69 is the answer

The IDFC-Duke-Chicago survey that concluded that 50% of Bangalore had covid-19 in late June only surveyed 69 people in the city. 

When it comes to most things in life, the answer is 42. However, if you are trying to rationalise the IDFC-Duke-Chicago survey that found that over 50% of people in Bangalore had had covid-19 by end-June, then the answer is not 42. It is 69.

For that is the sample size that the survey used in Bangalore.

Initially I had missed this as well. However, this evening I attended half of a webinar where some of the authors of the survey spoke about the survey and the paper, and there they let the penny drop. And then I found – it’s in one small table in the paper.

The IDFC-Duke-Chicago survey only surveyed 69 people in Bangalore

The above is the table in its glorious full size. It takes effort to read the numbers. Look at the second last line. In Bangalore Urban, the ELISA results (for antibodies) were available for only 69 people.

And if you look at the appendix, you find that 52.5% of respondents in Bangalore had antibodies to covid-19 (that is 36 people). So in late June, they surveyed 69 people and found that 36 had antibodies for covid-19. That’s it.

To their credit, they didn’t highlight this result (I sort of dug through their paper to find these numbers and call the survey into question). And they mentioned in tonight’s webinar as well that their objective was to get an idea of the prevalence in the state, and not just in one particular region (even if it be as important as Bangalore).

That said, two things that they said during the webinar in defence of the paper that I thought I should point out here.

First, Anu Acharya of MapMyGenome (also a co-author of the survey) said “people have said that a lot of people we approached refused consent to be surveyed. That’s a standard of all surveying”. That’s absolutely correct. In any random survey, you will always have an implicit bias because the sort of people who will refuse to get surveyed will show a pattern.

However, in this particular case, the point to note is the extremely high number of people who refused to be surveyed – over half the households in the panel refused to be surveyed, and in a further quarter of the panel households, the identified person refused to be surveyed (despite the family giving clearance).

One of the things with covid-19 in India is that in the early days of the pandemic, anyone found having the disease would be force-hospitalised. I had said back then (not sure where) that hospitalising asymptomatic people was similar to the “precogs” in Minority Report – you confine the people because they MIGHT INFECT OTHERS.

For this reason, people didn’t want to get tested for covid-19. If you accidentally tested positive, you would be institutionalised for a week or two (and be made to pay for it, if you demanded a private hospital). Rather, unless you had clear symptoms or were ill, you were afraid of being tested for covid-19 (whether RT-PCR or antibodies, a “representative sample” won’t understand).

However, if you had already got covid-19 and “served your sentence”, you would be far less likely to be “afraid of being tested”. This, in conjunction with the rather high proportion of the panel that refused to get tested, suggests that there was a clear bias in the sample. And since the numbers for Bangalore clearly don’t make sense, it lends credence to the sampling bias.

And sample size apart, there is nothing Bangalore-specific about this bias (apart from that in some parts of the state, the survey happened after people had sort of lost their fear of testing). This further suggests that overall state numbers are also an overestimate (which fits in with my conclusion in the previous blogpost).

The other thing that was mentioned in the webinar that sort of cracked me up was the reason why the sample size was so low in Bangalore – a lockdown got announced while the survey was on, and the sampling team fled. In today’s webinar, the paper authors went off on a rant about how surveying should be classified as an “essential activity”.

In any case, none of this matters. All that matters is that 69 is the answer.

 

More on Covid-19 prevalence in Karnataka

As the old song went, “when the giver gives, he tears the roof and gives”.

Last week the Government of Karnataka released its report on the covid-19 serosurvey done in the state. You might recall that it had concluded that the number of cases had been undercounted by a factor of 40, but then some things were suspect in terms of the sampling and the weighting.

This week comes another sero-survey, this time a preprint of a paper that has been submitted to a peer reviewed journal. This survey was conducted by the IDFC Institute, a think tank, and involves academics from the University of Chicago and Duke University, and relies on the extensive sampling network of CMIE.

At the broad level, this survey confirms the results of the other survey – it concludes that “Overall seroprevalence in the state implies that by August at least 31.5 million residents had been infected by August”. This is much higher than the overall conclusions of the state-sponsored survey, which had concluded that “about 19 million residents had been infected by mid-September”.

I like seeing two independent assessments of the same quantity. While each may have its own sources of error, and may not independently offer much information, comparing them can offer some really valuable insights. So what do we have here?

The IDFC-Duke-Chicago survey took place between June and August, and concluded that 31.5 million residents of Karnataka (out of a total population of about 70 million) have been infected by covid-19. The state survey in September had suggested 19 million residents had been infected by September.

Clearly, since these surveys measure the number of people “who have ever been affected”, both of them cannot be correct. If 31 million people had been affected by end August, clearly many more than 19 million should have been infected by mid-September. And vice versa. So, as Ravi Shastri would put it, “something’s got to give”. What gives?

Remember that I had thought the state survey numbers might have been an overestimate thanks to inappropriate sampling (“low risk” not being low risk enough, and not weighting samples)? If 20 million by mid-September was an overestimate, what do you say about 31 million by end August? Surely an overestimate? And that is not all.

If you go through the IDFC-Duke-Chicago paper, there are a few figures and tables that don’t make sense at all. For starters, check out this graph, that for different regions in the state, shows the “median date of sampling” and the estimates on the proportion of the population that had antibodies for covid-19.

Check out the red line on the right. The sampling for the urban areas for the Bangalore region was completed by 24th June. And the survey found that more than 50% of respondents in this region had covid-19 antibodies. On 24th June.

Let’s put that in context. As of 24th June, Bangalore Urban had 1700 confirmed cases. The city’s population is north of 10 million. I understand that 24th June was the “median date” of the survey in Bangalore city. Even if the survey took two weeks after that, as of 8th of July, Bangalore Urban had 12500 confirmed cases.

The state survey had estimated that known cases were 1 in 40. 12500 confirmed cases suggests about 500,000 actual cases. That’s 5% of Bangalore’s population, not 50% as the survey claimed. Something is really really off. Even if we use the IDFC-Duke-Chicago paper’s estimates that only 1 in 100 cases were reported / known, then 12500 known cases by 8th July translates to 1.25 million actual cases, or 12.5% of the city’s population (well below 50% ).

My biggest discomfort with the IDFC-Duke-Chicago effort is that it attempts to sample a rather rapidly changing variable over a long period of time. The survey went on from June 15th to August 29th. By June 15th, Karnataka had 7200 known cases (and 87 deaths). By August 29th the state had 327,000 known cases and 5500 deaths. I really don’t understand how the academics who ran the study could reconcile their data from the third week of June to the data from the third week of August, when the nature of the pandemic in the state was very very different.

And now, having looked at this paper, I’m more confident of the state survey’s estimations. Yes, it might have sampling issues, but compared to the IDFC-Duke-Chicago paper, the numbers make so much more sense. So yeah, maybe the factor of underestimation of Covid-19 cases in Karnataka is 40.

Putting all this together, I don’t understand one thing. What these surveys have shown is that

  1. More than half of Bangalore has already been infected by covid-19
  2. The true infection fatality rate is somewhere around 0.05% (or lower).

So why do we still have a (partial) lockdown?

PS: The other day on WhatsApp I saw this video of an extremely congested Chickpet area on the last weekend before Diwali. My initial reaction was “these people have lost their minds. Why are they all in such a crowded place?”. Now, after thinking about the surveys, my reaction is “most of these people have most definitely already got covid and recovered. So it’s not THAT crazy”.

Election Counting Day

At the outset I must say that I’m deeply disappointed (based on the sources I’ve seen, mostly based on googling) with the reporting around the US presidential elections.

For example, if I google, I get something like “Biden leads Trump 225-213”. At the outset, that seems like useful information. However, the “massive discretisation” of the US electorate means that it actually isn’t. Let me explain.

Unlike India, where each of the 543 constituencies have a separate election, and the result of one doesn’t influence another, the US presidential election is at the state level. In all but a couple of small states, the party that gets most votes in the state gets all the votes of that state. So something like California is worth 55 votes. Florida is  worth 29 votes. And so on.

And some of these states are “highly red/blue” states, which means that they are extremely likely to vote for one of the two parties. For example, a victory is guaranteed for the Democrats in California and New York, states they had won comprehensively in the 2016 election (their dominance is so massive in these states that once a friend who used to live in New York had told me that he “doesn’t know any Republican voters”).

Just stating Biden 225 – Trump 213 obscures all this information. For example, if Biden’s 225 excludes California, the election is as good as over since he is certain to win the state’s 55 seats.

Also – this is related to my rant last week about the reporting of the opinion polls in the US – the front page on Google for US election results shows the number of votes that each candidate has received so far (among votes that have been counted). Once again, this is highly misleading, since the number of votes DOESN’T MATTER – what matters is the number of delegates (“seats” in an Indian context) each candidate gets, and that gets decided at the state level.

Maybe I’ve been massively spoilt by Indian electoral reporting, pioneered by the likes of NDTV. Here, it’s common to show the results and leads along with margins. It is common to show what the swing is relative to the previous elections. And some publications even do “live forecasting” of the total number of seats won by each party using a variation of the votes to seats model that I’ve written about.

American reporting lacks all of this. Headline numbers are talked about. “Live reports” on sites such as Five Thirty Eight are flooded with reports of individual senate seats, which to me sitting halfway round the world, is noise. All I care about is the likelihood of Trump getting re-elected.

Reports talk about “swing states” and how each party has performed in these, but neglect mentioning which party had won it the last time. So “Biden leading in Arizona” is of no importance to me unless I know how Arizona had voted in 2016, and what the extent of the swing is.

So what would I have liked? 225-213 is fine, but can the publications project it to the full 538 seats? There are several “models” they can use for this. The simplest one is to assume that states that haven’t declared leads yet have voted the same way as they did in 2016. One level of complexity can be using the votes to seats model, by estimating swings from the states that have declared leads, and then applying it to similar states that haven’t given out any information. And then you can get more complicated, but you realise it isn’t THAT complicated.

All in all, I’m disappointed with the reporting. I wonder if the split of American media down political lines has something to do with this.

Opinion polling in India and the US

(Relative) old-time readers of this blog might recall that in 2013-14 I wrote a column called “Election Metrics” for Mint, where I used data to analyse elections and everything else related to that. This being the election where Narendra Modi suddenly emerged as a spectacular winner, the hype was high. And I think a lot of people did read my writing during that time.

In any case, somewhere during that time, my editor called me “Nate Silver of India”.

I followed that up with an article on why “there can be no Nate Silver in India” (now they seem to have put it behind a sort of limited paywall). In that, I wrote about the polling systems in India and in the US, and about how India is so behind the US when it comes to opinion polling.

Basically, India has fewer opinion polls. Many more political parties. A far more diverse electorate. Less disclosure when it comes to opinion polls. A parliamentary system. And so on and so forth.

Now, seven years later, as we are close to a US presidential election, I’m not sure the American opinion polls are as great as I made them out to be. Sure, all the above still apply. And when these poll results are put in the hands of a skilled analyst like Nate Silver, it is possible to make high quality forecasts based on that.

However, the reporting of these polls in the mainstream media, based on my limited sampling, is possibly not of much higher quality than what we see in India.

Basically I don’t understand why analysts abroad make such a big deal of “vote share” when what really matters is the “seat share”.

Like in 2016, Hillary Clinton won more votes than Donald Trump, but Trump won the election because he got “more seats” (if you think about it, the US presidential elections is like a first past the post parliamentary election with MASSIVE constituencies (California giving you 55 seats, etc.) ).

And by looking at the news (and social media), it seems like a lot of Americans just didn’t seem to get it. People alleged that Trump “stole the election” (while all he did was optimise based on the rules of the game). They started questioning the rules. They seemingly forgot the rules themselves in the process.

I think this has to do with the way opinion polls are reported in the US. Check out this graphic, for example, versions of which have been floating around on mainstream and social media for a few months now.

This shows voting intention. It shows what proportion of people surveyed have said they will vote for one of the two candidates (this is across polls. The reason this graph looks so “continuous” is that there are so many polls in the US). However, this shows vote share, and that might have nothing to do with seat share.

The problem with a lot (or most) opinion polls in India is that they give seat share predictions without bothering to mention what the vote share prediction is. Most don’t talk about sample sizes. This makes it incredibly hard to trust these polls.

The US polls (and media reports of those) have the opposite problem – they try to forecast vote share without trying to forecast how many “seats” they will translate to. “Biden has an 8 percentage point lead over Trump” says nothing. What I’m looking for is something like “as things stand, Biden is likely to get 20 (+/- 15) more electoral college votes than Trump”. Because electoral college votes is what this election is about. The vote share (or “popular vote”, as they call it in the US (perhaps giving it a bit more legitimacy than it deserves) ), for the purpose of the ultimate result, doesn’t matter.

In the Indian context, I had written this piece on how to convert votes to seats (again paywalled, it seems like). There, I had put some pictures (based on state-wise data from general elections in India before 2014).

An image from my article for Mint in 2014 on converting votes to seats. Look at the bottom left graph

What I had found is that in a two-cornered contest, small differences in vote share could make a massive difference in the number of seats won. This is precisely the situation that they have in the US – a two cornered contest. And that means opinion polls predicting vote shares only should be taken with some salt.

Kneel down

When Colin Kaepernick knelt down during the national anthem, it was cool, and a strong sign of protest against racial violence in the United States. When other athletes, in the US and elsewhere decided to copy him (and did so on their own volition), it was cool as well.

What I find not so convincing is that after the Floyd murder earlier this year, sports organisations across the world decided to institutionalise the kneel down. When the English Premier League restarted after the covid-19 induced break, it was decided that all players and referees would kneel for a minute at kickoff.

Now it seems like it has been decided that the gesture will continue for the 2020-21 season as well – players and officials will take a knee for a minute at the beginning of each game. Of course, it has also been decided to make it “non-mandatory” – players who choose not to not join the protest will be free not to kneel.

The problem with the institutionalisation of the protest is that the protest loses its information content. Prior to the institutionalisation in June, if a player knelt, he/she was making a statement that he/she believed that “black lives matter”. Now that kneeling has become standard practice, there is no way for a player to convey this information.

Alternatively, it is possible now for a player to send out the opposite information (that he/she doesn’t believe in this protest) by refusing to join the protest. However, given the PR repercussions of such a move, it is unlikely that any player is going to take that stance (no pun intended).

Actually – by institutionalising the kneel, the protest level is getting changed, from individual players to leagues. I can see why the protest is going to be continued – it will be a continuing statement by the sporting leagues that they believe in the cause. However, individual players will not have the opportunity to show their protest (or dissent) any more.

I also wonder if and when this protocol is reversed, since it takes effort for some team or league to “bell the cat”. Even saying that “this is mere symbolism” is bound to attract wrath of protestors elsewhere, so teams are all caught in a Nash equilibrium where they continue to kneel down in protest.

And the longer this kneeling down protest continues, the more the meaning that it will lose. Rather than serving to make a statement, it will end up as yet another ritual.

Unions and blacks

Did you know that trade unions were responsible for apartheid, which devastated the lives of black and coloured people in South Africa for nearly a century?

The logic was simple – black people were willing to work as miners for lower wages than white people. So the white-controlled unions lobbied to not allow black people to work in mines, so that their wages weren’t undercut. And what started as a movement to not let blacks work in diamond mines became an overall anti-black movement that led to apartheid.

This is captured in this beautiful old essay in Econlib. A couple of excerpts:

At first, however, the white capitalist could deal directly only with the few English and Afrikaner managers and foremen who shared his tongue and work habits. But the premium such workers commanded soon became an extravagance. Black workers were becoming capable of performing industrial leadership roles in far greater numbers and at far less cost. Driven by the profit motive, the substitution of black for white in skilled and semiskilled mining jobs rose high on the agenda of the mining companies.

[…]

Nonetheless, the state instituted an array of legal impediments to the promotion of black workers. The notorious Pass Laws sought to sharply limit the supply of nonwhite workers in “white” employment centers. Blacks were not allowed to become lawful citizens, to live permanently near their work, or to travel without government passports. This last restriction created a catch-22. If passports were issued only to those already possessing jobs, how was a nonwhite to get into the job area to procure a job so as to obtain a passport? Nonwhites also were prohibited from bringing their families while working in the mines (reinforcing the transient nature of employment).

[…]

To discourage mine owners from substituting cheaper African labor for more expensive European labor, the trade unions regularly resorted to violence and the strike threat. They also turned to legislation: the Mines and Works Act of 1911 (commonly referred to as the first Colour Bar Act) used the premise of “worker safety” to institute a licensing scheme for labor. A government board was set up to certify individuals for work in “hazardous” occupations. The effect was to decertify non-Europeans, who were deemed “unqualified.”

Read the whole thing. Going by modern American (or British) politics, this kind of a conflict between labour unions and blacks doesn’t make sense. After all, both these “communities” are among the biggest supporters of the Democratic (or Labour) Party, and so based on modern politics, you would imagine that they would be in harmony with each other on most counts.

However, I’m not sure the conflict between mostly-white unions and blacks has completely gone away.

I’ve been thinking of the brutal killing of George Floyd and the subsequent protests all over the USA (and elsewhere) over the last 10 days. The protestors have been protesting against racism, and the many cases of abuse of black people by white policemen in the US.

While the perpetrators of the crime were all racist white men, and the victim was a black man, I don’t know how much of the brutality can be attributed to racism, and how much simply to bad policing. Keep aside the victim’s race for a moment, and think about what happened – a policeman pinned down a suspect, and then knelt upon his neck for eight minutes until he was dead.

Racism has a part to play in that maybe the policemen thought they have a higher chance of getting away with it because the victim was black, but that the cop thought it was okay to brutalise just about anyone the way he did is atrocious.

Having largely been off social media, my reading about this (and related) issues is through the blogs that I follow, and one phrase that repeatedly make an appearance in this context is “police unions”. Policemen, like many other professions, are highly unionised in the United States, and the unions set rules for how the police can be treated, what they can be expected to do, their punishments, etc.

And from the stuff I’ve read (too many to link to everything), the unions give individual cops to behave the way they want to, knowing that punishment is going to be limited.

Today I came across this rather interesting post by Alex Tabarrok about Camden (New Jersey) where policemen marched with the Black Lives Matters protestors. There is a very interesting history to policing in Camden NJ.

In May of 2013, however, the entire police department was disbanded nullifying the union contract and an entirely new county police department was put into place.

And Tabarrok’s post goes on to show that the dissolution and reconstitution of the police force (basically the dissolution of the union) has led to tangible benefits in terms of reduced violent crime.

So it appears that, decades after apartheid was (in letter) abolished, white-controlled unions continue to make life really difficult for blacks.

Expertise

During the 2008 financial crisis, it was fairly common to blame experts. It was widely acknowledged that it was the “expertise” of economists, financial markets people and regulators that had gotten us into the crisis in the first place. So criticising and mocking them were part of normal discourse.

For example, most of my learning about the 2008 financial crisis came from following blogs written by journalists, such as Felix Salmon, and generalist academics such as Tyler Cowen or Alex Tabarrok or Arnold Kling, rather than blogs written by financial markets experts or practitioners. I don’t think it was very different for too many people.

Cut to 2020 and the covid-19 crisis, and the situation is very different. You have a bunch of people mocking experts (epidemiologists, primarily), but this is in the minority. The generic Twitter discourse seems to be “listen to the experts”.

For example, there was this guy called Tomas Pueyo who wrote a bunch of really nice blog posts (on Medium) about the possible growth of the disease. He got heavily attacked by people in the epidemiology and medicine professions, and (surprisingly to me)  the general twitter discourse backed this up. “We don’t need a silicon valley guy telling us epidemiology”, went the discourse. “Listen to the experts”.

That was perhaps the beginning of the “I’m not an epidemiologist but” meme (not a particularly “fit” meme in terms of propagation, but one that continues to endure). For example, when I wrote my now famous tweetstorm about Bayes’s theorem and random testing 2-3 weeks back, a friend I was discussing with it advised me to “get the thing checked with epidemiologists before publishing”.

This came a bit too late after I’d constructed the tweetstorm, and I didn’t want to abandon it, and so I told him, “but then I’m an expert on Probability and Bayes’s Theorem, and so qualified to put this” and went ahead.

In any case, I have one theory as to why “listen to the expert” has become the dominant discourse in this crisis. It has everything to do with politics.

Two events took place in 2016 that the “twitter establishment” (the average twitter user, weighted by number of followers and frequency of tweeting, if I can say) did not like – the passing of the Brexit referendum and the election of President Trump.

While these two surprising events took place either side of the Atlantic, they were both seen as populist movements that were aimed at the existing establishment. Some commentators saw them as a backlash “against the experts”. The rise of Trump and Brexit (and Boris Johnson) were seen as part of this backlash against expertise.

And the “twitter establishment” (the average twitter user, weighted by number of followers and frequency of tweeting, if I can say) doesn’t seem to like either of these two gentlemen (Trump and Johnson), and they are supposed to be in power because of a backlash against experts. Closer home, in India, the Modi government allegedly doesn’t trust experts, which critics blame for ham-handed decisions like Demonetisation and pushing through of the Citizenship Amendment Act in the face of massive protests (the twitter establishment doesn’t like Modi either).

Essentially we have a bunch of political leaders who are unpopular with the twitter establishment, and who are in place because of their mistrust of expertise, and multiplying negative with negative, you get the strange situation where the twitter establishment is in love with experts now.

And so when mathematicians or computer scientists or economists (or other “Beckerians“) opine on covid-19, they are dismissed as being “not expert enough”. Because any criticism of expertise of any kind is seen as endorsement of the kind of politics that got Trump, Johnson or Modi into power. And the twitter establishment (the average twitter user, weighted by number of followers and frequency of tweeting, if I can say) doesn’t like that.

The corner Bhelpuri guy

There’s this guy who sells Bhelpuri off a cart that he usually stations at the street corner 100 metres from home. His wife (I think) sells platters of cut fruit from another (taller, and covered) cart stationed next to him.

I don’t have any particular fondness for them. I’ve never bought cut fruit platters, for example (I’m told by multiple people that I’m not part of the target segment for this product). I have occasionally bought bhelpuri from this guy, but it isn’t the best you can find in this part of town. Nevertheless, every afternoon until mid-March he would unfailingly bring his cart to the corner every afternoon and set up shop.

He has since fallen victim to the covid-19 induced lockdown. I have no clue where he is (I don’t know where he lives. Heck, I don’t even know his name). All I know is that he has already suffered a month and half of revenue loss. I don’t know if he has had enough stash to see him through this zero revenue period.

The lockdown, and the way it has been implemented, has resulted in a number of misalignments of incentives. The prime minister’s regular exhortations to businesses to not lay off employees or cut salaries, for example, has turned the lockdown into a capital versus labour issue. Being paid in full despite not going to work, (organised) labour is only happy enough to demand an extension of the lockdown. Capital is running out of money, with zero revenues and having to pay salaries, and wants a reopening.

Our bhelpuri guy, running a one-person business, represents both capital and labour. In fact, he represents the most common way of operating in India – self employment with very limited (and informal) employees. Whether he pays salaries or not doesn’t matter to him (he only has to pay himself). The loss of revenue matters a lot.

The informality of his business means that there is pretty much no way out for him to get any sort of a bailout. He possibly has an Aadhaar card (and other identity cards, such as a voter ID), and maybe even a bank account. Yet, the government (at whatever level) is unlikely to know that he exists as a business. He might have a BPL ration card that might have gotten him some household groceries, but that does nothing to compensate for his loss of business.

If you go by social media, or even comments made by politicians to the media or even to the Prime Minister, the general discourse seems to be to “extend the lockdown until we are completely safe, with the government providing wage subsidies and other support”. All this commentary completely ignores the most popular form of employment in India – informal businesses with a small number of informal employees.

If you think about it, there is no way this set of businesses can really be bailed out. The only way the government can help them is by letting them operate (even that might not help our Bhelpuri guy, since hygiene-conscious customers might think twice before eating off a street cart).

One friend mentioned that the only way these guys can exert political power is through their caste vote banks. However, I’m not sure if these vote banks have a regular enough voice (especially with elections not being nearby).

It may not be that much of a surprise to see some sort of protests or “lockdown disobedience” in case the lockdown gets overextended, especially in places where it’s not really necessary.

PS: I chuckle every time I see commentary (mostly on social media) that we need a lockdown “until we have a vaccine”. It’s like people have internalised the Contagion movie a bit too literally.

Post-Covid Stimulus

There are two ways in which businesses have been adversely affected by the ongoing Covid-19 crisis. Using phrases from my algorithmic trading days, let me call this “temporary impact” and “permanent impact”.

For some businesses, the Covid-19 crisis and the associated lockdown means about three months or so of zero (or near-zero) revenues. There is nothing inherently unsafe about these businesses that makes their sales take a “permanent hit” after the crisis has passed us by. Once the economy opens up again, these businesses can do businesses like they used to before, except that they are staring at a three-odd month revenue hole at the top of their P&L.

The second kind of businesses are going to be “permanently impacted”. They involve stuff that are going to be labelled as “unsafe” even after the crisis is over, and people are going to do less of these.

For example, bars and restaurants are going to see a “permanent impact” because of the crisis – people are not going to relish sitting in a public place with strangers in the next one year, and a large proportion of restaurants will have to go out of business.

Similarly any industry associated with travel – such as transport (airlines, railways, buses), hotels and taxis will see a permanent impact from the crisis. Real estate is also likely to be hit hard by the crisis. For all these sectors (and more), even after the economy is otherwise back in full swing, it will be a very long time before they see the sort of demand seen before the crisis.

Now that distinction is clear (I mean there will always be sectors that will sort of lie in the borderline), but at least we have a classification, we can use this to determine how governments respond to stimulate economies after the crisis.

Based on all the commentary going around, it seems like a given that governments and central banks need to do their bit to stimulate the economies. The collapse in both demand and supply thanks to the crisis means that governments will collect less taxes this year than expected. So while to some extent they will be able to possibly borrow more, or monetise deficit, or set aside money from other budgeted items, the funds available for stimulating businesses are likely to be limited.

So what sectors of the economy should the governments (and central banks) choose to spend this precious stimulus on? My take is that they should not bother about businesses that will be permanently impacted by the crisis – at best, the money will go into delaying the inevitable at some of these companies, and if structured in the form of a loan, will be highly unlikely to be unpaid.

Instead, the government should spend to stimulate sections of the economy where the impact of the crisis is temporary – in order to make the crisis “more temporary”. By giving cash to sectors that are going to be fundamentally solvent, this cash can be more assured to “travel around the economy”, thus giving more of the proverbial bang for the buck.

This essentially means that sectors most affected by the current crisis should not get any help from the governments – this might sound counterintuitive, but if the true intention of the government stimulus is to stimulate the economy rather than helping a particular set of companies, this makes eminent sense.

Oh, and in the Indian context, this seems like the perfect time to “let go” of Air India.

Why Trump Will Retain Power

One piece of news that might have gone unnoticed in the middle of all this Covid19 news is that Bernie Sanders has suspended his campaign to be the Democratic nominee for this November’s American Presidential elections. So it looks highly likely that Joe Biden will take on fellow-septuagenarian Donald Trump.

Thinking about it, it doesn’t matter which Democrat takes on Trump. He is going to win. I suspect that Sanders realised this as the covid crisis was panning out, and so decided to fold.

Essentially what the Covid-19 crisis has been largely positive to things that American conservatives traditionally value, and showed the perils of some of the things that American “liberals” have traditionally valued. As a consequence of this, we will find that people who are on the margin (I’m told there are very few fence-sitting voters in the US, compared to India for example) are likely to shift more conservative.

In fact, everyone will become a little more conservative (in the American sense) after this crisis is over (though most Americans have such extreme political opinions that this won’t matter). And that means that in this year’s elections at least, the Republicans are going to win. So assuming he remains healthy, Trump has four more years in the Oval Office.

So what are these “conservative and liberal values” that influenced by this crisis? Let’s make a laundry list.

  • Borders: Open borders, at state and national level are a favourite of liberals (except, in the American context for some strange reason, for skilled labour immigration). They are great for economic growth, but also for pandemic growth. We are surely likely to see tougher border controls (maybe Brexit will be followed by Nordexit? Can’t be ruled out) continuing post this crisis.
  • Cities: Conservatives are all about urban sprawl, owning McMansions and commuting by car. Liberals bat for high density cities and public transport. The tail risk of high density cities as being higher risk for pandemic spread (which had largely been hidden following the rapid advances in medicine in the first half of the 20th century) has been exposed.
  • Families: When you are isolated you would rather be living with your family (“near and dear ones” as some like to put it). The lockdown has been hardest on people living alone or living “with roommates”. American conservatives are all about marrying early and staying married and “two parent families”, which means fairly low chances of living alone. On the margin, people are likely to rediscover “family”.
  • Individualism: Sort of related to the previous one. This is something that is likely to affect me as well. Liberals have been about “breaking free of the community” and living by and for yourself. Crises like this one make you realise the value of having a community, and cultivating relationships in good times that might come of use in bad. So we are likely to see less individualism.Related to this, liberals are far more likely than conservatives to cut ties with families on account of their political leanings. The pandemic might force a rethink on this.
  • Privacy: Countries that have managed to suppress the disease to great extent (such as Singapore, Taiwan, Hong Kong and South Korea) have done so by increasing surveillance on their citizens. As Raghu SJ wrote in this excellent blogpost, countries are facing an “impossible trilemma” in terms of protecting citizens’ privacy, containing the disease and protecting the economy.
    And he wholeheartedly agrees that privacy is the one thing that should be sacrificed now. I’m thinking he’s not alone. Moreover, instruments like Aadhaar and Aadhaar-linked bank accounts, which was vociferously opposed by privacy fundamentalists, can be of excellent use for fast direct transfer of benefits now (that India, which has this infrastructure, is only doing a tiny stimulus is another matter).
    Going forward, people will be more willing to trade off privacy (which a lot of us are already doing with Facebook, etc.) for superior service, and privacy fundamentalists will get less attention.

There are some mitigating factors as well.

  • Church attendances will go down, since religious gatherings have been shown to be a reliable source of infection spread.
  • The health crisis can mean that some sort of Obamacare might make a comeback.

On the balance, though, at least in the social sense, you can expect Americans to become more conservative. Move to smaller towns and suburubs (greater remote working will aid this), keep factories in the US (a favourite Trump theme) and become more family oriented. While all this may not last for too long, it should be enough to win Trump this year’s election.

It doesn’t matter how well or badly his government handles Covid-19.

I deliberately decided to not talk about India, since I’m not sure there’s that much of an ideological difference between political parties here. But similar trends, at the personal level, are likely to happen here as well.