Understanding Fiscal Policy (1/3)

I wrote this last week on the basis of this write-up by Sajjid Chinoy. The sequel came out last week, so let’s read through it together.

First things first:

  1. During times of a crisis, such as the one we are going through, it may be helpful to think of the economy as a sick person. That would make us economists and policymakers the diagnosticians and doctors respectively.
  2. Us diagnosticians often like to think about why the person got sick. Was it because of some previously administered medicine? Was it because of some external factor? Maybe both? That is, we identify the disease, and the cause of the disease.
    In this case, the economy is struggling because of the lockdowns and the uncertainty about (at least) the near future. Those are the symptoms. The cause is, of course, the virus.
  3. The doctors – that is, the policymakers – will want to remove the cause behind the economy’s illness first. That is what Sajjid Chinoy means when he says: “With a health crisis at the genesis of the current situation, it’s tautological to say that ramping up vaccinations is the “first-best” solution to tackling the crisis.” That is the cause of the crisis, and removing the thing that causes the crisis is of paramount importance.
    The “how to do this best” question has troubled all of us, and continues to trouble us, and it is worth your time to keep tracking this issue. And it is a great way to learn about how to think about public policy.
  4. But treating the symptoms (and the manifestations) of the cause is equally important. Job losses, reduced investment, reverse migration, subdued demand, rising inequality, reduced incomes, the exacerbated lack of social safety nets are all symptoms and manifestations of the crisis. How to treat the symptoms? That is where Sajjid Chinoy’s second article comes into play.

There are two courses of treatments available to us diagnosticians and doctors: fiscal policy and monetary policy. Sajjid Chinoy argues (and in my opinion, does so convincingly) that monetary policy has done all the heavy lifting it could in 2020, and there’s not much left in the RBI’s arsenal.

Monetary policy was the prime mover last year and markets will inevitably clamour for that pedal to be pressed even harder. But quite apart from the fact that monetary conditions are already very accommodative and core inflation has averaged 5 per cent since the start of 2020, what’s less appreciated is the reduced efficacy of monetary policy in periods of elevated uncertainty. That’s because monetary policy ultimately relies on economic agents (households, businesses, banks) to act on the impulses it imparts. But when agents are faced with acute health, income and macroeconomic uncertainty, they often freeze into inaction (“the paradox of thrift”). So households don’t borrow, businesses don’t invest and banks don’t lend. This is evident in the evolution of bank credit over the last year in India. Despite negative real policy rates and falling real bank lending rates, credit growth has continued to slow all year long, likely reflecting these uncertainties.


Homework: What is core inflation? Where is this data to be gotten from? Where do we get data on the evolution of bank credit from? What are negative real policy rates? What are falling real bank lending rates? Where do we get that data from? What is credit growth? Where do we get that data from?1

Which means we must now think about how to best deploy fiscal policy.

The baton must, therefore, pass to fiscal policy. While fiscal policy cannot mitigate the health uncertainties it can help alleviate income and macroeconomic uncertainties. Stronger spending will not only boost activity but, in so doing, will reduce demand uncertainties for firms. Furthermore, income support (in cash or kind) along with public-investment-indu­ced-job-creation can alleviate income uncertainties for households and thereby help catalyse the private sector.


Sajjid Chinoy highlights two broad areas to think about in his article:

  1. Recalibrating To New Realities
  2. Making Space While The Sun Shines

There is much to agree with (and add to) in each of these cases, and I’ll do so in the next two blogposts.

But the bottomline across both articles, for students of macroeconomics, is this:

  1. Think of the economy as a human body. Like the human body, the economy is impossibly complex, and all of its underlying connections, mechanisms and responses aren’t entirely clear.
  2. Like a good diagnostician, it is important to keep tabs on a variety of different metrics on an ongoing basis. That’s what Sajjid Chinoy’s first article should mean to you – and therefore this blogpost is homework you really should do.
  3. Once you have enough data about the patient, a good doctor should be able to recommend potential cures. As with the human body, so with the economy: different doctors will recommend different treatments, and for many (mostly good) reasons. This is the part that gets really tricky.
  4. Sajjid Chinoy’s recommended course of treatment is his second article. As a student, you must try and understand why he recommends this course of treatment and no other, and ask yourself to what extent you agree with him. If you disagree with him (which is fine!), you should be able to tell yourself why – from a theoretical viewpoint.
  5. For example, you may disagree with him and say that India can still effectively deploy monetary policy. Maybe so, but you must have theoretically valid reasons for saying so.
  6. In fact, as a student, my advice to you would be to read an article willing yourself to disagree with the author. “How might this person be wrong?” is a great way to learn while reading. It is also a great way to keep yourself awake in class, trust me.
  1. Not all of the links will give you the exact answers, and that is deliberate. The last two questions being “unlinked” is also deliberate. If you are a student looking to work or study further in areas relating to macroeconomics, start building out a file with your answers to these questions (and many more!), and update the data on a regular basis.[]

Probability, Expected Value…

… in No Country For Old Men

The Ecstacy and the Agony

I watch three sports somewhat regularly, and I’ll answer the question for each of them:
  1. Cricket: Chennai 1999. I agree with Kartik, in other words.
  2. Football: The last minute or so of the 2012 EPL season.
  3. Tennis: The men’s final at Wimbledon, 2019. I still don’t understand how he lost.

The broader question, of course, is whether the increase in the supply of cricket matches has reduced their value, at least for me. And I think the answer is yes. This also helps us understand why the ESL would have been a really bad idea. I need to explore this idea more thoroughly in 2021.

And thank god for Roger Federer!

On How To Be A Good Mentor

A student wrote in asking me this question: how should one approach mentorship, while remaining friends, or while being a senior, or both.

Well, a certain television series has one answer to this question, and I could take the easy way out, but here goes:

  1. For a mentorship to work, even a little bit, the mentee has to value the time of the mentor. This bit is non-negotiable. As a mentor, you have the right to ask that this be done, and you have the right to walk away if it is not done. This should be crystal clear throughout.
  2. But then again, on the other side, as the mentor you have to be ultra-professional yourself. That means showing up on time without fail, being prepared yourself, and dedicating the time that you promised. I am less than perfect in this regard, I am sorry to say.
  3. A good mentor nudges, but doesn’t become overbearing. Learning the art of pushing ever-so-gently is very, very difficult, and most mentors never learn it. Some mentors (and I think I am one of them) err on the side of pushing too little, which is also a problem. I find it easy to remain friends with my mentee, I find it difficult to push them to do better.
  4. Think of it as a spectrum (or if you want to geek out, like a two tailed test). The intensity that you bring to the table as a mentor can err on the side of being too little, as in my case, or too much. Both aren’t good, you want your intensity to be Goldilocks level. This intensity level differs on the basis of each separate mentee. Some need no nudges whatsoever, some require Evergiven levels of pushing. Most lie somewhere in between.
  5. But before starting on your job as a mentor, you should ask yourself which role you’d rather give up if it came right down to it: continue to be friends and stop mentoring, or continue mentoring and stop being friends.
  6. Whatever your choice, be consistent, and don’t hesitate to pull the trigger. In my case, I usually choose to continue being friends, and if I think a mentorship isn’t turning out well, I stop the mentoring gig, and as quickly as possible.
  7. Always try to mentor someone, and always try to get someone to be your mentor. Apply what you learn while being on one side of the fence to the other.
  8. It is easier to find a new mentor, it is difficult to find a new (good) friend. That’s my opinion, so I would rather continue to be a good friend, and sacrifice my role as a mentor if I had to choose.
  9. But that being said, as far as possible, avoid being a mentor to a really good friend.
  10. Never, ever make the mistake of commercializing the mentor-mentee relationship. Some things in life are sacred.*

*But cups of coffee being purchased by the mentee are fine. I’m just sayin’

What Else Is There But Stories?

I have spent the day immersed in Leave it To Psmith, and what a magnificent day it was. And I have now purchased Summer Lightning, and I refuse to feel the least bit guilty about it, so there.

On a related note, I also happened to read a (mostly) lovely essay by Salman Rushdie titled “Ask Yourself Which Books You Truly Love“:

All human life is here, brave and cowardly, honorable and dishonorable, straight-talking and conniving, and the stories ask the greatest and most enduring question of literature: How do ordinary people respond to the arrival in their lives of the extraordinary? And they answer: Sometimes we don’t do so well, but at other times we find resources within ourselves we did not know we possessed, and so we rise to the challenge, we overcome the monster, Beowulf kills Grendel and Grendel’s more fearsome mother as well, Red Riding Hood kills the wolf, or Beauty finds the love within the beast and then he is beastly no more. And that is ordinary magic, human magic, the true wonder of the wonder tale.


And (or should the word be but?) because us economists are always supposed to look at all ides of the issue, here’s the other side of the spectrum:

As a simple rule of thumb, just imagine every time you’re telling a good vs. evil story, you’re basically lowering your I.Q. by ten points or more.


Here’s the full talk.

(And finally, do remember that The Truth Always Lies Somewhere In The Middle)

Books about Macro

Praneet asked me this on the basis of yesterday’s post:

And so here we go:
  1. I and my batchmates spent hours reading Snowdown and Vane. Like any good book on macroeconomics, we were more confused for having read it, and I mean that as a compliment. (As an aside, I loved the bit in Amit Varma’s conversation with Karthik Muralidharan where they spoke about N Gregory Mankiw’s quip about being confused about economics. Don’t ask me what it was about, this is me trying to incentivize you to listen to the conversation!)
    But this really is an excellent book to read. It is mostly accessible, contains very very good explanatory diagram, and best of all, each chapter concludes with an interview with an economist who was most representative of that particular field of thought. If I remember correctly, the last question always used to be about whether Keynes would have won the Nobel prize had he been alive then. Fun book, and it would still be my top pick. (The listed prize on Amazon is barking mad, please note)
  2. I think I came across this paper via Marginal Revolution, but am not sure. It’s a pretty good paper to read as a macro student today, because it gives you a very good idea about what folks in the field have been up to in the last four decades or so. I personally think DSGE models are a little bit overrated, but you can’t ignore it if you want to build a career in academia as a macroeconomist. Most of all, though, as a student, you really want to understand the difference between description, pure theory, falsification, and model fitting papers. But on all accounts, if you want to read just one survey paper, this would be a good pick.
  3. Speaking of Marginal Revolution, this blogpost is a wonderful read, in the sense that it is full of wonderful reading references. By the way, I’ve been promising myself for well over a decade now that I will read more about Henry Thornton, but have never gotten around to actually doing so. As Professor Cowen says, please do read the second comment (the one by Kurt Schuler).
  4. Brad DeLong lists out books you should read on the Classical Economists over on FiveBooks.com, and that should serve you well. I have not read all of them, I should say. One book that I would add to the list (because the concept was so interesting) is Linda Yueh’s “The Great Economists: How Their Ideas Can Help Us Today”.
    Well, ok, another book: PJ O’Rourke On The Wealth of Nations. Easily the most fun book of the lot.
  5. Raffaele Rossi picks the five best macro textbooks here, and alas, DBF doesn’t make the cut. It was my first macro text, and I still remember working through IS-LM for the first time. I’m still working through it, because I still don’t understand it, but that is another story. Arnold Kling put up his own list, and I would personally prefer his list, especially Leamer’s book. And psst, Kling’s own book is very, very underrated.
  6. Now, India secific macro books: Joshi and Little’s book about post-91 reforms deserves mention, as does Macroeconomics of post-reform India. Joshi’s Long Road is also worth reading, as is The Turn of the Tortoise, by TN Ninan. TCA Srinvasa Raghavan had recommended an excellent collection of essays called Towards Development Economics, if you want to understand what India’s earliest modern (poor phrasing, I know) economists were up to. The festschrifts honoring Montek Singh Ahluwalia, and Manmohan Singh are also very good, as was Bibek Debroy’s book about getting India back on track. Bhagwati and Panagariya’s Tryst with Destiny also!
  7. Finally, a book I am really looking forward to reading is Alex Thomas’ book on macro. I’m a GIPE student, so heterodox is a good wonderful thing. But that is a whole different blogpost in its own right!
  8. Lists like these can never be comprehensive, and I’m sure there will be people reading this who will be chomping at the bit to add to this list. Please, have at it, and share. That’s the point of the internet, no?

A Summer Spent Doing Macroeconomics

Say you’re a student, and you’ve just finished learning a fair bit about macroeconomics. You’ve read and not understood Keynes, you’ve read and think you’ve understood Friedman, and you don’t have the faintest idea what folks in macro have been up to since Robert Lucas.

OK, all that is fine, but how should a budding macroeconomist spend her summer this year?

You could do a lot worse than reading this article, and asking yourself some simple questions.

Such as, do I hear you say? Read on!

Google mobility, for instance, is down more than 40 per cent since the start of April and currently at levels seen a year ago, when the national lockdown was in effect. This dynamic is also visible in the cross-section: states that forced down mobility more strongly have, in general, also seen a larger drop in positivity rates.


What is Google Mobility? What does the data for India look like? How does this data correlate with statewise Covid-19 numbers? Can I create simple tables and charts in, say, Google Sheets that show a link between the two? And write up a blog about how I did it? Or maybe create YouTube tutorials that show how I did it?

That said, there’s growing evidence the impact will not be trivial even if not of the same scale as the first wave. By the middle of May, power demand was down 13 per cent and vehicle registrations were down 70 per cent compared to the start of the quarter, while e-way bills in the first half of the month were at 40 per cent of where they should be. A broader composite index would suggest activity is tracking a 6-7 per cent sequential decline this quarter and, while this is much shallower than the 25 per cent sequential contraction witnessed last year this time, the fact that it comes on the heels of the first shock, and can potentially trigger more hysteresis, remains a source of concern.


Where does the data for power demand come from? Where does the data for vehicle registration come from? Where does GST data come from? What does the phrase “tracking a 6-7 percent sequential decline” mean? What is hysteresis?

Household income uncertainty and precautionary savings can be expected to rise. Even before the second wave, households had signalled caution about future spending (manifested in the RBI Consumer Confidence Survey) likely reflecting both an income hit and a precautionary savings motive. This behaviour is consistent with labour market dynamics wherein the unemployment rate, once adjusted for reduced labour force participation, had increased meaningfully even before the second wave.


What is the RBI Consumer Confidence Survey? How is it calculated (see Annexure A in this document)? Where do we get unemployment data from?

Private investment could also take time to pick up. Even before the second wave, utilisation rates were in the mid-60 per cent range, much lower than needed to jumpstart investment.


What is OBICUS? It stands for Order Book, Inventory and Capacity Utilization Survey. How else do we track capacity utilization?

We have previously found a strong elasticity of India’s exports to global growth and, if that holds, this should drive a strong export rebound in India. Some of this is already visible in the data with manufacturing exports surging in recent months, and currently 18 per cent (in nominal dollar terms) above pre-pandemic levels.


Where might that paper/research be, the one that talks about the strong elasticity of India’s exports to global growth? What does it tell us? What is different between the time that paper was written and today? Is that to India’s advantage or not? How do we tell?

If crude prices average close to $70 this fiscal year, as is expected, that would constitute a 50 per cent increase over last year and serve as a negative terms of trade shock that impinges on household purchasing power and firm margins — a process already underway.


EIA? Or something else? Should we take lagged data? If yes, with what lag? If no, why not? Where do we get information on firm margins? Bloomberg/Reuters? If yes, do we have access to a terminal? If no, whom do we ask for a favor?

When all is said and done, the completeness of an economy’s recovery from Covid-19 — and therefore the level of scarring — is assessed by comparing its post-Covid-19 path of the level of GDP with the path forecasted pre-Covid-19. If the aforementioned forecasts fructify, the level of quarterly GDP at the end of this year would be about almost 8 per cent below the level forecasted pre-pandemic. To be sure, India will not be the only emerging market to be below its pre-pandemic path. In fact, among the large economies, only the US and China will surpass it. But that said, an 8 per cent shortfall is meaningful.


What is the level of GDP, and how is it different from the growth rate of GDP? Which should one use, and how does the answer change depending on the context? Where do we get data on GDP of all countries at one time? Which one of these measures should we use for comparison, and why?

Macro is hard, and in many different ways. Understanding the theory is hard, but piecing together parts of the puzzle from disparate (and at lest in India, gloriously unfriendly) data sources is perhaps harder still. But if you want to “do” macro for a living, being familiar with the answers to these questions is table stakes.

That is, getting familiar with the answers to the questions I have asked here gets you the right to sit at the table. Playing the game better than the others once you’re in is a whole different story. And playing the game means using this data with your knowledge of theory to try and take a stab at the really important questions:

The question, therefore, is how should economic policy respond to this second shock? With fiscal and monetary policy already quite expansive, is there space to respond further? We assess policy options and tradeoffs in a companion piece tomorrow.


Trust me, macro is hard.

Proposed Examination Reforms

I’m not holding my breath, but this article has raised my hopes just a little bit:

Colleges and universities may soon adopt continuous comprehensive evaluation, a method that shifts focus from only annual or semester-level summative assessment system.
The suggestion has come from higher education regulator University Grants Commission (UGC) amid the increasing dependence on technology for education delivery in the current pandemic environment. Assessment at several intervals during and after achievement of learning outcomes specified for every module is needed as blended learning is gaining ground, UGC said in a draft proposal shared with higher educational institutions.


I’ve said it before, and I’ll say it again: everybody associated with academia in India knows how broken, pointless and screwed-up examinations are, but nobody wants to do anything about it. And the most often quoted reason is R Madhavan in 3 Idiots going “Abba nahi manenge”.

Abba being the UGC.

But now, hallelujah, the UGC is talking about open book examinations and on-demand examinations. This was a “tears in my eyes moment“:

Open book exams is the “right way to move away from the conventional approach of exam where remembering and reproducing is prime”, UGC said. “In real functioning beyond formal education, life is all about open book examination. Hence, in higher education, we must prepare students for work life by making them acquainted with open book examinations. It will also facilitate better understanding and application of knowledge,” UGC said, citing an internal committee report.


There is still a world of pain that awaits those of us who are in academia. The inertia associated with the old system will take years1 to overcome, and it will be a long, unpleasant journey.

More, we will run up against capacity constraints, because shifting away from the “State in brief” questions to having students think critically will require the changing of multiple mindsets, along with intensive training of faculty in all universities.

And even if some universities were to adopt this whole-heartedly, one unintended consequence will be the exacerbation of already ridiculously high inequality. The inequality I speak of is in terms of access to quality higher education, of course. Better colleges and universities will get better still, and while that is desirable for the students who are lucky enough to get into them, it doesn’t bode well for equitable educational outcomes across the country.

But even so, the very fact that this is even being discussed in the first place is a welcome move.

The one thing that gives me hope is something that is discussed almost as an after-thought in the article: e-portfolios.

An electronic porfolio (e-portfolio) is a purposeful collection of sample student work, demonstrations, and artifacts that showcase student’s learning progression, achievement, and evidence of what students can do. The collection can include essays and papers (text-based), blog, multimedia (recordings of demonstrations, interviews, presentations, etc.), graphic.


This blog, for example, is my “e-portfolio”. I pay around ten to twelve thousand rupees every year to maintain this blog, but one can of course start a blog for free. Or a YouTube channel, or an Instagram page or absolutely anything else you like.

In an ideal world, e-portfolios (and could we come up with e better name for it, please?) are solely the responsibility of the student. They can be in any language. They can be nurtured over time, for years together. Cultivating your e-portfolio needn’t cost money, in other words, and popularizing your e-portfolio is a life-skill worth developing in its own right.

Most importantly, developing one requires just a smartphone. Yes, this is still a challenge for large parts of our country, but I would argue that a learning system that revolves around the development of an e-portfolio is more efficient, cheaper and easier than even a perfectly reformed examination system.

Bottomline: marks, examinations and degrees are overrated. Doing the work, and sharing your work in the public domain is underrated.

Here’s a blogpost from last year about conducting examinations during these crazy times, and here are all the posts I have written about higher education on EFE.

  1. And if I am to be cynical, which is almost always the case, I’ll say decades[]

Supermarkets Explained

No Such Thing As Too Much Stats in One Week

I wrote this earlier this week:

Us teaching type folks love to say that correlation isn’t causation. As with most things in life, the trouble starts when you try to decipher what this means, exactly. Wikipedia has an entire article devoted to the phrase, and it has occupied space in some of the most brilliant minds that have ever been around.
Simply put, here’s a way to think about it: not everything that is correlated is necessarily going to imply causation.

But if there is causation involved, there will definitely be correlation. In academic speak, if x and y are correlated, we cannot necessarily say that x causes y. But if x does indeed cause y, x and y will definitely be correlated.


And just today morning, I chanced upon this:

And so let’s try and take a walk down this rabbit hole!

Here are three statements:

  1. If there is correlation, there must be causation.

    I think we can all agree that this is not true.
  2. If there is causation, there must be correlation.

    That is what the highlighted excerpt is saying in the tweet above. I said much the same thing in my own blogpost the other day. The bad news (for me) is that I was wrong – and I’ll expand upon why I was wrong below.
  3. If there is no correlation, there can be no causation

    That is what Rachael Meager is saying the book is saying. I spent a fair bit of time trying to understand if this is the same as 2. above. I’ve never studied logic formally (or informally, for that matter), but I suppose I am asking the following:
    If B exists, A must exist. (B is causation, A is correlation – this is just 2. above)
    If we can show that A doesn’t exist, are we guaranteed the non-existence of B?
    And having thought about it, I think it to be true. 3. is the same as 2.1

Rachael Meager then provides this example as support for her argument:

This is not me trying to get all “gotcha” – and I need to say this because this is the internet, after all – but could somebody please tell me where I’m wrong when I reason through the following:

Ceteris paribus, there is a causal link between pressing on the gas and the speed of the car. (Ceteris paribus is just fancy pants speak – it means holding all other things constant.)

But when you bring in the going up a hill argument, ceteris isn’t paribus anymore, no? The correlation is very much still there. But it is between pressing on the gas and the speed of the car up the slope.

Forget the phsyics and accelaration and slope and velocity and all that. Think of it this way: the steeper the incline, the more you’ll have to press the accelerator to keep the speed constant. The causal link is between the degree to which you press on the gas and the steepness of the slope. That is causally linked, and therefore there is (must be!) correlation.2

Put another way:

If y is caused by x, then y and x must be correlated. But this is only true keeping all other things constant. And going from flat territory into hilly terrain is not keeping all other things constant.


But even if my argument above turns out to be correct, I still was wrong when I said that causation implies correlation. I should have been more careful about distinguishing between association and correlation.

Ben Golub made the same argument (I think) that I did:

… and Enrique Otero pointed out the error in his tweet, and therefore the error in my own statement:

Phew, ok. So: what have we learnt, and what do we know?

Here is where I stand right now:

  1. Correlation doesn’t imply causation
  2. I still think that if there is causation, there must be correlation association. But that being said, I should be pushing The Mixtape to the top of the list.
  3. Words matter, and I should be more careful!

All in all, not a bad way to spend a Saturday morning.

  1. Anybody who has studied logic, please let me know if I am correct![]
  2. Association, really. See below[]