Month: April 2022

Highlights from EAGx Boston

James BaileyLeave a comment

Last weekend I was at Effective Altruism Global X Boston, a great conference that worked very differently from the academic ones I usually attend. The attendees were younger and the topics were different, but the big innovation was the use of Swapcard to encourage 1-on-1 meetings. At academic conferences I spend most of my time listening to formal presentations or talking to people I already know, but here I talked to 13 new people for a half hour each, and many others more briefly.

That said, the talks I did attend were excellent. Alvea is a 3-month-old company that already has a novel DNA-based Omicron-targeted Covid vaccine in Phase 1 trials. My notes on co-founder Ethan Alley’s talk:

Learning by doing is the way to go. I learned more in 3 months as a founder than 12+ months as an MIT grad student. Like that you have to pay a company $125k to randomize your clinical trial, and they take 8 weeks to do it

Richard Cash talked about the Oral Rehydration Therapy he helped develop that has saved tens of millions of lives. In short, many people who died of diarrheal diseases like Cholera were simply dying from dehydration, and he realized that this can be prevented cheaply and easily in most cases by having them drink a solution of water, glucose, and certain salts (basically Gatorade). He noted that much of the basic research behind this had been done in the US well before it was applied in the developing countries where it has helped most, so it was crucial to simply notice how important and broadly applicable the findings were. On the other hand, some things really did work differently in developing countries; here the medical conventional wisdom was that people shouldn’t eat while they had diarrhea, but if kids are already malnourished it turns out they are better off eating anyway.

Wave is a mobile payment company that is hugely successful in Senegal but has been slow to expand elsewhere. I asked their Chief Technical Officer Ben Kuhn why this was, and his answer made perfect economic sense:

Fixed costs plus local network effects. Fixed costs: need to get approval of a country’s central bank to operate, need to hire local staff, et c. Network effects: our system gets more valuable as more of the people you send money to/from use it, and these are usually within-country. Makes more sense to keep expanding within a country until its nearly totally saturated, and only then move to the next country. There’s also a limit of how much $ we have to expand, especially since we don’t want VCs to control the company.

(My notes, not a verbatim quote)

As I talked to people I was trying to narrow down my post-tenure plans. This didn’t really work, because people gave me good new ideas without convincing me to abandon any of my old ideas. Although I talked to several senior researchers at NGOs, the ideas that stuck with me most came from talking to undergrads, and were all things that sound obvious in hindsight but that I hadn’t actually been planning to do. The one I’ll mention here as a commitment device is to post my research ideas on my website. I have many more paper ideas than I have time to write about them, and I no longer care much about whether I get credit/publications for them or someone else does. This summer I’ll post a list of ideas there, and perhaps a series of posts fleshing them out here.

P.S. If you identify at all with Effective Altruism, I recommend trying to attend a conference. I’m planning to go next to the one in DC in September.

Deficits Are Here to Stay

Jeremy Horpedahl1 Comment

Last week President Biden released his Fiscal Year 2023 budget proposal. The annual release of the budget proposal is always exciting for economists that study public finance. The president’s proposal is the first step in the federal budgeting process, which in some cases leads to the full passage of a federal budget by the start of the fiscal year in October (though perhaps surprisingly, the process rarely works as intended).

This year’s budget is especially interesting to look at because it gives us our first look at what post-pandemic federal budgeting might look like. And while the budget has a lot of detail on the administration’s priorities, I like to go right to the bottom line: does the budget balance? What are total spending and revenue levels?

The bottom line in the Biden budget this year is that permanently large deficits are here to stay. Keep in mind that a budget proposal is just a proposal, but it’s reasonable to interpret it as what the president wants to see happen with the budget over the next 10 years (even if Congress might want something different). Over the next 10 years, Biden has proposed that budget deficits remain consistently right around 4.5% of GDP, with no plan to balance the budget in the near future.

How does this compare to past budget proposals? For comparison, I looked at the final budget proposals of Biden plus his two predecessors. I start Obama’s in 2021 to match Trump’s first year, and all three overlap for 2023-2026. I put these as a percent of GDP so we don’t have to worry about inflation adjustments (though we might worry about optimistic GDP forecasts, see below).

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The Different Classes of Crypto Stablecoins and Why It Matters

Scott Buchanan1 Comment

Last month the Biden administration issued an executive order outlining some priorities and aspirational goals regarding government initiatives and future regulations regarding cryptocurrencies.
These goals may be summarized as:

1.         Protect Investors in the Crypto Space

2.         Mitigate Systemic Risks from Innovations

3.         Provide Equitable Access to Affordable Financial Services

4.         Ensure Responsible Development of Digital Assets

5.         Limit Illicit Use of Digital Assets

6.         Research Design Options of a U.S. Central Bank Digital Currency (CBDC)

7.         Promote U.S. Leadership in Technology


These positions seem generally reasonable and moderate, and were welcomed by the cryptocurrency community, which had feared a more restrictive stance. (China, for instance, has banned cryptocurrency use altogether).

Why Fear Stablecoins?

Here I’d like to focus on #2, “Mitigate Systemic Risks from Innovations”. Although so-called stablecoins are not explicitly mentioned in the executive order, it is understood that they represent a key area of concern for regulators.

A stablecoin typically has its value pegged 1:1 to a leading national or international currency such as the U.S. dollar or the euro, or to some commodity like gold, or even to other cryptocurrencies. In practice, most of them have generally held pretty well to their pegs. So what’s not to like about them? Why would they be perceived as more of a threat that, say, bitcoin, whose dollar value is all over the map?

I think the reason is that market participants count on them maintaining their (say) dollar peg. These coins are used as dollar substitutes in billions of dollars’ worth of transactions and are depended on to hold their value.The total value of stablecoins in use is nearly $200 billion and is growing fast.  If a major stablecoin crashed somehow, it could lead to significant instability, which regulators don’t like.

Four Major Types of Stablecoins

Stablecoins may be classified according to how their “tether” is maintained:

( 1 ) Pegged to fiat currency, maintained by a central stablecoin issuer

The biggest U.S.-based stablecoin is USD Coin (USDC), which is backed by significant financial institutions. There is every reason to believe that there is in fact a dollar backing each USDC. Gemini Dollar (GUSD) is smaller, but also takes great pains to garner trust. Its issuer, Gemini, operates under the regulatory oversight of the New York State Department of Financial Services (NYDFS). It boasts, “The Gemini Dollar is fully backed at a one-to-one ratio with the U.S. dollar. The number of Gemini dollar tokens in circulation is equal to the number of U.S. dollars held at a bank in the United States, and the system is insured with pass-through FDIC deposit insurance as a preventative measure against money laundering, theft, and other illicit activities.”

So far, so good. The huge stinking elephant in the room here is a stablecoin called Tether. Tether is the largest stablecoin by market capitalization (at $79 billion), and is heavily used as a dollar substitute, mainly in Asia. It has been widely criticized as a shady, unaudited operation, operating from shifting off-shore locations to avoid regulation (and prosecution). There are justified doubts as to whether the claimed 1:1 dollar backing for Tether is really there. Tether sort-of disclosed its backing reserves in the form of a sparse pie-chart. Very little was in the form of cash or even “fiduciary deposits”. Some was in the form of “loans” to who-knows-what counterparties. The majority of their holdings were “commercial paper”; but nobody can find any trace of Tether-related commercial paper in the whole rest of the financial universe (it has become a sort of game for financial journalists to try to the be first one to actually locate any legitimate Tether assets).

So, Tether by itself may justify concern on the part of regulators. Also, without diving too deeply into it, a plethora of financial institutions and tech companies are starting to issue their own stablecoins, which again are purported to be as good as cash, and so are vulnerable to abuse.

( 2 )  Stablecoins backed by commodities

Tether Gold (XAUT) and Paxos Gold (PAXG) are two of the most liquid gold-backed stablecoins. Other coins are tied to things like oil or real estate. The holder of these coins is depending the  coins issuer to actually have the claimed backing.

( 3 )  Cryptocurrency Collateral (On-Chain)

It is hard to explain in a few words how this type of coin works.  A key point here is that your stablecoins are backed by other, leading cryptocurrecies (such as Ethereum), with the process all happening on the decentralized blockchainvia smart contracts. A leading coin here is DAI, an algorithmic stablecoin issued by MakerDAO, that seeks to maintain a ratio of one-to-one with the U.S. dollar. It is primarily used as a means of lending and borrowing crypto assets without the need for an intermediary — creating a permissionless system with transparency and minimal restrictions.

Unlike with the two types of stablecoins discussed above, you are not dependent on the honesty of some central issuer of the stablecoin. On the other hand, Wikipedia notes:

The technical implementation of this type of stablecoins is more complex and varied than that of the fiat-collateralized kind which introduces a greater risks of exploits due to bugs in the smart contract code. With the tethering done on-chain, it is not subject to third-party regulation creating a decentralized solution. The potentially problematic aspect of this type of stablecoins is the change in value of the collateral and the reliance on supplementary instruments. The complexity and non-direct backing of the stablecoin may deter usage, as it may be difficult to comprehend how the price is actually ensured. Due to the nature of the highly volatile and convergent cryptocurrency market, a very large collateral must also be maintained to ensure the stability.

( 4 ) Non-Collateralized Algorithmic Stablecoins

The price stability of such a coin results from the use of specialized algorithms and smart contracts that manage the supply of tokens in circulation,  similar to a central bank’s approach to printing and destroying currency. These are a less popular form of stablecoin. The algorithmic coin FEI proved unstable upon launch, although it has since achieved an approximate parity with the dollar.

Some takeaways:

Stablecoins are a big and fast-growing piece of practical finance.

These coins bring a different kind of risk, because (unlike Bitcoin or Ethereum), users depend on them holding a certain value.

For the coins backed by major fiat currencies or commodities,  risk is introduced by the need to depend on the honesty and competence of the centralized coin issuers.

For the non-centralized stablecoins like DAI and FEI, there are risks associated with proper automatic functioning of their protocols.

 

One can understand, therefore, the urge of the federal government to impose regulations in this area. That said, it does not seem to me that the existing system is broken such that the feds need to come in to fix it in a major way. The main shady actor in all this is Tether, which everyone knows to be shady, so caveat emptor (and the vast majority of Tether transactions occur outside the West, in the East Asian shadowlands).

Happiness is Zeno’s hedonic treadmill

mdmakowskyLeave a comment

I don’t take Maslow’s Hiearchy of Needs very seriously. I don’t much worry about hedonic treadmills. I don’t worry about a cursed existence where I am forever advancing half-way closer to whatever goal will bring happiness and emotional fulfillment.

I don’t worry about it, but I understand.

I’m struggling to find much inspiration sketching my little ad hoc economic models of daily life with the backdrop of Ukrainians struggling to survive in the face of an invading army. Perspective is a hell of a drug. This struggle has brought to the front of my mind Maslow’s Hierarchy of needs, which lays a psychological layering onto the economic prioritization of needs (food and shelter first, social needs second, “self-actualization” last). It’s the kind of model that gets used and abused because it adds a veneer of psychological depth to absurd reductionist theorizing. Don’t take my petty academic denigration too seriously, though. Just because I think it’s not particularly useful doesn’t mean it’s wrong.

Similarly, I find consternation over hedonic treadmills unnecessary because whenever your result is that utility is declining as resource constraints are loosening, the likely explanation is that you aren’t observing utility correctly. Specifically, there are dimensions to utility you aren’t observing, be it temporal (i.e. the distribution of future possibe utilities), network (i.e. sympathetic utilities of children, spouses, friends, etc), or most likely that you are in fact not observing utility but rather one of many inputs into total utility i.e. there’s more to utility than just “happiness”.

But maybe you’re not interested in how to optimally model the pursuit of happiness under the dual constraints of finite resources and the human condition. Maybe you’re just worried about managing your life under the limitations of your own flawed humanity. Maybe you’re worried about getting stuck on a hedonic treadmill, the carrot of self-actualization dangling forever just out of reach. Now I’m not a licensed therapist or trained psychologist, but I am an economist who has to constantly struggle against my own technical limitations. What that means is that I have a lot of experience solving problems beyond my own mathematical limitations, not through technical elegance but by simply hacking the problem until the problem solves itself.

You know. Cheating.

If you’re on a hedonic treadmill, all that really means is that you’ve defined your units wrong. It’s only a treadmill measured in feet. If you define happiness not as feet advanced but as having a positive first derivative in microns per microsecond, you can establish the model such that you’ll be long dead before you reach the dipping edge on the horizon. Happiness isn’t a destination or a journey. It’s a positive first derivative or, barring that, a sufficiently positive second deriviative. If that’s out of reach, f*** it, there’s a third one you can push into the positive.

Framed this way, Zeno’s paradox is no longer a curse, it’s a blessing. To always be advancing half-way to your goal for all eternity is to live in eternal bliss. To self-actualize. Whether you get there is outside the model. It’s irrelevant.

Which is a really long way of saying that one way you might hack the puzzle of self-actualization is to help support the physiological and safety needs of Ukrainians be transferring some of your resources to them as means of supporting the first-derivative of sympathetic inputs into your utility function.

A paper idea in Stigler (1964) on Oligopoly

Vincent Geloso1 Comment

Next week, I am teaching collusive agreements in my price theory class. I decided to take a different approach to the discussion than the one usually found in textbook. The approach consists in showing how economic thought on a topic has evolved over time. For collusion, I decided to discuss George Stigler’s 1964 article on the theory of oligopoly published in the Journal of Political Economy.

Simply put, Stigler proposes a simple approach for stating how collusive agreements can break apart by asking how much extra sales a firm can obtain by cutting its prices without being detected by other firms. Stigler argued that detection got easier as the number of buyers increased or as concentration increased. He also argued that detection became harder if buyers do not repeat purchases and if there is growth in the market through the addition of new customers as firms are not able to detect whether the growth of other firms is due to new customers or because old customers are purchasing its wares. Detection also became harder with a greater number of sellers but he also argued that this was of equal (or maybe lesser) importance than low repeat-sales rates or the arrival of new customers into the market.

This is pretty standard price theory and it is well executed. After postulating the theory, Stigler throws the empirical kitchen sink to see if, broadly speaking, his point is confirmed. One interesting regression is from table 5 in the article (which is illustrated below). That regression estimated rates for a line of advertising in newspapers market (i.e., cities) conditional on circulation in 1939 (its a cross-section of 53 markets). The regression itself is uninteresting to Stigler as he wants to consider the residuals. Why? Because he could classify the residuals by the structure of the market (with only one newspapers or with two newspapers. The idea is that more newspapers should be marked with lower rates as collusive agreements tend to be harder to enforce. Stigler thought this confirmed his idea that “that the number of buyers, the proportion of new buyers, and the relative sizes of firms are as important as the number of rivals” (p. 56).

While looking at Stigler’s regression, I thought that there might an interesting economic history paper to write. Notice that the source of the data used is cited below the table. Retracing that source and checking if (because there are clearly volumes of the Market and Newspaper Statistics) a panel can be constructed could allow for something interesting to be done. Indeed, a panel allows to directly test for the new customers’ hypothesis by adding a population growth variable. This advantage compounds that of increasing the number of observations. Both of those advantages could allow to test the relative importance of the mechanisms highlighted by Stigler.

A paper of this kind, I believe, would be immensely interesting. It is always worth engaging with important theoretical articles on their own terms. As Stigler set this test as one of his illustration, a paper that extends his test would engage Stigler on his own term and could provide a usefully contained discussion of the evolution of the theory of oligopoly. I honestly could see this published in journals like History of Political Economy or Journal of the History of Economic Thought or journals of economic history such as Cliometrica, European Review of Economic History or Explorations in Economic History.

When Keynes was gearing up for a second war

Joy Buchanan3 Comments

This is from The Price of Peace by Zachary Carter. What strikes me is the fact that a fleeing refugee doctor enabled Keynes to join the fight, again at the age of 58.

The following passage starts on page 316: “In the meantime, Keynes was at last in good health again. He owed his new energy in part to Hitler’s aggression. In 1939, Keynes had hired János Plesch, a Hungarian Jewish doctor who had relocated to London after fleeing Nazi persecution.

[Plesch resolved Keynes persistent throat infections by administering one of the earliest antibiotics (that was developed in German labs by Bayer before the war!).]

“After two decades of depression, however, the British economy was entering the fight of its life in ragged condition. … On the eve of war, worker productivity was 125 percent higher in the United States than it was in Britain.

“In the meantime, Germany had shifted its offensive focus to London. The Blitz…

“British diplomats didn’t have time to waste. After trying everything else, they brought in Keynes.”

“So Keynes went to Washington in May 1941 to negotiate more practical terms of cooperation and promptly infuriated nearly everyone he met.”

My thoughts: Money wins wars. Wars redistribute talent. Talent makes money. Is the cycle still going? Is this a post-industrialization phenomenon only? Will Tyler’s upcoming book on talent shed any light on this topic?

Two links for learning about Ukraine:

Post on the Donbas HT: Tyler

Podcast with Anne Applebaum on dictators (May overlap considerably with your Twitter stream of info, but at least you could walk while learning and take a scrolling break.)

Amazon Credit Card Rewards

Zachary Bartsch4 Comments

I have a credit card that gives me rewards. I get a nice 5% cash-back on purchases from Amazon and a lower cash-back rate on other purchases. Sometimes, there are promotions that provide a rate of 10% or even 15%. But what are these rewards worth?

To simplify, there are two reward options:

Option 1 adds to my Amazon gift-card balance. It’s attractive. When I’m checking out at Amazon, it shows me my reward balance and it also shows me what the total cost of my purchase could be if I applied the gift card. It’s like they’re trying to pressure me to redeem my rewards in this particular way.

Option 2 is simply to transfer my rewards as a payment on my credit card or as a credit to my bank account (for the current purposes, they’re identical). Either way, the rewards translate to the same number of dollars.

Say that I spend $1,000 at Amazon. Whether I choose option 1 or 2 has value implications.

Option 1

The calculation is simple. If I spend $1,000 at amazon this month, then I can spend another $50 in gift card credits at Amazon next month. That’s the end. There are no more relevant cashflows. I used my credit card one month, and then was rewarded the next month. The only detail worth adding is the time value of money, which at 7% per year*, yields a present value of rewards at $49.72. Option 1 is nice in the moment. It’s so enticing to have a lower Amazon check-out balance due.

But you should never select Option 1.

Option 2

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