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

What is the story that NFHS-5 is telling us?

… is, if you ask me, a question that we should ask ourselves, rather than have this question be answered for us by somebody else.

What I mean by that is that I could tell you what I think of the results, or I could point you to articles written by others that tell you what they think of the results. But the results are out there for us to analyze, easily available and fairly readable in terms of accessibility.

Here is the India fact sheet, and here is where you can access data split by states.


I would recommend that you not take the easy way out, by reading what other folks have written. Sit instead, with these reports, and take a look at the big picture – the all India level data. Then begin with the Indian state that you call home, and check how it is doing. Compare India’s performance and your state’s performance with some states that you think ought to do well, and some that you think might be relative laggards on health parameters.

See if the data matches your intuition. And if it doesn’t, ask if you should suspect the data or your intuition (or both!). Begin to build, no matter how long it takes, a picture of India’s health status in your head.

Ask questions about India’s population, its split by gender, ask about our obesity rates and split those up by states. Ask about whether men are doing better than women on some parameters, and if so which – and eventually, why. Ask if there are major changes between the 4th and the 5th round, and ask if the rate of improvement between the 4th and the 5th is different from the rate of improvement between the 3rd and the 4th. Then ask if these numbers are comparable at all, given that there is a difference of ten years in the latter case, but only 5 in the former.


Try to come up with a list of ten points at the all-India level that seem noteworthy to you. And once you’re done with the list, then take a look at what the newspapers and columnists and op-eds are saying.

Is the story that you have come up with similar to theirs? If not, why? Might it be because they’ve done a better job in highlighting relevant material, or might it because they’re biased in some ways? Do you think they’re biased because of what they’ve written in the past, or because their interpretation of NFHS-5 differs from yours, or both? What is the probability that you are biased against them, rather than they being biased while writing whatever it is that they have written? How can one tell, really?

The bottom-line is this: if you consider yourself a student of economics, don’t form your opinions and biases by mirroring and mimicking the opinions and biases of folks you like. Begin with the data, form your own opinions, and then test them against those of others. Defend your ideas and conclusions by pitting them against those of others, and by engaging in respectful debate.

It’s a good way to study our country! 🙂

Update: Please take a look at this excellent Twitter thread about the history of NFHS. H/T: Sumita Kale.

Understanding the idea behind the NFHS

Why should you, as an informed citizen of this country, be aware of how well India is doing in terms of health?

The question isn’t rhetorical. For its own sake is a more than good enough answer, of course, but here are additional reasons for keeping track of how well we’re doing as a country in terms of health:

  • If you think that the Solow model is a good way to start to think about the long term growth prospects of our nation, then thinking about the health of that workforce is important
  • If you think it is possible that different states may have different health outcomes, it makes sense to try and understand whether this is the case.
  • It also makes sense to dig into the data and try and understand the particulars of these differences. (A state may do poorly on life expectancy in comparison to other states, for example, but better along other dimensions. Why might this be so is an excellent question to ask, and this is just one of many possible questions.)
  • This is true for many other ways to “slice” this data. Are there different outcomes by, say, gender? By urban/rural divide?
  • The answers to each of these questions is important because it helps us understand how to build a framework to answer the mot important question of them all: if we have to improve India’s health, where should we start?

And for all of these reasons (and so many more) it makes sense for all of us to be aware of the results of the NFHS survey.


What is the NFHS Survey?

The National Family Health Survey (NFHS) is a large-scale, multi-round survey conducted in a representative sample of households throughout India. The NFHS is a collaborative project of the International Institute for Population Sciences(IIPS), Mumbai, India; ICF, Calverton, Maryland, USA and the East-West Center, Honolulu, Hawaii, USA. The Ministry of Health and Family Welfare (MOHFW), Government of India, designated IIPS as the nodal agency, responsible for providing coordination and technical guidance for the NFHS. NFHS was funded by the United States Agency for International Development (USAID) with supplementary support from United Nations Children’s Fund (UNICEF). IIPS collaborated with a number of Field Organizations (FO) for survey implementation. Each FO was responsible for conducting survey activities in one or more states covered by the NFHS. Technical assistance for the NFHS was provided by ICF and the East-West Center.

http://rchiips.org/nfhs/about.shtml

Why is the NFHS important?

Why do we have something like NFHS? To obtain data on health and nutrition, disaggregated to the level of districts. We want to take stock of developmental targets at a single point in time and wish to track improvements (or deterioration) over time.

https://www.newindianexpress.com/opinions/columns/2021/dec/13/nfhs-andwhy-surveys-are-better-than-asking-a-cab-driver-2394809.html

How often is the NFHS carried out?

That’s a little tricky to answer, but I can tell you that there have been five rounds so far. The first one was in 1992-93, the second in 1998-99, the third in 2005-06, the fourth in 2015-16 (and this decade long gap is why this question is a little tricky to answer) and the fifth in 2020-21.

OK, so we can use this data to see how health in India has evolved over time?

Um, not exactly:

To gauge improvements over time, ideally, we should have what statisticians and economists call a panel. In a panel, across time, questions are asked to the same individuals/households. For something like NFHS, that’s not possible. In addition, for NFHS-5, compared to NFHS-4 (2015–16), additional questions have been asked. For those questions, gauging improvements over time is naturally impossible.

https://www.newindianexpress.com/opinions/columns/2021/dec/13/nfhs-andwhy-surveys-are-better-than-asking-a-cab-driver-2394809.html

Then what can we use the data for?

Especially because the answer to the first question in this series included this: “wish to track improvements (or deterioration) over time.”

Well, yes, it did. And we do use this data to see how health in India has evolved over time. But it’s not a perfect comparison, because we aren’t tracking the same households over time, and it therefore isn’t an apples to apples comparison. But the perfect shouldn’t be the enemy of the good, especially in public policy! The fifth round has in fact been structured in such a way so as to make the results as comparable as possible.

How many households are covered?

NFHS-5 fieldwork for India was conducted in two phases, phase one from 17 June 2019 to 30 January 2020 and phase two from 2 January 2020 to 30 April 2021 by 17 Field Agencies and gathered information from 636,699 households, 724,115 women, and 101,839 men

http://rchiips.org/nfhs/NFHS-5_FCTS/India.pdf

What questions are asked in this survey?

That’s a great question to ask!

Four Survey Schedules – Household, Woman’s, Man’s, and Biomarker – were canvassed in local languages
using Computer Assisted Personal Interviewing (CAPI).

In the Household Schedule, information was collected on all usual members of the household and visitors who stayed in the household the previous night, as well as socio-economic characteristics of the household:

water, sanitation, and hygiene; health insurance coverage; disabilities; land ownership; number of deaths in the household in the three years preceding the survey; and the ownership and use of mosquito nets.

The Woman’s Schedule covered a wide variety of topics, including the woman’s characteristics, marriage, fertility, contraception, children’s immunizations and healthcare, nutrition, reproductive health, sexual behaviour, HIV/AIDS, women’s empowerment, and domestic violence.

The Man’s Schedule covered the man’s characteristics, marriage, his number of children, contraception, fertility preferences, nutrition, sexual behaviour, health issues, attitudes towards gender roles, and HIV/AIDS.

The Biomarker Schedule covered measurements of height, weight, and haemoglobin levels for children; measurements of height, weight, waist and hip circumference, and haemoglobin levels for women age 15-49 years and men age 15-54 years; and blood pressure and random blood glucose levels for women and men age 15 years and over. In addition, women and men were requested to provide a few additional drops of blood from a finger prick for laboratory testing for HbA1c, malaria parasites, and Vitamin D3.

http://rchiips.org/nfhs/NFHS-5_FCTS/India.pdf

Whoa, that’s… a lot!

Indeed it is! If you haven’t clicked through to those PDF’s that have been linked to in the previous question, take the time out to go and do so. Conducting one of these surveys isn’t easy. All of these, and across these numbers (636,699 households, 724,115 women, and 101,839 men) is pretty tough, and kudos to the team that did the work.

So how are these households selected?

Another excellent question. From the interview manual (and if you are a student of statistics, this manual ought to be mandatory reading):

All 29 states and seven union territories (UTs) will be included in NFHS-5. NFHS-5 will provide
estimates of most indicators at the district level for all 707 districts in the country as on 1 March
2017.

For NFHS-5, the sample consists of approximately 30,456 clusters (small geographically defined
areas) throughout the country. The households in each of these clusters have recently been listed or
enumerated. A sample of households was then scientifically selected to be included in NFHS-5 from
the list in each of the clusters. Each of these households will be visited and information obtained
about the household using the Household Questionnaire. Women and men within these households
will be interviewed using an Individual Questionnaire. Women age 15-49 years will be interviewed
using the individual Woman’s Questionnaire. Men age 15-54 years will be interviewed using the
individual Man’s Questionnaire. We expect to complete interviews with about 7,45,488 women and
1,19,501 men in 670,032 households in this survey.

http://rchiips.org/NFHS/NFHS5/manuals/NFHS-5%20Interviewer%20Manual_Eng.pdf

And how are the surveys conducted?

During NFHS-5 fieldwork, you will work in a team consisting of one field supervisor, three female
interviewers, and one male interviewer. Each team will be provided with a vehicle and driver for
travelling from one Primary Sampling Unit (PSU) to another to conduct the fieldwork.
In addition, the team will include two health investigators. These individuals will be responsible for
drawing blood from eligible persons for testing for anaemia status, blood pressure, and blood glucose. In
addition, the health investigators will collect blood drops from a finger stick on filter paper cards,
which will be tested for malaria, HbA1c, and Vitamin D3 in ICMR laboratories. They will also be
responsible for the anthropometric measurements of eligible women, men, and children. The supervisors
will also receive some biomarker training so that they can supervise the health investigators and assist
them as needed. All interviewers will be trained to assist the health investigators in taking the
anthropometric measurements(height, weight, and waist and hip circumference measurements).
Each team supervisor will be responsible for his/her team of interviewers and health investigators.
The specific duties of the supervisor are described in detail in the Supervisor’s Manual.

http://rchiips.org/NFHS/NFHS5/manuals/NFHS-5%20Interviewer%20Manual_Eng.pdf

This PDF, the one that I have excerpted from, is 182 pages long. I am not for a moment suggesting that all of you must read every single word. But I’ll say this much: if you are currently studying either statistics or economics, you should go through it more than once. It is one thing to learn from textbooks, and quite another to understand the on the ground realities.


In tomorrow’s post, let’s dig in and take a look at the data itself, and see what the NFHS-5 results tell us about our country’s health.

Make Examinations Relevant Again

Alice Evans (and if you are unfamiliar with her work, here’s a great way to begin learning more about it) recently tweeted about a topic that is close to my heart:

And one of the replies was fascinating:


I’ve asked students to create podcasts in the past for assignments, but not yet for final or semester end examinations, because I am constrained by the rules of whichever university I’m teaching in. There are some that allow for experimentation and off-the-beaten-path formats, but the vast majority are still in “Answer the following” mode.

But ever since I came across that tweet, I’ve been thinking about how we could make examinations in this country better, more relevant, and design them in such a way that we test skills that are applicable to the world we live in today, rather than the world of a 100 years ago.

To me, the ideal examination would include the following:

  • The ability to do fast-paced research on a collaborative basis
  • The ability to work as a team to be able to come up with output on the basis of this research
  • The ability to write (cogently and concisely) about how you as an individual think about the work that your team came up with

What might such an examination look like? Well, it could take many forms, but here’s one particular form that I have been thinking about.

Imagine an examination for a subject like, say, macroeconomics. Here’s a question I would love to ask students to think about for such an examination today. “Do you and your team find yourself on Team Transitory or Team Persistent when it comes to inflation today? The answer, in whatever format, should make sense to a person almost entirely unacquainted with economics.”

This would be a three hour long examination. Say the exam is for a cohort of 120 students. I’d split the class up into 10 groups of 12 each, and ask each group to spend one hour thinking about this question, and doing the research necessary to come up with an answer. They can discuss the question, split the work up (refer to textbooks, refer to material online, watch YouTube videos, discuss with each other, appoint a leader – whatever it is that they need to do) and come up with an outline of what their answer is.

The next hour would be coming up with the answer itself: write a blogpost about it, or record audio, or record video. The format is up to them, as is the length. The only requirement is that the output must answer the question, and must include reasons for their choice. Whether the background information that is required to make sense is to be given (or referenced, or skipped altogether) is entirely up to the students.

And the final hour must be spent on a short write-up where each individual student submits their view about their team’s submission. Given that the second hour’s output was collaborative, does the student as an individual agree with the work done? Why? Or why not? What would the student have liked to have done differently? This part must be written, for the ability to write well is (to me) non-negotiable.

To me, this examination will encompass research (which can only be done in an hour if the students are familiar enough with the subject at hand, so they need to have done their homework), collaboration and the ability to think critically about the work that they were a part of. Grading could be split equally on a fifty-fifty basis: half for the work done collaboratively, and half for the individual essay submission.


Sure, there would be some problems. Students might object to the groups that have been formed or students might end up quarreling so much in the first two hours that they’re not left with much time. Or something else altogether, which is impossible to foresee right now.

But I would argue that such examinations are more reflective of the work that the students will actually do in the world outside. More reflective than “Answer the following” type questions, that is.

The point isn’t to defend this particular format. The point is to ask if the current format needs to change (yes!) and if so how (this being only one suggestion).

Right now, examinations provide a 19th century solution to very real 21st century problems, and their irrelevance becomes ever more glaring by the day.


We need to talk about examinations, and we aren’t.

Should students of law be taught statistics?

I teach statistics (and economics) for a living, so I suppose asking me this question is akin to asking a barber if you need a haircut.

But my personal incentives in this matter aside, I would argue that everybody alive today needs to learn statistics. Data about us is collected, stored, retrieved, combined with other data sources and then analyzed to reach conclusions about us, and at a pace that is now incomprehensible to most of us.

This is done by governments, and private businesses, and it is unlikely that we’re going to revert to a world where this is no longer the case. You and I may have different opinions about whether this intrusive or not, desirable or not, good or not – but I would argue that this ship has sailed for the foreseeable future. We (and that’s all of us) are going to be analyzed, like it or not.

And conclusions are going to be made about us on the basis of that analysis, like it or not. This could be, for example, a computer in a company analyzing us as a high value customer and according us better service treatment when we call their call center. Or it could be a computer owned by a government that decides that we were at a particular place at a particular time on the basis of the footage from a security camera.

In both of these cases (and there are millions of other examples besides), there is no human being who makes these decisions about us. Machines do. This much is obvious, because it is now beyond the capacity of our species to deal manually with the amount of data that we generate on a daily basis. And so the machines have taken over. Again, you and I may differ on whether this is a good thing or a bad thing, but the fact is that it is a trend that is unlikely to be reversed in the foreseeable future.

Are the conclusions that these machines reach infallible in nature? Much like the humans that these machines have replaced, no. They are not infallible. They process information much faster than we humans can, so they are definitively better in handling much more data, but machines can make errors in classification, just like we can. Here, have fun understanding what this means in practice.

Say this website asks you to draw a sea turtle. And so you start to draw one. The machine “looks” at what you’ve drawn, and starts to “compare” it with its rather massive data bank of objects. It identifies, very quickly, those objects that seem somewhat similar in shape to those that you are drawing, and builds a probabilistic model in the process. And when it is “confident” enough that it is giving the right answer, it throws up a result. And as you will have discovered for yourself, it really is rather good at this game.

But is it infallible? That is, is it perfect every single time? Much like you (the artist) are not, so also with the machine. It is also not perfect. Errors will be made, but so long as they are not made very often, and so long as they aren’t major bloopers, we can live with the trade-off. That is, we give up control over decision making, and we gain the ability to analyze and reach conclusions about volumes of data that we cannot handle.

But what, exactly, does “very often” mean in the previous paragraph? One error in ten? One in a million? One in an impossibly-long-word-that-ends-in-illion? Who gets to decide, and on what basis?

What does the phrase “major blooper” mean in that same paragraph? What if a machine places you on the scene of a crime on the basis of security camera footage when you were in fact not there? What if that fact is used to convict you of a crime? If this major blooper occurs once in every impossibly-long-word-that-ends-in-illion times, is that ok? Is that an acceptable trade-off? Who gets to decide, and on what basis?


If you are a lawyer with a client who finds themselves in such a situation, how do you argue this case? If you are a judge listening to the arguments being made by this lawyer, how do you judge the merits of this case? If you are a legislator framing the laws that will help the judge arrive at a decision, how do decide on the acceptable level of probabilities?

It needn’t be something as dramatic as a crime, of course. It could be a company deciding to downgrade your credit score, or a company that decides to shut off access to your own email, or a bank that decides that you are not qualified to get a loan, or any other situation that you could come up with yourself. Each of these decisions, and so many more besides, are being made by machines today, on the basis of probabilities.

Should members of the legal fraternity know the nuts and bolts of these models, and should we expect them to be experts in neural networks and the like? No, obviously not.

But should members of the legal fraternity know the principles of statistics, and have an understanding of the processes by which a probabilistic assessment is being made? I would argue that this should very much be the case.

But at the moment, to the best of my knowledge, this is not happening. Lawyers are not trained in statistics. I do not mean to pick on any one college or university in particular, and I am not reaching a conclusion on the basis of just one data point. A look at other universities websites, conversations with friends and family who are practicing lawyers or are currently studying law yields the same result. (If you know of a law school that does teach statistics, please do let me know. I would be very grateful.)


But because of whatever little I know about the field of statistics, and for the reasons I have outlined above, I argue that statistics should be taught to the students of law. It should be a part of the syllabus of law schools in this country, and the sooner this happens, the better it will be for us as a society.

Were The Farm Laws a “1991 Moment”?

As with everything that happens in the world today, so also with the farm laws: a lot of heat, and hardly any light. Reams have been written about how the farm laws were good (or bad), about their introduction being a much needed thing (or not), and their withdrawal being a disaster for take-your-pick-from-Modi-BJP-India (or not).

I have neither the desire nor the energy to get into any of these debates. Here’s my simple take as a student of economics: markets almost always work. Where they don’t work, identify the reasons why they don’t work, and either correct those causal factors, or have the government step in until (and only until) those factors are corrected.

Things get tricky when you begin to ask pesky questions along these lines:

  • How do you define markets not working? Bench-marked against what standard? Who decides?
  • How do you correct these causal factors? How do you judge that they have been corrected? Are you sure they won’t return? On what basis?
  • To what extent should government step in? How are you sure this will make things better in all markets at all points of time? Using what framework?

But that is precisely what makes the study of India’s political economy so very interesting! And this is true of agriculture as well, not just in India, but in other places too.


For the moment, let’s take as a given the fact that government had to be present in agricultural markets in India these past decades. That may or may not be true, but for the purposes of this blog post, let us assume that there was a confluence of factors in India’s agricultural markets that necessitated the active presence of the government as a participant, not just as a regulator.

Now, if markets almost always work, and if government was present in agriculture, then we have to figure out a way for government to eventually not be present in agriculture. (Note, again, that your opinion may be different from mine. But play along with me for the moment, please.)


Yamini Aiyar and Mekhala Krishnamurthy argue in an HT article that in the case of the three farm laws, what the government missed out on was the word “eventually”. They argue that it was the suddenness of the move that was problematic, not the move itself.

There’s a political angle to the sudden withdrawal, and the authors refer to it in their piece. There’s a regulatory angle to the sudden withdrawal, and that is also covered by the authors. But there also is an institutional (and therefore economic) angle to it, and that is what I would like to focus on:

Consider this. The protesting farmers from Punjab, Haryana and western Uttar Pradesh are locked into a system where State intervention, driven by the logic of Minimum Support Prices (MSP) and the Agricultural Produce Marketing Committee (APMC) mandis, dominates. The State is not a benign actor. It has created and sustained local elites with vested interests – traders, middlemen and moneylenders, each of whom extracts to control market power. This undermines competition and compromises farmer interests in different ways. But farmers have learnt to negotiate these relationships of extraction. And the state through MSP and mandis has served as insurance that gives them bargaining power. Any attempt to break this system will inevitably, as the protests amply demonstrate, unleash anxieties.
In this context, the move towards genuine competition will not be viable without the State demonstrating its willingness to protect farmers interests and gain their trust.

https://twitter.com/AiyarYamini/status/1464452741325996032/photo/1

What is the point? The point is that the current system isn’t perfect, and it isn’t sustainable. As the authors point out, the farming sector isn’t competitive.

In theory, that should mean, to a student of economics, that they are not efficient. That, in turn, means that we should expect that producers aren’t producing as much as they could have, and whatever they produce is being produced at a higher cost than would otherwise have been the case. We should expect that procurement, storage and distribution are also potentially riddled with inefficiencies. We should expect divergent quality of produce, and we should expect consumers to be paying higher prices, potentially for a lower variety of goods.

We should also anticipate a whole host of things due to the fact that the farming sector isn’t competitive: prices aren’t transparently determined, there isn’t free entry and exit, certain sellers are likely to get a better deal, transaction and search costs are high, and on and on and on. This is microeconomics 101 in practice.

(A quick note to students of economics: ask yourself if you’re able to relate what you’re learning in your microeconomics courses to the two paragraphs above. If you disagree with my assessment, ask yourself what is it that is causing you to disagree. Can you frame your disagreement in the context of microeconomic theory? Secondly, irrespective of whether you agree or not, can you think of what data points you might need to empirically verify or disprove my arguments? Where might these data points be available? What models (economic and econometric) can we use to settle this debate? Finally, why stop at agricultural markets – which other markets can you analyze this way?)

And for all of these reasons and more, reform is needed. It cannot possibly be anybody’s argument that the status quo in India’s agriculture must persist forever.


Which then, in turn, gives rise to two separate questions:

  1. If reforms are to be introduced, how?
  2. However they are to be introduced, how fast should we proceed with their implementation?

Again, the question isn’t one of the desirability of reforms, or their appropriateness. Rather, the question is about whether the reforms should be a top-down, one-size-fits-all initiative, or a more locally driven approach. And second, should reforms be introduced all at once, or slowly and gradually, one step at a time.

And I would like to argue that at least in this one regard, we should be looking at China. Not for the specifics of their reform and a CTRL-C CTRL-V hit job. But for their approach, beginning in the late 1970’s.


When I first proposed the household responsibility system (HRS), I was criticized as follows: Chairman Mao had been dead only a few years. Supporting the HRS, a system he opposed, meant forsaking his principles. This was the severe environment that reform faced at first. Our support of the HRS, of institutional innovation, and of transformation of the agents of the rural microeconomy would inevitably involve adjusting a number of interests. To avoid risk, it was necessary to carry out trials first. Also, the HRS could not move ahead on its own. It had do so in connection with other institutions and be realized in the course of reforming the institutional environment as a whole. But this institutional reform is not something that could be accomplished in one fell swoop. To carry out reform, a strategy of gradual advance was unavoidable.

http://ebrary.ifpri.org/utils/getfile/collection/p15738coll2/id/125214/filename/125215.pdf (Emphasis added)

That’s Du Runsheng, the author of a short publication called The Course of China’s Rural Reform. He did, um, some other things besides.

In the publication that I have excerpted from above, there are some points that I am going to summarize that I think help me make my point better:

  1. Resistance to the introduction of market based reforms was anticipated in China back then, and was in some sense inevitable. Three measures were conceived of to reduce this resistance:
    1. “First, the reform would not initially call for abandoning the people’s communes, but rather would implement a production responsibility system within them. This approach enabled many who would have opposed the change to accept it.”
    2. “Second, the responsibility system could take a number of forms, among which the populace could choose. One did not impose one’s own subjective preference on the populace but respected its choice.”
    3. “Third, the reform began in a limited region, where it received popular support, and then widened step by step.” (Emphasis added)
  2. “In 1980, after the central leadership was reorganized on a collective basis, the top central leaders, including Deng Xiaoping and Hu Yaobang, consistently supported allowing different areas to adopt different forms of the agricultural production responsibility system. It was then proposed to divide them into three types of areas: impoverished areas would carry out the HRS; advanced ones would adopt specialized contracts with wages linked to output; and intermediate regions could freely choose.”
  3. Or, as Ajay Shah and Vijay Kelkar put it in their book:
    “The heterogeneity of economic and social development, across the regions of India, generates heterogeneity in the public policy pathways desired by different groups of people. A policy position that is well liked in Uttar Pradesh may not be liked in Kerala, and vice versa. This creates conflict in a centralized public policy process.”
    Kelkar, Vijay; Shah, Ajay. In Service of the Republic . Penguin Random House India Private Limited. Kindle Edition.
  4. Finally, there’s a lot to pick at and think about here when we get down to the specifics. I’m not suggesting that China in the late 1970’s had the exact same problems that India does today. Nor am I suggesting that India do today exactly what China did back then. I am making three points:
    1. I agree with Yamini Aiyar and Mekhala Krishnamurthy when they say that one of the problems was the suddenness of the proposed reforms, both in terms of their scope, and in terms of their geographical spread. I also agree with them when they say that the introduction of the reforms ignored the ground realities of the both the sociology of agricultural markets, and their institutional complexity (note that I am paraphrasing here, these are not their words).
    2. But having read their article, one must ask: if not the pathway that we have now left behind us, what else? That is, for better or for worse, the three farm laws now stand withdrawn. Is the status quo desirable? Should we seek to perpetuate it, or change it for “the better”? (Inverted quotes because better means different things to different people.) My opinion is that we should seek to change it for the better, and maybe yours is the same.
    3. But that gives rise to the next question: how? And that is where Du Runsheng and his write-up is of limited help. Learning how other nations did it is a good place to start if you are a student of economics, India or public policy, and post-Mao China holds some valuable lessons for us.

India and China’s GDP Components Over Time

This should go without saying, but ask yourself if you are able to recreate these charts given the data sources mentioned in the tweet. You needn’t use DataWrapper necessarily (although if you’re considering journalism or a related field, learning it will help) – but do see if you can create the chart!

“What Are You Optimizing For?”, The International Macro Edition

It is one of my favorite questions to ask whenever students come to me with doubts about “what to do next” in terms of either further education or a job.

(Side note: asking me what to do next probably isn’t a good idea, because my career has been gloriously unplanned. But that’s a whole separate story)

But one should be clear about what one is optimizing for: is it income, or free time, or job satisfaction, or rapid career growth – or something else altogether? And whatever it may be, optimizing for one will quite probably mean having to give up on some or all of the others.

And this applies to many more things than just the What To Do Next question, of course. In fact, relentlessly asking this question in many different contexts can take you a very long way in terms of understanding what seem like really difficult and complex topics.

Such as, for example, what China has been up to in terms of international trade, and what went so gloriously wrong.


The simple story of international trade (or trade in general for that matter) isn’t difficult to grasp. Bear in mind that reality is a little more complex, but it really boils down to comparative advantage.

As Michael Pettis points out at the start of this excellent Twitter thread, the so-called “China shock” *is* a shock, but it is not an indictment of the basic concept of international trade. China, as we’re about to find out, was playing a zero-sum game.

One of the most glorious things about economics is the fact that trade is a non-zero sum game. Both parties that have voluntarily entered into a trade with one another benefit for the trade having gone through, and so nobody loses. This is as true at your local chai tapri (you give ten bucks for a cup of chai, and both you and the chaiwala are happy with the trade) as it is in the context of international trade between the United States of America and China.


But beware overly simplistic stories, for they can trip up many a happy ending:

Isabella Kaminska, in an old but excellent article on FT Alphaville made a very similar point. I’ll get to that point in a bit, but may I also use this opportunity to urge the good folks at FT to make FT Alphaville free again?

Here’s the point from that old article:

What those who accused China of using its exchange rate to gain advantage probably misunderstood was that it wasn’t the currency which was being undervalued, it was the people. Stephen Roach, then chief economist of Morgan Stanley, explained this point in the Financial Times in 2003 (our emphasis):
“The Chinese phenomenon hardly amounts to grabbing market share from the rest of the world. It is more a by-product of the struggle for competitive survival by high-cost producers in the industrial world. Last year, a record $53bn of foreign direct investment flowed into China, making the country the largest recipient of such funds in the world.
These investments did not occur under coercion. A high-cost industrial world has made a decision that it needs China-based outsourcing to ensure competitive survival. Dismantling China’s currency peg would destabilise the very supply chain that has become so integral to new globalised production models in Japan, the US and Europe.
There are several other reasons why China should leave its currency unchanged. Contrary to widespread perception, China does not compete on the basis of an undervalued currency. It competes mainly in terms of labour costs, technology, quality control, infrastructure and an unwavering commitment to reform.

https://www.ft.com/content/d11a4c5e-d5fb-32f4-a606-e64d1483cea1 (Emphasis added)

This article was written in 2015, but it holds up very well. In fact, it is instructive to see how, in addition to labour costs and infrastructure, China has now centralized under government authority technology as well. It is also instructive to think about how (and in what direction) the “unwavering commitment to reform” has evolved, but that is a separate story.

To come back to the common thread between the old FT Alphaville article and the Twitter thread by Michael Pettis:

Stephen Roach, in 2003, spoke about how China was undervaluing its people. Isabella Kaminska in 2015 spoke about China competes (at least in part) on labor. And Michael Pettis in 2021 is talking about China competing by suppressing its wages (relative to productivity levels). But they’re all making the same point, and it is a point that merits greater emphasis:

The China shock needn’t have been a shock, in the sense that it is not as if economic theory stopped working once China started trading more with the rest of the world.

China, as it turns out, wasn’t optimizing for international trade. China was – and is – optimizing for an increase in her exports, and that over time.


That problem manifests itself in many different ways: The USA’s persistent trade deficit with China is just one glaring example. The Belt and Road Initiative is another (what the hell do you do with all those forex reserves, dammit?). And there’s many, many more.

But as Michael Pettis reminds us in this thread, the “China Shock” phenomenon becomes way more comprehensible when you ask a deceptively simple question: what is China optimizing for?


What is India optimizing for when it comes to international trade? What should India be optimizing for? In both cases, whatever your answer, why?


Critique this blogpost, and write your responses to the questions above. It is a great way to test yourself if you think you’re good to go in open macroeconomics or international trade.

Bibek Debroy on loopholes in the CPC

That’s the Civil Procedure Code.

The average person will not have heard of Dipali Biswas or Nirmalendu Mukherjee and may not be aware of the case decided by the Supreme Court on October 5, 2021. The case was decided by a division bench, consisting of Hemant Gupta and V Ramasubramanian and the judgment was authored by Justice V Ramasubramanian. Justice Ramasubramanian observed (not part of the judgment), “Not to be put off by repeated failures, the appellants herein, like the tireless Vikramaditya, who made repeated attempts to capture Betal, started the present round and hopefully the final round.” Other than smiling about a case that took 50 years to be resolved and making wisecracks about “tareekh pe tareekh”, shouldn’t we be concerned about rules and procedures (all in the name of natural justice) that permit a travesty of justice?

https://indianexpress.com/article/opinion/columns/civil-procedure-code-loopholes-justice-delay-7617291/

I know (alas) next to nothing about the law, but there were two excerpts in this article that I wanted to highlight as a student of statistics and economics. We’ll go with statistics first.

Whenever I start to teach a new course, I always tell my students that there are two kinds of errors I can make. I can either make sure that I complete the syllabus, irrespective of whether everybody has understood it or not. Or I can make sure that everybody has understood whatever I have taught, irrespective of whether the syllabus is completed or not. Speed versus thoroughness, if you will – and both cannot be optimized for at the same time. If you’re wondering, I prefer to err on the side of making sure everybody has understood, even if it comes at the cost of an incomplete syllabus.

This is, of course, closely related to formulating the null hypothesis and asking which type of error one would rather avoid. And the reason I bring it up, is because of this exceprt:

Innumerable judgments have quoted the maxim, “justice hurried is justice buried”. By the same token, justice tarried is also justice buried and inordinate delays mean the legal system doesn’t provide adequate deterrence to mala fide action. In my view, for most civil cases, the moment issues are framed, one can predict the outcome within a range, with a reasonable degree of certainty. (Obviously, I don’t mean constitutional cases before the Supreme Court.) With no disrespect to the legal system, I think AI (artificial intelligence) is capable of delivering judgments in such cases, freeing court time for non-trivial cases.

https://indianexpress.com/article/opinion/columns/civil-procedure-code-loopholes-justice-delay-7617291/

“Justice hurried is justice buried” and “Justice tarried is justice buried” are both problems, and optimizing for one means not optimizing for the other. What Bibek Debroy is saying here is that what we have ended up choosing to optimize for the former. We make sure that every case has the opportunity to be heard at great length, and with sufficient maneuvering room for both parties.

And that’s great, but the opportunity cost is the fact that sometimes judgments can take over fifty years (and counting!).

And what is Bibek Debroy’s solution? When he suggests that AI is capable of delivering judgments in such cases, he is not saying that the AI will give a perfect judgment every time. He is not even saying that one should use AI (I think the point is rhetorical, although of course I could be wrong). He is saying that the gains in efficiency are worth the occasional case being incorrectly judged. In other words, he is optimizing for justice tarried is also justice buried – he would rather avoid the error of taking up too much time for each case, and would (presumably) be fine paying the price of having the occasional case being misjudged.

It is up to you to agree or disagree with him, or with me when it comes to how I conduct classes. But all of us should be cognizant of the opportunity costs when we decide which error we’d rather avoid!


And economics second:

Litigants and lawyers (at least on one side of a civil case) have no incentive to finish a case fast (Does the judiciary have it?).

https://indianexpress.com/article/opinion/columns/civil-procedure-code-loopholes-justice-delay-7617291/

This is more of a question (or rumination) on my part – what are the incentives of the judiciary? I can imagine scenarios in which those “on one side of a civil case” can use both official rules and underhanded stratagems to delay the eventual judgment. And since there is no incentivization in terms of speedier resolutions, are we just left with a system that is geared towards moving along ponderously forever more?

And if so, how might this be changed for the better? This is, and I’m not joking, (more than) a trillion dollar question.


And finally, as a bonus, culture:

My friend Murali Neelakantan makes the point here that isn’t really about incentive design at all, that the problem is more rooted in how we, the people of India, use and abuse the provisions of the CPC.

That takes me into even deeper and ever more unfamiliar waters, so I shall think more about this before trying to write about it!

V Ananta Nageswaran on the IMF’s Medium-Term Forecasts for India and China

If you are an undergrad or post-grad student in India studying economics, you’ve no doubt been taught how to think about GDP (ways to measure it, ways to define it, its limitations, its advantages). But if you ask me, what we fail to do enough of is explain to students how one is supposed to use these concepts.

I often tell my students that GDP for a nation is like grades/marks obtained by a student. In much the same way that grades are not an accurate reflection of all of what a student has done in an academic year (even in purely an academic sense), GDP isn’t an accurate reflection of what a country has earned in a given time period. But also in much the same way that we have not been able to come up with a better way to assess students, we have not been able to come up with a better way to measure the economic output of a nation.

So while keeping in mind the fact that the measure isn’t perfect, but also that there isn’t a better measure in place just yet, let’s go ahead and read V Ananta Nageswaran’s excellent column in the Livemint about India and China’s medium term forecasts by the IMF.

What I am going to do below is highlight some sentences from this column and pose questions on the basis of these excerpts. Try and answer these questions, especially if you have been taught macro in your college/university. To my mind, this will go a very long way towards helping you understand if you have, well, understood key macroeconomic concepts:

  1. The International Monetary Fund (IMF) publishes its World Economic Outlook (WEO) twice a year after its Spring and Autumn meetings.

    Have you read the latest edition? If nothing else, take a look at the executive summary.
  2. “However, since then, many private-sector economists have upgraded their forecast for India’s economic growth this financial year to more than 10%, based on more recent and real-time indicators including mobility data.”

    What might a list of such indicators look like? Here’s a place to get started.
  3. “In October, India’s nominal GDP for 2026-27 was projected at ₹392.84 trillion and $4.393 trillion. In the April WEO edition, the corresponding forecasts were ₹389.01 trillion and $4.534 trillion. So, secondary-school arithmetic will tell us that the Fund has become relatively more pessimistic on the Indian rupee versus US dollar (USD) in October than in April. From 70.9 in 2020-21, the Fund sees the rupee depreciating to 89.4 against the US dollar by 2026-27. In April, the implied exchange rate forecast for 2026-27 was 85.8. So, the US dollar is stronger by 4.2% at the end of 2026-27 as per the October 2021 forecast versus April’s. The effect is that India’s nominal GDP in USD terms in 2026-27 is $140 billion lower than the April forecast.”

    Can you go back to the report and find out how the author reached these numbers? Do you agree with his calculations? Can you explain these calculations to somebody else? Do you find yourself able to write paragraphs like these? If not, what do you think you need to learn?
  4. “When it comes to forecasting exchange rates, the literature informs us that economic fundamentals do a poor job for any horizon under three years.”

    What might this mean in terms of statistical concepts? What does this tell you about how to think about long term investing (in financial assets, people and entire nations)?
  5. “Of all the economic fundamentals that influence exchange rates, the one enduring factor is the inflation differential.”

    Which are the other economic fundamentals that influence exchange rates? What is the inflation differential? Why does the author say that this particular factor is an enduring one?
  6. This is a truly remarkable graph, and worthy of thinking about deeply. Why does it look the way it does? Is this a good thing or a bad thing? For whom, exactly, and over what time horizon?
  7. “So, for any USD-INR forecast, higher inflation rates in India over the US that have been the default factor for the past few decades cannot form the basis. The Fund may have to revisit its implicit forecasts for USD-INR in April 2022.”

    Do you agree with the author’s assessment that inflation in India may not necessarily be higher than in the United States? Why or why not? With what implications beyond GDP calculations?

I’d recommend that you try and figure out the answers to these questions yourself, or even better, with a group of like-minded people. Run them past your prof(s), and see what they have to say. Wwrite up/record your answers and put ’em up for public consumption.

And best of all, try to come up with more such questions yourselves!