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10 Cr Without Good Jobs: India’s Demographic Night

The number of people who are in bad jobs is alarming, writes Goutam Das in a new book. The number is 10 Cr now, may rise to 20 Cr by 2025, Das quotes Mohandas Pai as saying.

There is a reason behind the present government’s stress on higher formal employment count. It enforces minimum wages and demands proper documentation of benefits by the employer. Formal jobs, perhaps more importantly, ensure dignity of labour, enable productivity improvements and, at times, access to formal training. But if counting formal employment is difficult, calculating informal employment is even more arduous.

Pulak Ghosh is a professor of data analytics at the Indian Institute of Management, Bengaluru (IIM-B). He has advised the State Bank of India and Bandhan Bank on analytics. Now, he is a senior fellow at NITI Aayog, where his primary responsibility is to use big data in policymaking and policy evaluation. Ghosh was part of the task force that recommended changes to improve employment data.

‘The Labour Ministry doesn’t collect anything on the informal sector. Over the last 10–12 years, [a] lot of contract employment happened. Nobody surveys that. For example, IIM-B has quite a few contract staff, in addition to the permanent staff. We need the count pan-India. Today, even the government may hire an officer on special duty. That salary comes from the discretionary budget, not from payroll. So how do I count [that]?’ Ghosh says.

Ghosh estimates that informal employment has grown 10 to 15 times in the last decade versus formal employment.

So what can India do to clean up its data?

‘The government needs a different approach,’ Ghosh recommends. ‘We need a central repository of all the employment data. Second, the government has to figure out how to count the informal employment. Be it crowd sourcing, looking at informal sources such as the number of cars and trucks on the road, number of people in the mandis, number of chartered accountants graduating every year or registered, number of doctors and nurses registered [echoed in the prime minister’s speech in Parliament]. There has to be a mechanism of collecting this data yearly.’

Most doctors are employed informally in nursing homes and don’t come under the payroll system. Ghosh suggests India enact a law that makes it mandatory for organizations to disclose their employment count on a quarterly basis.

There are, of course, other proxies to count informal employment. For instance, one can look at data from telecom towers to track local migration. People travel to suburbs for work and return to villages at night. One of Ghosh’s ideas is to record mobile tower data at night and estimate how many move out during office hours in a particular area and do this consistently for three to four months. That’s a proxy of how many are employed. Satellite imagery and mobile phones can be good proxies too; poverty and wealth can be predicted from mobile phone usage. A combination of such methods might work.

While India waits for the government to improve the mechanism with which it estimates employment–unemployment numbers, let’s consider what the country’s unemployment figure implies.

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