Happy New Year!

Here’s hoping for the best for all of us in 2022.

Happy New Year (in advance), everybody!

The Five Most Popular Posts of 2021 on EFE

5. Team “Kam Nahi Padna Chahiye”: An offbeat take on how to think about formulating the null hypothesis, by asking which problem would you rather avoid when hosting dinner parties:
avoid the problem of too much food (Team No Leftovers)
or
avoid the problem of having too little food to feed your guests (Team By God We Shouldn’t Run Out Of Food as Hosts)

4. Doing a PhD: This was a request post, in which I tried to answer a question a reader sent in. Short answer: PhD is more about signaling than anything else. Do it to earn street cred, but if you really want to learn, work, don’t study.

3. So You Want to Work in Public Policy: A post about how to think about working in the domain of public policy, and my thoughts about a short book that I really enjoyed reading a while ago.

2. Maximizing Soul: An essay about, well, maximizing soul. Read the whole thing, I’d much rather not try and describe this essay in a couple of sentences. My personal favorite among the things I wrote this year.

And finally, the most popular blogpost this year “Help Me Understand This, Somebody“. Why should this post be as popular as it is? I don’t have the faintest idea, but then again, nothing about April and May of 2021 makes any sense, so why should the metrics of this blog?

How Are You Optimizing?

One of the more popular blog posts on this blog this year was an essay I wrote in March, the title of which was Maximizing Soul. The essay was a lament of sorts about how obsessed we as a society have become about measuring every last thing that we do, and how we have become all about efficiency.

We have become a society of optimization through minimization. We’ve become very good at extracting the very last bit of juice out of a lemon.

https://econforeverybody.com/2021/03/08/maximizing_soul/

That essay was more about society and culture than it was about the economy directly. But more recently, Gulzar Natarajan wrote a blog post making what I take to be more or less the same point, but in the case of the global economy:

The Covid 19 pandemic has underscored the perils with efficiency maximisation at all costs and the importance of resilience. The excessive concentration of manufacturing, especially of critical Pharma products, in China and the supply chain disruptions have provided the most salient reminders. This post discusses the problems of pursuing efficiency at all costs and to the exclusion of all else in case of global manufacturing supply chains.

http://gulzar05.blogspot.com/2021/12/the-shift-from-efficiency-maximisation.html

The title I wanted for today’s blogpost was a bit of a mouthful: “How are you optimizing for whatever it is that you are optimizing for?” I went, instead, with what you see above. But the question I wanted to ask was the one you see in this paragraph.

Say you want to maximize profits (and who wouldn’t, eh?). Three ways you can do this: maximize revenue, minimize cost, or attempt to do both. And Gulzar Natarajan’s point in his blogpost is that the global economy has focused perhaps a wee bit too much on the cost minimization bit – and that we have, in the process, gone a bit too far.

Thanks to business schools and management gurus, it had become articles of faith that businesses should outsource, focus on comparative advantage, specialise functionally, concentrate suppliers and production facilities, minimise inventories, tighten supply chains, contract labour services, minimise tax payout through tax avoidance, and so on. For sure, when done in proportion, all of them have merits and are desirable. But when taken beyond reasonable proportions, they generate distortions.
A common underlying factor behind all these concepts is efficiency. Conventional wisdom has it that their pursuit leads to greater efficiency in some form or other (mainly cost reduction), all of which generally lead to greater profitability, the primary objective of businesses. Therefore efficiency maximisation by pursuing these concepts to their extremes becomes an innate and inexorable dynamic of the market. It does not help that globalisation and advances in information and communications technology and transportation end up furthering these trends.

http://gulzar05.blogspot.com/2021/12/the-shift-from-efficiency-maximisation.html (Emphasis added)

In effect, is blog post is making the point that cost minimization was done at the cost of ignoring the building up of risk:

Businesses and consumers doubtless benefited from these trends. It led to cost reductions which got distributed between higher profits (for businesses) and lower prices (for consumers). A virtuous cycle of consumption, production, and trade led to expansion of aggregate output.
Then the pandemic struck. Lockdowns and quarantines ensued. Supply chains were disrupted. Outsourced suppliers and producers were cut-off or failed to keep their commitments. The lack of diversification at country and company levels among suppliers and producers became painfully evident. Businesses realised that their pursuit of efficiency maximisation and cost reduction had gone too far.

http://gulzar05.blogspot.com/2021/12/the-shift-from-efficiency-maximisation.html (Emphasis added.)

My essay, written in March, tried to argue for maximizing profit by increasing revenue (so to speak), rather than by only minimizing costs. Gulzar Natarajan’s essay, I think, makes a complementary point. If one focuses on minimizing cost by ignoring everything else, there is another problem, that of increasing risks by increasing dependencies on a very small set of ultra-efficient supply chains.

The story in 2022 (and beyond) is going to be one of building more resilient systems. The opportunity cost of this strategy is that these new systems may not be as hyper efficient as the ones that existed pre-covid.

And that Gulzar Natarajan seems to say, is just fine by him.

And I completely agree.

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

A thought provoking Twitter thread from Anup Malani

I usually keep interesting Twitter threads for Saturdays, but this one is deserving of additional commentary and additional reading links:

Unintended consequences, or externalities, or spillovers (some might say these aren’t really interchangeable terms) are a well studied phenomenon in economics, as Anup Malani himself says. Read the classic paper, and listen to many, many conversations over on EconTalk about the topic to get a better understanding.


Anup Malani says towards the end of that first tweet that he has seen economics give explanations for 1 (but not for 2, which we’ll get to later). So what are the explanations for 1? For us to understand the explanations, let us first take a look at the examples that Anup Malani cites in this thread:

And as he himself says in a subsequent tweet in this thread, these phenomena can be understood using simple price theory. Driving becomes safer as a consequence of the introduction of seat belt laws. What does one do with this increased safety? One can either benefit from it by maintaining the same driving speed as before, or one can “spend” the increased benefit by increasing the driving speed.

If, for example, you are the kind of person who thought you were a safe and competent driver before wearing seat belts, you might now think that wearing the seat belt makes you safer still. But you were ok with the level of safety you had before – you are now “extra” safe. But that’s “too” safe for you, so you up the speed at which you drive. Students who have studied basic micro before, kudos if you were reminded of this. If you haven’t formally studied micro before, please do watch that video.


So, price theory helps us “get” how to think about unintended consequences. Although this does raise the rather interesting question about whether one should have anticipated these effects in advance (us economists, we don’t like using simple words. We say ex-ante instead of in advance. It’s the same thing.)

And if we could have anticipated these effects in advance, then were they really unintended consequences in the first place? Something to think about, eh? Maybe that’s why these terms (externalities, unintended consequences and spillovers) aren’t really interchangeable?


But now we get to the second case. Part two of Anup Malani ‘s first tweet in this thread: that which does not kill you makes you stronger.

What are examples of this phrase? (Here’s the Wikipedia article about the phrase itself)

Vaccines, of course! They make you sick sometimes (you are, after all, injecting yourself with a dramatically weakened version of the virus), but they leave you stronger in the sense that you body “learns” how to cope with the virus if it actually does enter you body. Vaccines don’t kill you, and they make you stronger!

But that’s an example from the field of biology. What about economic systems?

Anup Malani gives excellent three excellent examples in his thread, I’ll just mention one over here. Please take a look at the other two as well.

Import of cloth from India, where wages were low, threatened the domestic British cloth-making industry. It didn’t kill this industry, but it did threaten it. And the British responded by increasing mechanization. And the rest is, well, literally history.


Now, this is where Anup Malani ‘s Twitter thread really takes off for me. Price theory, he says, helps us understand unintended consequences. What theory helps us understand “that which does not kill you makes you stronger”?

Anup Malani says we don’t really know.


Might Nassim Nicholas Taleb’s book, Anti-Fragile, have an answer?

Antifragility is a property of systems in which they increase in capability to thrive as a result of stressors, shocks, volatility, noise, mistakes, faults, attacks, or failures. The concept was developed by Nassim Nicholas Taleb in his book, Antifragile, and in technical papers.

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

I’m not sure, and I might be wrong about this, but I think the answer is yes, it does have an answer. Read, in the context of what we’re speaking about in this blog post, chapter 4 from this book very carefully. Here’s one excerpt from that chapter to help you get started:

Nietzsche’s famous expression “what does not kill me makes me stronger” can be easily misinterpreted as meaning Mithridatization or hormesis. It may be one of these two phenomena, very possible, but it could as well mean “what did not kill me did not make me stronger, but spared me because I am stronger than others; but it killed others and the average population is now stronger because the weak are gone.” In other words, I passed an exit exam. I’ve discussed the problem in earlier writings of the false illusion of causality, with a newspaper article saying that the new mafia members, former Soviet exiles, had been “hardened by a visit to the Gulag” (the Soviet concentration camps). Since the sojourn in the Gulag killed the weakest, one had the illusion of strengthening. Sometimes we see people having survived trials and imagine, given that the surviving population is sturdier than the original one, that these trials are good for them. In other words, the trial can just be a ruthless exam that kills those who fail. All we may be witnessing is that transfer of fragility (rather, antifragility) from the individual to the system that I discussed earlier. Let me present it in a different way. The surviving cohort, clearly, is stronger than the initial one—but not quite the individuals, since the weaker ones died. Someone paid a price for the system to improve.

Taleb, Nassim Nicholas. Antifragile (p. 76). Penguin Books Ltd. Kindle Edition.

Mithridization? Here you go. Hormesis? Click here.

This blog post isn’t the place to get into the details of chapter four from Anti-Fragile. Please, do read the entire chapter (and the entire book!)

It is, of course, all too possible that I’m entirely wrong in saying that this is a good answer to Anup Malani’s question. And if you think so, I would love to learn how I’m wrong.

But for the moment, this is my first pass answer to a fascinating question at the end of a lovely thread.

Wendover Productions on The Economics of Airlines’ Loyalty Programmes

Games and Microsoft Excel

Via Navin Kabra on Twitter:

Three Charts Related to China

Read this post, and spend a good amount of time asking yourself some questions about the three charts. Here are my questions (note that I don’t have the answers):

  • Is China’s decoupling a good thing or a bad thing? For whom?
  • What time horizon should we use to think about the answer to the first question? Why?
  • To what extent is China’s reduction in exports as a percentage of GDP deliberate? Was it deliberate all along, or did they observe a trend, think through the consequences, and then make it a deliberate policy?
  • Is China’s decline the share of global GDP growth a good thing for the world? Why?
  • What about India, is it a good thing for India? If yes, along which dimensions? If no, along which dimensions?
  • Does China count the last chart in this blog post as a victory or a defeat, or is it “too soon to tell”? Whatever the answer, why so?
  • What are other data related stories from China that we have not been paying attention to?

I don’t have, as I said, the answers. And maybe I have missed asking some obvious questions. If you have material that will help me think through these issues, please do share.

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.