Volatility of the unemployment rate

The unemployment rate fell to 5.6 per cent during the week ended October 29. This was a significant fall from the 6.9 per cent rate during the preceding week. But, the 6.9 per cent rate was a significant rise from the 5.7 per cent in its preceding week.

What do we make of such volatility in the unemployment rate when it rises by 1.1 percentage points over a week only to drop by 1.2 percentage points in the next week? Given that the unemployed are of the order of 25 million, this implies that a few million people move in and out of being employed or unemployed.

Are such changes for real? Do people move in and out of employment in such large numbers over a week? Or are these changes a reflection of sample changes from one week to the next?

Vivek Moorthy, Economics and Social Sciences Professor at Indian Institute of Management, Bangalore raised this question to me in a recent conversation. He pointed out that volatility of the unemployment rate in most developed countries is quite low. A small change in the rate indicates a change economic conditions. In fact small changes can move markets. In comparison, the month-to-month volatility in India is much higher than in the US -- too high for comfort.

Prof Moorthy's observation is bang on but, his concern may not be. No wonder the Indian financial markets don't give a penny. They have been on a nearly perpetual roll. No one quite knows why they keep rising relentlessly but nobody cares because its making many rich and who would like to spoil such a profitable party.

Back to Professor Moorthy's question on volatility of the unemployment rate.

It is true that unemployment rate in India is a lot more volatile than in developed countries. We study the period January 2016 through August 2017 since this is the period for which we have data for India, thanks to the BSE-CMIE partnership in producing such statistics. We compare the volatility of monthly series of unemployment rate over this 20-month period. Interestingly, this period can be divided equally into a pre-demonetisation and a post-demonetisation period as November 2016 sits exactly at the center.

Over this period, volatility of the monthly unemployment rate in India is much higher than in OECD countries. The coefficient of variation was 8.3 times higher. But this period contains multiple shocks of demonetisation and GST. It could be useful to see the volatility before these shocks became effective.

During the 10 months of January through October 2016, volatility of the monthly unemployment rate was 7.7 times that in OECD countries. So, the high relative volatility cannot be explained by the shocks. The post-demonetisation period did see a substantial increase in the volatility of monthly unemployment rate. The coefficient of variation increased from 8.8 per cent (pre) to 23.5 per cent (post). Since there is a huge difference between the pre and post-demonetisation period, the overall coefficient of variation is even higher at 32.5 per cent.

During recent times no country has faced economic shocks such as by India and therefore it is not a good idea to compare its data for the entire period with the others. But, it should be perfectly fine to make such a comparison for the period before demonetisation. The coefficient of variation for India during this period is 8.8. The closest among OECD countries is Hungary at 7.2 per cent. Next comes Turkey at 6.2 per cent and then Estonia and Israel at 5.8 and 5.2 per cent.

It is apparent that high volatility is not uncommon. It is the nature of employment that plays an important role in determining volatility of the unemployment rate. In India, a large proportion of the labour force does not have a regular job. People are mostly employed as daily wage workers, agricultural labourers, small farmers and self-employed traders. These include the assortment of plumbers, masons, cargo loaders, badli workers, etc. These move in and out of "jobs" fairly rapidly.

It is the high proportion of these workers in India that makes the unemployment time-series volatile. What is useful is to see is in the monthly unemployment rate series is that there is a trend. It is not random. It therefore does carry useful information. But, I'd like to not waste Prof Moorthy's observation. It would be useful to add a new series to the unemployment rate -- one that is based on only the organised sector. We should expect low volatility in this.

 
Every Tuesday, Business Standard brings you CMIE’s Consumer Sentiments Index and Unemployment Rate, the only weekly estimates of such data. The sample size is bigger than that surveyed by the National Sample Survey Organisation. To read earlier reports on the weekly numbers, click on the dates:
November 21November 28December 4, December 11December 18December 25January 1January 8January 15 , January 22January 29February 4 , February 12February 19February 27March 5March 13March 19, March 26April 02, April 10April 17April 23May 1May 8May 15May 21May 28June 4June 11June 18June 25July 2July 10July 16July 23July 30August 7August 14August 21August 27September 3September 10September 17September 24October 1October 8October 15, October 22
Methodology

Consumer sentiment indices and unemployment rate are generated from CMIE's Consumer Pyramids survey machinery. The weekly estimates are based on a sample size of about 6,500 households and about 17,000 individuals who are more than 14 years of age. The sample changes every week but repeats after 16 weeks with a scheduled replenishment and enhancement every year. The overall sample size run over a wave of 16 weeks is 158,624 households. The sample design is of multi-stratrification to select primary sampling units and simple random selection of the ultimate sampling units, which are the households.

The Consumer Sentiment index is based on responses to five questions on the lines of the Surveys of Consumers conducted by University of Michigan in the US. The five questions seek a household's views on its well-being compared to a year earlier, its expectation of its well-being a year later, its view regarding the economic conditions in the coming one year, its view regarding the general trend of the economy over the next five years, and finally its view whether this is a good time to buy consumer durables.

The unemployment rate is computed on a current daily basis. A person is considered unemployed if she states that she is unemployed, is willing to work and is actively looking for a job. Labour force is the sum of all unemployed and employed persons above the age of 14 years. The unemployment rate is the ratio of the unemployed to the total labour force.

All estimations are made using Thomas Lumley's R package, survey. For full details on methodology, please visit CMIE India Unemployment data and CMIE India Consumer Sentiment.

The creation of these indices and their public dissemination is supported by BSE. University of Michigan is a partner in the creation of the consumer sentiment indices.


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