We have been repeatedly warned against blindly believing everything we read or are forwarded. With that dash of sodium chloride, here is the gist of a message I was forwarded, not as a prospective job applicant, since I possess qualifications for neither. A restaurant 89 km from Ankamaly (Angamaly) requires a full-time porotta maker, at a monthly salary of Rs 18,000 to Rs 20,000. A concern 60 km from Thrissur requires a full-time “civil engineering B.Tech or diploma holder, at a monthly salary of Rs 6,000 to Rs 7,000”. These are two isolated advertisements from Kerala and don’t constitute a proper sample. However, some sample survey data is available on the internet, though sample sizes are small. For instance, the salary of a cook (not a chef) is Rs 12,000 per month in Delhi and that of an engineering diploma (not degree) holder between Rs 10,000 and Rs 12,000 per month. That of a driver is Rs 14,000 per month. Therefore, the correlation between education and salary isn’t quite what we might expect a priori. Let me thrown in an anecdote from a colleague. His maid/cook is around 45 and has two sons, aged 18 and 20. These two have finished school and sit at home, subsisting on their mother’s salary. When my colleague asked them, “Why don’t you work as a cook?” the response was, “That is work meant for girls.”
There is an anecdote that features in jokes about economists. In many versions of the account, economists in general take the place of Kennethh Arrow. The only authentic source of this account I know is attributed to Curt Monash, who studied in Harvard. This account goes: “I was standing with Ken Arrow by a bank of elevators on the ground floor of William James Hall at Harvard. Three elevators passed us on our way to the basement. I foolishly said ‘I wonder why everybody in the basement wants to go upstairs.’ He responded, almost instantly: ‘You’re confusing supply with demand.’” The labour market is segmented, sectorally and geographically. However, regardless of sector and geography, principles of economics — supply-demand relations — do apply. There is a quote wrongly attributed to Thomas Carlyle. “Teach a parrot the terms ‘supply and demand’ and you’ve got an economist.” There is no evidence that Carlyle ever said or wrote anything like this. Parrot or not, the price of everything, labour included, is determined by the intersection of supply and demand, unless institutional constraints get in the way of that clearing function. Let’s take the example of a cook’s wages being more than that of an engineering diploma
What we have observed is a market clearing wage. Purely on this basis, it is impossible to ascribe it to either purely
supply or demand, since the outcome happens to be a combination of both. Because the National Sample Survey data on unemployment is dated, a lot of people use the BSE-CMIE data with a fairly decent sample size. This is based on household surveys, a better indicator in a country like India than enterprise surveys. There has been discussion in the media about what this says about the unemployment rate — at the all-India level as well as in the states. For example, in September 2017, the urban unemployment rate was very high (more than 15 per cent) in Goa and Haryana. The rural unemployment rate was very high (more than 10 per cent) in Haryana and Jammu and Kashmir. On October 3, the all-India rate was 5.83 per cent for urban and 3.75 per cent for rural. While the unemployment rate and its trend merits discussion, as does the question of creation jobs, what’s the definition of “unemployment rate”? Before that, the survey has four categories: Currently employed; not employed, but is willing to work and is actively looking for a job; not employed, is willing to work, but is not actively looking for a job; and not employed, is not willing to work and is not looking for a job. “The unemployment rate is computed as the sum of number of persons not employed but willing to work and actively looking for a job as a per cent of the total labour force, where the total labour force is the sum of all those who are employed and those who are not employed but are willing and looking for a job.”
We should certainly have a discussion on the unemployment rate. However, given the example I started with, there is an aspect that is missing from the customary discussion. This is highlighted in the document, “Unemployment in India, A Statistical Profile” — a separate product from the same survey. This has the standard unemployment rate, but also has something known as greater unemployment rate, that is, including those who are unemployed and willing to work, but inactive in seeking jobs. The gap between the two rates is highest in the 15-19 age-group, followed by the 20-24 age-group for males, while it is uniform across all age-groups for females. Going back to supply and demand curves for labour and their intersection, everything else remaining the same, wages drop/increase when either supply or demand curves, or both, shift. I think there is an issue of correlation between education and skills, or its lack. Some educational attainment may help acquisition of skills, but the correlation isn’t strong. For females, the gap is uniform across age. However, for younger males, the job-seeker’s perception may be of a stronger correlation than warranted.