India’s “Jobs Scenario” is Really Bad, Screams Media. When You get to know How They Concluded this. You’ll scream too (With Disgust)

India Jobs

Shoot & scoot is the new mantra in India. The media it seems is trained to look at Facts at their convenience; in fact, much of reporting nowadays is anecdotal which is rehashed and retweeted by Social Media Warriors. One such issue has been ‘Jobs in India’. There has being far too much debate and anecdotal talks about JOBS in India. In fact, the debate has stretched from NO JOBS to LOSS OF JOBS to SHUTDOWNS to BAD MODINOMICS. Demonetization and GST has only given people additional mis-thoughts and have concluded that India is facing job losses and retrenchment and humongous unemployment.

This article is to remove the chaff from the wheat and see whether India really is seeing large scale retrenchment / job losses. This is a LONG ONE, don’t read unless you are interested in facts and not MODI BASHING.

This article is structured as under:

  1. Databases of Employment statistics & their efficiency
  2. Look at the recent report from such databases
  3. Are there other reports or sources?
  4. What is the way forward?

As per NSSO Survey for 2011-12 the employment nearly 50% of India is employed in the agriculture sector, which is continually shedding jobs.

Split of employees by broad segments in FY12

Moreover, over the past 10 years i.e. from FY00 to FY12, a total of 7.4 cr., jobs were created i.e. ~74 L jobs per annum. However, maximum jobs were created in the construction sector i.e. 40% plus of growth had being in the construction sector; while agriculture continued to shed jobs.

First & foremost, India does not have an efficient data collection on jobs. This claim is based on NITI AYOG report. The biggest problem is that most of the databases are based on samples. In fact, you will see later, that the latest 2015-16 EUS report has a sample which covers merely 0.32% of the total employable population and derives its results. While I am not in favor of the same, but media houses have been upbeat about quoting data from these reports wherever it suits their agenda. However, what has been common in many articles is they start attacking the government about Joblessness and then conveniently ignoring the fact that not data is there to discuss or even gaude the jobs trend. In fact, The issue of dearth of data solely rests with the Statistical organizations. If we look at the first Quarterly Employment Survey, we see mere ~10,000 units were surveyed, which is extremely low compared to the total employed population in the country. In fact, one key point was that EPFO added 10.13 million or 1.013 cr new subscribers in first six months of 2017 because of an amnesty scheme. This is a good starting point as well. Moreover, data from ESIC, Profession Tax etc., also need to be vetted prior to forming an opinion.

Before the humbug over job losses etc., the real task at hand is finding the correct data and not resorting to attacks over anecdotal references. Even reports which are based on estimates seem unreliable on both job creation or job losses fronts.

Having said that, let us take a look at the key findings of NITI AYOG TASK FORCE ON EMPLOYMENT STATISTICS.

SOURCES OF EMPLOYMENT & UNEMPLOYMENT ESTIMATES

India faces major data challenges especially in the jobs / employment space. Modi Government recognized early the need for better dataset. Accordingly, the Government of India appointed a Task Force for improving employment data in India on May 11, 2017 under the chairmanship of Vice Chairman, NITI Aayog. The existing report had multiple flaws in the data collection process.

Firstly, Let us understand the agencies undertaking the collection and dissemination of employment data in India:

  1. Primary Agencies:
    1. Ministry of Statistics and Programme Implementation (MOSPI)
      1. Central Statistical Office (CSO) and
      2. The National Sample Survey Office (NSSO)
    2. The Ministry of Labour and Employment (MoLE)
      1. The Labour Bureau under MoLE
    3. The Ministry of Home Affairs (MoHA)
      1. The Registrar General and Census Commissioner of India under MoHA
    4. Secondary agencies undertaking occasional data collection
      1. The Ministry of Micro, Small and Medium Enterprises (MSMEs)
      2. The Directorate General of Technical Education (DGET)

Let quickly discuss the efficiency and efficacy of the database.

HOUSEHOLD SURVEY

Three official household surveys and population census collect employment statistics viz., ‘Employment – Unemployment Survey by NSSO, Annual Labour Force Survey conducted by MoLE and Population Census under MoHA.

Employment – Unemployment Survey (EUS) by NSSO

The last NSSO survey was conducted in 2011-12; these surveys were stretched throughout the year, to account for any seasonal variations in employment. Accordingly, the unemployment rate is the lowest as per the Usual Status definition, ranging between 2 to 3% and the highest as per the daily status, varying between 5 and 8%. According to the latest NSSO EUS survey, the total workforce in India was 47.36 crore in 2011-12. Of these workers, 23.16 crore were employed in agriculture and 24.2 crore in industry and services.

Annual Labour Force Survey

Started in 2009-10, the most recent one was conducted in 2015-16. However, the survey is conducted only in part period and not during the entire year.

Census & Survey of Enterprises or Establishments

Economic Census

Workforce & Industry Characteristics of India 2013-14

 

 

According to the sixth and latest round of the Economic Census, the total workforce employed in all establishments in 2013-14 was 13.1 crore. Comparing this figure to 24 crore workers employed in industry and services as per 2011-12 NSSO household survey, we see that a substantial part of non-agricultural force is not captured by the Economic Census. This is because the Economic Census does not cover self-employed workers that are not a part of any establishment.

Additionally, it is possible that many small establishments escape coverage. The own-account enterprises (OAEs), which do not employ any regular workers, and enterprises employing less than 10 workers together accounted for almost 79% of India’s workforce engaged in industry and services establishments in 2013-14. As Figure 1 highlights, nearly 70% of this workforce was employed in enterprises with five or less workers. As per the 2013-14 economic Census, only 2.7 Crore workers in India were employed in establishments with 10 or more workers. These establishments represented a tiny 1.37% of all establishments in India.

Similarly, data from Annual Survey of Industries (ASI) suffers from time lag, limited coverage and outdated frame.

The key challenges with existing dataset / surveys are:

  1. Different definitions across survey
  2. More survey oriented rather than factual
  3. Absence of updated questionnaire
  4. Non-reliance on standard databases

EMPLOYMENT & UNEMPLOYMENT SURVEY

A look at the EUS Report 2015-16 conducted by Labour Bureau. The Bureau conducted survey covering total sample of 156,563 households with 88,783 household in rural region and 67,780 households in rural India. From these households the Bureau interviewed 781,793 members were inquired out of which 448,254 respondents in rural households and 333,359 in urban households. The report presents a detailed extrapolated data for the country based on the above sample. However, given that India has a working population of ~24.1 cr., as per 2011-12 survey, this coverage is mere 0.324% of the total dataset. In fact, the listed companies in India employ ~52.0 Lakhs employees.

I believe this statistical sampling exercise is extremely low, and so does NITI AYOG. There is needs to change how data is collected and detailed roadmap should be in place with faster implementation.

IS THERE ANY BETTER WAY TO LOOK AT JOBS DATA

JOB CREATION IN FY16-17 by listed companies

In Sep 2017, CLSA came out with a study on the jobs based on review of the 916 listed companies in India having total employee base of 5.24 mn. It is observed that the listed companies have in fact created jobs in FY17 i.e. period from April 2016 to Mar 2017. The growth in jobs was 3.7% or 187803 during the year. My estimate is that given the direct employment growth in listed company space, there would definitely have been matching job growth in the companies which are dependent on such companies. One may safely assume that about ~2,00,000 would have added in similar companies.

In fact, the five year job creation average of was 3.2%, vs in FY17 the addition was 3.7%; this is remarkably higher than long term average. The job creation is marginally lower than that of FY16, but better than FY13-15.

Additionally, it is observed that

  • In the listed companies, the Services sector (~61% of total headcount) drove the entire growth of job creation as manufacturing headcount declined by 0.6%.
  • IT sector growth seems to be decelerating in FY18, growth in private financial/NBFCs could offset that. Private Financials employ 0.55m employees and grew 11% in YoY in FY17.
  • Growth in outsourcing of security personnel, housekeeping staff, etc, has resulted in the employee base of Teamlease, SIS and Quess growing to more than 0.4m

A positive addition of jobs in the listed space is extremely positive vs., the noise made otherwise. This goes a long way in bolstering investor confidence in the country. The negative news needs to be countered by facts.

JOB CREATION IN FY16-17 via MUDRA scheme

Further during FY2016-17 a total disbursement of Rs. 1,75,312.13 cr was done over 3,97,01,047 accounts. Of these accounts, new entrepreneur accounts are 99,89,470. Assuming these accounts employ even 1 person still about 1.0 cr., new entrepreneur or jobs were created due to MUDRA scheme. I highly doubt the SKOCH report data of 5.5 cr., new jobs. But, MUDRA may have created about 1.0 cr., jobs. There are lot of factors before we can conclude the efficacy of jobs generation from MUDRA scheme, but conservatively I am taking just new Entrepreneur number, then job generation would be about 1.0 cr. in FY2016-17

RECOMMENDATIONS FOR BETTER DATABASE

It is quite evident that everyone is hanging to some database and drawing conclusion. NITI AYOG in its report has suggested that jobs database structure needs to be re-looked at. Accordingly, summary of NITI Aayog’s recommendation are as under:

  1. Widening of definition as under:
    1. Workers covered under any one of the following Acts:
      1. The Employees’ State Insurance Act, 1948 (or other similar insurance)
      2. Employees’ Provident Funds and Miscellaneous Provision Act, 1952 (or other similar social security scheme)
    2. Government and other public-sector employees
    3. Workers having coverage under private insurance or pension schemes or provident funds
    4. Workers subject to tax deduction at source on their income through submission of Form 16 or similar Income Tax form
  2. Use of data from Government schemes
    1. Quick survey of MUDRA data for smaller enterprises vide quarterly filings for banks which are in turn transmitted to MUDRA agency
    2. Employment in major Government schemes & programs
  3. Create central server of database
  4. Investing in modernizing and revamping the Statistical system

In addition to the above, the following information bases should be tapped in.

  1. For companies with lending from banks should submit monthly / quarterly information on the salaries paid and number of employees
  2. Such companies should also submit record of contract workers and total contracting expenses
  3. Changes should be made in the Annual report and Quarterly report submitted by Companies for listed companies such that the same is reflected in their financials
  4. For unlisted companies, data on number of employees, should be part of the Annual reporting structure
  5. For entities other than private limited, the ITR form should mention the quarterly number of employees along with their salary paid
  6. There needs to be self-certification on employee database from all entities

All this information should be matched via big data analytics and slowly inconsistencies should be weeded out. This should be supplemented via detailed sampling exercises. The sampling exercises should be more frequent and the Government must invest in people to ensure that minimum 20% coverage is achieved via sampling. Further, the labor laws need to see some relaxation which will further enhance compliance. Many times, companies are unwilling to share data given the higher penalties in one or other law.

CONCLUSION

Having pointed to two data sets of job creation i.e. listed companies and MUDRA, it is important to note that taking anecdotal references would not be right from an overall perspective. For example, in Pune, I have managed to raise monies for 3 companies, which have led to jobs for ~200 people of which 1 is construction and 2 are agro processing units. There are multiple news stories showing that IT companies are laying off staffs. But these layoffs need to understood from a more historical perspective. And, if the layoffs are going to high, the first casualty shall be home loans, consumer durable sales and auto sales. In fact, if people were really losing jobs like its projected in media, most of the NBFCs like Bajaj Finance, or HDFC would be huge trouble. Which is clearly not the case.