Happy National Statistics Day

by Mahesh Vyas

During the week ended June 28, the unemployment rate was 8.6 per cent. This was just a tad higher than it was in the preceding week when it pencilled 8.5 per cent. The labour participation rate fell from 42 per cent in the previous week to 41.4 per cent in the latest week and the employment rate also fell from 38.4 per cent to 37.8 per cent.

In spite of this small deterioration of labour conditions in the latest week compared to the preceding week, the data indicate a dramatic improvement over the labour conditions in April and May. The unemployment rate has declined and simultaneously, the participation rate has recovered to close-to pre-lockdown period.

The sudden and sharp increase in the unemployment rate immediately upon the imposition of a lockdown surprised us initially; then the loss of 122 million jobs in April shocked us. But, after the initial jolt, both could be explained as the direct consequence of a very effective national shutdown to curb the virus. As the lockdown stretched itself into several weeks and then months, its ensuing misery manifested itself in heart-breaking pictures of helpless migrant workers trudging back home; and in a pall of gloom setting in over economic prospects. Real GDP forecasts now average around five per cent shrinkage.

Given this massive shock to the vulnerable and the deep despondency among those who are better endowed, expectations of a return to normalcy anytime soon was not on anyone’s mind. Then, how do we square the streaming data on this National Statistics Day with perceptions of reality. How do we explain the rapid return to pre-lockdown rates of labour participation, unemployment rate and employment rate?

The improvement in rural India is explained by the rise in MGNREGA spending by the government and by the increase in kharif sowing. Person days of jobs provided under MGNREGA had reached an all-time high of 568 million in May 2020. This was 54 per cent higher than the level of May 2019. Data for June 2020 accessed on June 29 from the official site of the scheme at 348 million was 66 per cent higher than it was for the month exactly a week ago. This either implies a sharp increase during the week or substantial revisions for the month. Either ways it implies a continued increase in MGNREGA spending into June. Person-days of jobs in June 2020 were already 8.4 per cent higher than they were a year ago.

Kharif sowing till June 26 was more than twice it was a year ago.

There is no overlap between MGNREGA work and sowing work. The two together therefore have evidently powered the rural employment surge in June. This could have also absorbed a part of urban labour as well. The high demand for labour in rural India because of aggressive sowing and the rising wages in rural India are drawing urban labour into the rural India. But, this could have absorbed only a small proportion of the total urban labour.

This absorption of urban labour into rural regions cannot explain the surge in employment in urban India. What could have led to urban employment rates recovering?

Newspapers provide anecdotal evidence of markets and malls opening up across towns. Factories are opening up and even some migrant workers have returned. But public transport is not operating for all practical purposes. We are not back to normal. Neither the markets nor the factories are working to pre-lockdown capacity. Work has begun in urban India, but, differently.

Labour market in India for the most part is like a classical free market. Demand-supply balances determine wages. In times such as these, when the supply of labour is far in excess of its demand, the only way in which markets can clear are for wages to drop.

Urban labour has reasons to be desperate for jobs. It cannot afford to stay unemployed for so long. Marianne Bertrand, Kaushik Krishnan and Heather Schofield found that during the second fortnight of April, only 66 per cent of households could survive the lockdown for more than a week without getting into distress. (Click here to access the report.) The cost of living and poverty rates in urban India are higher than in rural India. This is what drove the migrants out. This is what compels the rest to drop wages to find odd jobs to survive.

Usually, urban wage rates are 50 per cent higher than rural wage rates. But, this could be narrowing very rapidly now.

The experience of the past three months provides proof that Indians do not protest loss of jobs. They just drop their rates and continue with their lives. Lack of protest is no proof of lack of extreme distress. Data is a better guide. Watch out for data on farm prices falling in October after a bumper crop. Lets not wait for farmers to burn their crops rather than spend on harvesting then. Happy National Statistics Day.


Published first in Business Standard Link

CMIE STATISTICS
Unemployment Rate
Per cent
9.1 -0.0
Consumer Sentiments Index
Base September-December 2015
42.7 0.0
Consumer Expectations Index
Base September-December 2015
44.9 +0.7
Current Economic Conditions Index
Base September-December 2015
39.4 -1.1
Quarterly CapEx Aggregates
(Rs.trillion) Sep 19 Dec 19 Mar 20 Jun 20
New projects 3.12 5.15 3.39 0.57
Completed projects 0.85 1.65 1.70 0.17
Stalled projects 0.41 0.61 0.77 0.11
Revived projects 0.43 0.83 0.42 0.53
Implementation stalled projects 0.90 0.15 9.30 0.07
Updated on: 10 Jul 2020 9:28AM
Quarterly Financials of Listed Companies
(% change) Jun 19 Sep 19 Dec 19 Mar 20
All listed Companies
 Income 4.6 -2.3 -1.7 -4.0
 Expenses 2.7 -3.1 -2.2 -0.9
 Net profit 17.5 -1.3 -11.1 -43.0
 PAT margin (%) 6.2 5.3 5.1 3.1
 Count of Cos. 4,486 4,445 4,407 2,650
Non-financial Companies
 Income 2.4 -6.3 -5.5 -8.1
 Expenses 1.6 -6.7 -6.4 -4.0
 Net profit -7.5 -13.5 -14.1 -46.0
 PAT margin (%) 6.3 5.8 5.7 4.2
 Net fixed assets 10.4 13.8
 Current assets 5.0 2.8
 Current liabilities 5.0 3.8
 Borrowings 8.4 14.9
 Reserves & surplus 6.0 4.3
 Count of Cos. 3,361 3,335 3,301 2,044
Numbers are net of P&E
Updated on: 10 Jul 2020 9:28AM
Annual Financials of All Companies
(% change) FY18 FY19 FY20
All Companies
 Income 8.3 13.2 4.3
 Expenses 9.8 13.4 2.8
 Net profit -39.9 20.7 15.0
 PAT margin (%) 2.0 2.4 10.3
 Assets 10.9 9.2 11.8
 Net worth 7.5 8.5 6.5
 RONW (%) 3.5 4.4 11.7
 Count of Cos. 26,220 24,732 364
Non-financial Companies
 Income 8.5 13.6 0.1
 Expenses 8.6 13.8 -1.2
 Net profit -8.7 23.5 4.6
 PAT margin (%) 2.8 3.2 12.7
 Net fixed assets 7.1 4.9 30.4
 Net worth 6.1 8.4 3.6
 RONW (%) 5.7 7.0 15.3
 Debt / Equity (times) 1.0 0.9 0.5
 Interest cover (times) 2.1 2.4 6.3
 Net working capital cycle (days) 77 69 -13
 Count of Cos. 21,415 20,146 258
Numbers are net of P&E
Updated on: 09 Jul 2020 7:12PM