On Confidence

Around mid-November 2020, I spoke to a bunch of macroeconomics students at IIM Ahmedabad on data in economics. After I had spoken, one of the questions asked was how can we use data to say things with absolute certainty (or something along similar lines).

My simple straightforward answer to the question was that we can’t. Over the years, economists had ended up portraying their subject as a science simply because it has a lot of mathematical equations built into it. But macroeconomics was always more of an art. Hence, we could say things with a reasonable amount of confidence, but never with total confidence.

I don’t think the student was convinced about what I said. And I don’t blame him for it because in the world that he lives in, economists, investors, analysts, politicians and just about everyone speaking to the world at large, is saying things with total confidence.

Let’s take the case of economists. Their economic growth forecasts are made to the precision of a single decimal point.

If we talk about investors, they forecast a stock market index reaching a particular level in a certain amount of time, with total confidence.

Analysts forecast the price of a stock or a commodity reaching a certain level at a certain point of time.

And let’s leave politicians out of this. Untangling their confidence levels will take a book.

The trouble is all this confidence comes in a world that keeps rapidly changing, where if we stick to our ideas all the time, we will largely turn out to be wrong.

As Dan Gardner writes in Future Babble—Why Expert Predictions Fail and Why Believe Them Anyway:

“The simple truth is no one really knows, and no one will know until the future becomes the present. The only thing we can say with confidence is that when that time comes, there will be experts who are sure they know what the future holds and people who pay far too much attention to them.”

And people pay far too much attention to experts who predict/forecast/comment confidently simply because confidence convinces. The audience is looking for a buy in and nothing helps get that more than the confidence of the expert talking.

Also, in these days of the social media, many a time we are simply looking for a confirmation of something that we already believe in. If the expert ends up saying something along those lines, he tends to become our go to man. Our echo chambers are really small.

Let’s take the case of the investor Rakesh Jhunjhunwala, a man known to make confident bold statements when it comes to the Indian economy and the stock market. He recently forecast that India will overtake China in the next 25 years. As he put it: “You may call me a fool… but I can tell you one thing – India will overtake China in the next 25 years.”

The media and the investors as usual lapped it up, without putting that simple question to him: How?

The Indian gross domestic product (GDP) in 2019 was at $2.94 trillion. And that of China was at $11.54 trillion (World Bank data, 2010 constant US dollars). What this means is that if Chinese GDP stagnates at its current level for the next 25 years, India still needs to grow at 5.62% every year for the next 25 years to get where China currently is.

So, the chances of something like this happening are minimal, given the current state of things. But Mr Jhunjhunwala might know something that ordinary mortals like you and I, probably don’t.

The funny thing is that the Big Bull, as the media likes to call him, has made similar such forecasts in the past, which have gone horribly wrong. In October 2007, he had forecast that the Sensex will touch 50,000 points in the next six to seven years.

And he is not the only one making such forecasts. In June 2014, the domestic brokerage Karvy had forecast that the Sensex will touch 1,00,000 points by December 2020.

People making a living out of the stock market (or any other market for that matter) have an incentive in saying that future will be better than the present is. Many analysts make a living by simply doing this on the business news TV channels, on a regular basis.

The media looking for bold headlines to run, laps it up. And the investors who are more like sheep ready to be slaughtered, follow the sheep in front of them.

In fact, the trick is to make bold bigger forecasts and not small ones. I mean, if you currently forecast that Sensex is going to touch 55,000 points this year, no one is going to pay interest. But if you say Sensex is going to cross 1,00,000 points by 2023 or 2024, everyone is going to sit up and take interest.

An excellent example of this is Jhunjhunwala’s 2014 forecast on the stock market index Nifty touching 1,25,000 points by 2030.

Of course, if he turns out to be right, everyone will be dazzled by the forecast he had made. If he turns out to be wrong, no one will remember. Did you remember that Karvy had forecast the Sensex touching 1,00,000 points by December 2020? That’s how the game is played.

Big investors are trying to drive up stock prices, so that their investment portfolios can also gain in the process, which is why they publicly need to be seen as being confident.

A similar game is now played on the social media where traders claim to have generated a humongous amount of return in a short period of time. Of course, there is no way to verify this, except believing him or her.

This is accompanied by other confident predictions of how the future is going to be. The idea is to sell some training programme that they are offering. And no one is going to buy a training programme from a trader who doesn’t sound confident.

For the economists, the game is a little different. They tend to treat their pet theories as gospel. So, an economist who believes in free markets will keep parroting the free market line on everything.

As Scott Galloway writes in his excellent book Post Corona—From Crisis to Opportunity:

“The libertarian argument… is that…regulation and redistribution is inefficient, that left to its own devices the market will regulate itself. If people value clean rivers, the argument goes, they won’t buy cars from companies that pollute. But history and human nature shows that this does not work.”

An excellent example of this is the river Ganga in India, which people keep polluting despite the fact that at the same time they look it as a holy river.

Galloway offers a few more examples. “Nobody wants to see children working eighteen hours a day in a clothing factory, but at the H&M outlet, the $10 T-shirt is an unmissable bargain… Nobody wants to die in a hotel fire, but after a long day of meetings, we aren’t going to inspect the sprinkler system before checking in.” The point being that some sort of regulation is necessary.

There is economic theory and then there is how things play out in real life. As Adam Grant writes in Think Again—The Power of Knowing What You Don’t Know: “In theory confidence and competence go hand in hand. In practice, they often diverge.”

Other than continuing to believe in their pet theories, there is one more reason for economists to portray confidence. Over the years, they have sold their subject as a science, if not to others, at least to themselves in their heads. I mean the first step before convincing anyone else is to convince oneself first.

Hence, the economic growth figure is forecast to the precision of one decimal point. I have always wondered about how economic growth, which is something very complex and is impacted by so many factors, can be forecast in such a precise way.

Now, this is not to say that the forecasting economic growth is not important. It is very important, simply because without that governments and corporations won’t be able to plan for the future.

Without knowing the economic growth number for the next year, a government wouldn’t be able to forecast its fiscal deficit or the difference between what it earns and what it spends expressed as a percentage of the country’s GDP. Without forecasting the fiscal deficit, the government wouldn’t know what kind of money it has to borrow in order to meet this gap. Without the government knowing the government’s borrowing target, the country’s central bank won’t be able to set the country’s monetary policy. And so on.

Nevertheless, the world would be a much better place if the economists started forecasting in ranges. Like, in 2020-21, the Indian economy is likely to contract by 8-10% or even 8-9%, rather than saying something as specific like the Indian economy is likely to contract by 8.3%.  In this scenario, the governments could also forecast a range when it comes to their fiscal deficit.

As John Maynard Keynes is said to have supposedly remarked: “It is better to be roughly right than precisely wrong.”

Hence, forecasting ranges and pointing towards the right direction is more important than being extremely precise about the economic growth.

As Tom Bergin writes in Free Lunch Thinking—How Economics Ruins the Economy:

“If economic models or theories can point us in the right direction and give us a reasonable estimate of the scale of a force or impact, they’re helpful. For example, if consumers are building up levels of personal debt that will require ever-rising house prices and wages to sustain – think the United States in 2006 –economists don’t need to tell us exactly how much a drop in GDP this situation will likely result in. If they can simply show the risks are unsustainable and material, this can prompt and inform government action and protect society.”

I learnt this the hard way. In 2013, when I first started writing about real estate, looking at the situation at hand, I started predicting a real estate bust very confidently. In the years to come, I turned out to be partly right, with parts of the country seeing a substantial fall in prices.

But the deep state of Indian real estate (the bankers, the builders and the politicians) essentially ensured that a real bust never really came. Of course, having learnt from this, now I point out more towards the perils of owning real estate at a price you cannot really afford because that is point people looking to buy a house to live in, essentially need to understand.

Also, one can more confidently say that the real estate sector will continue to remain moribund in the days to come, than confidently predict a bust. As far as investors are concerned, the real estate story has been over for a while.

Sometimes the confidence of economists comes from the prevailing narrative. As Daniel Acemoglu and James A Robinson write in Why Nations Fail – The Origins of Power, Prosperity and Poverty:  

“The most widely used university textbook in economics, written by Nobel Prize-winner Paul Samuelson, repeatedly predicted the coming economic dominance of the Soviet Union. In the 1961 edition, Samuelson predicted that Soviet national income would overtake that of the United States possibly by 1984, but probably by 1997. In the 1980 edition, there was little change in the analysis, though the two dates were delayed to 2002 and 2012.”

Of course nothing of this sort happened, and the Soviet Union broke up in December 1991. But those were the days, and the narrative framed around the success of the Soviet style of economics, driven by its Five-Year Plans, was very popular. Samuelson was not the only one to be seduced by it. In fact, an entire generation was.

Interestingly, the economist Phillip Tetlock has carried out extensive research on experts and their predictions. Gardner, from whose book I have quoted above, documents this in Future Babble.

As he writes:

“Tetlock recruited 284 experts— political scientists, economists, and journalists—whose jobs involve commenting or giving advice on political or economic trends…Over many years, Tetlock and his team peppered the experts with questions. In all, they collected an astonishing 27,450 judgments about the future.”

It turned out that the expert predictions were no more accurate than random guesses. As Gardner writes: “Experts who did particularly badly… were not comfortable with complexity and uncertainty. They sought to “reduce the problem to some core theoretical theme.” This means that they had this one big idea and they stuck to it, without trying to realign their view to the new information coming in.

An excellent example of this is all the gold bulls who came out of the woodwork post the financial crisis of 2008. They talked about gold reaching very high price levels (The highest I encountered was $55,000 per ounce).

As a journalist I interviewed many such individuals and the confidence they had in their forecasts was amazing. In that round, gold didn’t even touch $2,000 per ounce. But the audience lapped the interviews I did. Why? Because these experts exuded confidence in their interviews, even though they eventually turned out to be wrong.

In 2012, when I turned into a freelance writer, I exuded the same confidence on gold while writing about it. And when the prices actually started to fall, it sort of struck at a core belief I had developed over the years and it took me a couple of years to get around to the whole thing.

As Grant writes: “When a core belief is questioned… we tend to shut down rather than open up. It’s as if there’s a miniature dictator living inside our heads, controlling the flow of facts to our minds.” This is referred to as totalitarian ego and a decade later I can see this ego among many bitcoin experts, whenever one questions the entire idea of bitcoin as money, and that has me worried.

Now getting back to Gardner and Tetlcok. Experts who did better than the average of the group that Tetlock had recruited had no template or no big idea. They tried to synthesise information from multiple sources.

As Tetlock writes: “Most of all, these experts were comfortable seeing the world as complex and uncertain—so comfortable that they tended to doubt the ability of anyone to predict the future. That resulted in a paradox: The experts who were more accurate than others tended to be much less confident that they were right.”

This explains why most business TV news anchors, podcasters, YouTuber, social media influencers, etc., who are popular, sound very confident. They believe in this one big idea, which sounds sensible to people, irrespective of whether it is right in the real world or not, and they keep hammering it over and over again, to their audience.

It also explains why guys who are normally right about things aren’t really popular with the media or the public at large. This is simply because they are not totally confident about what they are saying. They have their ifs and buts built into what they say and are constantly revising the information in their heads. And as and when they feel like it, they are ready to revise their views as well. This constant revision comes across as lack of confidence to the world at large. Tetlock called such experts foxes and experts who believed in that one big thing as hedgehogs.

The categorisations were from an essay written by political philosopher Isaiah Berlin, in which Berlin had recalled a small part of an ancient Greek poem. “The fox knows many things… but the hedgehog knows one big thing.” After knowing this, it is easy to figure out who is a fox and who is a hedgehog.

As Gardner writes:

“If you hear a hedgehog make a long-term prediction, it is almost certainly wrong. Treat it with great skepticism. That may seem like obscure advice, but take a look at the television panels, magazines, books, newspapers, and blogs where predictions flourish. The sort of expert typically found there is the sort who is confident, clear, and dramatic. The sort who delivers quality sound bites and compelling stories. The sort who doesn’t bother with complications, caveats, and uncertainties. The sort who has One Big Idea.”

Hence, the kind of expert found in the media is the kind of expert who is more likely to be wrong. One of the key findings that emerged from Tetlock’s data was: “The bigger the media profile of an expert, the less accurate his predictions are.”

In a world filled with confident forecasts, this is a very important point that needs to be kept in mind. If we really need to make sense of the world we are in, we need to figure out who the foxes are and follow them, however mentally disconcerting it might be. The hedgehogs need to be discarded.

Why Capitalism Won

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After the end of the Second World War, the Soviet inspired communism and socialism started to spread through large parts of the world.

Some of it (the communism bit) was pushed by the Soviets themselves with the weight of their big army. And some of it (the socialism bit) the countries adopted on their own. India is a good example of the latter trend.

In fact, for a very long time, the bet was that the Soviets would win and the Soviet economy would become larger than the American one. But that never materialised. In fact, this idea was even a part of the most read economics text book during those days, written by the American economist Paul Samuelson.

As Daniel Acemoglu and James A. Robinson write in Why Nations Fail – The Origins of Power, Prosperity and Poverty: “In the 1961 edition, Samuelson predicted that Soviet national income would overtake that of the United States possibly by 1984, but probably by 1997. In the 1980 edition there was little change in the analysis, though the two dates were delayed to 2002 and 2012.”

But nothing like that happened. By the time Mikhail Gorbachev became the General Secretary of the Soviet Union in 1985, the Americans and the rest of the West, had won. Gorbachev was more practical than the previous Soviet leaders and even launched the policies of glasnost (“openness”) and perestroika (“restructuring”) to get the moribund Soviet economy going.

The story goes (and it is perhaps apocryphal) that Gorbachev sent a key aide to London to learn a thing or two about what the British were doing well, which the Soviets clearly weren’t.

The British played good hosts and Gorbachev’s aide was taken for a tour of the city with places like the London Stock Exchange and the London School of Economics being on the itinerary.

As Yuval Noah Harari writes in Homo Deus—A Brief History of Tomorrow: “After a few hours, the Soviet expert burst out: ‘Just one moment, please… We have been going back and forth across London for a whole day now, and there’s one thing I cannot understand. Back in Moscow, our finest minds are working on the bread supply system, and yet there are such long queues in every bakery and grocery store.”

Gorbachev’s aide was surprised that in London there were no lines in front of supermarkets and shops for bread, even though millions of people lived in the city. The aide ended up saying: “I haven’t seen a single bread queue. Please take me to meet the person in charge of supplying bread to London. I must learn his secret.”

Of course, it need not be said, there was no one in charge for supplying bread to the city of London. And this is precisely why there were no queues. As Donald J. Boudreaux writes in The Essential Hayek: “There is no overarching—no “central”—plan for the whole…That larger outcome is… spontaneously ordered.”

This is precisely the secret of success of capitalism. Unlike in communism there was no central processing unit to supply bread to the city of London. As Harari writes: “The information flows freely between millions of consumers and producers, bakers and tycoons, farmers and scientists. Market forces determine the price of bread, the number of loaves baked each day and the research-and-development priorities.”

And this is why capitalism won at the end of the day. As Harari puts it: “Distributed data processing works better than centralised data processing, at least in periods of accelerating technological changes…When all the data is accumulated in one secret bunker, and all important decisions are taken by a group of elderly apparatchiks, you can produce nuclear bombs by the cartload, but you won’t get an Apple of a Wikipedia.”

Or even a Facebook for that matter.

The column originally appeared in Bangalore Mirror on October 26, 2016

 

Of Nehru and India’s unemployable

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For many years, the most widely used economics textbook all over the world was written by the American economist Paul Samuelson. Samuelson in different editions of his textbook maintained for a very long period of time that in the years to come the economy of the Soviet Union would grow bigger than that of the United States.  

As Daniel Acemoglu and James A Robinson write in Why Nations Fail – The Origins of Power, Prosperity and Poverty: “The most widely used university textbook in economics, written by Nobel Prize-winner Paul Samuelson, repeatedly predicted the coming economic dominance of the Soviet Union. In the 1961 edition, Samuelson predicted that Soviet national income would overtake that of the United States possibly by 1984, but probably by 1997. In the 1980 edition there was little change in the analysis, though the two dates were delayed to 2002 and 2012.”

Of course nothing of this sort happened and the Soviet Union broke up in December 1991. But those were the days and the narrative of the success of the Soviet style of economics driven by five-year-plans was very popular. Samuelson was not the only one to be seduced by it. In fact, an entire generation was.

The trouble as Acemoglu and Robinson point out was: “In reality, what got implemented in Soviet Union had little to do with the five-year-plans, which were frequently revised and written or simply ignored. The development of industry took place on the basis of commands by Stalin and the Politburo, who changed their minds frequently and often completely revised their previous decisions.”

Closer to home, Jawaharlal Nehru was also a great fan of the Soviet style of economic development. So India had its own set of five-year-plans. The second five year plan (1956-1961) put into practice the idea of economic growth driven by public sector enterprises. Further, trained people were needed to run these public sector enterprises.

As PC Mahalanobis who was the Honorary Statistical Advisor to the government of India as well as the brain behind the second five year plan said in November 1954: “In dealing with the programme of industrial production one of the most important questions would be an adequate supply of trained personnel at all levels. This may indeed prove to be a serious bottleneck.”

In order to tackle this bottleneck the government moved its focus towards higher education. As Sanjeev Sanyal writes in The Indian Renaissance—India’s Rise After a Thousand Years of Decline: “Rather than invest in the general primary education, the country used up all its education budget to provide specialized personnel for grandiose public-sector-projects…The needs of the Mahalonobis model…meant that the country had invested heavily in tertiary education and built up a handful of world-class institutions.”

An impact of this, as Sanyal writes was that “the bulk of the country’s workforce was effectively not employable in anything other than subsistence agriculture.” And this is something which hasn’t really changed. Currently more than half of country’s population works in agriculture but contributes only around 18% of the gross domestic product (GDP).

This means there are many more people working in agriculture than there should be. If India needs to get its millions out of poverty, it is critical that other earning opportunities are created for these individuals. In fact, only 17% of the people who work on farms survive only on money they make from their farm. Everyone else does some extra work.

Hence, a bulk of these people need to be moved on to other jobs. The question is what kind of jobs they can really take on, given that many of them have very basic literacy skills or almost none at all. This pushes skilled or even semi-skilled jobs for that matter, out of the equation.

The point here being that the choice of a wrong economic model has had major consequences for India. And the sad part is that we still don’t seem to have learnt enough from the disaster of public sector driven development.

(Vivek Kaul is the author of the Easy Money trilogy. He tweets @kaul_vivek)

The column originally appeared in the Bangalore Mirror
on Sep 23, 2015