Variants of Concern

I didn’t do so well last year in terms of posting regularly around this time onwards, and it was because thinking about Covid overwhelmed me. I’ve studiously tried to avoid writing about it since then as much as possible, but this post is an exception to that self-imposed rule.

First, about the “second” wave in India. We’ve been here before, about a century ago. I’d written down notes from Laura Spinney’s excellent book, The Pale Rider in March of last year, and there was this bullet point:

The flu struck in three waves, and the second wave was by far the deadliest.

There are many possible reasons for why the second wave is likely to be much worse than the first, and I do not know enough to be able to even speculate which one is the most likely. But both a century ago and now, the second wave was by far and away the worst:

Please, read the whole thread.

And here we are, a century down the road. Via the excellent, indefatigable Timothy Taylor, this little book. And from that little book, this not-so-little excerpt:

Manaus, a city on the Amazon River of more than 2 million, illustrates the dangers of complacency. During the first wave of the pandemic, Manaus was one of the worst-hit locations in the world. Tests in spring 2020 showed that
over 60 percent of the population carried antibodies to SARS-CoV-2. Some policymakers speculated that “herd immunity”—the theory that infection rates fall after large population shares have been infected— had been attained.

That belief was a mirage. A resurgence flared less than eight months later, flooding hospitals suffering from shortages of oxygen and other medical supplies. The pandemic’s second wave left more dead than the first.

Scientists discovered a novel variant in this second wave that went beyond the mutations identified in the United Kingdom and South Africa. This new variant, denominated P.1, has since turned up in the United States, Japan, and
Germany. Scientists speculate that a high prevalence of antibodies in the first wave may have helped a more aggressive variant to propagate. The hopes for widespread herd immunity may be dashed by the emergence of more infectious
virus variants.

Since the outbreak in Manaus in January 2021, P.1 has now spread throughout Brazil. The variant is much more transmissible than those that had been circulating previously in the country. High transmissibility and the absence of
measures and behaviors to stem the dissemination of the virus have led to the worst health system collapse in Brazilian history. The country has been on the front pages of major news outlets around the world not only due to the dramatic
situation that is currently unfolding but also because of the global threat posed by a major country with an uncontrolled epidemic.

The point is not to read more about the P1 variant. That is a worthy exercise, and you can see this, this and this for starters. But the point that I want to make is this – well, the points I want to make are these:

  1. The one other instance we have of a global pandemic tells us that the second wave was deadlier.
  2. That seems to be the case this time around as well, because the same virus has mutated into a variety of different forms over the past year in different parts of the world.
    1. Each of these so-called “variants-of-concern” will have different impacts, both in their countries of “origin” and (inevitably) elsewhere.
    2. How variant x affects individual y in region z is down to a long list of potential factors.
  3. And therefore 2021 already is, and will continue to be, worse in many ways compared to 2020.

And again, not just because of the P1 variant. That is simply one (worrisome, to be sure) variant – there are many more, and there will be more still to come.

Bottomline: we’re just getting started with the second wave. It isn’t the beginning of the end – it is the end of the beginning.

Chitarman’s “Shah Jahan on a Terrace, Holding a Pendant Set With His Portrait,”

You’ve probably seen this already, for it has been making the rounds on Twitter this past week. But just in case you haven’t, arm yourself with a cup (or two) of coffee, and spend about thirty minutes going over this feature.

It is beautifully done, and covers India, Persia, aspects of Christianity, Rembrandt(!), the advent of the British in India, Aurangzeb, the Taj Mahal and much more in a wonderfully informative package. Plus, personally speaking, I added two words to my vocabulary: anthomaniac, and lapidary.

Playing Around With Data

In yesterday’s post, I spoke about collection, and a teeny-tiny bit about the history of the institutions behind data collection exercises in India.1

In today’s post, I’ll compare two websites – one American and one Indian – to show you how both countries allow researchers to use the data that has been collected. Spoiler alert: the American website does a way better job. The idea isn’t to run down the Indian website, but to see how much distance we need to cover in terms of improvement.

And I think it is a worthwhile question to ask – why is the American website so much better? What is it about us that we cannot come up with a website of a similar quality? Is it a question of capacity, of bureaucratic inertia, of not enough demand from the research community in India or something else altogether? This is a topic worth thinking about… but not today.

The American website is FRED, hosted by the St Louis branch of the Federal Reserve. FRED stands for Federal Reserve Economic Data, and it is a magnificent resource. It really and truly is.

Federal Reserve Economic Data (FRED) is a database maintained by the Research division of the Federal Reserve Bank of St. Louis that has more than 765,000 economic time series from 96 sources. The data can be viewed in graphical and text form or downloaded for import to a database or spreadsheet, and viewed on mobile devices. They cover banking, business/fiscal, consumer price indexes, employment and population, exchange rates, gross domestic product, interest rates, monetary aggregates, producer price indexes, reserves and monetary base, U.S. trade and international transactions, and U.S. financial data. The time series are compiled by the Federal Reserve and many are collected from government agencies such as the U.S. Census and the Bureau of Labor Statistics.

The economic data published on FRED are widely reported in the media and play a key role in financial markets. In a 2012 Business Insider article titled “The Most Amazing Economics Website in the World”, Joe Weisenthal quoted Paul Krugman as saying: “I think just about everyone doing short-order research — trying to make sense of economic issues in more or less real time — has become a FRED fanatic.”

I’ve been using the website for years now in classes that I teach, but I’m sure there are features of the website that I have not been able to use. It’s got the ability to create charts on the fly, it has embeddable widgets, it even has a functional Excel add-in.

If you’re looking at this website for the first time, try going through these exercises. Or, if you are a video kind of person, try this playlist on YouTube.

It is, all things considered, a wonderful way to take a look at data – mostly American, naturally, but it does have a whole host of other data series as well.

The Indian website is our comparable offering: the database on the Indian economy. As you will see once you click on the link, it isn’t nearly as user-friendly as FRED, and in my experience, the website itself isn’t always “up” all the time. There isn’t, to the best of my knowledge, a YouTube channel that explains how to use the website, and while there is a brochure about DBIE, it isn’t quite as helpful as it ought to be.

Indian researchers will also visit the MOSPI website often. That is the Ministry of Statistics and Programme Implementation. If you read the link supplied in the first footnote of today’s blogpost, you will know that MOSPI is the culmination of India’s data collection exercises – these have been ongoing since at least 1881.

The MOSPI website itself is a bit problematic, because there are two now. One is, which is the one I have linked to above, and the other is This one seems to not be fully functional just yet, and the data is far from complete. Gratifyingly, what little data there is on the new website is made available in Excel formats.

That is actually a major problem, because on the old (but current, if you see what I mean) MOSPI, data is given in PDF format. There is an army of Indian researchers who have fought the Great PDF Wars, as a consequence, and therefore have learnt about Chrome extensions, and about Tabula. If you are planning on researching the Indian economy, you will have to acquire these skills sooner or later, for MOSPI and DBIE are the best we have on offer in terms of data portals2.

I said I won’t speak about the “why” regarding data portal quality, but I would like to offer a suggestion about the “how” in terms of improving it.

Appoint an educational institute to be the nodal agency3, and get them to work on a report about what needs to change, and why and how, for the DBIE website to become better than it is right now. That doesn’t mean (at all) a blind copy of FRED, awesome though FRED definitely is.

And if the team that does end up working on this is also allowed to come up with a beta version of the new website, well, that would just be the proverbial cherry on top.

I mean, why not?

  1. Really teeny-tiny bit. Please read the whole thing[]
  2. that are free and government run. There are other data portals available, but of course one must pay for them[]
  3. IGIDR would be a good pick for obvious reasons[]

Notes from Does Management Matter? Evidence from India, by Bloom et al

  • Yesterday, I had linked to a paper by Bloom et al, and said that it would be a good place to start reading about productivity, particularly from an Indian point of view. Here are my notes from the paper:

  • As per Hsieh and Klenow the ratio of TFP in Indian and Chinese firms is 5(!) between the 90th and the 10th percentile
  • The quality of management, and therefore management practices, is one explanatory factor
  • Economists tend to not buy into this because they assume that profit maximization implies cost minimization
  • So in other words, if firms are not minimizing costs by adopting good management practices, it is because “wages are so low that repairing defects is cheap. Hence, their management practices are not bad, but the optimal response to low wages.”
  • In this paper, large multiplant textile firms were split into treatment and control groups. The treatment groups were given management consulting from a top consulting group, the control groups weren’t.
  • The result: “We estimate that within the first year productivity increased by 17%; based on these changes we impute that annual profitability increased by over $300,000. These better-managed firms also appeared to grow faster, with suggestive evidence that better management allowed them to delegate more and open more production plants in the three years following the start of the experiment. These firms also spread these management improvements from their treatment plants to other plants they owned, providing revealed preference evidence on their beneficial impact.”
  • So why wasn’t this being done already?
    • No need, because benchmarking was with local competition, who weren’t doing it anyway
    • Simple lack of awareness
    • A naïve belief that nothing would change by adopting these practices
  • But even within local competition, why did firms not exit?
    • Competitive pressures were heavily restricted
      • High import tariffs
      • No entry of firms by lack of external finance
      • Number of male family members
      • Lack of trust of professional managers (family owned businesses)
  • TFP in India is about 40% that of the USA, as per Caselli 2011
  • “Indian firms tend not to collect and analyze data systematically in their factories, they tend not to set and monitor clear targets for performance, and they do not explicitly link pay or promotion with performance. The scores for Brazil and China in the third panel, with an average of 2.67, are similar, suggesting that the management of Indian firms is broadly representative of large firms in emerging economies.”
  • The interventions comprised of improvements in:
    • Factory operations
    • Quality control
    • Inventory
    • Human Resource Management
    • Sales and order management
  • This was done by implementing the following steps:
    • A diagnostic phase
    • An implementation phase (this was for only the treatment group, obviously)
    • A measurement phase
  • The authors carefully consider whether the Hawthorne effect was at play, and reject the possibility.
  • ” In every firm in our sample, before the treatment, only members of the owning family had positions with any real decision-making power over finance, purchasing, operations, or employment. Non-family members were given only lower-level managerial positions with authority only over basic day-to-day activities. The principal reason seems to be that family members did not trust non-family members. For example, they were concerned if they let their plant managers procure yarn they may do so at inflated rates from friends and receive kickbacks.”
  • “A key reason for this inability to decentralize appears to be the weak rule of law in India. Even if directors found managers stealing, their ability to successfully prosecute them and recover the assets is likely minimal because of the inefficiency of Indian courts”
  • “Hence, the equilibrium appears to be that with Indian wage rates being extremely low, firms can survive with poor management practices. Because spans of control are constrained, productive firms are limited from expanding, so reallocation does not drive out badly run firms. Because entry is limited, new firms do not enter rapidly. The situation approximates a Melitz (2003)–style model with firms experiencing high decreasing returns to scale due to Lucas (1978) span of control constraints, high entry costs, and low initial productivity draws (because good management practices are not widespread).”
  • There are three reasons for inefficiency:
    • motivation problem
    • inspiration problem
    • perception problem
  • I need to read Lucas (1978) and Melitz (2003) next!

A Hoarding Index. Because Why Not?

Are there easy, fun ways to combine what you learn in a classroom with easily available technology? Can these learnings be deployed for everybody to see and play around with, and can meaningful data emerge from such an exercise?

I’ve been asking myself this question for a while now, and have bee playing around with a couple of ideas in my head. Today’s post is about one such idea: it is me thinking out loud, and inviting you guys to throw suggestions, criticisms and potential problems my way. If anybody reading this wants to run with the idea, please – whatcha waiting for?

There isn’t an Indian road that isn’t riddled with hoardings. I mean, there may be the odd exception in each city, but it is safe to say that over 90% of all thoroughfares in all Indian cities have hoardings.

Calcutta learns no lesson from Chennai, hoardings boom - Telegraph India
Image Credit: Telegraph India
Original URL:

What if two students got on a bike once a month, and took photographs of every single hoarding along a three kilometer stretch of road in their city? Same road, on the same date, every single month. What if this was done for many roads in may cities in India?

Almost all phones these days will allow you to geotag your photographs. Take the photos of these hoardings, and identify which ones have an advertisement on them, and which ones have those “CONTACT” signs, which effectively means that there is no advertisement on it for that month. Identify which ones have advertisements related to real estate, and which ones have non-real-estate advertisements.

You needn’t restrict yourself to only No advertisement/Advertisement for real estate/ Advertisement for non-real estate, of course. Make it as granular as you like!

And once you have the data, start to automate reports about it. The index could be a barometer for how well the local economy is doing, and how well it correlates with the state’s economy, or the Indian economy. You could build separate indices for all the sectors that you tag in your database. You could measure month-on-month changes, quarter-on-quarter changes, and you could build your own time-series data.

If enough students in enough cities get in on the exercise, you could do comparisons across cities, and across time.

This would, of course, naturally raise questions about which roads in which cities. How many roads in each city? Is MG Road in Pune city comparable to Baner Road in the same city? Why or why not? Are hoardings in Pune comparable to hoardings in Mumbai? What about Cochin? What about Bhopal? What about Lucknow?

One way to learn research methodology is to sit in a classroom and learn about it in the abstract. Any prof will tell you that a subject like RM can never be taught in the abstract. You need to get your hands dirty, you need to ask yourself these questions – that is when the subject comes alive.

Plus, this project has the advantages of teaching you:

  • Team Building: there will be a lot of enthusiasm to begin with, but these things have a habit of petering out. It needs coordination, the ability to persistently motivate, and the anticipation that people will drop out over time. Do you need back-up teams? For which processes? Who decides?
  • Systematic data collection: creating a template that all team members will follow is hard, at least the first time around. But without that template, documentation ain’t possible, and without documentation, serious research ain’t possible.
  • Documentation: Everything will need to be documented, if you eventually want to make this work at scale. Who is working on which road, in which city, and for how long? How was the data captured? Do you have records of the journey on Google Maps? Are the photos correctly tagged? Are they of acceptable quality? What happens if a particular team visits not on the specified day, but three days later?
  • Sampling: Why this city? Why this road? Is a small notice attached to a lamp-pole a hoarding or not? If yes, then do we take photos of every last little hoarding? If no, then were do we set the cut-off limit? On what basis? Do different cities have different definitions for hoardings? Do these definitions change over time?
  • Dashboarding: How should the end-user (in this case, ideally the public) view this data? How do we make it informative, yet easy and entertaining at the same time?
  • Google Map Overlays: How should we go about building one? Can it scale? Do we have to pay? Whom do we ask?

And that’s just me pecking away at a keyboard, entirely off the cuff. When we begin the work, there’ll be a thousand more questions a day.

But, on the bright side, you will get to learn about:

Hoarding regulations | Pricing | Sampling | Data collection |Team Building | Basic Statistics | Seasonality | Data Storage | Data Pulls | Geotagging | Map Overlays | Dashboarding | Marketing | (eventually) Funding

‘Tis but a thought, but I can’t help that it will be a better way to learn than just look at a computer screen, which is what the last year or so has been all about.

I want to try and gets started on this at my workplace, if possible. I’ll keep you posted about what (if anything) comes of this.

A Conversation With Rationality

I’d gone to the RTO the other day for some work, and I suppose you know what comes next.

I wouldn’t say it is impossible to get work done without the help of an agent, but it is certainly true that it isn’t a breeze either. And if one teaches opportunity costs, it makes sense to take the “help” of an agent. Sure you can do it yourself, but it then becomes eye-wateringly expensive in terms of time. And therefore, money.

And while I waited in the numerous byzantine lines to get my work done, I reflected, like every good economist should, on what could be done to reform the system.

Just ban agents, my understandably irrational brain screamed as a first pass solution. Why doesn’t the bureaucracy come up with a better process map that just gets out of the way instead, Cold Calculating Rationality suggested.

Because they aren’t incentivized to, C.C.R went on to reason, proceeding to shut me out of the conversation altogether. Although I was, truth be told, a very interested bystander by now.

But why aren’t they incentivized to – isn’t that the next logical question to ask, mused C.C.R.

I mean, won’t it make their job easier if they make their processes easier?

Well, yes, but they earn the same either way, no? It’s not like payments are linked to productivity increases.

How would they earn more?

Maybe through a Coasean solution in which there’s connivance with the agents, and they get a cut? That is, make the process impossibly cumbersome, and continue to keep it cumbersome, no matter what any well meaning committee proposes. That then facilitates agents stepping in and “helping” blissfully ignorant citizens get their work done faster – for a fee, of course.

They take a cut of the fee – and hey, there you have it! Bureacracts have an incentive – but not to simplify the system! They have an incentive to continue to clog up the system.

C.C.R needed a break at this point in time, so it and I played a couple of rounds of Fruit Ninja on my phone.

But why, C.C.R asked – for it can take only so many minutes of mindless swiping – would anybody want to be an agent? I mean, there are surely better, more remunerative ways to earn a living.

C.C.R. and I stared at each other in part jubilation, and part horror.

“There aren’t better ways, no?!”, we said in unison.

“I mean, if markets are weakly efficient, nobody would willingly work as an agent, surely”, said C.C.R triumphantly.

“And so”, C.C.R went on to say in that insufferably smug way that is its wont, “if you really want to reform the system, you need to create better employment opportunities everywhere else. Reforming this particular system is just putting a band-aid on a cancer. Because yes middle-mean are bad, but nobody grows up dreaming of being a middleman. Of course the middlemen, and that entire nightmare of a system is going to be up in arms if you seek to eliminate it. The lack of alternative, viable careers: that’s the real problem.”

“So, just more pro-growth policies, you’re saying?”, poor old irrational me asked timidly.

“Well, yes. Easy answer, tough implementation, I’ll concede that point”, replied C.C.R.

“I wonder where else we can apply this line of thinking”, I was about to ask C.C.R… but then it was my turn at the window, and I was so happy that I was finally done with the whole thing that I stopped thinking about it altogether.

So it goes.

All of the best about *that* match

Siddharth Monga on Cricinfo

Slightly delirious, if you ask me, but given the circumstances, who can blame Sharda Ugra?

Vivek Kaul pours cold water on this being the rebirth of Test cricket, as only a finance/econ writer can – but a genuinely fun read nonetheless.

Sambit Bal, to end on as perfect a note as we started.

The title of the post is edited (it originally read as “five of the best”) – but here’s more to add in:

Sidvee, being Sidvee. Self-recommending, as they say. (There’s a post about reflections on this essay next week, plijj keep an eye out for it)

Girish, along similar lines.

Greg Baum, gracious as ever.

And a request: send more along! Happy to read as many as you can send, and add all of them in here. Whatay repository this has the potential to be!

Sidvee was kind enough to send along this Twitter thread by @_ImPK. It is ridiculously, impossibly good. Please see the whole thread, for it contains much more – I have only listed here articles from that list that are about the Brisbane test. Thank you, Sidvee and @_ImPK!

Bharat Sundaresan, who points out that this time, it was the Aussies looking at the Indian team in awe. I watched the ’99 series, so I cannot tell you how much this means to me.

There was a point, while watching this match, when – and this is true – I was on a Signal call with a friend who is in Atlanta. He shared his screen with me on the call, because Sony Liv (eff you, Sony Liv, eff you) was on the blink here. Among other things in this post by krtgrphr, this resonated so much.

Geoff Lemon, over in The Guardian.

When Ian Chappell says he’s never seen the likes before, that’s saying something.

Heroes assembled, indeed. Vinayakk Mohanarangan over at Scroll.

Niyantha Shekhar Dunkirks her way through the match. And it is every bit as spellbinding as the movie. For a cricket fan, it’s even better.

For these times, this series. Barney Ronay in The Guardian.

Pant had nine successive scores of 25 or more in Australia heading into the Brisbane test, Rohit Sankar informs us. He does much more than that, of course.

Jarrod Kimber points out that the person who’s been on our screen the most during the series is probably the physio, and it’s not even hypoerbole. (I’m joking, Mr. Pujara, I’m joking.)

Only Prem Panicker can combine Simon Barnes, western novels, and a reference to Horatius in a piece on a cricket match. The Getafix of cricket writers. He’s got one more piece out, but it is behind a paywall, and I cannot read it. But it is Prem Panicker, so sight unseen.

Again, I’m a glutton for more, so if you find more pieces, please, send them along. Thank you.

End of the week reading list: 6th Nov, 2020

The NYT comes up with a lovely selection of Agatha Cristhie novels. Light Diwali vacation reading if you are new to her works, perhaps?
(Also, every time I am reminded of this book below, I feel this urge to apologize to that one friend I inadvertently revealed the ending to – so once again, I’m really sorry!)

That would be “The Murder of Roger Ackroyd,” the story of a wealthy man slain in his study less than a day after the woman he hoped to marry commits suicide. Although — as Hercule Poirot discovers — the dead man’s assorted friends, relatives and servants have reasons to wish him ill, “The Murder of Roger Ackroyd” will still leave you reeling. When you find out who the murderer is and begin leafing through the pages, looking for missed clues, you’ll realize just how completely Christie snookered you.

On the race to redesign sugar:

As public opinion turns against sugar, food companies have outdone one another in pledges to cut the quantities of it that appear in their products. Pepsi has promised that by 2025 at least two-thirds of its drinks will contain a hundred calories or fewer from added sweeteners. A consortium of candy companies, including Mars Wrigley, Ferrero, and Russell Stover, recently declared that by 2022 half of their single-serving products will contain at most two hundred calories per pack. Nestlé has resolved to use five per cent less added sugar by the end of this year—though, as of January, it still had more than twenty thousand tons of the stuff left to eliminate.

A short (and delightful) history of mashed potatoes:

During the Seven Years War of the mid-1700s, a French army pharmacist named Antoine-Augustin Parmentier was captured by Prussian soldiers. As a prisoner of war, he was forced to live on rations of potatoes. In mid-18th century France, this would practically qualify as cruel and unusual punishment: potatoes were thought of as feed for livestock, and they were believed to cause leprosy in humans. The fear was so widespread that the French passed a law against them in 1748.

The excerpt below was an excerpt in the post I am linking to (if you see what I mean), but well worth your time, the entire blog post:

70% of us think that the average household income of the top 1% is more than ₹2.5L. In fact, a majority of us guess it is more than ₹5L. Similarly, a majority of the respondents assume that the average income of the top 10% of households is more than a ₹1L… We think of the top 1% as super-rich people. A majority of the respondents estimate that all of the top 1% have 4-wheelers. And 70+% feel that at least 90% of the top 1%-ers have 4-wheelers.

Robin Hanson wonders about taking rest:

While we seem to “need” breaks from work, many of our break activities often look a lot like “work”, in being productive and taking energy, concentration, and self-control. So what exactly is “restful” about such “rest”?

India, Bangladesh, GDP. Sigh.

When I explain GDP to folks unfamiliar with the concept, I often use the analogy of marks.

“Do you”, I intone in the most professorial voice I can muster, “remember how many marks you scored in your math exam when you were in the 4th grade?”

The point behind asking that question is to help the class realize that there were many other things going on in their life in the 4th grade. The measurement of how well you did on the specific questions you were asked in that test on that day do very little to show you how much math you actually learnt that year. Leave alone, of course, the question of how little the math test had to do with all of what you learnt while you were in the 4th grade.

A similar point was made about GDP recently, in the Business Standard:

Take GDP first. In India, we don’t measure the output of 65 per cent of the economy and make only well-informed guesses about the remaining 35 per cent.

That’s exactly right, of course. You shouldn’t obsess over GDP numbers, much like you shouldn’t obsess over grades. But we do obsess over both!

And the analogy between marks and GDP works really well especially now, because when it comes to GDP, we now have a Sharmaji ka beta in the neighbourhood.

Hello, Bangladesh.

About two years ago, India’s Home Minister Amit Shah spoke of “infiltrators” who were hollowing out the country “like termites”. A Minister from Bangladesh retorted that Shah’s statement was “inappropriate”, “unwanted”, and “not based on information”. The IMF’s recent per capita GDP projections for South Asian countries show that the alleged ‘termite factory’ is shining — Bangladesh, which has been doing better than both India and Pakistan on social and human development indicators for several years now, is also beginning to march ahead on the economic front.

In much the same way that you shouldn’t compare marks obtained by students, you really shouldn’t compare GDP per capita between nations.

But (and you knew there was a but coming along, didn’t you), as I also say in my classes – what else you got, eh? It’s all well and good to say we shouldn’t, but it’s not like we have readymade alternatives. And if you take the GDP factory away from us economists, how do we fill our days?

TCA Srinavasa-Raghavan, in the same column cited above, has three answers:

Only three things: Food inflation, because it has a direct bearing on welfare; foreign exchange reserves, because they serve as a powerful signalling device to foreign investors and sellers of goods; and the revenue deficit. These are the only things the Centre has total control over. In determining all other indicators, the states play a big role.

Read the whole article (which, I’m sorry, may well be behind a paywall). I don’t necessarily agree with all of it, about which more below, but the point that GDP is overrated as a useful barometer for the state of the economy is a point I agree with wholeheartedly.

TCA’s suggestions about what is to be used instead (food inflation, the revenue deficit and forex reserves) are worth considering, but there is a long list of alternatives that have been suggested. Here is just one example:

Provincial officials have long been suspected of overstating growth. Adding their figures together suggests that China’s economy was $364 billion bigger in 2009 than the total in the national accounts. Mr Li preferred to track Liaoning’s economy by looking at other indicators: the cargo volume on the province’s railways, electricity consumption and loans disbursed by banks.

Other folks may come up with other things to use as a proxy for measuring the state of the economy, but really, it is the old story of the six blind men and the elephant all over again. Whatever you use will give you only a limited picture. That’s just the nature of the beast.

Worse! Whatever you agree to measure instead of GDP immediately becomes susceptible to Goodhart’s Law:

In a paper published in 1997, Anthropologist Marilyn Strathern generalized Goodhart’s law beyond statistics and control to evaluation more broadly. The phrase commonly referred to as Goodhart’s law comes from Strathern’s paper, not from any of Goodhart’s writings:

When a measure becomes a target, it ceases to be a good measure.

(Emphasis added)

So sure, you could ask that food inflation, revenue deficits and forex reserves be the target. But it’ll just be cobras or rat tails all over again.

So GDP, whether you like it or not, whether its measurement is favorable or not, is not going to go away anytime soon, whether in India or elsewhere.

Consider the concluding paragraph from a column in the Livemint yesterday by R Jagannathan:

This does not make GDP calculations worthless, but the real focus should be on sectors. More than macroeconomics, sectoral understanding and microeconomics ought to be central to policy-making. Future GDP will best be estimated as a sum of its parts, and not as a whole extrapolated from numbers in the more visible parts of the economy.

Yes, well, sure. Absolutely.

Now if only we could figure out the how.

Inflation: Oh ’tis problematic. Or is it?

A student messaged last week, asking some questions about inflation and its measurement in India. In particular, they wanted to know about food and its impact on inflation right now.

Well, outsourcing is always and everywhere a good idea, and Vivek Kaul had already answered the question at great length:

What this means is that, despite the end consumers of food paying a higher price, the farmers are largely not benefitting from this rise in food prices, given that they sell their produce at the wholesale level.
This difference can be because of a few reasons.

a) A collapse in supply chains has led to what is being sold at the wholesale level not reaching the consumers at the retail level, thus, leading to higher prices for the consumer.

b) This could also mean those running the supply chains hoarding stuff, in order to increase their profit.

Having said that, the former reason makes more sense given that stuff like vegetables, egg, fish and meat, etc., cannot really be hoarded. Also, hoarding stuff like pulses, needs a specialized storage environment which India largely lacks.

The entire article is worth reading (and so is subscribing to Vivek’s blog, so please do so!). And if you think 2020 isn’t depressing enough already, do read this article, also written by him. A short excerpt follows:

To conclude, the Indian economy will contract during the second half of the financial year. There is a slim chance of growth being flat for the period January to March 2021. Inflation, even though it might come down a little, is likely to remain high due to the spread of the covid pandemic. Hence, India will see conflation through 2020-21.

From a reading-the-tea-leaves perspective, it would seem the RBI actually isn’t that worried about inflation right now (and rightly so!). Here’s an excerpt from an excellent newsletter, Anticipating the Unanticipated that makes this point:

But the RBI wants to signal it is willing to live with inflation running above ‘comfortable’ level in the coming days. The MPC report last week claimed almost 80 per cent of the increase in inflation beyond the 4 per cent target can be attributed to supply chain disruptions and increase in fuel prices. This it believes is a short-term phenomenon and inflation will be in the 5 per cent range next year. This is underlined to give comfort to bond investors to buy government securities without the fear of a near-term interest rate hike to contain inflation. Further, the other step announced by RBI in extending the HTM (hold-to-maturity) limits by another year to March 2022 is to protect any bondholder from the volatility of prices and booking losses on account of it. The overall RBI signal is it doesn’t want the worry of rising inflation and a consequent rate increase to come in the way of growth. It’s focus now is on improving the transmission of rate cuts to the borrowers to stimulate growth.

… and here is Anantha Nageswaran making the same point, but by utilizing a different analysis:

This exercise generates the hypothesis that there is little or no intersection of the household inflation expectations formation and the monetary policy regime. Two, high inflation expectations peaked in September 2014. Similarly, the current high inflation expectations should peak as supply disruptions ease. So, in my view, RBI is betting correctly that the rate of inflation would ease and project policy on hold for the next few quarters. Three, inflation generation process should matter only to the extent that it affects medium-term output and employment generation. For now, other indicators suggest that it is not as disruptive as it was in 2011-13. Therefore, there is no need to turn it into a fetish. The new MPC and the central bank have done well and done good. They should be pleased.

And for the data nerds among you, here is the Inflation Expectations Survey of Households by the RBI (do keep in mind the point Ananta Nageswaran makes about trimmed means in his article). Note that currently at least, not too many people seem to be too worried about persistently high food inflation.

Side note: Jason Furman’s podcast with Tyler Cowen contained this interesting snippet:

FURMAN: GDP could be more meaningful if we measured it better. The inflation rate gets harder and harder to measure over time. So I think the one that probably has deteriorated in meaningfulness is the measure of inflation. Number one, we don’t measure it well, and number two, it’s low enough that it’s hard to get that excited about it.

COWEN: Is that a quality-of-goods problem? Or how we do chaining over time? Where are we going wrong in measuring inflation?

FURMAN: Just more and more of the economy is in areas that are harder to measure the quality of, healthcare being the most notorious.

I’ve said it before, and I’ll say it again: macro is hard.

Finally, here are past EFE articles on inflation.