Yesterday’s post covered what industrial policy is, a taxonomy of industrial policy, some details about South Korea’s industrial policy, and the importance of negative incentives.
So… well, then. We’re done, right? We know industrial policy is important (and why). We know what we did wrong, we know what South Korea got right. So let’s go ahead and er, make shit happen.
Industrial Policy From Here on In Won’t Be Easy
But hang on, let’s first make coffee.
What do we need to make coffee? Well, we need some coffee, we need some water, we need heating equipment of some kind, and we need a person to do all of this for us. In the language of the economist, we can combine raw materials, capital and labor in order to produce output.
But hang on for a second. Do we really need the last item on that list?
Now, you might notice that the cup was placed on the stand, the water was already in the machine, and about a thousand other “Well, actually” responses are possible. And depending on how we think about robotics and AI, our responses are likely to be biased towards either end of the “OhThat’sSoFreakingCool – WTF!” spectrum.
But like it or not, here’s the truth: the advent of AI and robotics is here, and it is only a matter of time before capital replaces many, many jobs in not just manufacturing…but also services.
Yeah, but that’s way out in the future, right?
The Ticking Time Bomb That is India’s Unemployment Problem
Um, not so much:
From 1990 to 2007, the study shows, adding one additional robot per 1,000 workers reduced the national employment-to-population ratio by about 0.2 percent, with some areas of the U.S. affected far more than others.
This means each additional robot added in manufacturing replaced about 3.3 workers nationally, on average.
That increased use of robots in the workplace also lowered wages by roughly 0.4 percent during the same time period.
“We find negative wage effects, that workers are losing in terms of real wages in more affected areas, because robots are pretty good at competing against them,” Acemoglu says.
The paper, “Robots and Jobs: Evidence from U.S. Labor Markets,” appears in advance online form in the Journal of Political Economy. The authors are Acemoglu and Pascual Restrepo PhD ’16, an assistant professor of economics at Boston University.
https://news.mit.edu/2020/how-many-jobs-robots-replace-0504
And the kicker is that this article was published in May 2020. Dunno if you’ve noticed, but there have been a couple of advancements in AI since then.
Long story short, there may just not be that much of demand in manufacturing for labor in the years to come. And that’s a problem for us, because the one thing we will have a lot of is, well, labor:
18 million people turn 18 each year in India and we have over a 100 million people surplus in agriculture. Unless we create 20 million new jobs each year, India’s dream of a demographic dividend could easily turn into a nightmare!
https://takshashila.org.in/20mj
And how are things going on the job creation front?
The number of fresh formal jobs created fell by 10 per cent in 2023 compared to the previous year, reflecting slowdown in the pace of formal job creation, a Business Standard analysis of the latest payroll data shows. This is crucial as only the formal workforce enjoys social security benefits and is protected by labour laws.
Released by the Employees’ Provident Fund Organisation (EPFO), the latest data available till October 2023 shows that 9.06 million new subscribers joined the Employees’ Provident Fund (EPF) between January and October. The figure was 10.1 million in the corresponding period of the previous year.
https://www.business-standard.com/economy/news/fresh-formal-jobs-creation-falls-10-to-9-06-mn-in-2023-epfo-data-123122600612_1.html
The data also shows that the number of new young subscribers belonging to the 18-28 age group declined by 11 per cent to 5.97 million this year from 6.71 million in the corresponding period last year. This is crucial because subscribers in this age group are usually first-timers in the labour market, thus reflecting its robustness.
Quality Over Quantity is Applicable to Debates Too, Y’Know
Now, if you like, you can yip about whether this is the correct way to calculate employment and go on a “actually, it is not all that bad” op-ed writing spree. If you like, you can yap about how this actually understates the problem, and go on a “actually, it is much worse” op-ed writing spree.
Me, I prefer to internalize the fact that we are simply not creating enough jobs, and haven’t been doing so for years.
Worse, the demand for labor is going to go down in manufacturing from here on in. Thinking through this problem is, I would argue, a better use of our time than generating forwardable content for WhatsApp.
This matters, by the way, because election season is upon us, and we will soon have hordes of people yelling at each other on every platform available to humanity, online and offline. Half of them will yell about how 2004-2014 was heaven, and 2014-2024 was hell. The other half will yell about exactly the same thing, but with a (-1) outside the bracket.
Is it half and half? Or is it 37% and 63%? Quick, somebody run an RDD on this so that we can talk about truly important stuff on Twitter!
I invite you, dear wise and discerning reader, to stick your tongue out at all those rabble rousers and look at this chart instead:
Fact: if we had an industrial policy across these twenty years, it has failed. Full stop. No proof required, one might say.
Manufacturing as a percentage of GDP has not only not gone up in this time, it has actually declined from 16% to 13%. I look forward to the world class econometric analysis that Extremely Angry Economists on both sides of the divide will come up with to show that “No, actually, most of the decline occurred in <U/N,P/D,A> era”…
…but again, my personal stance is why bother trying to figure out who couldn’t get a stalled car to start? It’s still sitting right where it was twenty years ago, and that’s the real problem.
And it gets worse:
So let’s get one thing straight:
Not a single government has managed, over the last three decades, to set India on a sustained and sustainable path of increasing industrialization.
What Have We Learned, And What Do We Know?
Asking why no government could do this so far is a good use of our time. Asking what can be done from here on in is a good use of our time. Squealing and screaming about who is responsible for it not having happened so far may be cathartic, but that’s about it. Doesn’t help much beyond that.
So what can be done from here on in? Well, if the manufacturing chart is a depressing one, here is one imbued with some optimism:
Can services absorb all those young folks looking for jobs in the years to come? Or will manufacturing have to come to the rescue? Can it, given robotics and AI?
How should a policymaker think about this in general? How should a policymaker think about this in an Indian context? What are the strengths and weaknesses of either approach? What does research say about all of these questions? That’s what we will talk about in tomorrow’s post.
But make no mistake: this is what really and truly matters. India managed a good start on the long road to development in 1991, but we haven’t traveled far enough on that route in the years since. And that long road is about to get a whole lot tougher, given AI and robotics.
So please, let’s get a move on.
Should we get started on this then, or should we continue to shirk our responsibilities and shout inanities online instead?
Now that’s the kind of s and sh pontification that I can truly get behind.
EconForEverybody 