss the topic in terms of formal/informal types of employment. Pakodanomics anyone ??However, if we dig a little deeper we see that it is size and stability of income that are the main factors. Therefore, we need to understand employment through the lens of income size and stability rather than conventional categories of the formal/ informal, organised/unorganised. Plotting the 2 variants of income size and stability, we can see that casual labour with low income and low stability will fall in the first quadrant , govt jobs that provide high stability and income in the fourth. Gig economy jobs fall in somewhere in the middle. With this analyis it is obvious that we need to move people from the first quadrant towards the centre at least. As the last few years have shown us, growing GDP alone is not our ticket out of hell. So, we are grappling with a triple whammy of quantum, size of income and stability of jobs !
It is a war on all fronts and we need to build our ammunition fast ! In the quest for this preparedness we need to go back to the basics and get the data right. We need to understand the jargon and most often used terminology used in explaining employment. Here is the basic ready reckoner :
Working age population (WAP): refers to people between the ages of 15 and 64. This represents the universe of people who can work in the country. Parsing through various reports, this number can be pegged between 800 and 900 million. This is the so called dividend we speak of .
Labour force participation rate (LFPR): is the actual number of people who are actively seeking employment .This is arrived at by removing student population and people who have dropped out of the work force out of despondency of not finding employment. The LFPR is alarmingly low at 45–50% of WAP- which is about 400–450 million. Specifically the LFPR for women is at an abysmal 27% and has been falling over the years. Socio-cultural reasons are a probable explanation to this. It has also been observed that as family incomes rise, women opt out of the workforce. This could be the low of the J curve and we could see an uptick from here on.
EMPLOYED: refers to the number of people who are currently employed in any form/sector. The difference between the LFPR and the employed numbers gives us the unemployment statistic. Dividing this by the population will give us the unemployment rate. The official unemployment rate currently hovered around 3% until the NSSO data that got leaked a few days ago. The leaked data showed that unemployment was at a 43 year high of 6. 1% https://www.thewire.in/labour/nsso-data-puts-unemployment-at-45-year-high-in-2017-18-report
JOBS: refer to employment in the organised sector which provide reasonable levels of security and income size.
Methodology used: Unlike the US that has a reliable system of reporting jobs created, data in India is fraught with problems of time lag and inaccuracies that accompany surveys. We therefore had to parse through a multitude of reports. (Appendix 2)
Summarising various reports analysed, accounting for the population growth rate to reach replacement rate by 2022, and assuming the women’s LFPR had reached the low of the J/U/hockey stick curve and will only rise from here, the employment trends and the jobs needed can be summarised as follows:
Current Employment Scenario :
The employed section is approximately 400m. There is a huge cushioning to this number by way of disguised unemployment specially in the agricultural sector. This can be gleamed from the fact that agriculture employs 51% of all labour but only contributes about 12–13% to GDP.
The ratio of total population to the employed is 3:1, which means every employed person will be supporting 2 other people in addition to himself/herself.
Conclusion:
- We are staring at a huge job crisis. By 2030, will need employment opportunities for estimated 1.2 billion population that will be seeking livelihood. We need to lay the foundation now.
- We need to recognise the unemployment/under employment present in agriculture right now and move the large % of unproductive population into the unemployed category while estimating the quantum of jobs.
- The immediate need is to increase the labour force participation rate and specifically increase participation of women in the labour force from the current abysmal 27% to about 65% (on par with BRICS nations).
- To do the above, we need to create a “dazzling array of possibilities” to present. Once these are presented there is no doubt that people will take them up. What these possibilities are is the million dollar question.The real challenge lies in identifying the sectors and ways that can provide these opportunities.
Solutions: Policy interventions need to address not just the quantum of jobs but must also seek to increase size of income and stability. Needless to say, the oft repeated solutions of liberalisation of agriculture, impetus on rural infrastructure and ancillary industries and tech innovation need to be pushed through aggressively. However, these will only help to address the problem incrementally. The spectres of automation and artificial intelligence will only add another dimension to this. We’d like to believe that much like the past, old jobs will get replaced by new ones and the skills needed will spell out more opportunities . We need a multi pronged approach and have to be constantly on the look out for a few silver bullets that will act as our ticket to a better world. The time to roll up our sleeves and get to “work” is today(actually yesterday)! Towards a “productive” future!
Appendix: data sources:
Waiting for Jobs (Radhicka Kapoor)
The India Employment Report-IMA
Employment- Unemployment Survey (Labour Bureau Survey of India 2016)
Ghosh and Ghosh (2017)
MLOE(2014–2015)
