U.S. Politics

Lots of people want to frame the 2020 US election as a fight between the left and the right, with the wrong side being near an extreme on that spectrum. They are deceiving you.

The U.S. is facing some extremism, but it has little connection to the extremes of the left-right spectrum [1]. The latest dangers are extreme mainly on a very different spectrum. A spectrum on which Trump and the woke are very similar.

How to describe this spectrum? I’m unsure what the best description is, so I’ll list some that capture important components of it:

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Lots of people have been asking recently why the stock market appears unconnected with the economy.

There are several factors that contribute to that impression.

First, stock market indexes are imperfect measures of the whole stock market. Well-known indexes such as the S&P500 are higher than pre-pandemic, but the average stock is down something like 10% over the same time period. The difference is due to some well-known stocks such as Apple and Amazon, which have unusually large weights in the S&P500.

See this Colby Davis post for some relevant charts, and for some good arguments against buying large growth stocks today.

Stock markets react to the foreseeable future, whereas the daily news, and most politicians, prefer to focus attention on the recent past. People who focus on the recent past see a US that’s barely able to decide whether to fight COVID-19, whereas the market sees vaccines and/or good treatments enabling business to return to normal within a year.

Stock markets don’t try to reflect the costs associated with death, chronic fatigue, domestic violence, etc. Too many people want the market to be either a perfect indicator of how well we’re doing, or to dismiss it as worthless. Sorry, but imperfect indicators are all we have.

Plenty of influential people have been exaggerating the harm caused by the pandemic, in order to manipulate the average person into taking the pandemic seriously. As far as I can tell, this backfired, and contributed to the anti-mask backlash. It also contributed to stocks being underpriced in the spring, so parts of the stock market rebound have simply been reactions to the growing evidence that most large companies are recovering.

The vaccine news has been persistently good, except for the opposition from big pharma and their friends at the FDA to making vaccines available as soon as possible.

Another modest factor is that many companies dramatically reduced their capital expenditure plans starting around March and April. That will reduce production capacities for the next year or two, thus making shortages of goods a bit more common than usual. This should prop up profit margins. But I haven’t noticed much connection between the most relevant industries and rising stock prices.

Why is there such a large divergence between the S&P500 and the average stock?

Investors have developed a somewhat unusual degree of preference for well-known companies whose long-term growth prospects seem safe.

I guessed last year that this would be a rerun of the Nifty Fifty. I still see important similarities in investor attitudes, but I see enough divergences in patterns of stock prices that I’m guessing we’ll get something in between the broad, gradual peak of the Nifty Fifty and a standard bubble (i.e. with a well-defined peak followed by a clear reversal within months).

Remember that high volatility is somewhat correlated with being in a bubble. We’ve recently seen Zoom Video Communications rise 40% in one day, and Salesforce rise 26%, in response to good earnings reports. That’s a $50 billion one-day gain for Salesforce. It reminds me of the volatility in PetroChina in 2007 (PetroChina has declined 87% since then). There was also that $173 billion rise in Apple after it’s latest earnings report, but that was a mere 10.5% rise.

Some of the divergence is due to small retailers losing business to Amazon, and to small restaurant chains losing business to fast food chains.

The bubble is a bit broader than just tech stocks – Home Depot and Chipotle are well above their pre-pandemic levels, by much larger amounts than can be explained by any near-term changes in their profits.

Incumbent politicians have been trying to buy votes by shoveling money to influential companies and people. There’s been some speculation that that’s biased toward large companies. It seems likely that large companies are better able to take advantage of those deals, because they’re more likely to employ someone with expertise at dealing with the government than is, say, a barbershop.

But I don’t see how that explains more than 1% of the stock market divergence. Stocks like Apple and Tesla have risen much more than can be explained by any change in this year’s profits. Any sane explanation of those soaring stocks has to involve increased optimism about profits that they’ll be making 5 to 10 years from now.

Large companies have better access to banks. Large companies typically have someone who is an expert at dealing with banks, and they have the accounting competence to make it easy for banks to figure out how much they can safely lend to the company. In contrast, a family-owned business will be slower to figure out how to borrow money, and therefore is more likely to go out of business due to unusual problems such as a pandemic. That might explain a fair amount of the divergence between the S&P500 and what you hear by word of mouth, but it explains little of the divergence between the S&P500 and the publicly traded companies that are too small for the S&P500.

I’ve only done a little selling recently, and I’ve been mostly avoiding large companies for many years. I’m guessing that Thursday’s tech stock crash wasn’t the end of the bubble. Bubbles tend to continue expanding until the average investor gets tired of hearing pundits say that we’re in a bubble. That suggests the peak is at least a month away, and I could imagine it being more than a year away.

I’ve been brainstorming about what might happen with this year’s election. Here’s one of the more interesting (but not likely) scenarios that I’ve imagined:

Most parts of the US are experiencing their second or third wave of the pandemic. Two of the more heavily funded vaccine trials have just been declared to be failures. No US or European company expects to have a vaccine ready for FDA approval before December. Prediction markets say Trump’s chances of re-election have dropped to 20%.

China announces on October 27 that Sinopharm Group has a COVID-19 vaccine that meets China’s safety and effectiveness standards, and can deliver about 1 million doses by November 2.

China offers to allocate half of this initial batch of vaccines to the US, on the grounds that the US is a relatively needy country, and Donald Trump is currently a close friend of China.

Why, I hear you wonder, would China treat Trump as a friend?

China is strong enough that the government can afford to tolerate Trump’s annoying trade wars, and they maybe even see some benefit from reducing China’s somewhat excessive dependence on the US. It’s important to keep in mind that democracy is one of the larger threats to the Beijing regime (h/t scholars-stage). 2020 has proven to be a good year to mount a campaign to demonstrate that socialism with Chinese characteristics is superior to US-style democracy. I’ll leave as an exercise for my readers to figure out how many ways the idea of democracy could be discredited by a Trump re-election.

Why would a Chinese company be faster than US/European companies at producing a vaccine? My initial guess was differences in regulatory red tape would favor China, but my attempt to find evidence for such a pattern turned up nothing. My current guess is that differences between countries in who volunteers for a vaccine trial will have important effects on how quickly the control groups get infected. Trials in some countries may attract only people who are sufficiently risk-averse that the control groups are slower than expected at getting infected. Please don’t assume that I have any useful expertise here; I’m mostly just guessing.

I also wondered whether willingness to do human challenge trials would determine who verifies their vaccine first. I have vague intuitions that China is more likely than other countries to try that, but I haven’t found evidence to confirm those intuitions.

How would voters react to this scenario? My best guess is that the election would be surprisingly close, but Trump would still lose.

The stock market would rise due to the vaccine benefits. There would be no good way to infer the market’s opinion about the election until the results are announced. I’m still confused as to how this scenario should affect my investment strategies.

P.S. – China and Sinopharm aren’t willing to predict when they’ll able to submit the forms needed for FDA approval, and ask that the US consider the approval of China’s NMPA to be good enough evidence of the vaccine’s safety and effectiveness. How does the FDA react?

Book review: Black Death at the Golden Gate: The Race to Save America from the Bubonic Plague, by David K. Randall.

Imagine a story about an epidemic that reached San Francisco, after devastating parts of China. A few cases are detected, there’s uncertainty about how long it’s been spreading undetected, and a small number of worried public health officials try to mobilize the city to stop an imminent explosion of disease. Nobody knows how fast it’s spreading, and experts only have weak guesses about the mechanism of transmission. News media and politicians react by trying to suppress those nasty rumors which threaten the city’s economy.

Sounds too familiar?

The story is about a bubonic plague outbreak that started in 1900. It happens shortly after the dawn of the Great Sanitary Awakening, when the germ theory of disease is fairly controversial. A few experts in the new-fangled field of bacteriology have advanced the radical new claim that rats have some sort of connection to the spread of the plague, and one has proposed that the connection involves fleas transmitting the infection through bites. But the evidence isn’t yet strong enough to widely displace the standard hypothesis that the disease is caused by filth.

There was a vaccine for the bubonic plague, which maybe helped a bit. It was only 50% effective, the benefits lasted about 6 months, and the side effects sound like cruel and unusual punishment. It was controversial and often resisted, much like the compulsory smallpox vaccinations of the time.

Yet the plague didn’t seem to know that it was supposed to grow at exponential rates. That left an eerie sense of mystery about how the plague could linger for years, with people continuing to disagree about whether it existed.

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New infections have been declining at an almost adequate pace (10% per week?) in most parts of the US, and probably the rest of the developed world.

The overall reported new cases look more discouraging, for two reasons.

One reason is the increase in testing. I estimate that two months ago, a bit less than 10% of new infections were being confirmed by tests, and I estimate that now it’s above 20%, maybe getting close to 25%. That means that if the new infection rate were unchanged, we’d be seeing a roughly 10% per week increase in reported cases.

Nearly all parts of the country have done a good deal better than that.

I estimate the change in new infections since the early April peak by multiplying the early April confirmed daily cases by 10 or 12, and the June ones by 4 or 5, and I get a current rate that’s about 1/4 to 1/3 of the peak.

The bad news is that there are some heavily populated areas for which the trend doesn’t look very good over the past few weeks. When the rate of new infections remains constant in some areas, but declines at exponential rates in others, the exponential declines stop affecting the total numbers before too long. E.g. much of California has suppressed the pandemic, but a few cities, such as Los Angeles and Oakland, are enough to keep the state’s total count of new infections steady.

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In this post, I make some conjectures about U.S. economic growth over the next year or two.

Many people expect a depression, due to the current high unemployment numbers. But depressions aren’t caused by unemployment – that’s a symptom, with little predictive power.

The main cause of poor economic growth has been an inability to alter wages so that the supply of and demand for labor are in balance. That typically means deflation, or a large, unexpected decline in the inflation rate, combined with sticky wages.

So I’ll mostly focus on guessing whether we’ll have inflation or deflation.

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Elon Musk has gotten some well-deserved flack for predicting (in March) close to zero new infections in the U.S. by now.

Yet the focus on national or statewide infections has obscured a curious phenomenon: if he’d just predicted infections in Santa Clara county, he’d have been partly right – new cases peaked on April 10 at 83, were down to 23 on April 27, and appear to have dropped more since then (reporting may be incomplete for more recent days). (Santa Clara county roughly coincides with Silicon Valley; Tesla’s plants are a few miles from the Santa Clara county border, technically in Alameda county, but in most senses Tesla’s plants are part of Silicon Valley, which I’ll treat as a city, even though it’s more a city-less suburb).

Meanwhile, the statewide totals fail to show a trend of doing much more than stabilizing the rate of new cases. A good deal of that is due to Los Angeles.

What’s different between LA and Silicon Valley that would explain this difference?

It’s probably not much due to differences in government policy. California is using a mix of statewide rules and county rules, which makes it tricky to say whether there are policy differences. My impression is that most differences between county policies have relatively minor effects. I guessed that the most important difference would be in when they required facemasks use. Yet it looks like LA required facemasks on April 17, in synchrony with most of the bay area. But Santa Clara county differed by strongly urging, but not requiring, facemasks.

Maybe the reason that Santa Clara county didn’t create a formal facemask rule is that residents were sufficiently quick to adopt them that there was less need than in other counties? That fits my intuitions fairly well.

The LA area has been in the news for having crowded beaches. Outdoor activity in warm, sunny weather seems relatively low risk, but I doubt that the people on those beaches carefully evaluated the effects of ventilation, sun, and temperature on their risk, so it’s likely that the crowded beaches are at least a symptom of attitudes which cause the spread of infections.

I can see from Ohio that there are significant regional differences in people’s willingness to wear facemasks. I’m surprised that Ohio voters won’t put up with a rule to make them wear masks in order to enter stores. (Ohio’s Governor DeWine deserves much better constituents than he’s currently stuck with. Here in Berkeley, I get the impression that a majority decided that we needed to follow that rule before our government got around to announcing it).

Another relevant difference is that Silicon Valley workers switched to working from home more readily than most other places. This is likely a moderate factor, but I’d have expected a peak before April 10 if it explained more than half of Silicon Valley’s success.

Another influence might be blood types: type A blood creates higher risk of COVID-19, while type O lowers risk. Judging from the blood type differences between the U.S. and China, the large Chinese population in Silicon Valley ought to lower risk a bit.

LA’s apparently steady number of new cases can’t be very stable. People’s willingness to take precautions will decline at some point if herd immunity looks inevitable. Pushing in the other direction: increasing numbers of people will become immune, reducing the virus’ ability to spread. It seems almost impossible for these forces to balance out.

Robin Hanson sees a world polarized between regions that prevent infections and regions that get something like herd immunity. I expect that many regions, such as LA, will end up at various places in between, with maybe 10% of the population becoming immune. Since the people most likely get infected and to spread the virus will be over-represented in that fraction, it will put a sizable dent in R, enough to enable significant periods of suppression.

Robin expects that variance in R will be harmful. Zvi counters that variance is not bad, given sufficiently effective travel restrictions.

I mostly agree with Zvi here. The cost of restricting nearly all travel to commuting distance or less from home is much lower than the cost of the current drastic restrictions, so voters will typically demand a shift in that direction. My main concern is that these travel restrictions are getting lumped in with “lockdown measures” such as stay at home, and shut down “nonessential” businesses. That means that pressure to reopen activities that ought to be reopened could become pressure to remove most travel restrictions.

How many politicians will see beyond simple categories such as lockdowns versus reopening the economy, to pick and choose between the good and bad pieces of lockdowns? My impression is that at least half of the state and local politicians are on track to doing so, and have enough power to sidestep whatever problems exist at the federal level.

I sympathize with Musk’s desire to reopen Tesla plants, and it’s somewhat plausible that now is the right time for that. But I’m reluctant to side with him until he alters his tweets to be more narrowly targeted on specific, arguably safe, changes. I don’t want the world polarized between openers and closers.

Some links to information sources that I’ve been using:

Food delivery is erratic in Berkeley. GoodEggs seems to have major food shortages, and maybe some labor shortages. Model Meals has been working almost as smoothly as normal, providing I place my order a day before their deadline – they are selling out of most things near their deadlines. I tried Instacart for the first time, and it seems substantially degraded by high demand – I had problems with getting 2 apples when I ordered 2 3-lb bags of apples (no that wasn’t listed as a substitution – the intentional substitutions worked fine). I’m guessing I’ll want to go back to shopping at grocery stores in person in a week or so. Infection rates are almost certainly dropping here now that the shelter-in-place rules have been around for a while, but it will likely be a week before much evidence confirms that.

I hiked in Briones Regional Park on Friday. I expect to see no more than 5 cars at the trailhead on a weekday; this time there were more than 30! People seemed unusually friendly. Most were making a decent effort to keep a 6 foot distance from me, but a few of the younger ones seemed to not care.

I think OPEC just collapsed, and nobody celebrated. I suppose the climate change implications might be a bit bad, but most effects will be pretty good.

Will auto sales be up or down a year from now? Loss of wealth will delay some purchases, and a fair number of existing drivers will drive less. But some people will switch from public transport to owning a car; others will switch from UberPool to UberX.

A modest number of maids will be replaced by Roombas [disclosure: I just bought stock in iRobot].

Politicians are talking about bailing out airlines, with terms that prevent them from stock buybacks. I expect that restriction to be purely symbolic – it will be a while before airlines are tempted to do buybacks anyway. If politicians were really upset about buybacks, they would instead deny the bailout to a single airline that was the most reckless in buybacks (maybe the one that achieved the worst debt to tangible equity ratio? I think that’s Delta). Alas, politicians won’t do that. After all, it might help people see that bailouts are somewhat targeted at helping bond and stock holders, and that the planes, workers, etc., don’t just vanish in the (somewhat unlikely) event that bankruptcy proceedings cause one company to shut down.

Some senators are under fire for insider trading on some sort of COVID-19 insights. If they profited from improved analysis of public information, I think that’s great! I’d like them to have an incentive to listen to experts. It would be suspicious if they profited from secret data, but I can’t find much reason to think that’s what happened – as far as I can tell, the relevant evidence was made public fairly quickly, and what mattered was competent evaluation of that evidence. And the most important question is what else they did to prepare. If, as the news storytellers vaguely imply, they did little else to warn people, then either they were more confused than the reports suggest, or they were recklessly negligent.

Shutting borders can hurt:

One issue has been restrictions on travel intended to stem the spread of coronavirus, which has affected [U.S. ventilator maker] ResMed’s Singapore factory which employs many workers from neighbouring Malaysia. He said ResMed has appealed to the Malaysian government for an exemption so its workers can travel to Singapore.

Biomerica has a new COVID-19 test with some apparently nice features that differ from the common PCR-based tests. However:

Biomerica is positioned to begin filling large international orders of this disposable one-use tests within weeks, assuming international product shipping channels remain open and active.

In addition, Biomerica has begun the application process with the FDA under the COVID-19 Emergency Use Authorization (EUA), aimed at the possible clearance and eventual use of the test in the US. At this time, the product is not available for sale or use in the US.

And finally, some related entertainment about flattening the curve of armchair epidemiology.

Book review: Where Is My Flying Car? A Memoir of Future Past, by J. Storrs Hall (aka Josh).

If you only read the first 3 chapters, you might imagine that this is the history of just one industry (or the mysterious lack of an industry).

But this book attributes the absence of that industry to a broad set of problems that are keeping us poor. He looks at the post-1970 slowdown in innovation that Cowen describes in The Great Stagnation[1]. The two books agree on many symptoms, but describe the causes differently: where Cowen says we ate the low hanging fruit, Josh says it’s due to someone “spraying paraquat on the low-hanging fruit”.

The book is full of mostly good insights. It significantly changed my opinion of the Great Stagnation.

The book jumps back and forth between polemics about the Great Strangulation (with a bit too much outrage porn), and nerdy descriptions of engineering and piloting problems. I found those large shifts in tone to be somewhat disorienting – it’s like the author can’t decide whether he’s an autistic youth who is eagerly describing his latest obsession, or an angry old man complaining about how the world is going to hell (I’ve met the author at Foresight conferences, and got similar but milder impressions there).

Josh’s main explanation for the Great Strangulation is the rise of Green fundamentalism[2], but he also describes other cultural / political factors that seem related. But before looking at those, I’ll look in some depth at three industries that exemplify the Great Strangulation.

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The stock market reaction to the election was quite strange.

From the first debate through Tuesday, S&P 500 futures showed modest signs of believing that Trump was worse for the market than Clinton. This Wolfers and Zitzewitz study shows some of the relevant evidence.

On Tuesday evening, I followed the futures market and the prediction markets moderately closely, and it looked like there was a very clear correlation between those two markets, strongly suggesting the S&P 500 would be 6 to 8 percent lower under Trump than under Clinton. This correlation did not surprise me.

This morning, the S&P 500 prices said the market had been just kidding last night, and that Trump is neutral or slightly good for the market.

Part of this discrepancy is presumably due to the difference between regular trading hours and after hours trading. The clearest evidence for market dislike of Trump came from after hours trading, when the most sophisticated traders are off-duty. I’ve been vaguely aware that after hours markets are less efficiently priced. But this appears to involve at least a few hundred million dollars of potential profit, which somewhat stretches the limit of how inefficient the markets could plausibly be.

I see one report of Carl Icahn claiming

I thought it was absurd that the market, the S&P was down 100 points on Trump getting elected … but I couldn’t put more than about a billion dollars to work

I’m unclear what constrained him, but it sure looked like the market could have absorbed plenty more buying while I was watching (up to 10pm PST), so I’ll guess he was more constrained by something related to him being at a party.

But even if the best U.S. traders were too distracted to make the markets efficient, that leaves me puzzled about asian markets, which were down almost as much as the U.S. market during the middle of the asian day.

So it’s hard to avoid the conclusion that the market either made a big irrational move, or was reacting to news whose importance I can’t recognize.

I don’t have a strong opinion on which of the market reactions was correct. My intuition says that a market decline of anywhere from 1% to 5% would have been sensible, and I’ve made a few trades reflecting that opinion. I expect that market reactions to news tend to get more rational over time, so I’m now giving a fair amount of weight to the possibility that Trump won’t affect stocks much.