Thanks for choosing to visit this page, and my blog.
My name is Ashish, and I'm a bit of a wanderer when it comes to vocations. I'm not quite sure what I want to do with my life, and I'm not even sure that it is any one single thing.
But I know I like knowing about a lot of things, as many as possible. I know I like bike rides, I know I like the city I was born (Pune) and I know I like reading and writing.
Feel free to drop me a line if you feel like a chat - I'll look forward to it.
Office hours on Zoom, for one, which strikes me as a pretty good idea too.
I think I’m going to keep my office hours remote and on zoom—make them mandatory for students I think I need to see. Calling people into the office if they aren’t showing up for office hours—that seems a little heavy-handed to me. Phone calls with people you do not already know—that is not terribly effective. But zoom! It is much better than a phone call, and does not (or does not any longer) seem too heavy-handed.
But his other idea is something I would love to do, but have always failed at:
The other innovation I want to adopt is for courses in which each week is a book. Having the group “discuss” the book for an hour, and then call up the author on zoom—that seems to me to be a very good innovation. It is Barry Eichengreen’s. It is a wonderful thing. It should become the rule rather than the exception in the future.
I have tried this in multiple ways over the years in my classes, but nothing has really worked. My utopian classroom would be one in which every single student walks in having read the prescribed book, and we run out of time while discussing different aspects of the book.
What usually ends up happening is an involved discussion with the three students or so who have read the book, while the rest of the class listens in politely for as long as they can bear to. I should be clear – I do not mandate attendance in my classes, and I don’t blame the students for not having read the book – but I sure wish they had!
From the Sokratic point of view, the purpose of the entire educational establishment can only be to create opportunities for the Dialectic to manifest itself—and question and answered dialogue between teacher and student, between student and student, and between student and figment of the student’s imagination. Good educational systems maximize those opportunities. Bad educational systems do not.
Education is about conversations, and conversations cannot happen at scale. My best learnings have happened over relaxed conversations with professors in their offices, over cups of coffee, and on some especially delightful occasions, over mugs of beer – but not in a classroom.
But how to have those in-depth conversations with as many students as possible, as often as possible, without making the experience too expensive for all concerned is the trillion dollar question in higher education, and I don’t think we’re anywhere close to solving it.
But to circle back to the original excerpt, office hours on Zoom might be a good place to start.
Also, if you teach economics, and are looking for a wonderful syllabi to discuss in depth with your students, you couldn’t do much better than How to Change the World, taught by Chris Blattman.
I joined Genpact as a data analyst in the year 2006, fresh out of college. Genpact was one of the few firms that had visited our campus for recruitment that year, and I was lucky enough to be “placed” along with three other batchmates.
My starting salary? 3.75 lakh rupees, or INR 375,000/-.
I remember thinking how princely an amount this was back then, and I couldn’t for the life of me figure out how I could possibly spend whatever amount I got on a monthly basis. Of course, life very quickly taught me the same lesson that it has taught everybody else – so it goes.
But the reason I bring this up is because of a Finshots write-up that’s been shared with me a fair few times this past week:
₹3.6 lakhs That was the typical salary paid out to a fresher in 2010 when they entered one of India’s top IT companies. Think — TCS, Infosys, HCL, and Wipro. A decade later, they were still being paid roughly the same sum. So technically, if you were to take into account inflation, freshers in 2020 were far worse than their counterparts back in 2010. And the salary hikes weren’t particularly enticing too.
I’m not sure where they got the data from, but anecdotally, this sounds about right. I’ve been in charge of placements at the Gokhale Institute, where I work, for about four years now, and while we’ve managed to get firms on campus that pay substantially more, starting salaries for most firms at the entry level are at about this number, more or less.
Which, as the Finshots newsletter goes on to point out, is ridiculously low for 2022. And why might this be so?
Well, two ways to think about it. First, as the newsletter itself points out, it’s simple economics. There’s excess supply.
You see, India produces roughly 1.5 million engineering graduates every year. And IT firms hire around 200,000 people every year. This means the effective pool of applicants remains sizeable and IT companies continue to be spoilt for choice. Even others attributed it to cartelization, alleging that IT companies banded together to deliberately suppress salaries. But despite what you want to believe, the bottom line remains the same — Entry-level salaries simply did not budge a lot in the past decade and IT graduates were getting a bit angsty.
It’s worth learning more about economics to help yourself understand what terms such as excess supply, homogenous goods, elasticity, cartelization, inefficient labor markets mean, because they help you understand why starting salaries are so low. Search for these terms online, on this blog, or begin with MRU videos, but help yourself by learning about these concepts if you are unfamiliar with them.
Or watch AIB videos!
If you ask me, do both. It’s a great way to learn econ theory and have a bit of fun.
But as the newsletter goes on to point out, things are changing, and they say this is because of three reasons: increased attrition, greater recruitment by start-ups and burnout from the pandemic. Each of three, I should add are inter-related, but I broadly agree with their explanation.
Average salaries are up, firms are paying more, and it’s a great time to be out there looking for a job. But, as the conclusion of the newsletter points out, it would seem that there is a recession looming on the horizon, and that may drag starting salaries back to square one.
How does one find out about the probability of a recession? Well, there’s lots of ways, but without being too meta, keep an eye out for the kind of questions that are being asked about the macroeconomic situation:
One data point doesn’t add up to much, I’ll admit, but there’s other ways to keep yourself abreast of the situation:
And when I say kids, I’m not exaggerating either. The youngest was in the 8th grade or standard, and the oldest was just about to enter their tenth grade/standard. Anyways, a lot of fun was had, and I hope I get to do this again.
I taught the kids two different one week long courses. One was on economics, and the other was on statistics. But along with these two courses, there were lots of other courses on offer, and one of them happened to be on AI/ML, taught by the excellent Navin Kabra. People like Navin can single handedly present excellent arguments for remaining on Twitter, and I would strongly recommend that you follow him if you are on Twitter.
During one of the many excellent conversations I had with him, he brought up an essay, and asked me if I had read it. The title is “Camels and Rubber Duckies“, and I hadn’t read it. But with a title like that, how could I keep away from it?
It’s a wonderful read, and I would strongly encourage you to read it, no matter how good your microeconomics basics are. It is engagingly written, liberally sprinkled with oddball humor, and explains a lot of concepts in microeconomics without making the subject boring. And trust me, this is difficult to do.
Here are my notes for having read it:
Follow along with a spreadsheet and try and run the simple exercises yourself.
He actually uses the word Visicalc, which is a lovely little rabbit hole in its own right
The old Excel charts generate so much nostalgia. I’d forgotten the dull as death grey backgrounds, and the horribly jarring pink and blue colors.
The law of demand, the calculation of profits, the maximization of profits, the meaning of consumer surplus, segmentation, inelastic demand, coupons, opportunity costs – and best of all, real world problems that occur when it comes to pricing software, all have been wonderfully explained.
Focus groups and market research are also explained intuitively
I realize this is a post from 2004, but he talks of RSS feeds and RSS readers! I shall use this opportunity to once again lament the passing away of Google Reader, the best social networking site cum RSS reader there ever was.
Besides writing about camels and rubber duckies to help explain economics, he’s also come up with some products you’ve heard of, such as Trello, or Stack Overflow. Joel Spolsky is a person you want to learn more about.
That’s the very last sentence of a thought-provoking column by Nitin Desai. The column is about why the NITI Aayog (in Nitin Desai’s opinion) hasn’t done all of what was hoped of it, and what needs to change for some of these hopes to be realized.
But for us to reach the end of this column, we need to start somewhere, and we’ll start with the setting up of the Planning Commission.
The Indian planning project was one of the postcolonial world’s most ambitious experiments. It was an arranged marriage between Soviet-inspired economic planning and Western-style liberal democracy, at a time when the Cold War portrayed them as ideologically contradictory and institutionally incompatible. With each Five-Year Plan, the Planning Commission set the course for the nation’s economy. The ambit ranged from matters broad (free trade or protectionism?) to narrow (how much fish should fisheries produce to ensure protein in the national diet?). The Commission’s pronouncements set the gears of government in motion. Shaping entire sectors of the economy through incentives, disincentives and decree, the Planning Commission’s views rippled across the land to every farm and factory. Despite this awesome power, economic planning in India was considerably different from the kind practised in communist regimes. The Planning Commission was reined in by democratic procedure that required consultation with ministries in an elected government, with people’s representatives in Parliament—and ultimately with the popular will—through citizens voting every five years.
Menon, Nikhil. Planning Democracy (p. 9). Penguin Random House India Private Limited. Kindle Edition.
That’s from a book I’m currently reading (and thoroughly enjoying), Planning Democracy. There’s a lot to like about the book, and I hope to write a full review once I’m done, but for the moment, think about just the title. There’s a (hopefully healthy) tension implicit in it, because as the excerpt above puts it, the Planning Commission was to be reined in by democratic procedure.
What was it supposed to do? Further on in the same chapter from the book I have just quoted is a nice compact description of what was supposed to have happened:
Its potency stemmed from its authority to draw up an economic roadmap for the country and back it with all the resources and policy instruments available to the Government of India.
Menon, Nikhil. Planning Democracy (p. 21). Penguin Random House India Private Limited. Kindle Edition.
That is, there are two separate but interlinked things worth noting: it had to develop an plan of economic development for a newly independent India, and in order to do so, it had the backing in terms of resources and policy instruments. By the way, there is a reason the word “resources” has not been qualified with a word like financial – the back was not just financial, but also political, given the presence of the Prime Minister and other cabinet ministers as members.
The story of how the Planning Commission evolved, struggled, and refined itself over time (not always successfully, it should be mentioned) is a fascinating one, but not one that we can cover in a single blog post, alas. But long story (very) short, the Planning Commission came to an end in 2015:
Born the same year, Modi and the Planning Commission shared another milestone together. In his first Independence Day address as India’s leader, Modi declared that the Planning Commission had once merited its place and made significant contributions. Now, however, he believed it had decayed beyond repair. ‘Sometimes it costs a lot to repair an old house,’ he said, ‘but it gives us no satisfaction.’ Afterwards we realize ‘that we might as well build a new house’, Modi explained with a smile. He would build it by bulldozing a decrepit structure and raising a shiny new one, the NITI Aayog (National Institution for Transforming India).
Menon, Nikhil. Planning Democracy (p. 8). Penguin Random House India Private Limited. Kindle Edition.
And how has the NITI Aayog done?
But despite progress in these areas, some 7 years since the establishment of NITI Aayog, questions are being raised as to whether India can continue to function without medium-term planning. Annual budget allocations are made by the Finance Ministry to meet various investment goals and objectives but without a well-defined plan. NITI Aayog’s advice is also not taken seriously by state governments as it comes without resources. Some feel that NITI Aayog should have resources it allocates to address development imbalances and that the Ministry of Finance is naturally focused on budgetary management rather than development outcomes.6While no one wants a return to the old Planning Commission, a more involved and competent NITI Aayog, with a stronger voice is clearly needed.
The idea itself isn’t all that new. Back in 2019, Vijay Kelkar had given a speech in which he proposed “NITI Aayog 2.0”:
It should rather strive to be a think tank with “praxis” possessing considerable financial muscle and devote its energies to outline coherent medium and long term strategy and corresponding investment resources for transforming India. Towards this, my preliminary study suggests that the NITI Aayog 2.0 will annually need the resources of around 1.5% to 2% of the GDP to provide suitable grants to the States for mitigating the development imbalance. These formulaic annual grants, whether capital grants or revenue grants for the relevant CSS will need to be conditional to ensure that (1) outcomes are commensurate and (2) it discourages an individual State to adopt policies that have negative policy externalities, e.g., creation of populist subsidies and thus avoid race to the bottom. Such presence of “negative policy externalities” we notice often, e.g., the provision of free “electricity,” irrigation water subsidies, etc. “Gresham’s Law” seems to be relevant not only for the currency markets alone!
All of which eventually gets us back to the column that we started with, by Nitin Desai:
The real problem of strategy formation for development is that it is not being done. The NITI Aayog has produced some vision documents; but they are not agreed strategies formulated after widespread consultations with experts and discussion with the states. The word “niti” in the name of this organisation is an abbreviation for National Institution for Transforming India. This task requires looking a level above the designing of programmes to a strategy from which programmes must be derived. A grand strategy for development must spell out the opportunities and threats faced by the key objectives of development which are growth, equity and sustainability. It must then identify the changes in the role of the public and private sector, shifts in global economic alliances and policy shifts that are required to maximise benefits from opportunities and manage risks from threats. The time frame for a grand strategy has to be long-term but the more specific strategies derived from it must take into account short- and medium-term challenges that the country faces.
We need, that is to say, a NITI Aayog that focuses on not just reporting what has been (or is being) done, but also on explaining what needs to be done, over what time period, and why, along with some pointers towards what risks we might encounter. Or as Nitin Desai puts it, “The new Vice-Chairman, Suman Bery, must bring in the talent required and launch a process of broad-based consultation, particularly with the states, to secure a broad national consensus on a long-term growth strategy. Specific programmes must be based on the implementation of this strategy.”
Easier said than done, of course, but this is where NITI Aayog needs to go next.
This has been doing the rounds on my Whatsapp groups recently, and maybe you’ve seen it too:
Mildly funny, but the story behind it is quite something.
Bots have been a problem for many many years – much before Elon Musk thought of buying Twitter. And as long as sixteen years ago, folks were trying to solve the problem of stopping bots from signing up for services. So how does a computer make sure that the entity trying to sign up for a service actually is a human?
Well, by showing images such as these, and asking the entity on the other side to make out what the word is:
We’ve all been subjected to a variant of this, haven’t we.
Now, one of the folks who came up with this system – it’s called Captcha (say it out aloud and you can figure out the reason behind the name) ran the numbers:
And at some point I did a little back of the envelope calculation about how many of these were typed by people around the world, and it turns out the number I came up with was about 200 million. So about 200 million times a day somebody would type one of these CAPTCHAs, and that’s when I started thinking, “I wonder if we can do something with this time.” Because the thing is each time you type one of these, not only are they annoying but also they waste about ten seconds of your time, and if you multiply ten seconds by 200 million, you get that humanity as a whole is wasting like 500,000 hours every day typing these annoying CAPTCHAs.
Work that will gladden the heart of any economist. And so the guy who did these back of the envelope calculations tried to figure out how these 500,000 hours might be put to better use. Thus was born reCAPTCHA. And the idea was a very, very good one.
When you digitize, or scan books for the first time, there will be books with old fonts, outdated fonts. And therefore there will be a fair few words that computers will not be able to decipher. And not just books, this is also true of newspaper archives.
So if we have scanned books and newspaper archives that are non-machine-readable, and we have humans spending 500,000 hours every day… what about connecting the two, and having humans read these words, one at a time?
Scanned text is subjected to analysis by two different OCRs. Any word that is deciphered differently by the two OCR programs or that is not in an English dictionary is marked as “suspicious” and converted into a CAPTCHA. The suspicious word is displayed, out of context, sometimes along with a control word already known. If the human types the control word correctly, then the response to the questionable word is accepted as probably valid. If enough users were to correctly type the control word, but incorrectly type the second word which OCR had failed to recognize, then the digital version of documents could end up containing the incorrect word. The identification performed by each OCR program is given a value of 0.5 points, and each interpretation by a human is given a full point. Once a given identification hits 2.5 points, the word is considered valid. Those words that are consistently given a single identity by human judges are later recycled as control words. If the first three guesses match each other but do not match either of the OCRs, they are considered a correct answer, and the word becomes a control word. When six users reject a word before any correct spelling is chosen, the word is discarded as unreadable.
The system has evolved since then, and this version of reCAPTCHA (known as reCAPTCHA v1) is no longer around. We now have reCAPTCHA v2 and reCAPTCHA v3, and if you’re curious, you can learn more about it here.
But I really like the idea behind reCAPTCHA v1, even though it is no longer in use. It used the opportunity presented by a necessary but time-consuming activity by matching it with a necessary but money-and-effort-consuming activity, to the benefit of all concerned.
Turns out the person who came up with the idea has been thinking about computers and human brains as being complementary to each other for a fairly long time, even writing a PhD thesis about it:
Von Ahn’s Ph.D. thesis, completed in 2005, was the first publication to use the term “human computation” that he had coined, referring to methods that combine human brainpower with computers to solve problems that neither could solve alone. Von Ahn’s Ph.D. thesis is also the first work on Games With A Purpose, or GWAPs, which are games played by humans that produce useful computation as a side effect. The most famous example is the ESP Game, an online game in which two randomly paired people are simultaneously shown the same picture, with no way to communicate. Each then lists a number of words or phrases that describe the picture within a time limit, and are rewarded with points for a match. This match turns out to be an accurate description of the picture, and can be successfully used in a database for more accurate image search technology. The ESP Game was licensed by Google in the form of the Google Image Labeler, and is used to improve the accuracy of the Google Image Search. Von Ahn’s games brought him further coverage in the mainstream media. His thesis won the Best Doctoral Dissertation Award from Carnegie Mellon University’s School of Computer Science.
And here’s the kicker: the same idea, human computation, is at work another venture that Louis von Ahn has started. You may have heard of it, it has got this cute little green owl as its mascot:
So the way this works is whenever you’re a just a beginner, we give you very simple sentences. There’s a lot of very simple sentences on the web. We give you very simple sentences along with what each word means. And as you translate them and as you see how other people translate them, you start learning the language. And as you get more advanced, we give you more complex sentences to translate. But at all times, you’re learning by doing.
Both reCAPTCHA v1 and Duolingo have different business models now, of course. But as students of economics, its’s worth appreciating the idea of complementarity between humans and computers, and the idea of turning a necessary but time intensive activity into a socially useful one.
It may be a funny Whatsapp forward, sure, but as it turns out, there’s quite a story behind it. No?
Here is Max Roser’s introduction of himself from a Reddit AMA (Ask me Anything) he had done a while back:
“Hi Reddit! My name is Max Roser. I visualize global development data on OurWorldInData.org, a free online publication on how living conditions around the world are changing.
Now I am working with a great team and we want to cover global development as broadly as we can to show how our world is changing. Our World in Data now includes data and research on global health, violence, poverty, inequality, economic growth, environmental changes, food and agriculture, energy, technological change, education and more specific topics.
While much of the news is focussing on what happened yesterday or even what is currently “breaking news”, I think that many of the very important changes, which fundamentally reshaped the world that we are living in, happen very slowly and persistently over the course of decades or centuries. On ‘Our World in Data’ we don’t report the ‘breaking news’ and instead zoom out to show the slow trends that dramatically change our world.
Other than that I am a researcher – mostly focusing on inequality and poverty – at the University of Oxford.”
And Our World in Data? Check out their About page.
But better still, consider this extract:
“Why have we made it our mission to publish the “research and data to make progress against the world’s largest problems”?
At the heart of it is a simple truth. When we look around us, it is clear that the world faces many very large problems:
Every year 300,000 women die from pregnancy-related causes, this means that on any average day 830 mothers die
The majority of the world – 65% – lives on less than $10 per day. And almost 10% live in ‘extreme poverty’, they live on less than $1.90 per day.
The world deforested 47 million hectares of forest in the last decade, that’s an area the size of Sweden.
60 million children of primary school age are not in school.
Almost a quarter of the world population – 23% – live in autocratic regimes.
14% of the world’s adults do not know how to read and write.
And 3.7% of all children die before they are five years old. This means that 5.2 million children every year and on any average day the world sees 14,200 child deaths.
This is a list of terrifying problems. And as we don’t hear much that would tell us otherwise, it is easy to be convinced that we can’t do anything about them. Even in the extensive 24/7 news cycles we hear little that suggests it would be possible to make progress against these problems. The same is true for our education — questions like how to end hunger, child mortality, or deforestation are rarely part of the curriculum.
As a consequence it is not surprising that many have the view that it is impossible to change the world for the better. For many large problems the majority in fact believes that they are getting worse.
This however, is not the case. We know that it is possible to make progress against these large problems, because we have already done so.”
How do we know that we have already done so? Take a look at this one chart:
Click on that little toggle next to the world “Relative” in the chart, and the chart becomes even better. Here’s a simple way to think about it: Max Roser is a person who wants to help you understand two things:
Take the glass half full view, because the world is genuinely becoming better over time.
But don’t for a single moment forget the fact that the world needs to become a lot better, and for that to happen, we need to move faster.
Or, in much more eloquent terms:
Because our hopes and efforts for building a better future are inextricably linked to our understanding of the past, it is important to study and communicate the global development up to now. Studying our world in data, and understanding how we overcame challenges that seemed insurmountable at the time, should give us both confidence and guidance to tackle the problems we are currently facing. Living conditions can be improved, we know from the past that they already have been. For each of the problems we face today we need to also address the difficult question of whether and how we can make progress in the years ahead.