Using Economics to Save Presents from the Economists

Economists like to hate on gift giving. Many of them consider purchasing a gift for another person as a futile attempt at imagining the preferences of another person. Given that you can’t perfectly know another person’s preferences, your gift selection will be sub-optimal. The argument goes that your friend or spouse or whomever would have been better off if you had given them money instead. Then they could have made the gift decision fully equipped with the information that is necessary to make them happiest.

There are some obvious things that are glossed over. Purchasing a good gift – or even writing a card – carries a big load of signaling value. People like to be liked and receiving a good gift signals that the giver cared enough to research appropriate gifts. Also, receiving money as a gift puts the onus of research and transaction costs on the receiver. If the recipient’s value of time is adequately high, then cash payments are even more resource destructive than giving a non-pecuniary gift. Especially if there is an expectation that the giver will later enquire about how the funds were used. At that point, the giver is saddling the recipient with all of the anxieties and costs of choosing a gift that makes another person happy.

But I want to talk about a non-obvious benefit of gift giving.

First, I want to talk about student loans (I promise, it’s relevant). Plenty of people argue that college students don’t understand debt and that they therefore don’t understand the future cost that they will bear by borrowing. When the lender is the department of education, there is no defaulting with the hope of bankruptcy. The debt will get repaid…. So far anyway.

If it’s true that students don’t understand debt, then we can appropriately construe future student loan payments as lump-sum costs. Of course there is deferment and forbearance – but put those to the side. The bottom line is that, almost regardless of a debtor’s activities, they must repay their debt. It doesn’t matter how the debtor earns or consumes, the debt must be paid. This fits the description of a lump-sum cost. Usually, things like lump-sum taxes are hypothetical and unpopular among the laity. But, if we accept that the decision-making-student has incomplete information in regard to the debt’s future payment implications, then the debt payments are exogenous and unavoidable from the future debtor’s perspective.

This is a good thing for the productivity of our economy. Because people are making tradeoffs between the two goods of leisure and consumption, a lump-sum tax causes individuals to work more than they would have worked otherwise. Lump-sum taxes don’t reduce the marginal benefit of working. Essentially, a debtor’s first several hours of work pay-off his debt first and then he gets to work for his own consumption.

Importantly, this ignores any human capital effects of the education. It doesn’t matter whether education actually makes people more productive. The seemingly exogenous debt payments cause debtors to work more and produce more for others. The RGDP per capita of our economy rises and we know that most of the benefits of work do not accrue to producers. Student debt, with the accompanying assumptions laid out above, therefore increases our incomes because it acts as a lump-sum tax.

Now it’s time to save presents from the economists.

As families get older and siblings drift apart, gift-giving begins to become less exciting. I’m tempted to say there is a natural process in which the first couple of adult-sibling Christmases include decent gifts. Then, the gifts become not-so-great as siblings become less familiar with each others’ preferences. Knowing this and still wanting to give a suitable gift, siblings may turn to gift cards. The less that a sibling knows the preferences of another, the more general the gift card.

If you’ve grown more distant from your brothers/sisters and you know that you’ll receive a gift, then it’ll probably be an Amazon, or Walmart, or some other gift card that permits spending on a broad variety of gifts. There comes a point when you’re spending $X on gift cards each year where $X = $x(n). That is, you’re spending some amount on each sibling for a total of $X each year. And for the sake of social cohesion and norms, all of your siblings are doing the same thing and spending the same amounts.

Importantly, you don’t control the social norms, nor your number of siblings. It might seem like you’re all just trading dollar bills at a unitary exchange rate, leaving no-one better or worse-off. But, trading cash is gauche. So, distant siblings trade broadly attractive gift cards in order to achieve that gift-like aura.

Social norms also say that gift giving is not a trade. If you don’t receive a gift, then you’re supposed to be ‘ok’ with that. So, each year you will spend $X on gift cards for your distant siblings and there is some probability that you get nothing in return. If you can’t control the number of siblings that you have and you can’t control whether you receive a gift card in return, then giving cash or cash-like gift cards to your siblings each year is a lot like a lump-sum cost. Socially – or maybe morally – you shouldn’t just ignore your siblings and it is incumbent upon you to give a gift.

Having to give away a lump-sum of money or money-like things no matter what else you do is a lump-sum cost. If people bear lump-sum costs, then they will work a little bit more and produce a little bit more for society. If gifts suboptimal but at least considered a ‘good’, then we’re better off: we work more to make others somewhat better off with resources that wouldn’t exist if we hadn’t chosen to give to others.

There are some caveats, of course. Economists are often not so popular at parties for a variety of reasons. One reason is that they flout social conventions. An economist might scoff at the social constraints as unbinding. Others would disagree. Another point of contention may be that an individual can choose to work no more, but to invest less instead. But this really just pushes the problem off until the individual has less income in the future and works more to compensate for it at a later time. A 3rd caveat is that we can choose the amount that we spend in others. But that just implies that at least part of the gift giving ritual isn’t a lump-sum cost. It does not imply that none of gifting giving is a lump sum cost.

Regardless, the social convention of giving gifts can provide for a Schelling point that makes us a more productive as a society. We spend on others, to a great degree beyond our individual control, in order to avoid severe social stigma. And, if we can’t control all of who counts as a worthy recipient of gifts, then we have a lump-sum cost to some degree. Giving gifts makes sense as a productive convention because it makes us a richer as part of a general equilibrium – if not a partial equilibrium. Merry Christmas.

Certificate of Need and Mental Health

Most US states require hospitals and other healthcare providers to obtain a “Certificate of Need” (CON) from a state board before they are allowed to open or expand. These laws seem to be one reason why healthcare is often so expensive and hard to find. I’ve written a lot about them, partly because I think they are bad policies that could get repealed if more people knew about them, and partly because so many aspects of them are unstudied.

States vary widely in the specific services or equipment their CON laws target- nursing homes, dialysis clinics, MRIs, et c. One of the most important types of CON law that remained unstudied was CON for psychiatric services. I set out to change this and, with Eleanor Lewin, wrote an article on them just published in the Journal of Mental Health Policy and Economics.

We compare the state of psychiatric care in states with and without CON, and find that psychiatric CON is associated with fewer psychiatric hospitals and beds, and a lower likelihood of those hospitals accepting Medicare.

Together with the existing evidence on CON (which I tried to sum up recently here), this suggests that more states should consider repealing their CON laws and letting doctors and patients, rather than state boards, decide what facilities are “economically necessary”.

Is Travel Back?

According to the most recent TSA data, on December 21st of this year there were 1,979,089 people traveling by plane. That’s almost exactly equal to the number of people that flew in the US on the same date in 2019: 1,981,433 travelers. It’s also double the number of people that few on December 21, 2020 (about 992,000). These numbers are encouraging. Does that mean that we’re back to normal levels of travel?

Not quite. We shouldn’t read too much into one day of data, for a variety of reasons, but most importantly because while we’re looking at the same date, travel varies throughout the week and December 21st is a different day of the week every year (Tuesday this year, Saturday in 2019). It’s better to use a weekly average and compare it to 2019. Here’s what the data looks like for 2020 and 2021.

With this data, we can see that airline travel is back to about 85 percent of 2019 levels. That’s not bad, but airline travel was already back to 85 percent by early July 2021, with some variation since then, but generally staying in the 70-90 percent range for most of the second half of the year.

For those that are flying this year, there is good news in terms of prices (unusual to have good prices news right now): airfares are still about 20 percent cheaper than pre-pandemic levels. In fact, airline prices are the cheapest they have been since 1999. In nominal terms! If you are interested in even more historical price data, take a look at my May 2021 post on the “golden age” of flight.

And of course, flying is not the most common way that people travel for Christmas and the holiday season. According to estimates from AAA, only about 6 percent of holiday travelers choose to fly. This was true in 2019, and will be roughly true in 2021 (as usual, 2020 was the exception: around 3 percent). By far the most common mode of travel in the US is driving, accounting for over 90 percent of holiday travel.

If you are traveling by car, there isn’t much good news for prices. As you have no doubt heard constantly for the past few months, gasoline costs a lot more than it did last Christmas, on average about $1 per gallon more. But even compared to Christmas 2019, gasoline prices are almost 29 percent higher. The last time gasoline prices were this high (in nominal terms) around Christmas was in 2013.

I hope you all have safe holiday travels, and we’ll all look forward to better prices in the New Year!

How Can Cryptocurrency Accounts Pay Such High Interest?

As noted last week, I am happily receiving 9% interest in my new crypto account at BlockFi. How can they do that? The short answer is that BlockFi lends out my holdings to other parties, who pay somewhat more than 9% interest to BlockFi. This model is common to essentially all of the crypto brokers who pay out interest, but I will focus on BlockFi because (a) I have skin in the game there, and (b) they have been fairly transparent about their operations.

On the simplest level, this operates like a plain bank savings account does. A bank takes in funds from depositors, and (to oversimplify) lends those funds out to borrowers. The bank then pays to its depositors a portion of the interest it receives from its borrowers. Up until the last few years, this bank savings account model worked pretty well;  a depositor might receive something like 2-3% interest on a savings account or certificate of deposit. More recently, short term rates have been near zero, so depositors get almost nothing in a bank savings account.

As noted earlier, BlockFi pays up to 4.5% interest on Bitcoin and 5% on Ethereum. These are leading, high volume coins that are widely used in decentralized finance (defi). Here is how BlockFi describes the parties to which it lends (mainly) Bitcoin:

Who Borrows Crypto?

BlockFi works with institutional counterparties for trading and lending cryptocurrency. These counterparties look to us to help them provide liquidity for their businesses. But who are some of these borrowers?

( 1 ) Traders and investment funds who see a fragmented marketplace and discover arbitrage trading opportunities. Arbitrageurs need to borrow crypto in order to close mispricing between exchanges or dispersed markets. Similarly, margin traders need to borrow in order to execute their trading strategies. This is a simple example, but it demonstrates how arbitrage and margin trading activities facilitate price discovery, which is an essential component of developed markets.

( 2 ) Over the counter (OTC) market makers make money by connecting buyers and sellers who do not want to transact over public exchanges. OTC desks need to keep inventory on-hand to meet their client demand. Owning crypto outright is capital intensive and comes with the attendant risks of price fluctuations. Instead, they may prefer to borrow inventory in order to facilitate transactions. Liquidity is another essential component to healthy markets.

( 3 ) Businesses that require an inventory of crypto to provide liquidity to clients. This bucket includes companies like crypto ATMs. These businesses also need to be able to support withdrawals while keeping the vast majority of their crypto assets in cold storage. The liquidity we provide them helps with these basic and important functions.

A key piece of this lending is to require that the counterparty post adequate collateral for the loans. This is somewhat similar to a bank lending you money to buy a house, with the house as collateral for your loan. If you lose your job and cannot pay back the loan, the bank has the right to sell your house to recovery its money. Similarly, BlockFi wants to ensure that if something goes sour with their loan of your Bitcoin, they can get their funds back and make your account whole. Obviously, BlockFi customers like me are relying on BlockFi to manage this properly and to minimize lending losses. BlockFi goes on to reassure us:

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Something is going on with shoplifting

Organized shoplifting mobs! Retailers claiming increases in shoplifting! Journalists claiming its an overstated numbers grift! Other journalists saying we should ignore shoplifting because corporate theft! The conversation about shoplifting is often hysterical and occasionally stupid, but that doesn’t mean something isn’t actually happening. Some of the facts seem clear, others murkier, and the underlying causes, like everything during this pandemic, are no doubt complex and uncertain. Let’s see if we can organize our thoughts a bit.

What we know

Shoplifting has been on the rise across the United States, with increasing theft of both staples for survival and the goods most easily resold on the black market. More specifically, and perhaps even more certainly, a still wealthy San Francisco, where one would expect retailers to desperately want a presence, can only seem to watch as its retailers flee. CVS is out. Walgreens is out. One Target it out (but not the biggest one). And the reason they claim is not commercial real estate overhead costs or declining customer bases, but an overwhelming increase in shoplifting (or what the retail industry used to call “inventory shrink”). While obviously not the whole story, the effective decriminalization of theft under $950 in San Francisco seems a key component. It doesn’t take any clever or subtle theorizing to expect that if the cost of theft under a certain threshold is radically lowered, then all you have to do is disaggregate your theft events across time and people to yield a sufficiently lucrative use of time (especially for those who are struggling or already carry the far weightier burden of a felony record). You can’t lower the opportunity cost of labor (less jail time) in a field of endeavor (boosting consumer goods) and pretend to be shocked when supply increases (more theft).

What we think

I am sure there is no shortage of “greedy corporations are abandoning American cities” and other malice-based theories, but those aren’t particularly useful theories. Retailers want customers and cities have a lot lot of them. So the first possibility is that they are simply telling us, and their shareholders, the truth– theft has reduced the profitability of stores such that the optimal decision is to close the doors. It would be a pretty shocking development to look back one day and realize that shoplifting was what closed the book on brick and mortar retail. Not Amazon or delivery drones, but the favored hobby of bored delinquents and subsidy of struggling families.

To those ends, though, a meteoric rise in shoplifting nonetheless feels, if not convenient, then incomplete as an explanation. CVS isn’t just closing in San Francisco, it’s closing 900 stores and moving to a new “store format”. Perhaps the better way of framing these closures isn’t a “crime wave of shoplifting” but rather more evidence that the brick and mortar retail industry is incredibly fragile, where any unforeseen increase in costs immediately threatens profitability. In a composite of shoplifting, online competition, the unabated growth of Costco and other wholesale clubs, and the rise in reservation wages of labor all across the country, which story would you want to emphasize to your shareholders as you close shops in urban centers? That you can’t compete? That you can’t afford labor? Or that you are being forced out by the crumbling of civilization into Mad Max dens of wayward lawlessness? At least the last one holds out hope that your business model isn’t wholly obsolete.

Still, people definitely seem to be stealing a lot of stuff, and that just creates one more cost advantage for online competitors and venues that require membership for admission. Things are changing, perhaps at an accelerated rate thanks to the pandemic and it’s accompanying bundle of policy responses. When considering fundamental change, observation of chaos rarely offers evidence to the contrary.

What can or should we do?

There are lots of things we should decriminalize. Lots. But I am extremely confident that theft is not one of them. The consequences are obvious, and in the short run will be felt almost exclusively by the poorest, who depend on local retailers, particularly those on the public transportation routes they take to work. Further, this is a problem that can metastasize as people don’t just supplement their incomes with theft, but specialize in it. It will hollow out the largest retailers and the smallest bodegas. It will change the the entire structure of physical marketplaces. It will change how people interact with core components of our welfare system. It will poison another relationship, this time between seller and customer, where people are increasingly viewed as a threat.

So what should we do? Desperate people stealing rice and other staples is one more argument for an unconditional universal basic income. People opting for black market income is one more argument for wage subsidies to increase relative attractiveness of wages in the legal market. And people stealing because the price of getting caught approaches zero? That’s an argument for raising the price of theft. Not to new and cruel heights, but to the levels they were at before i.e. high enough that theft is nothing but a last resort. A very last one.

Book Review: Cronyism: Liberty versus Power in Early America, 1607–1849

For the past few weeks, economist Patrick Newman has been doing the rounds for his new book (i.e. in the title of this blog post) on American economic history from 1607 to 1849. Well, its not only about American economic history. Its a bit more about the institutional history of the United States before 1850 and how it relates to economic history. It is an amazing book. Unfortunately, I expect many economic historians to ignore or fail to notice it. I hope that this blog post will at least reduce the likelihood of this happening because Newman’s book holds strong explanatory power if one is interested in the link between growth and institutions.

Newman’s argument is actually quite simple. First, there are two broadly-defined camps: the forces of liberty and the forces of power. Already, some may balk at this dichotomy but I would advise them not to. There are many reasons to keep going. The first is that It invokes an older tradition in historical studies that starts with Lord Acton and has been continued by numerous historians on the left and right. The other reasons become evident as one moves along in the book.

The forces of liberty are those that seek to constrain the state and the exercise of power. The forces of power, for their part, are those that seek to be empowered by a strong, capable and relatively unconstrained state. The forces of power, however, invite cronyism because the empowerment also permits personal aggrandizement (e.g. legally protected monopolies such as charters, tariffs, subsidies, grants, patronage).

The founding of the United States was, according to Newman, a battle between both forces with the British being the forces of power. After the Revolution, the forces of power continued inside the Federalist Forces — who basically dominated the constitutional convention of 1787 and the first Congress. Acting a de facto (because that is the title I give him) heir to Murray Rothbard, Newman adopts the position that the foundation of the US was in fact a rent-seeking bargain thanks to the federalists forces (Newman notably edited the lost volume of Rothbard’s Conceived in Liberty on the early republic).

After that, antifederalists and republicans coalesced into a working coalition that reinterpreted the constitution in a way that backfired against the Federalists and led to the Jeffersonian revolution of 1800. Important reforms, which Newman credits as being beneficial to living standards, were adopted. However, the Jeffersonians rapidly became corrupted by power. And here is the second reason to not balk at Newman’s dichotomy of the forces of power/liberty: people can move between camps. In other words, ideological commitment is not inelastic. Some in one camp or the other can switch when the rewards to do so change. However, the key point that Newman makes is that commitment to the forces of liberty is far more elastic than the commitment to the forces of power (which is more inelastic). The Jeffersonians’ commitment to liberty waned and they eventually enacted relatively similar policies to those of the federalists. They too engaged in cronyism. The same ebb and flow reoccurred later with the Jacksonians.

And here comes the third reason not to balk at Newman’s dichotomy: it actually hold pretty decent explanatory power. One common argument among financial and economic historians is that the United States may have sounded like a Jeffersonian project but the policies of the Early Republic and Antebellum were distinctly Hamiltonian (i.e. Federalist). To be sure, there is some evidence to that effect — which is what someone could retort to Newman. However, the old adage that “one in a glass house should not throw bricks” applies here. Revisions to the historical estimates of living standards have gradually swung in favor of the predictions associated with Newman’s model of the forces of power/liberty.

Consider this new article in Historical Methods by Frank Garmon (of Christopher Newport University). Garmon took issue with data from 1798 used by many scholars. In 1798, Congress introduced the a direct property tax to prepare for the possibility of a war with France. As Garmon succintly summarizes: “The law creating the tax consisted of three elements: a flat tax on slaves per head, a progressive tax on houses with rates escalating based on value, and a proportional tax on land based on value to make up the difference in each state’s obligation”. Other scholars, such as my co-author Peter Lindert and Jeffrey Williamson, argued that these features invited corruption during the assessing of tax liabilities. This was particularly true in the south because of the flat tax per slave. Thus, if one tries to use the tax data to estimate economic activity circa 1800, one has to augment it to some degree to reflect the geographically varying levels of corruption. Garmon finds that corruption was not an issue. The disparities pointed out by others (which made sense at first glance) could be largely explained by normal economic factors such as population density (which would affect land valuations etc.). Thus, Garmon argues that there is no need to deflate. As a result, he finds that incomes were roughly 5% lower in the southern states in 1800 (a proportion that would have been smaller in northern states).

Why is Garmon’s result relevant to Newman’s claim? Because any lowering of the 1800-level of income is going to increase the rate of growth from there to 1840 when the commonly-used estimates (produced by R.A. Easterlin) become available. Any increasing in that rate of growth goes in favor of Newman’s model because his prediction because the era from 1800 to 1840 is predominantly occupied with pro-liberty forces (even though there are ebbs and flows).

I am not in full agreement with Newman’s book and his Rothbardian narrative (I am much less fond of Rothbard than he is notably because of the tendency for villains and heroes to exist in his narrative). However, the reality is that Newman’s description (and the Rothbardian narrative he imports and adapts) holds strong explanatory powers.

Will we repeat the Christmas Covid wave?

EDIT at 7pm, same day as posting: You know you have good friends when someone quietly emails you and tells you that the news about Omicron just got much worse and you should probably edit your post. I’ve been trying to rationalized why this January will be better than last January. Of course if it were not for Omicron, I would expect very little from holiday gatherings among mostly-vaccinated Americans. However, having known Omicron was looming, I probably shouldn’t have even tried to speculate. Get your booster and be prepared to hunker down in January if the 2-3 week data indicates that infections are turning extra-lethal. </edit>

In keeping with the “dismal science” brand, let’s dwell on the horrible death toll of the January 2021 Covid wave in the US that followed the Christmas holiday. Here comes Christmas (and other winter holidays) again, a major public health event.

https://www.cnbc.com/2021/01/27/us-reports-record-number-of-covid-deaths-in-january.html

This graph I borrowed from CNBC shows how fast deaths spiked up after the winter holidays of 2020. See also https://data.cdc.gov/.

According to Google search auto-complete, the public is more interested in whether there will be another Christmas Prince movie than whether there will be another Christmas Covid death wave.

I think it’s unlikely that we will see a repeat of exactly what happened last year. I’ve been looking online for predictions and mostly I have found articles warning that Omicron will cause a some kind of wave. No one wants to commit to predicting how many people will die, because anyone who tries is sure to be wrong. The consensus is that breakthrough infections are likely but that vaccines protect against extreme illness.

Nearly a million Americans have died from Covid already (Jeremy argues for a million). Some of those deaths, in retrospect, can almost certainly be tied to family travel during the holidays in 2020. The January Covid wave has only happened once, so it’s impossible to predict what will happen this time. Unfortunately we may get an interaction from increased holiday travel plus a novel highly infectious variant.

The Omicron variant is spreading fast, but no one knows if it will be worse than we we are currently dealing with from Delta. It seems like triple-vaxxed people are not at high risk, from preliminary data. That is reassuring to me personally. Thank you South Africa for being fast and sharing data with the world. For communities with low vaccination rates, it seems certain that more deaths will result from fast-traveling Omicron. Yet, from my reading this week, it is hard to know if it’s really much worse than what they are currently experiencing from Delta.

I’m keeping a Twitter thread going of what other people are saying. Caleb Watney points out that we have two things going for us. Widely available vaccines keep people safer from infection and reduces the chance of needing medical treatment. Secondly, we have gotten better at treating the disease. Together, that should mean less deaths in January 2022, as long as people seek treatment quickly and hospital capacity does not become a limiting factor. Omicron could multiply cases so quickly that we can’t apply all our best treatments to everyone. That is the biggest reason to worry.

Even though people will be less cautious about winter holiday travel this year than they were last year, the country has been open for many months now, including the recent Thanksgiving holiday. The vulnerable population this time should be smaller, in terms of the people likely to die from Omicron.

To say that we won’t blindly exactly repeat the biggest mortality event of my lifetime is not “optimism”. It seems like this January will not be as bad as last January for the reason Watney states: better medical tech on hand, most importantly vaccines for prevention.

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Covid-19 & The Federal Reserve

I remember people talking about Covid-19 in January of 2020. There had been several epidemic scare-claims from major news outlets in the decade prior and those all turned out to be nothing. So, I was not excited about this one. By the end of the month, I saw people making substantiated claims and I started to suspect that my low-information heuristic might not perform well.

People are different. We have different degrees of excitability, different risk tolerances, and different biases. At the start of the pandemic, these differences were on full display between political figures and their parties, and among the state and municipal governments. There were a lot of divergent beliefs about the world. Depending on your news outlet of choice, you probably think that some politicians and bureaucrats acted with either malice or incompetence.

I think that the Federal Reserve did a fine job, however. What follows is an abridged timeline, graph by graph, of how and when the Fed managed monetary policy during the Covid-19 pandemic.

February, 2020: Financial Markets recognize a big problem

The S&P begins its rapid decent on February 20th and would ultimately lose a third of its value by March 23rd.  Financial markets are often easily scared, however. The primary tool that the Fed has is adjusting the number of reserves and the available money supply by purchasing various assets. The Fed didn’t begin buying extra assets of any kind until mid-March. There is a clear response by the 18th, though they may have started making a change by the 11th.  One might argue that they cut the federal funds rate as early as the 4th, but given that there was no change in their balance sheet, this was probably demand driven.

https://fred.stlouisfed.org/graph/?g=JYVL
https://fred.stlouisfed.org/graph/?g=JYVy

March, 2020: The Fed Accommodates quickly and substantially.

In the month following March 9th, the Fed increased M2 by 8.3%. By the week of March 21st, consumer sentiment and mobility was down and economic policy uncertainty began to rise substantially – people freaked out. Although the consumer sentiment weekly indicator was back within the range of normal by the end of April, EPU remained elevated through May of 2020. Additionally, although lending was only slightly down, bank reserves increased 71% from February to April. Much of that was due to Fed asset purchases. But there was also a healthy chunk that was due to consumer spending tanking by 20% over the same period.

https://fred.stlouisfed.org/graph/?g=JYXj
https://fred.stlouisfed.org/graph/?g=JYYz

In the 18 months prior to 2020, M2 had grown at rate of about 0.5% per month. For the almost 18 months following the sudden 8.3% increase, the new growth rate of M2 almost doubled to about 1% per month. The Fed accommodated quite quickly in March.

April, 2020: People are awash with money

Falling consumption caused bank deposit balances to rise by 5.6% between March 11th and April 8th. The first round of stimulus checks were deposited during the weekend of April 11th. That contributed to bank deposits rising by another 6.7% by May 13th.

By the end of March, three weeks after it began increasing M2, the Fed remembered that it really didn’t want another housing crisis. It didn’t want another round of fire sales, bank failures, disintermediation, collapsed lending, and debt deflation. It went from owning $0 in mortgage-backed securities (MBS) on March 25th to owning nearly $1.5 billion worth by the week of April 1st. Nobody’s talking about it, but the Fed kept buying MBS at a constant growth rate through 2021.

May, 2020 – December, 2021: The Fed Prevents Last-Time’s Crisis

Jerome Powell presided over the shortest US recession ever on record. The Fed helped to successfully avoid a housing collapse, disintermediation, and debt deflation – by 2008 standards. The monthly supply of housing collapsed, but it had bottomed out by the end of the summer. By August of 2021, the supply of housing had entirely recovered. The average price of new house sales never fell. Prices in April of 2020 were typical of the year prior, then rose thereafter. A broader measure of success was that total loans did not fall sharply and are nearly back to their pre-pandemic volumes. After 2008, it took six years to again reach the prior peak. A broader measure still, total spending in the US economy is back to the level predicted by the pre-pandemic trend.

The Fed can’t control long-run output. As I’ve written previously, insofar as aggregate demand management is concerned, we are perfectly on track. The problem in the US economy now is real output. The Fed avoided debt deflation, but it can’t control the real responses in production, supply chains, and labor markets that were disrupted by Covid-19 and the associated policy responses.

What was the cost of the Fed’s apparent success? Some have argued that the Fed has lost some of its political insulation and that it unnecessarily and imprudently over-reached into non-monetary areas. Maybe future Fed responses will depend on who is in office or will depend on which group of favored interests need help. Personally, I’m not so worried about political exposure. But I am quite worried about the Fed’s interventions in particular markets, such as MBS, and how/whether they will divest responsibly.

Of course, another cost of the Fed’s policies has been higher inflation. During the 17 months prior to the pandemic, inflation was 0.125% per month. During the pandemic recession, consumer prices dipped and inflation was moderate through November.  But, in the 16 months since April of 2020, consumer prices have grown at a rate of 0.393% per month – more than three times the previous rate. Some of that is catch-up after the brief fall in prices.

Although people are genuinely worried about inflation, they were also worried about if after the 2008 recession and it never came. This time, inflation is actually elevated. But people were complaining about inflation before it was ever perceptible. The compound annual rate of inflation rose to 7% in March of 2021. But it had been almost zero as recent as November, 2020. That March 2021 number is misleading. The actual change in prices from February to March was 0.567%. Something that was priced at $10 in February was then priced at $10.06 in March. Hardly noticeable, were it not for headlines and news feeds.

Hospital Merger Update

The panel on the proposed merger of Rhode Islands two largest hospital systems I mentioned last week happened yesterday, I’ll post some reactions here, there was a lot I didn’t get to say since my section only had 45 minutes split across 4 panelists and Senator Whitehouse naturally got more of the time.

The Lifespan and Care New England CEOs trying to merge their systems opened with what to me seemed like their weakest argument, a general appeal to togetherness. They said that if the Patriots offense and defense had to be kept as separate teams, they wouldn’t be very good. To me the right metaphor is that if you merged all the NFL teams into one super team, they wouldn’t try very hard.

To their credit though, overall the hospital CEOs and President Paxson of Brown University were surprisingly honest about the risks, basically acknowledging that hospital mergers are often just a way to gain market power at everyone else’s expense, but arguing that for various reasons this one is different. They seem to realize that if you define the relevant market area as the state of Rhode Island (as e.g. the Dartmouth Atlas does in their “Hospital Referral Regions”) then the merged entity would have a nearly 80% market share and be challenged by the FTC as an obvious monopoly. So they argue that the relevant market should include Boston and much of Connecticut. They argue that it won’t just be an excuse to raise prices because they are non-profits and the state has rate regulations.

They identified two potential true efficiencies, integrating the electronic medical records of the two systems and being able to easily conduct research across both systems (both systems have many employees who are faculty at Brown Med School, including my wife). In a reasonable world these efficiencies could be gained without merging, though I suspect HIPAA prevents this, meaning one of its many perverse unintended consequences would be incentivizing mergers.

Their biggest admission against interest was that “the primary benefit [of the merger] comes from scale” and that “scale matters for purchasing supplies and staffing”. To me this implies “don’t worry, we won’t use our monopoly power against consumers, we’ll just use it against suppliers and staff”. But the FTC just repealed their consumer welfare standard, and so I think these statements could come back to haunt the merging parties.

800,000 Deaths? Or 1 Million Deaths?

According to the Johns Hopkins COVID tracker, the US has now surpassed 800,000 COVID deaths during the pandemic. The CDC COVID tracker is almost to 800,000 too. But is this number right? Confusion about COVID deaths and total deaths has been rampant throughout the pandemic, especially when comparing across countries.

One method that many have suggested is excess deaths, which is generally defined as the number of deaths in a country above-and-beyond what we would expect given pre-pandemic mortality levels. It’s a very rough attempt at creating a counterfactual of what mortality would have looked like without the pandemic. Of course, you can never know for sure what the counterfactual would look like. Would overdoses in the US have increased anyway? Hard to say, though they had been on the rise for years even before the pandemic.

So don’t treat excess deaths as a true counterfactual, but just a very rough estimate. I wrote about excess deaths in the US way back in January 2021 (feels like a lifetime ago!), and at the time for 2020 it looked like the US had about 3 million total deaths (in the first 48 weeks of 2020), which was about 357,000 deaths more than expected (again, based on historical levels of the past few years), or about 13.6% above normal.

But once we had complete data for 2020, deaths were even higher: about 19% above expected, or somewhere around 500,000 excess deaths. This compares with the official COVID death count of about 385,000 in 2020 for the US.

What happens if we update those numbers with the most recent available mortality data for 2021? Keep in mind that data reporting is always delayed, so I’ll just use data through October 2021. The following chart shows both confirmed COVID deaths and total excess mortality, cumulative since the beginning of 2020.

As we can see in the chart, there are a lot more excess deaths than confirmed COVID deaths. There were already over 1 million excess deaths through the end of October 2021 in the US, cumulative since January 2020. This compares with about 766,000 confirmed COVID deaths. That’s a big gap!

We could spend a lot of time trying to understand this gap of 250,000 deaths. Is this under-reporting of COVID deaths? Is it deaths caused by government restrictions? Is it caused by the overwhelming of the health system?

I won’t be able to answer any of those questions today. Instead, let’s ask a different question: is the potential US undercount of COVID deaths unusual?

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