Catching up with the employment rate

The employment rate is an interesting concept that has not been used very often in public discourse. It is the proportion of people who are employed to the total working-age population.

World Bank's South Asia Economic Focus of Spring 2018 is titled "Jobless Growth?". Its findings are based on a substantial standardisation of household census and household survey data obtained from south asian countries over time. The key variable it uses in its analysis is the employment rate.

Keeping the employment rate reasonably high and constant, or at least not letting it fall from a minimum, seems to be a useful macro-economic target. It is important to ensure that sufficient people are working and sufficient new jobs are created to at least provide work in the same proportion as in the past to the new comers into the working age population. That sounds logical and elementary. But, it is different from a macro-economic objective of keeping the unemployment rate low.

A low or falling unemployment rate as we have seen in this column in the past can be misleading when the labour participation rate is also falling. If people who lose jobs following an economic shock like demonetisation do not even look for alternate jobs following the shock or, if the new potential entrants to the labour markets simply do not enter the labour markets (possibly disheartened by the state of the jobs market) then the unemployment rate falls and misleads to imply that the shock had a positive impact.

This happens because the unemployment rate is disconnected from the working age population. Its connection is only to the labour participation rate which consists only of those who are either working or seeking work. It does not include the inactive population at least some of which could have been working.

The World Bank report brings into focus the importance of the employment rate as it tries to relate it to the income levels.

The World Bank report suggests that there is a U-shaped relation between per capita GDP and the employment rate. The employment rate is high for very poor countries -- perhaps because of the necessity of employment at the low income levels. The employment rate falls when the per capita GDP increases initially as a somewhat richer society spends more time on education and women prefer to pay greater attention to the family. As income rises further, the employment rate rises smartly reflecting access to better overall infrastructure. 

However, India along with Pakistan, Bangladesh and Sri Lanka have a much lower employment rate compared to their respective expected values given their per capita GDP levels. Original data was standardised by World Bank researchers to bring about better comparability of the data across nations.

According to the World Bank report, India's employment rate is 50 per cent, which is significantly lower than the expected rate of about 60 per cent.

Although the report presents standardised data, its standardisation is based on official statistics which are too liberal in considering a person to be employed.

We believe that India's employment rate is much lower than the World Bank's estimate of 50 per cent. Further, and rather worryingly, India's employment rate has been falling.

Estimates based on the BSE-CMIE effort to measure employment / unemployment in India show that India's employment rate averaged at 42.9 per cent between January and October 2016. This is the average for the ten months preceding demonetisation in early November 2016. Then, after demonetisation in November 2016 it fell and has kept falling steadily. In the ten months following demonetisation the average employment rate fell by 100 basis points to 41.9 per cent. And in March 2018, it fell to its lowest level of 40 per cent.

India's much lower employment rate compared to its expected value given its per capita income as shown in the World Bank report and the falling employment rate as shown from the BSE-CMIE surveys point to a malaise in India's economic development that needs urgent expert attention. 

World Bank estimates presented in its Jobless Growth report show that India needs to add 8.5 million jobs annually to keep its current employment rate constant. But, if it aspires to catch-up to the U-curve level in 20 years, it needs to add 13.5 million jobs a year. This, the report estimates could require real GDP growth rates of 10-15 per cent per annum. This is implausible and therefore there will be a need to add more jobs per GDP growth compared to the levels today.


 

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.