On Muddling Through

Anticipating the Unintended is an excellent newsletter, and you should subscribe to it. This past Sunday, the authors came up with a lovely read on the Agnipath scheme. You may or may not agree with their analysis, but I would heavily recommend that you read it. There’s a lot that is important in it, but for today’s blogpost, I want to focus on this excerpt:

Considering the constraints, it is difficult to see what else the government could have done here. The need to reduce wage and pension costs to fund modernisation is real. And given the fiscally conservative instinct of this government, it won’t deficit fund the modernisation programme. As is its wont, it has chosen to put a bold announcement with emphasis on other benefits while trying to solve its key problems under cover. There’s this myth that a big bang approach to reform is the only model that works in India. That’s wrong. A lot of what has looked like big reforms in India have actually had a long runway that’s often invisible to people. A more comprehensive reading of the history of ‘91 reforms makes this clear.
So, the usual template has been followed so far: minimal consultation, no plans to test it out at a smaller scale and instant big bang implementation. The results are unsurprising.

https://publicpolicy.substack.com/p/173-lathpath-lathpath-lathpath-agnipath#details

Let’s figure out they key questions at play:

  1. What is the problem?: Wage and pension costs for the military spiraling out of control. You could argue that this is an old, inevitable problem made worse by the implementation of the OROP scheme, but for the moment, look past the cause and consider the effect. And the effect is that the Indian government spends over half of it’s budget on pension benefits (24%) and on wages (28%).
  2. What is the proposed solution?: That’s the Agnipath scheme in its entirety. I invite you, once again, to read the whole thing, but the first two to three paragraphs in the newsletter summarize the scheme very well, if you are not familiar with it yet.
  3. Why is this solution important?: Their takeaway is that the main focus of the Agnipath program is to reduce wage and pension costs, and that this is necessary. I agree on both counts – no matter what else is being said, and no matter what else Agnipath might achieve (a younger military, among other things) it’s main aim is to reduce wage and pension costs. And even a cursory glance at our government’s finances should make clear that this is necessary.
  4. The How: That’s what the rest of today’s blogpost is about! Here’s the thing: there is a problem, and it needs a solution. That (to me, at any rate) is clear. But is this (Agnipath) the best possible solution? And even if it is, is the current method of implementation the best way of going about it?

I don’t mean to get into a discussion of whether Agnipath is the best possible solution for this specific problem, nor do I mean to definitively answer the question of whether the method of implementation is optimal.

Instead, I hope to help you build a framework to start to think about the answer to these two questions (is this the best solution | is this the best way to implement said solution) in general. And then, if you like, you might want to use said framework to judge for yourself the Agnipath solution. I do exactly that in what follows: outline the principle, and apply it to the Agnipath case.


Minimal Consultation | No Plans to Test It Out | Instant Big Bang Implementation

Of the three things that RSJ and Pranay have highlighted in their excerpt , I plan to focus on the latter two in terms of the how question. The answer to the question about whether consultations were done or not, and whether they were minimal or not is essentially a grotesque Rorschach test, and I’ll skip it entirely. But the latter two – no plans to test it out, and instant big bang implementation – don’t just ring true, but are also truly important, especially if you are a student of public policy.

Let’s focus on the word “It” in the second phrase, “No Plans To Test It Out”. What does “it” mean, in this context? That’s simple, you might say – test the solution out.

And what’s the solution? Agnipath, you might answer a tad impatiently. Ah, but how do we know that this is the best possible solution? And here’s the simple answer to this question: you don’t know that this is the best possible solution, because as with everything else in life, the proof of the pudding is in the eating of it. Your models might tell you that this solution is the best one, but all models work well, if at all, only in theory. To mix an apt metaphor, no battle plan survives contact with the enemy.

In other words, Agnipath is one of many different solutions to this problem. Moving to something like the NPS might be one, a modified version of Agnipath might be another, curtailing expenditures in other areas might be a third (to those who know their public finances in an Indian context, no I don’t think so either, but play along for the moment). May be the final solution that will be implemented at scale will be a mix of all these and more, who knows – but the point is, there are many possible solutions, of which at least some are worth trying out in an experimental sense.

The process should be seen as experimental, and probably involve acting on multiple potential solution ideas at a time (instead of just one). It can also be accelerated to ensure the change process gains and keeps momentum (to more or less degree, depending on where one is in the change process and what
problems, causes or sub-causes are being addressed). Trying a number of small interventions in rapid “experiments” like this helps to assuage common risks in reform and policy processes, of either appearing too slow in responding to a problem or of leading a large and expensive capacity building failure. This is
because each step offers quick action that is relatively cheap and open to adjustment; and with multiple actions at any one time there is an enhanced prospect of early successes (commonly called “quick wins”).

Andrews, M., Pritchett, L., & Woolcock, M. (2017). Building state capability: Evidence, analysis, action (p. 288). Oxford University Press., pp 170

So begin small, and begin with many different potential solutions. See which of these work and which don’t – which need tiny modifications to be better, and which need major surgery. Which might be usefully combined with some other solution(s)? Iterate towards a solution set that works “best” – and then implement this solution set at scale. But never presume, and especially without on the ground small scale implementation, that a proposed solution is necessarily the best one.

Pritchett and Woodcock have an excellent diagram for helping us think through this:

Andrews, M., Pritchett, L., & Woolcock, M. (2017). Building state capability: Evidence, analysis, action (p. 288). Oxford University Press., pp 172

“A.” in this case is the status quo, and given that there are no overt protests about it, we can say that the status quo is administratively and politically possible. But it is, as we have discussed, not fiscally sustainable, and hence undesirable.

“D.” in this case is the Agnipath solution. Let’s assume that it is a technically correct solution, and let’s assume that it (or something very similar to it) has either solved a similar problem in other countries (empirically validated) or has solved this exact problem, but in a simulation (theoretically validated). But it is not, as we are observing, politically possible. Now, sure, you can talk about the political motivations of the organizers of the protests, you can (and you should!) condemn the use of arson and wanton violence, and you can bemoan the role of the media. But if you accept that there is at least an inconvenient iota of truth in the idea that some sections of society feel hard done by this decision (warranted or otherwise), then you do in effect accept that it is not altogether politically possible. Your assessment may well differ from mine (and that is fine) but hopefully only in magnitude and not in direction.

The point is that we are trying to move from “A” to “D” in one fell swoop. Not only is that not a good idea in public policy, but we don’t even know if Agnipath is “D”! The very definition of D (or Agnipath) has changed in the recent past, is changing as we speak, and is likely to further iterate in the days/weeks/months/years to come. Which is as it should be, of course – my point simply is that these iterations and experimentations should happen in the design stage, not the roll-out stage.

So the general principle is that iterating through potential solutions at restricted scales is better. Even better when you learn from these iterations, modify your solutions, and come up with a hybrid that stands a better chance of working at scale. This helps in building out buy-in for your proposed solution as well. Won’t work perfectly, because nothing ever does, but remember that in public policy utopia ain’t our aim, being better than the status quo is.

Also, if you’re wondering about the title of the blog post, it is a tribute of sorts to a paper that ‘started’ studies in this particular area. Look up that phrase and the the name “Charles Lindblom” to go down a very nice little rabbit hole.


Bottomline: Crossing the river by feeling the stones remains excellent advice.

Neelkanth Mishra on the Inflation Spectrometer

There’s learning macroeconomic theory, and there’s applying what you know to the world around you. In an excellent column, which we shall parse together, Neelkanth Mishra teaches us how to use basic micro and macroeconomics to make sense of the world around us.

He begins with an analogy of the spectrometer, a device used to ‘disentangle’ waves. Having explained what a spectrometer is, and what it might be used for, he then goes on to say that you might be able to do something similar with economic phenomena, and asks if you could use an idea analogous to the spectrometer to disentangle the phenomena that are causing inflation.

Let’s dig in.


In theory, inflation is a macroeconomic phenomenon, and analysing it by category is unwise, as prices shift both supply and demand between categories — sometimes global and local factors mix as well. For example, higher oilseed prices could shift acreage from pulses in the upcoming Indian kharif crop, pushing up prices of pulses even though the initial supply disruption was in Ukrainian sunflower oil.

https://tessellatum.in/?p=433

It’s one thing to learn about supply and demand. It is quite another to learn about partial equilibrium. But it is a whole other thing (and the point of the entire exercise) to be able to apply these ideas to what we see around us. Can higher oilseed prices cause an increase in the price of pulses? And even if you were to tentatively say ‘yes’, the real challenge would be the follow-up question: through what channels, and why?

He identifies two clear strands of driving factors that are responsible for inflation today, beginning with a larger than necessary stimulus applied in America during Covid-19. As an interesting aside, he says that this ended up pushing retails sales ten standard deviations above normal.

If you are a student reading this, take the time to pause over here and reflect on this statistic. Ten standard deviations above normal? That sounds like a lot! But you should also ask yourself the following:

  1. What does above normal mean? How is it defined? Average annual sales over the last decade? Or is it monthly sales over the last five years? Or some other construct?
  2. The standard deviation only makes sense given our understanding of the first bullet point. What period has been used? How often have ten standard deviation events taken place in the last, say, one hundred years (assuming we have data going back that far, of course)?
  3. None of this, to be clear, is me doubting what Neelkanth Mishra has said. The point I am making is that you, as a student of economics, should try and run some Google searches to find out where that number comes from, or best of all, try and run the analysis yourself. Search for retail sales on Fred St Louis, and knock yourself out with a spreadsheet. As they say, get your hands dirty!
  4. Read the rest of the paragraph to get a sense of how to think through macroeconomic issues and understand them better.

The downward lash of this bullwhip is now starting, which can push apparent demand well below real demand. US federal fiscal deficit as a share of gross domestic product or GDP in the last three months is the lowest since June 2019. As services restart, a goods-to-services switch in consumption is underway; shipping bottlenecks have eased (though not fully); global industrial production got back above trend in February (though recent lockdowns in China hurt); and there is evidence of excessive inventory in many supply chains. Prices of TV panels and memory chips are falling, and the year-on-year price increases in metals are now much below those seen in April. Prices may not go back to the pre-Covid levels (meaning deflation from here), but the inflationary impulse does seem to be behind us.

https://tessellatum.in/?p=433
  1. Learn about the bullwhip effect.
  2. Play around with this chart to verify for yourself the fiscal deficit point. (If anybody reading this works, or can work with the RBI, please push for the DBIE website to be more like, and indeed better than, the Fred St Louis website. Thank you.)
  3. Run some searches for memory chip prices (add words like “trend”, 2022, H2 2022 and use Google’s search filters to narrow down the search results).
  4. Reflect on whether you agree about the inflationary impulse from the USA’s fiscal stimulus now being behind us. Say you had to disagree with his point: what would you choose to drag up as points that negate his hypothesis?

The second global impulse, the start of the Russia-Ukraine conflict, may be harder to adjust to, with demand and supply adjustments likely to take many quarters. The conflict and the associated sanctions have reduced the global supply of food and energy. Given that global GDP growth and the use of dense energy are intimately linked, fiscal and monetary measures can only redistribute what remains between countries; they cannot offset the shortages. Nearly every major economy has announced energy subsidies — while this is understandable, given the domestic political compulsions as well as the need to sustain growth, they will only prolong the period of higher energy prices. This can be seen as countries competing for the remaining supplies of energy, pushing up prices until the weak hands (countries) give up. Higher prices have also not triggered investments in new supplies yet, as suppliers lack certainty on how long the shortages may persist. These trends could keep prices higher for longer than currently anticipated.

https://tessellatum.in/?p=433
  1. Understand the point about fiscal and monetary stimuli being of limited use in a global context.
  2. Understand the unseen effect of domestic subsidies on global oil prices
  3. Trust me on this – there’s many, many, many pages of reports, news articles and blog posts that have been read for that one seemingly simple fragment of a sentence: “as suppliers lack certainty on how long the shortages may persist”. Learn, for your own sake, the art of reading a lot in order to be able to give a concise summary.

Moving to local drivers of inflation: Inflation occurs when a stimulus pushes aggregate demand above the economy’s capacity to meet it. Even though state governments’ deficits are much lower than budgeted, the total government deficit in India is higher than in pre-Covid times. The recent fiscal steps to prevent a rise in fertiliser and fuel prices, while prudent and to some extent necessary, may serve only to spread inflation over a longer period. The rise in India’s current account deficit (CAD), with May balance-of-payments (BoP) deficit run-rate at nearly 2 per cent of GDP, also suggests domestic demand, at least in its current mix, is unsustainable.

https://tessellatum.in/?p=433

If I was conducting an interview for a student who was aspiring to join the corporate world as an economist, I would have liked to have shown the candidate this paragraph, given them a laptop with an internet connection, and told them that they have thirty minutes to find the answers to the following questions:

  1. Find out for me the original source from where we can find out that state government’s deficits are much lower than budgeted
  2. Find out for me the original source for India’s CAD and B-O-P deficits.
  3. Answer for me, with data to back up your answer the following question: is India’s current mix of domestic demand unsustainable?

If you are not able to answer these questions, and you are currently a student of macroeconomics, you might wish to add stuff outside of your textbooks into your diet.


But now, best of all, for the three paragraphs that follow the one that I quoted in the previous section, I won’t come up with a list of comments and questions. I’ll in fact ask you to come up with questions yourself, along the lines that I just did, and then see if you can answer them.

Go ahead, give it a try!


This article is a great example of what hands on macroeconomics looks like. If you are in college and are wondering what your syllabus has to do with the world outside, ask yourself a simple question: do you see yourself as being capable of writing a similar article yourself?

That, if you ask me, is a true examination. Write it, please, and share it with all of us by putting it up for us to read in the public domain. What a great addition to your CV that would be.

No?

How To Look for Inflation

Here are links to the official sources:

The RBI’s DBIE website.

The latest CPI report on the MOSPI website.

The WPI PDF report from the EA Industry website.

If you want a secondary source with better graphs, Trading Economics is a good option.


But that’s not what I want to talk about today. What I want to talk about is how you might think about inflation.

Greg Ip, the chief economics commentator for the Wall Street Journal, speaks about how he came to deeply understand the topic of inflation when his mother told him that his pocket money would be linked to the consumer price index in Canada, which is where he grew up.

It’s one thing to ask students in a class to visit a website that provides information about inflation, and it is quite another to have a young person’s pocket money be linked to it. Guess who is more likely to follow the website keenly, and guess who is likely to ask questions along the lines of “But why should the prices of zarda, kimam and surti impact my pocket money, huh?”

(Item code 2.1.01.3.1.07.0 and these together carry a weightage of 0.04869% in our CPI. Link here, and while you are at it, look up 6.1.04.1.1.03.0, and 6.1.04.2.2.01.0, and ask yourself some very interesting questions. There’s lots more to ponder about in that PDF, these are just to get you started!)


But there’s other things to ponder about where inflation is concerned too:

If it really wanted to get ahead of the inflation challenge, India’s central bank should have paid more attention to Surf Excel.
The price of the laundry detergent went up by 20% in January. While that’s hardly news when most everyday things are becoming dearer everywhere, the interesting part was the retail price before the change: Rs 10 (13 US cents) for a bar.
Such tiny bars of detergent are targeted at less affluent consumers who are often unable to spend a rupee more without having to cut back on something else. To prevent these customers from downgrading to cheaper products, Unilever Plc’s India franchise relies on “magic price points” — such as Rs 5 or Rs 10 — that help buyers stay within their tight budgets.

https://theprint.in/opinion/magic-prices-did-warn-of-indias-sticky-inflation-but-rbi-didnt-notice/957873/

Read the rest of the article, and if you are unfamiliar with pricing, especially in an Indian context, this will help you learn about the nuances of inflation. You may or may not agree with the article’s conclusions about spotting inflation in India, and that’s fine, as far as we’re concerned. But what we should be learning is an important lesson:

Inflation is about more than just changing prices.


And finally, give a listen to this podcast – and if you can’t be bothered to listen to the whole thing, the really interesting bit starts at around the 24th minute or so, where Tyler Cowen and James Altucher help you understand how you might build your own inflation index. We got a puppy home recently, and I can attest to some of the points made in that section!


Read the news and make sure you keep an eye on inflation, sure. But learn – especially when it comes to a topic like inflation – that textbooks and newspaper articles are only a start. These topics are way more complicated than that.

Where Next For the NITI Aayog?

The NITI Aayog must be converted from a Department of Development Implementation to a High Command of Development Strategy.

https://www.business-standard.com/article/opinion/reforming-the-niti-aayog-122051601487_1.html

That’s the very last sentence of a thought-provoking column by Nitin Desai. The column is about why the NITI Aayog (in Nitin Desai’s opinion) hasn’t done all of what was hoped of it, and what needs to change for some of these hopes to be realized.

But for us to reach the end of this column, we need to start somewhere, and we’ll start with the setting up of the Planning Commission.


The Indian planning project was one of the postcolonial world’s most ambitious experiments. It was an arranged marriage between Soviet-inspired economic planning and Western-style liberal democracy, at a time when the Cold War portrayed them as ideologically contradictory and institutionally incompatible. With each Five-Year Plan, the Planning Commission set the course for the nation’s economy. The ambit ranged from matters broad (free trade or protectionism?) to narrow (how much fish should fisheries produce to ensure protein in the national diet?). The Commission’s pronouncements set the gears of government in motion. Shaping entire sectors of the economy through incentives, disincentives and decree, the Planning Commission’s views rippled across the land to every farm and factory. Despite this awesome power, economic planning in India was considerably different from the kind practised in communist regimes. The Planning Commission was reined in by democratic procedure that required consultation with ministries in an elected government, with people’s representatives in Parliament—and ultimately with the popular will—through citizens voting every five years.

Menon, Nikhil. Planning Democracy (p. 9). Penguin Random House India Private Limited. Kindle Edition.

That’s from a book I’m currently reading (and thoroughly enjoying), Planning Democracy. There’s a lot to like about the book, and I hope to write a full review once I’m done, but for the moment, think about just the title. There’s a (hopefully healthy) tension implicit in it, because as the excerpt above puts it, the Planning Commission was to be reined in by democratic procedure.

What was it supposed to do? Further on in the same chapter from the book I have just quoted is a nice compact description of what was supposed to have happened:

Its potency stemmed from its authority to draw up an economic roadmap for the country and back it with all the resources and policy instruments available to the Government of India.

Menon, Nikhil. Planning Democracy (p. 21). Penguin Random House India Private Limited. Kindle Edition.

That is, there are two separate but interlinked things worth noting: it had to develop an plan of economic development for a newly independent India, and in order to do so, it had the backing in terms of resources and policy instruments. By the way, there is a reason the word “resources” has not been qualified with a word like financial – the back was not just financial, but also political, given the presence of the Prime Minister and other cabinet ministers as members.

The story of how the Planning Commission evolved, struggled, and refined itself over time (not always successfully, it should be mentioned) is a fascinating one, but not one that we can cover in a single blog post, alas. But long story (very) short, the Planning Commission came to an end in 2015:

Born the same year, Modi and the Planning Commission shared another milestone together. In his first Independence Day address as India’s leader, Modi declared that the Planning Commission had once merited its place and made significant contributions. Now, however, he believed it had decayed beyond repair. ‘Sometimes it costs a lot to repair an old house,’ he said, ‘but it gives us no satisfaction.’ Afterwards we realize ‘that we might as well build a new house’, Modi explained with a smile. He would build it by bulldozing a decrepit structure and raising a shiny new one, the NITI Aayog (National Institution for Transforming India).

Menon, Nikhil. Planning Democracy (p. 8). Penguin Random House India Private Limited. Kindle Edition.

And how has the NITI Aayog done?

But despite progress in these areas, some 7 years since the establishment of NITI Aayog, questions are being raised as to whether India can continue to function without medium-term planning. Annual budget allocations are made by the Finance Ministry to meet various investment goals and objectives but without a well-defined plan. NITI Aayog’s advice is also not taken seriously by state governments as it comes without resources. Some feel that NITI Aayog should have resources it allocates to address development imbalances and that the Ministry of Finance is naturally focused on budgetary management rather than development outcomes.6While no one wants a return to the old Planning Commission, a more involved and competent NITI Aayog, with a stronger voice is clearly needed.

Ajay Chhibber, 2022. “Economic Planning in India: Did We Throw the Baby Out with the Bathwater?,” Working Papers 2022-03, The George Washington University, Institute for International Economic Policy.

The idea itself isn’t all that new. Back in 2019, Vijay Kelkar had given a speech in which he proposed “NITI Aayog 2.0”:

It should rather strive to be a think tank with “praxis” possessing considerable financial muscle and devote its energies to outline coherent medium and long term strategy and corresponding investment resources for transforming India. Towards this, my preliminary study suggests that the NITI Aayog 2.0 will annually need the resources of around 1.5% to 2% of the GDP to provide suitable grants to the States for mitigating the development imbalance. These formulaic annual grants, whether capital grants or revenue grants for the relevant CSS will need to be conditional to ensure that (1) outcomes are commensurate and (2) it discourages an individual State to adopt policies that have negative policy externalities, e.g., creation of populist subsidies and thus avoid race to the bottom. Such presence of “negative policy externalities” we notice often, e.g., the provision of free “electricity,” irrigation water subsidies, etc. “Gresham’s Law” seems to be relevant not only for the currency markets alone!

Towards India’s New Fiscal Federalism, No. 252, NIPFP Working Paper Series, Vijay Kelkar (https://www.nipfp.org.in/media/medialibrary/2019/01/WP_252_2019.pdf)

If you don’t know what Gresham’s Law is, take a look here.


All of which eventually gets us back to the column that we started with, by Nitin Desai:

The real problem of strategy formation for development is that it is not being done. The NITI Aayog has produced some vision documents; but they are not agreed strategies formulated after widespread consultations with experts and discussion with the states. The word “niti” in the name of this organisation is an abbreviation for National Institution for Transforming India. This task requires looking a level above the designing of programmes to a strategy from which programmes must be derived.
A grand strategy for development must spell out the opportunities and threats faced by the key objectives of development which are growth, equity and sustainability. It must then identify the changes in the role of the public and private sector, shifts in global economic alliances and policy shifts that are required to maximise benefits from opportunities and manage risks from threats. The time frame for a grand strategy has to be long-term but the more specific strategies derived from it must take into account short- and medium-term challenges that the country faces.

https://www.business-standard.com/article/opinion/reforming-the-niti-aayog-122051601487_1.html

We need, that is to say, a NITI Aayog that focuses on not just reporting what has been (or is being) done, but also on explaining what needs to be done, over what time period, and why, along with some pointers towards what risks we might encounter. Or as Nitin Desai puts it, “The new Vice-Chairman, Suman Bery, must bring in the talent required and launch a process of broad-based consultation, particularly with the states, to secure a broad national consensus on a long-term growth strategy. Specific programmes must be based on the implementation of this strategy.”

Easier said than done, of course, but this is where NITI Aayog needs to go next.

The Solow Model and China

If you don’t know what the Solow model is, here is a great place to get started:

There are 11 videos in that series, and if you can spare the time, please watch all of them. Just two a day (they’re not more than 5 minutes each), and you’ll be done come the weekend.

But in effect, here is what the Solow model says:

  1. Output for a nation is a function of three (actually four) things:
    1. Capital (K): Buidings, ports, dams… infrastructure, basically.
    2. Education Augmented Labor (eL): The amount of hours that a person is able to put in to their work, but with the built in assumption that an educated person is likely to be more productive than a person without education.
    3. Ideas: Read the paragraph below to get a sense of what this means in practice.

Think about this blogpost that you are reading. I wrote it using my laptop, which is my capital. I will spend about an hour (that’s my plan, I’ll update you towards the end of this post about how well it worked out) writing it, and that’s the labor that I’ll be putting into this post. The fact that I have been “educated” in economics should mean that this post will be easier to write for me than, say, a gardener. The gardener could have written this post as well, of course, but it’s safe to assume that she would first have had to learn about the Solow model, and that, presumably, would have taken longer.

So that’s K and eL where the output (this blogpost) is concerned. But now think about it this way: what if another person, with a similar level of economics education as mine were to write this blogpost instead of me? Would that person have chosen this video, and these paragraphs to explain the Solow model? Maybe they would have recommended some other video, or some other podcast, or chosen to share details of an online textbook in which the Solow model is explained. That’s one way to think about ideas.

And so when you combine the capital (the laptop), the labor (the time I spend on this blogpost, given my education levels) and the ideas (what I choose to put into this blog post, and how), you get the output you’re reading right now.

What if I double the capital? Will the blogpost be done in half the time? Say I have an external monitor attached to my laptop – will two screens mean finishing the blogpost in half the time? It will save some time, but not by a factor of two, surely. Trust me, I have tried.

What if I double the labor? Hire an assistant to write this blogpost with me? The way I work, trust me, it will probably take longer! What if I go get a post-doc, to augment my education? Will that save me time? The hysterical laughter you hear in the background is the response of any PhD/post-doc student anywhere in the world, and that sound means a loud and resounding no.

In a sense, the Solow model asks these and related questions, and answers them using some graphs and equations. Except, of course, the Solow model does it for not one guy writing one blog, but for an entire nation at a time. There is no sense in me explaining the whole model over here, for it would be a case of me reinventing what is already a very good wheel. Please watch the videos.


But the Solow model is a remarkably useful way to get a handle on the long run growth prospects of a country. Is India likely to grow in the future? Well, is it going to add to its capital stock? Yes. Is it going to augment it’s stock of education augmented labor? Yes. Is it likely to produce more ideas than it is right now? Yes. And so the growth prospects for India look reasonably good.

Of course, there is more to the Solow model. All of this holds true given a strong and stable political system, well established rules of law, and strong and capable institutions. But so long as you believe that these are likely to continue to be so in the Indian case, you should be bullish on India.

What about, say, Japan? It has a capital stock that is more in need of replacement than new construction ( a feature of the Solow model that we have not discussed here, called depreciation), so it is unlikely that it will grow its capital stock too much. Here’s an example of what I mean. What about it’s stock of education augmented labor? Well, the news ain’t very good. Ideas? Trending upwards, but not by much. So if I had to bet on which country would grow more over the next twenty years, I would bet on India, not Japan.

Bear in mind that this is a model, and like all models, it is an imprecise abstraction of reality. So it is possible that at the end of the twenty year period, we find out that I am completely wrong. But if you think the Solow Model is a reasonably good model, you ought to bet the way I did.


So what about China?

Well, now, that’s a whole different story, and one that Noah Smith talks about in a recent blog post. Long story short, he doesn’t think China’s growth prospects are that great.

But the story is a little more complicated than that. The Solow model is a good model, sure, but it’s not as if the Chinese authorities/experts aren’t aware of the problem. And in his blog post, Noah looks at arguments put forth by two people who know a thing or two about China, and analyzes them critically.

The first argument is that sure, China’s demographics are on a downward trend, but what if we raised the retirement age for Chinese workers? Would that not solve the problem? Noah says no, probably not, because firms made of exclusively old folks isn’t necessarily a good idea. I wholeheartedly agree.

What about adding to China’s urbanization, and therefore its infrastructure? After all, China’s urbanization rate is “only” 64%. The inverted quotes around only in the previous sentence is because we, in India, are officially at 31%, but as in the case of China, it very much is a function of how you define urbanization. But similarly, in China, the urbanization rate is actually way more than 64%, and the Lewis turning point has already taken place in China, or will do so any moment.

And about ideas, well, China is an even more complicated story. Noah makes the point that China’s industrial policy is essentially a one-man army that is trying something that has never been tried before, and Noah is betting on it not quite working out. And given the events of the last year and a half or so, it is hard to disagree.

And so the Solow Model would probably tell you that China is unlikely to grow as fast in the near future as it did in the recent past, and even if you take into account potential adjustments, it likely will still be the case that China’s growth rate will start to plateau.


Please, read the entire post by Noah. But if you are a student of economics who has not yet met the Solow Model, begin there, and then get on to Noah’s post – your mileage will increase considerably.

CinemaRare on Hidden Gems on Zee5

I plan to spend part of this summer watching movies, and this list seems to be a good way to get started with movies from India:

Reflections on Whole Numbers and Half Truths

Single narratives have never been able to explain all of India.

S, Rukmini. Whole Numbers and Half Truths: What Data Can and Cannot Tell Us About Modern India (p. 220). Kindle Edition.

There is this line that is often quoted when big picture discussions about India take place, and it is only a matter of time before it comes up: whatever you say about India, the opposite is also true. The quote is attributed to Joan Robinson, and I can’t help but wonder if I will end up creating a paradox of sorts by agreeing wholeheartedly with it.

But I do agree with the spirit of the quote, which is why that one line extract from Rukmini S’s book, Whole Numbers and Half Truths, resonated so much with me. All countries are complex and complicated, but India takes the game to giddying heights.

Take a look at this map, a version of which is present in Rukmini’s book:

https://en.wikipedia.org/wiki/List_of_states_and_union_territories_of_India_by_fertility_rate

What is India’s TFR? First, for those uninitiated in the art and science of demography, what is TFR? It stands for Total Fertility Ratio, or as Hans Rosling used to put it, babies per woman. Well, it’s 2.0, which is good, because roughly speaking, two parents giving birth to two children will mean we’re at the replacement rate (note that this is a very basic way of thinking about it, but useful as a rough approximation).

But as any student of statistics ought to tell you, that’s only half the story (or half the truth). Uttar Pradesh, Bihar and Jharkhand are well above the so-called replacement rate, and that will have implications for labor mobility, taxation, political representation and so, so much more in the years to come.

Data then, is only half the story. How is the data collected? If it is a sampling exercise rather than a census, how was the sampling done? Has the sampling method changed over time? If so, are earlier data collection exercises comparable with current ones?

How should one think about the data that has been collected? What does it mean, and how much does context matter? For example:

‘That’s data about marriage, madam,’ he said—not about love. ‘I think if your data asked people if they have ever fallen in love with someone from another caste or religion, many will say yes. I see that all around me among my friends. But when it comes to getting married, most of us are not yet ready to leave our families. That’s why your data looks like that,’ he said. As for the rest? ‘There is a lot we will not admit to someone doing a survey. But things are changing. At least for some of us,’ he said.

S, Rukmini. Whole Numbers and Half Truths: What Data Can and Cannot Tell Us About Modern India (pp. 127-128). Kindle Edition.

Rukmini’s excellent book is, in one sense, a deep reflection on the data that we have, have had, and would like to have where India is concerned. It speaks about how data has been collected, which are the agencies and institutions involved, how these have changed (and been changed) over time, and with what consequences.

But it also is a reflection on a truism that many economists and statisticians underrate: data can only take you so far. As the subtitle of her book puts it, it is an analysis of what data can and cannot tell you about modern India.

And what data leaves out is often as fascinating as what it includes:

Yet, most people know little about the NCRB’s processes and methodology. For instance, the NCRB follows a system known as the ‘principal offence rule’. Instead of all the Indian Penal Code (IPC) sections involved in an alleged crime making it to the statistics, the NCRB only picks the ‘most heinous’ crime from each FIR for their statistics. I stumbled upon this then unknown fact in an off-the-record conversation with an NCRB statistician in the months after the deadly sexual assault of a physiotherapy student in Delhi in September 2012. In the course of that conversation, I learnt that the crime that shook the country would have only made it to the NCRB statistics as a murder, and not as a sexual assault, because murder carries the maximum penalty. This, I was told, was to prevent the crime statistics from being ‘artificially inflated’: ‘If the FIR is for theft, there will be a[n IPC] section for assault also, causing hurt also. If you include all the sections, people will think these are separate crimes and the numbers will seem too huge,’ he told me. After I reported this,2 the NCRB for the first time began to include the ‘principal offence rule’ in its disclaimer.3

S, Rukmini. Whole Numbers and Half Truths: What Data Can and Cannot Tell Us About Modern India (p. 13). Kindle Edition.

The paragraph that follows this one is equally instructive in this context, but the entire book is full of such Today-I-Learnt (TIL) moments. Even for those of us involved in academia, there is much to learn in terms of nuance and context by reading this book. If you are not in academia, but are interested in learning more about this country, recommending this book to you is even easier!

Rukmini’s books spans ten chapters on ten different (but obviously related) aspects of India. We get to learn how Indians tangle (or quite often choose not to!) with the cops and the courts, how we perceive the world around us, why Indians vote the way they do in the first three chapters. The next three are about how (and with whom) we live our lives, and how we earn and spend our money. The next trio is about how and where we work, how we grow and age and where Indians live. The final chapter is about India’s healthcare system.

Each chapter makes us familiar with the data associated with each of these topics, but each chapter is also a reflection on the fact that data can only take us so far. When you throw into the mix the fact that the data will always (and sometimes necessarily) be imperfect, we’re left with only one conclusion – analyze the data carefully, but always bear in mind that the reality will always be more complex. Data is, at the end of the day, an abstraction, and it will never be perfect.


One reason I liked the book so much is because of its brevity. Each of these chapters can and should be be a separate book, and condensing them into chapters can’t have been an easy task. But not only has she managed it, she has managed to do so in a way that is lucid, thought-provoking and informative. Two out of these three is a good achievement, to achieve all three and that across ten chapters is a rare ol’ achievement.

If I’m allowed to be greedy, I would have liked a chapter on the world of data that the RBI collects, and to its credit does share with us via its website. But it does so in a way that is best described as unintuitive. In fact, a book on how data sharing practices with the citizenry need to improve out of sight where government portals across all verticals and at all levels are concerned would be a great sequel (hint, hint!).


I’d strongly recommend this book to you, and I hope you enjoy reading it as much as I did.

We will be hosting Rukmini on the Gokhale Institute campus this coming Friday, the 29th of April. The event will be from 5.30 pm to 7.00 pm at the Kale Hall. She and I will speak about the book for about an hour, followed by a Q&A session with the audience.

If you are in Pune, please do try and make it!

Read Blogs Written by Gulzar Natarajan

Regular readers must be sick and tired of hearing me say this, I suppose, but please: read blog posts written by Gulzar Natarajan!

Especially so if you happen to be a student of economics. The art of taking a complex topic, asking simple questions about it, marrying them to the appropriate economic concepts that will help in the analysis, and reaching a cogent, well argued conclusion is a rare, rare skill. And Gulzar Natarajan possesses it in spades!

Consider the post titled The Demand Supply Gap in Medical Education.

The demand supply gap is stark. About 1.6 million students appeared for the National Eligibility cum Entrance Test (NEET) in 2021, of which only 88,120 make it to the 562 public and private medical colleges. That’s 19 applicants for every seat. Those numbers are now 89,875 and 596.
How do you analyse this market? What will be the impact on seat prices due to supply changes of medical seats? How will the supply side react to this situation of large numbers of Ukraine returned students? What will be the profile of supply side?

https://gulzar05.blogspot.com/2022/03/the-demand-supply-gap-in-medical.html

These are not hard questions to frame. In fact, I would argue that most of us will be able to frame these questions even without having studied economics formally. But that being said, framing them this simply and concisely takes years of practice.

He identifies four main problems that we need to deal with:

  1. The major constraint is the source of quality faculty
  2. Private supply of medical colleges is unlikely to make up the shortfall (he explains why in the post, and I tend to agree)
  3. As he puts it, “In an acutely supply deficient market, the limited marginal supply is likely to bid up the medical seat prices even more”. I would only add one word to this sentence, between the words marginal and supply: quality. It’s not so much about the supply going up as it is the degree to which high quality supply goes up.
  4. Ah, but alas, that brings us to an even more difficult question: quality as it truly exists, or quality as perceived by prospective students and by society? I studied in Fergusson College in Pune, so I have a moral right to ask this question. And that’s what he means by the phrase “lemon problem“. If you’re wondering why this is known as a lemon problem, take a look at this.

His preferred solution is having the government step in to augment the supply, using government district hospitals and some area hospitals. This, he says, is preferable to the public-private-partnership (PPP) model. I don’t dispute the assessment of the PPP model, and its shortcomings. But I’m curious about why he would say that government institutions are always going to assure a certain basic minimum assured quality. Is this necessarily true, even in a relative sense? And if so, why?

And the concluding paragraph is at once depressing and optimistic:

Finally, this is a teachable example on the reality that though many problems have no immediate solutions, we try to solve them. Part of it is about wanting to do something and also be seen doing something. This is a human reflex and a political economy compulsion. Bridging the demand-supply gap in medical education is one such problem. Given our context and constraints, it’s very unlikely that we can bridge this gap in the foreseeable future. Like with other similar problems like affordable housing, agricultural productivity, or traffic congestion, we can only create the conditions required for its mitigation and gradual easing.

https://gulzar05.blogspot.com/2022/03/the-demand-supply-gap-in-medical.html

Depressing because, as he says, it is unlikely to be solved any time soon. Optimistic because creating the conditions is easier said than done, but it is achievable.

What might these conditions be? How does one go about creating them? If you’re interested in the answers to these questions, you are, like it or not, now a student of economics and public policy.

P.S. And the answers themselves require many more blogposts, but please, feel free to search around on this blog for some of ’em! 🙂

Aamdani rupaiya, kharcha atthanni

If you’re not familiar with the Hindi language, the title of this post is a play on a fairly popular phrase: aamdani atthanni, kharcha rupaiya

In effect, your income is less than your expenses. Which, of course, isn’t a desirable state of affairs:

For all of the last decade, the primary metric for evaluating budgets was the fiscal deficit. How much would the government target to bring it down by, and how credible were the numbers? The source of that stress was the massive stimulus set in motion by the government well before the global recession showed up, as it was inundated by taxes in the 2006 to 2008 period. The challenge with that stimulus was that it was hard to roll back, much of it being a large increase in state and central government salaries and pensions.

https://tessellatum.in/?p=409

But we find ourselves in unchartered territory, says Neelkanth Mishra:

Tax collection is surprising positively, and should be more than 1 per cent of GDP higher than before the Covid-19 lockdowns (though assumptions are lower). Further, financial markets appear to be expecting both central and state governments to incur large fiscal deficits for several years, with the anchor shifting higher by 3 per cent of GDP. Let us assume that GDP being below where it was supposed to be if the pandemic had not happened means an extra per cent-and-a-half of costs for the government. Interest costs have risen as governments borrowed to bear a large part of the economic loss during the lockdowns. Further, some government expenses, like salaries and pensions, keep rising irrespective of the level of GDP. This still leaves 2.5 per cent of GDP of space for governments to increase spending.

https://tessellatum.in/?p=409

And as it turns out, it is unchartered territory for everybody, the government itself included. Neelkanth Mishra points out that we’re bringing off-budget items on to the budget, we’re paying off export incentives that were due, and the debt write-off for India has also been accounted for. Even so, he says, cash balances maintained by the government with the RBI are at an all time high.

So what can be done? Well, part of the answer this time around lies in asking the states to step up and spend on building out physical infrastructure:

The sharp increase in capital expenditure from Rs 5.45 trillion to Rs 7.5 trillion shows the intent of the government is to stay away from distributing freebies (commendable, given the upcoming state elections), and focus instead on productive spending, which may be rolled back if necessary. However, half of this increase is an allocation for interest-free loans to state governments for capital expenditure, and some of the rest is the inclusion of off-budget provisions in last year’s budget in the budget numbers this year. There are increases in the allocation for defence (particularly once adjusted for the lower spend on aircraft purchases this year), the Nal se Jal scheme, and for roads and railways, but these are incremental rather than substantial.
Allowing state governments more fiscal space (deficits up to 3.5 per cent of GDP are allowed, with another half a per cent if the state undertakes power sector reforms), and dangling the carrot of more funding if they undertake capital expenditure is the right approach in theory. Much of the necessary investments need to occur at the state level: Like in health, education, urban infrastructure, water supply, sanitation and power distribution. However, the gap between states’ intent to spend and their execution has widened substantially during the pandemic, and their total spending is far lower than budgeted, despite increases in non-discretionary expenses like interest costs, salaries and pensions.

https://tessellatum.in/?p=409

And the limiting factor there, ironically, is limited state capacity.

…many developing countries and organizations within them are mired in a “big stuck,” or what we will call a “capability trap”: they cannot perform the tasks asked of them, and doing the same thing day after day is not improving the situation; indeed, it is usually only making things worse. Even if everyone can agree in broad terms about the truck’s desired destination and the route needed to get there, an inability to actually implement the strategy for doing so means that there is often little to show for it—despite all the time, money, and effort expended, the truck never arrives.

Andrews, M., Pritchett, L., & Woolcock, M. (2017). Building state capability: Evidence, analysis, action (p. 10). Oxford University Press.

In other words, we have more money to spend this year, but our constraint is quite literally our inability to spend it usefully and efficiently.

It would be worth our collective while, then, to learn a little bit more about state capacity!

Visualization and the NFHS

A very quick post today, because the end of the year is proving to be anything but a holiday, alas.

My third post in the series about NFHS was going to be about a pet theme (and peeve) of mine: our inability to get better visualization for our data, and indeed better reporting of data in general. But there is good news on this front, finally – there is now an excellent resource that we can use to visualize the results of the NFHS-5 survey.

Here’s just one chart to whet your appetite: blood sugar level among adult women (high, or very high or taking medicine). Note that the chart for men is largely similar.

https://geographicinsights.iq.harvard.edu/nfhs-tracker-districts

This is great work, and kudos to everybody associated with this visualization project! 🙂

H/T: Shashank Patil