Livemint, Hindu Business Line, Business Standard, Times of India, The New York Times, The Hindu, The Washington Post, The Economist, Bloomberg Quint and Noah Smith’s Substack.
These are, as of now, my sources of news online that I pay for.
There are other newsletters that I subscribe to and pay for (The Browser is an excellent example), and I read stuff published in other newspapers too, but I’m restricting myself to only the current news sources that I pay for. I would like to subscribe to the Financial Times and to Stratechery too, but my budget line begins to cough firmly and insistently at this point, more’s the pity.
But here’s the thing: reading news online sucks.
Some are worse than others, and I’m very much looking at you, Business Standard. Their app is a joke, and the number of times one has to sign in while reading the paper on a browser isn’t funny. Some are, relatively speaking, better. The NYT website and app are both pretty good, as is the Economist. But still, it isn’t friction free, and there really should be a way to get the user experience to be better than it is right now.
And more than better, a more urgent word is uniform. Here’s a simple use case: let’s say I want to read articles on the current lockdown in Shanghai. I have to go to each website, and either run a search, or navigate to the appropriate section. But on each website, the search button will be located in a slightly different place, with a slightly different user experience. Each website while have their own navigation system. Each website will have different ways to filter search results.
Some will allow you to copy excerpts, some won’t. Some will allow clips and force an appendage at the end (“Read More At XYZ” – I’m looking at you, ToI). But by the time I finish visiting the third website to read about the topic I wanted to – current lockdowns in Shanghai – I’m pretty much done out of sheer exasperation.
It shouldn’t be this hard!
Workarounds kind of exist. For example, I can add the RSS feeds to Feedly, or any other feed reader of your choice. If you’re not familiar with Feedly, or RSS readers in general, here is an old post about it. But the reason I say kind of is because most (if not all) newspapers will not provide the full article in the RSS feed. You have to click through to read the full thing.
Which, to be clear, is entirely understandable. User tracking, ads, and all the rest of it, I get it. But it does mean that Feedly isn’t a great way to keep track of all these articles in one place.
What I would really like is an app/service that aggregates all news sources in full in one place, and allows me to sign in to premium news sources via that app/service.
Does such a service exist? Or are there workflows that solve this problem?
III.39 Going forward, the focus of the Reserve Bank’s monetary policy stance during 2015-16 will be on fostering a gradual and durable disinflationary process towards the target of below 6 per cent by January 2016 in order to achieve the centrally projected rate of 4 per cent by the end of 2017-18. At the same time, the efficacy of the monetary policy transmission mechanism needs to improve since the pass-through of recent cuts in policy rate to the bank lending rate has been partial, reflecting constraints in transmission under the existing base rate system. Identifying the impediments in pass-through and implementing an alternative method, such as marginal cost based credit pricing or identifying an appropriate benchmark for the bank lending rate will be a priority for the Reserve Bank. In this regard, it is imperative to develop market based benchmarks by developing the term segment of the money market. Thus, liquidity support may have to be progressively provided through regular auctions of longer term repos with reduced dependence on overnight fixed-rate liquidity support. While doing so, it will also be important to dampen deviations of WACR and other money market rates such as CBLO rates from the repo rate in a narrow range. The Reserve Bank will continue to explore and augment its instruments of liquidity management, including standing deposit facility for absorption of surplus liquidity, as recommended by the Expert Committee.
(Students should also look up, by the way, what WACR and CBLO are). But back to our story: in 2016, the RBI was “continuing to explore and augment its instruments of liquidity management” – including a facility that we’ve all read a bit about this past week, the standing deposit facility.
First, what is liquidity management?
The “liquidity management” of a central bank is defined as the framework, set of instruments and especially the rules the central bank follows in steering the amount of bank reserves in order to control their price (i.e. short term interest rates) consistently with its ultimate goals (e.g. price stability).
In English: the central bank would like to try and control short term interest rates in the economy, in order to keep prices as stable as possible. The framework that allows them to do so is referred to as liquidity management.
So how does liquidity management work in practice, whether in India or abroad? In most cases, via the “repo” rate and the “reverse repo” rate. The first of these is the rate at which banks can borrow from the central bank, and the second of these is the rate at which the central bank can borrow from the banks. Here’s a good, basic, explainer.
So ok, we have a framework, and we now know how it works. Then why, Mandar asks, do we now have the SDF?
Which, of course, begs the question: what is the SDF?
At the last meeting, banks were offered a facility to park surplus liquidity through an auctioning system, which was in addition to reverse repo facility. The idea is to suck the surplus liquidity out of the system through the variable reverse repo rate. Now, RBI has regularized the same under the SDF window, which offers 3.75% interest rate for funds parked without any collateral backing. The SDF window will help banks earn a minimum return when they have surplus funds. The SDF rate of 3.75% would be the floor policy rate.
If banks in our country have excess funds (and right now, they most certainly do) what can the banks do with them? One option is to use the reverse repo mechanism and park these funds with the central bank. Or you could use the auctioning system, as the excerpt above explains. But now, in addition to both of these, you can also make use of the SDF.
The reverse repo in our country is right now at 3.35%, while the SDF will give you 3.75%. If you are a bank with excess funds, the RBI says you can give me these excess funds and I’ll pay you a) an interest rate of 3.35% if you use the reverse repo route OR b) I’ll pay you 3.75% if you use the SDF.
The naïve response to this is to go with option b). The not so naïve response is to ask “Wait, what’s the catch?”
Well, the catch is that reverse repo’s come with collateralization. When the central bank accepts excess funds from you, what it does in practice is it “sells” you securities, and “buys” them back at a slightly higher rate when it gives the funds back. “Buying them back” is a repurchase, and hence the terms repo (bank to central bank) and reverse repo (central bank to bank). When securities are involved, we say the deal is collateralized.
SDF? No collateralization.
Why? Well, there’s so much of excess liquidity floating about that the central bank was running out of securities to offer as collateral.
But ain’t this a rather risky thing, parking excess funds without collateralization? Well, this is the RBI we’re talking about. If you don’t trust the central bank, then what else is there boss? So no, we don’t need to worry about the lack of collateralization is the current stance, and all are ok with this.
So the effective rate is now 3.75, not 3.35?
Um no, it’s actually 4.00%. Remember those reverse repo auctions? Those have been averaging around 4%. So (and if you think this is confusing, join the club), if you’re a bank and have excess funds, the central bank now gives you three choices:
Good ol’ reverse repo, with collateralization, but 3.35%
About the title of today’s blogpost: I couldn’t resist, I’m sorry. The post is about something Noah Smith calls the “The Two Paper Rule”, about which much more below – but the title is courtesy Paul Krugman. About which, also, more below.
Noah wrote this post a while ago, in May 2017. His original post is about a Very Simple Idea that hopefully solves a Very Real Problem. Here’s the Very Real Problem:
I don’t know why academic literatures are so often referred to as “vast” (the phrase goes back well over a century), but it seems like no matter what topic you talk about, someone is always popping up to inform you that there is a “vast literature” on the topic already. This often serves to shut down debate, because it amounts to a demand that before you talk about something, you need to go read voluminous amounts of what others have already written about it. Since vast literatures take many, many hours to read, this represents a significant demand of time and effort. If the vast literature comprises 40 papers, each of which takes an hour to read, that’s one week of full-time work equivalent that people are demanding as a cost of entry just to participate in a debate! So the question is: Is it worth it?
Anybody who has suffered through a PhD knows the problem all too well. These days, anybody who has been asked to do a literature review for any paper knows the problem all too well. There is just too much to read.
And folks who want to make sure that uppity folks don’t get, well, too uppity always have a fail-safe defense at the ready: “Have you read all the relevant literature?”. There’s so much stuff that is being published about everything imaginable, that you’re never going to be able to get through even a fraction of it. Why, there’s even a law about it! And there’s a law about the law, which only goes to prove the point further, I suppose.
And here’s Noah’s Very Simple Idea to solve this Very Real Problem:
My solution to this problem is what I call the Two Paper Rule. If you want me to read the vast literature, cite me two papers that are exemplars and paragons of that literature. Foundational papers, key recent innovations – whatever you like (but no review papers or summaries). Just two. I will read them. If these two papers are full of mistakes and bad reasoning, I will feel free to skip the rest of the vast literature. Because if that’s the best you can do, I’ve seen enough. If these two papers contain little or no original work, and merely link to other papers, I will also feel free to skip the rest of the vast literature. Because you could have just referred me to the papers cited, instead of making me go through an extra layer, I will assume your vast literature is likely to be a mud moat. And if you can’t cite two papers that serve as paragons or exemplars of the vast literature, it means that the knowledge contained in that vast literature must be very diffuse and sparse. Which means it has a high likelihood of being a mud moat.
I love this idea, and for the following reasons. One, I have an immediate repartee whenever I’m attacked with the “But have you read the literature?” question. And it’s not just a repartee, but a genuine request that serves two purposes. The person asking the question had better be able to come up with at least two papers on the spot. There is otherwise not much point in they having asked the question! Second, assuming the person does come up with two papers I haven’t read, there’s more to read and more to learn.
But second, as a student, what a wonderful way to start building up a repository of papers about a series of subjects! Always ask your profs, no matter the subject, about the two papers worth reading about today’s topic, and keep a running list. (Hint: this is a great way to spend a summer!)
Third, and I’m personally very curious about the results in this case, what about asking young profs and old profs this very question about the same subject? If the answers differ, this is a field worth examining rather more deeply, for it obviously has evolved fairly rapidly. I did my PhD in business cycles, and trust me, the answers would never have been the same – by age, adherence to a particular school of macroeconomics thought, or even by nationality.
Paul Krugman loved the idea (Noah links to Krugman’s blog towards the end of Noah’s blog post, but the link seems to be down. The excerpt below is from Google’s cache):
What about trade? Autor/Dorn/Hanson on the China shock may not be the last word, but surely a revelatory approach. In a strange way, I’d put Subramanian and Kessler in the same category: realizing that this globalization is different from anything that came before is a big deal. I guess that in a way I’m pushing back against Noah’s nihilism (noahlism?) even while endorsing his method. I think there has been a lot of good economics done, even if there are also vast literatures not worth your time.
… and you now know, of course, where the title of today’s post comes from! What I think Krugman is getting at when he refers to his pushing back against Noah’s idea is that perhaps just two papers is too restrictive. And if that be the case, Tyler Cowen agrees:
The difference between total value and marginal value may be relevant. You might conclude a field literature has low total value, but the marginal value of learning more about that area still could be quite high. That is in part because muddy fields and results don’t spread so readily, and so dipping into the muck can yield some revelations. That is another reason why I would not offer the “two paper standard” as practical advice.
I have quoted only one of Tyler’s points (he’s got nine others), but in general, I don’t think we should be taking the two part of the two paper rule as being sacrosanct. In some cases you may need to read five, in some rarer cases ten. So long as the number is reasonable (and the standard will change), we can still live with the spirit of the two paper rule.
But if you are a student in college, the two paper rule is a good way to build up a repository of about fifty odd papers that you Really Should Have Read. Twenty five courses (roughly speaking), two papers each.
(C) GDP figures are “man-made” and therefore unreliable, Li said. When evaluating Liaoning’s economy, he focuses on three figures: 1) electricity consumption, which was up 10 percent in Liaoning last year; 2) volume of rail cargo, which is fairly accurate because fees are charged for each unit of weight; and 3) amount of loans disbursed, which also tends to be accurate given the interest fees charged. By looking at these three figures, Li said he can measure with relative accuracy the speed of economic growth. All other figures, especially GDP statistics, are “for reference only,” he said smiling.
This is an excerpt from the Wikileaks archive, and people familiar with modern economic history will know it all too well. This is, of course, the famous Li Keqiang index. If you prefer, you can read the original Economist article about it, although for once, the trademark Economist pun in the headline falls short of their typically high quality.
GDP measurements have always been tricky, and reading about GDP – it’s evolution, the data collection, the computation and the hajjar problems that arise from there – should be mandatory for any student aspiring to learn economics. Here’s a post from six years ago about some sources, if you’re interested.
But back to that excerpt above. What Li Keqiang was saying was that GDP statistics in China would often give a misleading picture, and he preferred to reach his own conclusions on the basis of other economic data. His preferred metrics were the ones mentioned in the abstract above: electricity consumption, volume of rail cargo and loans disbursed. Think of it this way: he’s really asking three questions. Is stuff being produced? Is stuff being moved around? Is stuff being purchased?
But what about covid times? Do these measures stand up, or do we need new proxies for GDP?
The variant’s speed also means that China’s economic prospects are unusually hard to track. A lot can happen in the time between a data point’s release and its reference period. The most recent hard numbers on China’s economy refer to the two months of January and February. Those (surprisingly good) figures already look dated, even quaint. For much of that period, there was no war in Europe. And new covid-19 cases in mainland China averaged fewer than 200 per day, compared with the 13,267 infections reported on April 4th. Relying on these official economic figures is like using a rear-view mirror to steer through a chicane. For a more timely take on China’s fast-deteriorating economy, some analysts are turning to less conventional indicators. For example, Baidu, a popular search engine and mapping tool, provides a daily mobility index, based on tracking the movement of smartphones. Over the seven days to April 3rd, this index was more than 48% below its level a year ago.
But as the article goes on to say, this metric will tell you about movement across cities. But metro traffic gives you an idea of intra-city mobility, as do courier company express deliveries (and we did some very similar exercises in India during the lockdowns, of course. Here’s one example for Pune district.)
But the point isn’t just to come up with what else might be useful as GDP proxies. A follow-up question becomes equally important: do the GDP statistics make sense? As the Economist articles says, good numbers for metrics such as investment in fixed assets are hard to square with declines in steel output. The article contains many other such examples, and what you should take away as a student is your ability to develop a “smell” test for a given economy. Don’t take the reported numbers at face value, but “see” if they seem to be in line with other statistics about that economy.
I really like this article as an introduction to this topic because it also hints at how statisticians need to be especially careful about comparing data over time. Weekly declines might happen because of festivals, bad weather or a thousand other things, which may of course be going on along with pandemic induced lockdowns. Teasing out the effects of just one aspect isn’t an easy thing to do.
And finally, think about how you can apply this lesson in other domains! Should an interviewer look only at marks, or try and figure out other correlates. Or, as Mr. Keqiang puts it, are marks “for reference only”? What about quarterly earnings reports? Press releases? Smell tests matter, and the earlier you start developing them, the better you get at detecting, and calling bullshit.
And finally, the concluding paragraph from the article we’ve discussed today:
To help avoid some of the traps lurking in these unconventional indicators, Mr Lu and his team watch “a bunch of numbers, instead of just one”. In a recent report he highlighted 20 indicators, ranging from asphalt production to movie-ticket sales. “If seven or eight out of ten indicators are worsening, then we can be confident that GDP growth is getting worse,” he says. Right now, he thinks, the direction is clear. “Something must be going very wrong.”
Regular readers must be sick and tired of hearing me say this, I suppose, but please: read blog posts written by Gulzar Natarajan!
Especially so if you happen to be a student of economics. The art of taking a complex topic, asking simple questions about it, marrying them to the appropriate economic concepts that will help in the analysis, and reaching a cogent, well argued conclusion is a rare, rare skill. And Gulzar Natarajan possesses it in spades!
The demand supply gap is stark. About 1.6 million students appeared for the National Eligibility cum Entrance Test (NEET) in 2021, of which only 88,120 make it to the 562 public and private medical colleges. That’s 19 applicants for every seat. Those numbers are now 89,875 and 596. How do you analyse this market? What will be the impact on seat prices due to supply changes of medical seats? How will the supply side react to this situation of large numbers of Ukraine returned students? What will be the profile of supply side?
These are not hard questions to frame. In fact, I would argue that most of us will be able to frame these questions even without having studied economics formally. But that being said, framing them this simply and concisely takes years of practice.
He identifies four main problems that we need to deal with:
The major constraint is the source of quality faculty
As he puts it, “In an acutely supply deficient market, the limited marginal supply is likely to bid up the medical seat prices even more”. I would only add one word to this sentence, between the words marginal and supply: quality. It’s not so much about the supply going up as it is the degree to which high quality supply goes up.
Ah, but alas, that brings us to an even more difficult question: quality as it truly exists, or quality as perceived by prospective students and by society? I studied in Fergusson College in Pune, so I have a moral right to ask this question. And that’s what he means by the phrase “lemon problem“. If you’re wondering why this is known as a lemon problem, take a look at this.
His preferred solution is having the government step in to augment the supply, using government district hospitals and some area hospitals. This, he says, is preferable to the public-private-partnership (PPP) model. I don’t dispute the assessment of the PPP model, and its shortcomings. But I’m curious about why he would say that government institutions are always going to assure a certain basic minimum assured quality. Is this necessarily true, even in a relative sense? And if so, why?
And the concluding paragraph is at once depressing and optimistic:
Finally, this is a teachable example on the reality that though many problems have no immediate solutions, we try to solve them. Part of it is about wanting to do something and also be seen doing something. This is a human reflex and a political economy compulsion. Bridging the demand-supply gap in medical education is one such problem. Given our context and constraints, it’s very unlikely that we can bridge this gap in the foreseeable future. Like with other similar problems like affordable housing, agricultural productivity, or traffic congestion, we can only create the conditions required for its mitigation and gradual easing.
Josiah Willard Gibbs is a name likely to be unfamiliar to many people today. I must be honest and tell you that I myself wasn’t too familiar with it, and needed a couple of searches on Google to help me out.
I was familiar, though, with a quote that he is responsible for. It is a quote that appears in a book that I am not particularly fond of, and we will get into my reasons for my dislike in a bit. Here is the quote though, in all of its four word glory:
“Mathematics is a language”
I was reminded of the quote when I read Dilip D’Souza’s lovely little rumination on just this question: whether mathematics ought to be considered a language or not. Dilip, in his essay, focuses on whether mathematics was invented or discovered, and says it is perhaps a bit of both. As an amateur student of mathematics, I cannot answer the question definitively one way or the other, and I’m happy to go along with his best guess.
But to go back to Dilip’s original question: is mathematics a language? Well, if it is one, it certainly isn’t one of the easier ones. Back in college, if you had given me the choice to study irregular verb conjugations in French or learn mathematics better, I would undoubtedly have chosen the former.
But over time, my attitude towards mathematics has changed, and I think for the better. The older I get, the more I am inclined to agree with Gibbs: it really is a language, and a beautiful one at that.
It is a language with beauty, as Euler’s identity makes abundantly clear. It is a language pregnant with mystery. And not just the kind of mystery that one associates with school-time tribulations! Try finding out what the sum of all natural numbers is, for example. And then wonder how Ramanujan thought the answer to be self-evident. If that doesn’t strike you as a mystery, nothing will.
And as with all things mysterious and beautiful, the more time you spend with mathematics, the more mysterious and beautiful it becomes. Dilip hints at the wonder that is Bolyai and Reimann geometry in his essay, and both are worth learning more about. But why stop there? Once you find yourself going down the rabbit-hole of discovering mathematics for its own sake, you find yourself in a wonderland that makes Alice’s look positively quotidian.
But as with all languages, so also with mathematics. Your love and affinity for it is very much a function of the way you were introduced to it. If your introduction to it was through dull and dreary classroom exercises, carefully designed to suck every single trace of fun out of the experience, then you are unlikely to have fallen in love with it.
And that, I suspect, is the case with most of us. Myself included, to be clear. But I was lucky. I was reintroduced to the subject by a professor of mine, who introduced to me the beauty that lies in wait beneath the seemingly impenetrable surface of the subject. And over the years, I have fallen in love with the language.
Noam Chomsky is famous for hypothesizing that we are all born with an innate ability to understand language – any language. Now, some languages may well be more difficult than others, but the more time I’ve spent with the subject, the more I have come to believe that Chomsky may well have a point. Mathematicians such as Steven Strogatz, Edward Frenkel and Grant Sanderson have helped me appreciate the language more.
And while I may never be able to compose even a limerick in this language, let alone author a magnum opus, the more I learn about it, the more I am able to appreciate the works of those who have gained some mastery over it.
A brief coda:
Gibbs’s quote, with which I started this essay, comes as an epigraph in a book that I don’t particularly like. As any economist of a certain age will tell you, that book is The Foundations of Economic Analysis, written by Paul Samuelson.
The reason I do not like it is because I think the book helped push the study of economics a little bit too far in the direction of mathematical analysis for its own sake. Mathematics helps make economic analysis more tractable, and more amenable to logical analysis, but it is the dose that makes the poison. The study of economics may have become more tractable because of mathematics, but in my opinion, the mathematical formalism has been taken too far.
As the wise Kenneth Boulding put it: “”Mathematics brought rigor to economics. Unfortunately, it also brought mortis.”
But make no mistake, this is at best a criticism of how economics as a field has developed over the years, if that. Samuelson himself admitted as much, and it is a sign of the greatness of the man that he did it in 1952(!). 1
For mathematics, today, I have nothing but gentle love and affection, and above all, a sense of awe and wonder.
And I wish and hope for more of the same for you!
Economic Theory and Mathematics–An Appraisal Paul A. Samuelson The American Economic Review Vol. 42, No. 2, Papers and Proceedings of the Sixty-fourth Annual Meeting of the American Economic Association (May, 1952), pp. 56-66 (11 pages). [↩]
My way of unwinding at the end of the day is to watch YouTube videos. I suspect I’m not the only one, and yes, I’m well aware of how it’s not the best thing to do before one falls asleep, but it’s a habit that has, well, stuck.
So it goes.
Yesterday, one of the videos I ended up watching was this one:
I came across Veritasium thanks to a recommendation I received sometime last year, and if you aren’t familiar with this channel, I strongly encourage you to look it up. You might also want to read up about the person behind the channel, Derek Muller.
These waves were detected at the Laser Interferometer Gravitational-Wave Observatory. They have a shorter name, thankfully: LIGO.
The design and construction of LIGO was carried out by a team of scientists, engineers, and staff at the California Institute of Technology (Caltech) and the Massachusetts Institute of Technology (MIT), and collaborators from over 80 scientific institutions world-wide that are members of the LIGO Scientific Collaboration.
Here’s just one of many astounding facts from the LIGO website:
At its most sensitive state, LIGO will be able to detect a change in distance between its mirrors 1/10,000th the width of a proton! This is equivalent to measuring the distance to the nearest star (some 4.2 light years away) to an accuracy smaller than the width of a human hair.
Here’s what I found remarkable, as a student of economics: even if one assumes that there was only one person from each of these 80 scientific institutions that worked on this project, it still means that there were 80 people whose job it was to create really, really long tunnels (four kilometers in length!) that would have one trillionth of the normal atmospheric pressure, so that they could detect almost imperceptible gravitational waves that started their journey 1.3 billion light years away. If all this sounds mind-boggling, well, it is.
But think about those 80 people for a minute. Our civilization has become wealthy enough, over many millennia, that we’re able to say to those eighty people that they can spend a significant chunk of their careers on building long tunnels to try and check on barely detectable phenomena that actually took place a really, really long way away.
Was there a time in our past when humanity could afford to dedicate human labour, money and other resources to a pursuit such as this one? You and I may have different opinions about whether we should or not (and I think we should), but I think we can all agree that it is remarkable that we can.
Homo sapiens sapiens is the only animal that engages in elaborate task-sharing—the division of labor as it is sometimes known—between genetically unrelated members of the same species. It is a phenomenon as remarkable and uniquely human as language itself. Most human beings now obtain a large share of the provision for their daily lives from others to whom they are not related by blood or marriage.
Pg 4, Introduction, The Company of Strangers, by Paul Seabright
And because most human beings now obtain a large share of the provision for their daily lives from others to whom they’re not related by blood or marriage, they are free to do other things with their time. Some of us write blogs on economics, while others build really, really large tunnels to detect barely perceptible gravitational waves. Others create videos about these really long tunnels. But none of these proposals would have gone down well in earlier times, because there were more urgent and pressing tasks at hand, such as growing enough food for everybody to be able to eat.
And so while the completely amateur fan of modern physics in me appreciated learning more about LIGO, the economist in me was struck by how impressive a fact it was they we have the ability to dedicate so much resources to the development of this laboratory.
Again: you and I may have different opinions about whether or not we should be building these laboratories, or sending people to the moon (or Mars, soon enough!), or everything else that we get up to these days. But the fact that we can is truly remarkable.
And don’t forget Derek Muller! Isn’t it remarkable that I, sitting in the comfort of my living room, can cast a video off of my phone on to my television, and watch an excellent video about the LIGO laboratory without having to pay a cent to Derek?
I only learnt of Derek’s existence last year, and I can guarantee you that he is blissfully unaware of mine. And yet, the society we live in has made it possible for me to learn about his work, and this video in particular. I pay YouTube Rs. 189 every month so that I and five other members of my family can watch YouTube videos without being bombarded by ads, but that money apart, I had to pay nothing more to enjoy this video – and by all accounts, Derek is able to do fairly well for himself by putting videos out there for people to watch and learn from.
How did we get from hunter-gatherer societies to here? How did division of labor help? Was agriculture a wonderful, welcome development, or was it all a big fat mistake? What about the development of kingdoms, the advent of religions, the desire to educate our young, the development of the study of physiology and eventually health and medicine, and so, so many other things? What explains how and why we were able to do all of these things, and so many more? If we could reset the clock and play the movie all over again, would all of these things happen, or not? Could we do an even better job? If so, how?
Economics is about so much more than graphs and diagrams and equations (that stuff is important too, of course, but there is so much more to this field than just that).
Every now and then, economics is also about taking a step back while watching a wonderfully well made video, and just reflecting on how far we’ve come as humanity. Yes, there is a lot that remains to be done, and yes, we’ve often taken one step forward and two steps back. And yes, we’ll probably figure out how to take ten steps back in the near future.
But for the moment, I find it remarkable that at least eighty people got together and built a pair of really, really large tunnels to detect Very Small Movements.
That’s division of labor, that’s economics, and it is a truly remarkable thing to think about.
And it’s just one of many, many reasons to study economics.