We also heard stories about growing discontent in Northern Germany. In a small village along the Danish border a large group of former Danish nationals had gathered in a theater. A newsreel shot of Hitler boarding a new German built plane was flashed on the screen. As he was getting into the plane, someone in the audience shouted, “Greet Hess!” The film was stopped. Lights were turned on. The gestapo demanded the identity of the person who had shouted. They were met with silence. The show was discontinued, but the people sat for two hours singing Danish national songs. This is from Olga Guttormson, Ships Will Sail Again, Minneapolis: Augsburg Publishing House, 1942, p. 47. “Hess,” of course, refers to Rudolf Hess, Deputy Fuhrer of the Nazi Party, who, on May 10, 1941, flew solo to Scotland to try to engage in peace talks with the Duke of Hamilton, who he thought was opposed to Britain’s war policy. He was captured and spent the rest of his long life in prison, until he committed suicide at age 93. I came across the book while researching my upcoming talk later this month on Uncle Fred and Aunt Jamie’s being taken prisoner by a German raider in April 1941. Their ship, the Zam Zam, was sunk. Guttormson was one of 7 Canadian women (Aunt Jamie was another) held in Berlin. I found the story inspiring. (0 COMMENTS)

Mike Huemer’s new Justice before the Law is predictably excellent. I’ll eventually discuss it in greater depth, but for now I’ll focus on Huemer’s critique of plea bargaining.  The heart of the critique is that plea bargaining is coerced confession: It is universally agreed in legal theory that coerced confessions are unacceptable. The main reason is that to accept coerced confessions would conflict with the central purpose of the court system… Coerced confessions do not establish the truth, nor do they promote justice, since the innocent can be coerced to confess as well as the guilty. Now suppose that you’re innocent, and the prosecutor offers you this deal: “Plead guilty to get a sentence of 5 years in prison.  Or go to trial, and get 15 years with 90% probability.”  What are the odds that you’ll take the deal despite your innocence?  Very high indeed – and Huemer points out that this is a realistic scenario: In the actual status quo, defendants, in return for pleading guilty, are commonly offered sentences one third as severe as they could expect if they were convicted at trial. Standard rational choice theory dictates that in such a situation, a rational defendant accepts the plea bargain as long as his probability of being convicted at trial is greater than one third.13 Imagine, then, the spectacle of a defense attorney advising his client that, since he is “only” 60% likely to be acquitted at trial, it is in his interests to plead guilty. Or imagine a prosecutor deciding that, since the evidence he has gives him about a 35% chance of convicting a suspect at trial, it is worth going ahead and filing charges. Something has gone very wrong in a justice system in which those would be correct calculations. Surely a defendant who would probably be acquitted should not be given incentives sufficient to make it rational to plead guilty. Even worse: Prosecutors have enormous control over this factor and can and do adjust it in individual cases to take account of the strength of the case against the defendant. A prosecutor thus has a good chance of extracting a confession from a rational defendant given almost any nonzero probability of obtaining a conviction at trial. For instance, if there is just a 10% chance of convicting the defendant at trial (more precisely, if the defense believes there is a 10% chance), the prosecutor need only adjust his offer to ensure that the expected punishment if the defendant goes to trial and is convicted is more than ten times greater than the punishment offered in the plea agreement. Moreover: Experimental evidence confirms that innocent people can be induced to admit to wrongdoing. In one study, students were accused of cheating and were encouraged, through offers analogous to plea bargains, to admit their guilt. The study created conditions in which some students actually cheated, while others were innocent. The researchers found that actually guilty students were more willing to admit their guilt in exchange for leniency (89%), but that the majority of innocent students (56%) would falsely condemn themselves in conditions analogous to those of defendants in the criminal justice system. After reading Huemer’s critique, I realized that our plea bargaining system is epistemically inferior to extracting confessions using what I call “thoughtful torture.” Yes, “people will confess anything under torture.”  Torture’s most thoughtful defenders, however, have long insisted that the real point of torture is to get suspects to confess things they couldn’t know unless they were guilty.  Torturing someone to confess, “I did it!” shows nothing.  Torturing someone to show you where the missing body is buried, in contrast, reveals guilt, or at least complicity. Both plea bargaining and thoughtful torture unjustly punish the innocent.  Unlike thoughtful torture, however, plea bargaining doesn’t seriously try to unearth the truth.  Sure, you could give novel details when you plead guilty to a crime, but normally you merely need to parrot the prosecutor’s preferred narrative of the crime. Huemer’s main suggestion for reforming plea bargaining is to drastically reduce the difference between the sentence if convicted and the sentence if you plead guilty: The most serious problem with plea bargaining as currently practiced is that it creates incentives sufficient to induce rational defendants to plead guilty even if they are innocent and would probably be acquitted in a trial. In such a system, a defendant’s willingness to plead guilty does not provide strong evidence of his guilt; a court therefore cannot proceed to punish a defendant on that basis without violating its central duty to pursue justice in the case. This problem is mitigated by a sufficiently tight constraint on the trial penalty. A 20% trial penalty is unlikely to induce an innocent person to plead guilty. My alternative reform, in contrast, is that plea bargains should only be accepted if the accused reveals novel hard evidence of their own guilt.  If they know something they couldn’t have known unless they were guilty, or at least complicit, they can bargain for a reduced sentence.  Otherwise, no deals. Wouldn’t this merely amplify the problem of mass incarceration?  The opposite is true.  Right now, prosecutors only take 3% of cases to trial.  They handle the other 97% with plea bargaining.  Under my rule, prosecutors would have to take most cases to trial in order to secure a punishment.  And since they lack the resources to conduct vastly more trials, prosecutors would wind up dropping vast numbers of weak and low-priority cases.  For the individual criminal, plea bargaining is a way to avoid a harsh sentence.  For the criminal justice system, however, plea bargaining is a way to make harsh sentences the norm – for innocent and guilty alike. (0 COMMENTS)

I’ve posted twice now (here and here) on Sam Enright’s critique of my co-blogger Bryan Caplan’s case for open borders. I have two more points, one where I agree with an Enright critique and one where I disagree with an Enright compliment of Bryan. The critique I agree with is that Bryan’s analysis is too America-centric. This is what Bryan knows and this, plus Canadian immigration policy, is what I know. Together those two countries could easily take a few hundred million more people, as could western Europe. But it would be nice to see, in a book titled Open Borders: The Science and Ethics of Immigration, a multi-country approach. Possibly there are economists and other scholars in Europe and Japan who could extend Bryan’s work. The implicit compliment of Bryan’s work is in this paragraph from Enright’s critique: In the US, a disproportionate amount of innovation comes from immigrants. More inventors immigrated to the US from 2000 to 2010 than to all other countries combined. Immigrants account for a quarter of total US invention and entrepreneurship. Maybe this is just because America selectively lets smart and innovative people move there. But maybe there are some agglomeration effects going on here specifically related to immigration? Immigration and clustering people together seems to have been key to the success of various intellectual hubs throughout history, like the Bay Area recently, Vienna in the 20th century, and Edinburgh in the 18th century. This is a ripe topic for progress studies to tackle. Aesthetically, I agree with Caplan’s choice not to talk about this much. People talking about all the “amazing contributions” made by a certain immigrant group often comes off as condescending, in much the same way as token engagement with other cultures might. Make the case for immigration from prosperity and freedom, or don’t make it at all! The one criticism I had of Bryan’s book in my November 2019 review of his book was that he failed to make a closely related point. I wrote: While few people would accuse Caplan of understating the benefits from immigration, I am one of those few. Immigrants start businesses at a rate that is twice that of native-born Americans. Among the main beneficiaries of such immigrant employees, therefore, are American workers. Yet nowhere in his book did I find mention of that fact. It’s possible, of course, that this overstates the benefits to native Americans; think of the Korean dry cleaner that largely employs other family members. Still, the odds are high that most of these employers employ some non-family and non-immigrant workers. If a point in favor of immigration is both true and important, it should be made. Enright argues that making the point often comes off as condescending. I don’t see it. Complimenting people on their contributions seems like the opposite to me. If the formulation that bothers him is “amazing contributions,” that formulation can easily be changed to “large contributions.” Also, Enright ends his compliment by writing: Make the case for immigration from prosperity and freedom, or don’t make it at all! Ok, but the more innovators we have, the more prosperous we get. So making the case based on prosperity would seem to require noting the role of immigrant innovators. (0 COMMENTS)

As is so often the case in macroeconomics, the title of this post isn’t even a question. Terms like ‘supply’ and ‘demand’ are not clearly enough defined to make this a meaningful question. Whatever answer you provide is defensible, depending on how one defines terms. Let’s consider a few plausible possibilities. 1. Total aggregate demand (NGDP) has been rising at a rate of just under 4% over the past 7 quarters. This is close to trend. Thus there has been no unusual demand shock by this metric. 2. But the Fed doesn’t target NGDP; it targets inflation. Inflation has somewhat exceeded the Fed’s 2% target over the past few years. Thus policy was too expansionary by this metric. Therefore the problem is excessively expansionary monetary policy, i.e., too much demand. 3. But the Fed doesn’t just target inflation; it has a dual mandate that includes employment. Employment is still somewhat depressed. Indeed NGDP is one plausible way of think about the dual mandate, as it includes both inflation and real growth. And as we saw in point #1, by that metric demand is right on target. The question of whether there is too much supply or too much demand depends in part on what sort of benchmark you use. What is a “normal” or “appropriate” increase in aggregate demand? Opinions will differ. Even worse, the terms ‘supply’ and ‘demand’ have ambiguous meanings that differ between macroeconomics and microeconomics. And even worse, many people (most?) don’t understand this distinction. Ramesh Ponnuru has a tweet linking to an article that argues the inflation is due to supply issues. Someone responded to his tweet as follows: This tweet raises an interesting point; how do we think about sectoral demand shifts that look like supply shocks at the aggregate level? Readers of this blog know that I frequently point out that the AS/AD model has almost nothing to do with supply and demand as we use the terms in microeconomics.  Thus consider a sudden drop in demand for services due to Covid.  If the Fed does enough stimulus to keep total demand rising at 4%/year, then by necessity the demand for goods will soar well above trend to offset the decline in services. The problem here is that it’s difficult to suddenly turn unemployed hotel workers into truck drivers delivering goods.  Even harder to suddenly build more port capacity.  At a macro level, the excess demand for physical goods looks like a negative supply shock, and indeed in a sense it is a negative shock to aggregate supply.  For a given level of nominal spending, our economy is not capable of producing as much real output (goods and services) as before, at least relative to trend.  Reallocation is difficult.  That’s a negative aggregate supply shock at the macro level, and an excess demand for goods shock at the sectoral level. In the end, the debate about whether this is “actually” a supply or demand shock is completely sterile.  The terms are not well enough defined to offer a definitive answer.  It’s not an interesting question.  What is an interesting question is whether monetary policy is appropriate, too expansionary or too contractionary.  I suppose that those who view the current problem as “supply” are mostly content with the recent monetary stimulus.  Those who regard the inflation as due to “demand” mostly think Fed policy has been too expansionary.  If so, then they should say that directly. PS.  Nick Rowe once said: Some people argue about whether the macroeconomy is inherently stable or unstable. I don’t think that’s a very useful question. Because…..it depends. And one of the things it depends on is monetary policy. And that is a useful discussion to have, because we can actually do something about monetary policy. After I wrote the final paragraph of this post I was reminded of this Nick Rowe comment, and looked it up.  Now I feel that I almost plagiarized Nick.  Sometimes other people influence our thinking without us even realizing it.   (0 COMMENTS)

In 2020, Trump tried to ignore the results of the election.  His efforts were incompetent, but he was plainly searching for the button that says, “President for Life” – then push it.  And despite my blanket view that politicians are extremely power-hungry, I think that Trump was much more eager to become President for Life than any major U.S. presidential candidate in living memory.  The other candidates over the last century, in contrast, were basically normal Americans who happened to be extremely power-hungry.  Even FDR didn’t try to use World War II to postpone the 1944 election – and that would have been a fairly easy sell. The upshot is that if Trump runs for the Presidency again, he will very likely try to ignore the electoral results again.  And this time around, his supporters are planning ahead.  While Biden, not Trump, now has the incumbency advantage, this is a troubling prospect for anyone who values an honest democratic process. The standard reaction so far has been to take maximum advantage of unified government – and ramp up aggressive partisan rhetoric.  This makes sense if your goal is to get the policies you want.  Sure, the Republicans will try to undo some of them, but due to status quo bias, you’ll probably get to keep most of the policy changes you pass. However, if you value the small-d democratic process over big-D Democratic policies, there is probably a better path.  Namely: Strive to put Republicans’ minds at ease. How?  Take the initiative to de-escalate partisan tensions.  Conspicuously refrain from pushing for more government spending, more regulation, or more taxes.  Declare victory on Covid and return to normalcy.  Drop the rhetoric about “systemic racism” and end controversial indoctrination in public schools.  In short, make peace from a position of strength.  Say: “If we Democrats were half as bad as Republicans claim, we’d be pushing all kinds of crazy policies.  Instead, we’re giving the country a much-needed four-year vacation from acrimony.  For us, the preservation of American democracy has top priority.” Would this work?  Not on everyone, and certainly not on every Republican.  Yet it would probably sway tens of millions of non-Democrats.  And since the next election will otherwise be close, that’s crucial.  Furthermore, since Trump will probably be too old to run in 2028, and no successor is likely to enjoy similar devotion, that takes the country out of the danger zone.  Woke Twitter will hate you, but in exchange you avoid turning the U.S. political system into an imitation of Russia’s, Turkey’s, or Hungary’s. Some will object, no doubt, that Republicans are so crazy that they’ll paint the olive branch as a dagger-in-the-back.  And they’re obviously right about some Republicans.  I can’t imagine my strategy winning over Trump himself.  Fortunately, that’s not necessary.  As usual in democracy, you only need to win over the marginal actors.  You don’t even need to convince them to change their vote.  Just convince the marginal actors that the end is not nigh – that turning the U.S. into Australia or Venezuela is the furthest thing from your minds.  Once convinced, plenty will simply stay home.  I’ve said it before and I’ll say it again: Appeasement often works. Why, though, you may ask, should Democrats have to bear this burden?  If Republicans are endangering democracy, shouldn’t they be the ones who strive to put Democrats’ minds at ease?  The answer is that life’s not fair.  Republicans simply care less about democracy than Democrats, so they’re not going to spend political capital trying to save it.  Hence, their opponents have to pick up the slack.  As Galadriel tells Frodo, “This task was appointed to you. And if you do not find a way, no one will.” Admittedly, I could be wrong about Democratic priorities.  Perhaps getting their way today matters more to them than the fate of American democracy tomorrow.  Or maybe they just want to throw the dice and hope everything works out. (2 COMMENTS)

Have you ever been on a truffle hunt? Do you savor the memories of truffles shaved over your pasta or risotto? Are you a dog lover? If any of these apply, then this episode was made for YOU! EconTalk host Russ Roberts welcomed author Rowan Jacobsen to talk about his book, Truffle Hound. Jacobsen spent two years on the hunt for this “inspirational fungus” with its seductive scent. He learned a lot about the business of this gourmet delicacy, but also lots about culture, cooking, and of course, dogs. Let’s see what you took from this episode. Use the prompts below and share your thoughts in the comments, or use them to start your own conversation- preferable over a yummy bowl of tagliatelle al tartufo!     1- Why are truffles so expensive? Why do white ones cost more than black? What role do dogs play in the market for truffles?   2- How has “truffling” become a tourist attraction, and how does this experience compare to a REAL hunt? Should truffle hunters be mad or glad about the rise of fake tourist “hunts”? (Bonus if you use a supply and demand graph in your answer!)   3- Why do most people think they’re getting a great bargain with truffle oil? Truffle oil presents an economics puzzle: does introducing this super cheap ersatz version undercut the real thing or make the real thing more valuable?   4- Roberts reads the following quote from Jacobsen’s book: “Take a wild resource and enough time, and the locals will work it out, no government required.” What does this mean? How do truffle hunters manage to avoid the tragedy of the commons?   5- How did the influx of Chinese “fake” truffles affect the larger truffle market? What other disruptions are occurring in the market? (Hint: trees and cell phones are both mentioned in the conversation.) To what extent do you think this market will become increasingly “democratized”? Is that a good thing or a bad thing? Explain. (0 COMMENTS)

As regular readers of my posts know, I oppose lockdowns, favor vaccines, oppose government hyping the threat of Covid to children, and oppose government mask mandates. So when life starts to look kind of normal, especially for children, I cheer. I had much to cheer about last night, Halloween. Normally, we have 50 to 100 children come by and collect candy. Last year, we had 3. This year we had just over 60. Many of them wore masks, of course, because those were part of the costumes. But they were typically masks with holes for nose and mouth. In other words, they weren’t the kind you use to prevent the spread of Covid. Also, I didn’t see kids or their parents fretting about the fact that I wasn’t wearing rubber gloves while handing out candy. All in all, a normal evening. A couple of fun highlights: My pleasure is in asking the kids what they’re dressed up as because if it isn’t ghosts, witches, clowns, or Captain America, I don’t know. One young girl, who was probably about 10 or 11, said she was a character from Harry Potter and then with total pride told me she had read every Potter book and seen every Potter movie. Towards about 8:30, when the teenagers were coming by, one had a fun smart-ass comment. His friends had each been saying “Trick or treat.” He said, “I’ve been saying ‘Trick or treat’ all night. I’m due for a trick.” One interesting thing I noticed. We live in a fairly pricy neighborhood where there are not a lot of Latinos. But in a typical year, about 35% of the kids are Latino. This year I would put it at about 15 to 20%.   (0 COMMENTS)

Milton Friedman once debated Robert Mundell on exchange rates. Mundell advocated using monetary policy to fix the exchange rate, whereas Friedman suggested that this sort of price control was interfering with the free market, and thus a bad idea. Friedman was probably right that fixed exchange rates are a bad idea, but his argument was flawed in two very important respects. First, Mundell was advocating the targeting of nominal exchange rates. The real exchange rate (which is what matters) would still be set by the free market. That’s very different from things like rent controls and minimum wage laws, where the government controls the real price of a good or service. Second, Friedman’s own preferred monetary policy involved fixing the growth rate of the money supply, which is every bit as interventionist as fixing the exchange rate. In fairness, Friedman only advocated fixing the nominal quantity of money; the real quantity would still be determined by the public. Similarly, Keynesians favor targeting the nominal interest rate, but the real rate is still controlled by the public. Gold standard advocates favor defining the nominal price of gold, but the real price would still be determined by the public. I favor targeting NGDP, but real GDP would still be determined by the public. Commenter Andrew recently suggested: As long as we put the right Market Socialists in charge of centrally planning NGDP, we never have to pay any price for funding unprofitable investments out of money that hasn’t been voluntarily saved! Perhaps Andrew is referring to Friedrich Hayek, who favored NGDP targeting.  My response is that NGDP targeting is only “centrally planning NGDP” in the sense that targeting inflation is centrally planning the price level, or defining the dollar as 1/35 oz. of gold is centrally planning gold prices, or setting a limit of 22 million Bitcoin is centrally planning Bitcoin, or Tesla executives planning on producing 320,000 cars in Q4 is centrally planning Tesla output. Whoever is in charge of X gets to decide how X is run.  Whoever is in change of money gets to decide how money is run. When people use the term “central planning” as a pejorative, they usually have in mind something completely different.  They are thinking of a Soviet planning bureau telling all sort of other enterprises what sort of prices and output are appropriate.  How many shoes should be produced by enterprise X, how much steel should be sold to tractor company Y by steel mill Z.  Etc., etc. In contrast, setting a monetary policy is merely setting a policy for the very thing that the institution is in charge of producing.  Imagine visiting a monetary authority and asking them how they determine how much money they print, and hearing the response, “We don’t have any policy at all, we just produce money at random”.  You’d probably view that as being pretty weird.  Whatever policy a monetary authority has is a monetary policy, whether it involves setting an interest rate, a quantity of money, an exchange rate, a price of gold, or targeting the price of a NGDP futures contract.  And that’s equally true of publicly and privately produced money. Don’t waste time opposing “monetary policy”—there will always be monetary policy.  Spend your time opposing bad monetary policies. PS.  That’s not to say that we shouldn’t worry at all about central planning.  George Selgin recently pointed out that the nominee to head the Office of Comptroller of the Currency seems to favor replacing private bank accounts with government produced bank accounts.  I don’t know if that’s exactly central planning, but it’s certainly more of an infringement on the free market than NGDP targeting. (0 COMMENTS)

The cryptocurrency world has continuously grown since the launch of Bitcoin in January 2009. The novel cryptocurrency was initially launched as a payment technology, namely, to make peer-to-peer transactions without the need for a financial intermediary between the parties.1 That the cryptocurrency phenomenon unveiled during the 2008 crisis is no accident. Justified or unjustified, it is another reaction against the so-called “evil” financial market during the financial crisis. Since then, the question of whether cryptocurrencies such as Bitcoin can become money has been at the center of much discussion and debate. The recent monetary reform in El Salvador, which mandates the acceptance of Bitcoin as a means of payment, only fuels the debate over the feasibility of cryptocurrencies as money. History shows that new moneys do emerge. History also shows that private money can work as efficiently, if not more efficiently, than state money. Yet cryptocurrencies in general, and Bitcoin in particular, face a few significant challenges to becoming well-established money, that is, a commonly accepted means of exchange. Much expectation rests on Bitcoin, the forerunner in the crypto-world. However, Bitcoin faces three crucial challenges to becoming money: (1) the scalability constraint, (2) the need to break network effects, and (3) the problem of choosing the right monetary rule. The scalability constraint problem This problem relates to the number of transactions that a cryptocurrency technology can verify per second (TPS–transactions per second). Consider the situation when you buy a coffee at a coffee shop. You swipe a debit or credit card, and after just a few seconds and beeps, the transaction is verified and approved. A few moments later, you get your cup of coffee. For instance, VISA can certify up to 56,000 TPS. Paypal can do up to 115 TPS (0.2-percent of VISA). Bitcoin can only authenticate seven transactions per second. Bitcoin’s TPS is well suited for a small community with only a few transactions. But, as the number of Bitcoin users and transactions increases, a bottleneck occurs, delaying transactions beyond a threshold acceptable for a well-functioning means of exchange. Ironically, miners who certify Bitcoin transactions can charge a fee to move a transaction up the line—a similar type of fee that ideally would be avoided with a peer-to-peer technology such as blockchain. The scalability constraint can be a significant deterrent for a cryptocurrency to graduate to money. The issue is not simple. For many cryptocurrencies, increasing their TPS capacity means reducing the safety of their transactions. Intuitively, the faster a transaction is verified and recorded in the blockchain, the easier it is for a miner to pass a fake transaction to the record. On the contrary, the more time a transaction waits to be verified, the more time for other miners to spot a fake trade being added to the network and take action before it becomes final. A new cryptocurrency that wants to have a competitive TPS can do so at the expense of less security or resigning itself to being a decentralized network. VISA, for instance, is a centralized network (only VISA gets to see the transactions that need verification). For cryptocurrencies built on decentralized doctrine, this is not an option because decentralization is part of their identity. Yet, there are two options to get around the scalability constraint. The first one is called SegWit, a shorthand for segregated witness. It works this way. A block in the blockchain contains information such as the transaction amount and “witness” information such as a timestamp. By moving the “witness” information to an attached block, the SegWit, space is freed for more transactions to be added to the main blockchain. SegWit allows increasing the TPS without sacrificing the information being recorded in the blockchain. SegWit is one of the options to increase Bitcoin’s TPS. The second one is known as the lightning network. In this case, two parties open their private communication channel to perform all their business transactions (secured by a smart contract). Once their business is complete, they only report the final balance to the main blockchain. Say, for instance, that two parties perform ten transactions in their business. Then, all they have to do is report to the main blockchain their final transaction that cancels any outstanding balance between the parties. The previous nine transactions take place in the “lightning network.” This parallel blockchain allows for fast and immediate certification of the first nine transactions between the involved parties. Whether SegWit and the lightning network are enough to deal with the scalability constraint is yet to be seen. These two developments remain examples of private solutions to what is perceived as a high transaction cost in the Bitcoin network. Network effect problem “Money is a network good. The more individuals and firms use the same means of exchange, the more beneficial it is to use the same means of exchange.” An important characteristic of money is that it depicts network effects. A network good is one whose utility depends on the number of individuals connected to the network. A typical example is a phone. These goods are useless if no one else has one—no point in having a phone if there is no one to call. The more individuals have a phone, the more utility this device yields to the consumer. A more modern example would be social networks such as Facebook, Twitter, or Instagram. Money is a network good. The more individuals and firms use the same means of exchange, the more beneficial it is to use the same means of exchange. If everyone around me uses U.S. dollars, it is easier for me to use U.S. dollars even if I like Bitcoin better. Because of the network effect, network goods compete in contestable markets. These are markets where competition is for all-or-nothing. The network good that wins takes all or most of the market share, and the network good that loses must leave the market or only capture a minor share. The presence of network effects is, of course, significant. Any cryptocurrency that aims to become money must break the network effect of already well-established currencies. Network effects are tough to break even for higher-quality goods. Remember the short-lived experience of Google+, intended to compete with Facebook? The toughness of network effects is not mere speculation. We can look at real-world examples. A relevant one for this discussion is the fate of the Somali shilling after the collapse of the government. The Somali shilling value went into a free fall. There was no enforcement to keep Somalis using their national currency. All they had to do was start using the money of any of their neighbors and trade partners. Yet, a currency (or network) swap did not occur. The network effect was just too strong. Cryptocurrencies face a much tougher challenge. Cryptocurrencies are not contesting the market for depreciating currency, as was the case with the Somali shilling. They contest the market for currencies such as the U.S. dollar, the Euro, the British Pound, or the Japanese Yen (to mention just a few). Breaking the network effect is not easy. Yet, some market processes help in this respect. Take the presence of a middleman between a buyer and a seller. Say a consumer who owns cryptocurrency wants to purchase a good from a seller who wants U.S. dollars. There is an entrepreneurial opportunity to become the middleman between these two. The middleman takes the cryptocurrency from the buyer and gives U.S. dollars to the seller. Problem solved. The buyer uses his crypto, and the seller gets his dollars. The seller does not want exposure to the price volatility risk of a cryptocurrency such as Bitcoin, but the middleman seeks to profit from that risk. These middlemen are unintentionally helping to expand the cryptocurrency network. Yet, it is doubtful that the presence of these middlemen is enough to break the network effect of currencies that are well established at the international level. Even the middlemen measure their profits in terms of U.S. dollars (or any other currency). Any cryptocurrency that aims to become money should pay serious consideration to the presence of network effects.2 The monetary rule problem The third problem I want to comment on is how the supply of cryptocurrency should behave. For exposition purposes, I divide cryptocurrencies into three generations. The first generation of cryptos is built around a fixed supply conception. This is the case with Bitcoin. Even if the money supply increases for these cryptocurrencies, it does so at a decreasing rate up to the point where no more cryptos are created. The concept is that of a fixed money supply, even if the application is not a literal one. The second generation of cryptos are stablecoins that fix their exchange rate with a currency such as the U.S. dollar. In this case, the supply of cryptos varies (or should vary) as needed to maintain the exchange rate fixed. The third generation is a more recent development. In this case, the cryptocurrency neither fixes the money supply nor the exchange rate against another currency. Now changes in supply are aimed at maintaining monetary equilibrium. If demand goes up, more cryptos are created. If demand goes down, cryptos are taken out of circulation. This is the case of yet-to-be-launched Quahl (formerly known as Initiative Q). The problem with the first generation of cryptocurrencies should be apparent. Their supply cannot accommodate changes in demand. In other words, the fixed-supply conception is a recipe for monetary disequilibrium and high price volatility. The fixed supply notion is a problem for a cryptocurrency to become money. Still, it is a good feature for trying to reap capital gains (buy at a low price, sell at a high price). If supply is fixed (a vertical line in the typical demand and supply graph), any change in demand translates to price changes. No wonder currencies such as Bitcoin are so volatile. No wonder, also, that cryptocurrencies such as Bitcoin have become more of an investment vehicle than a new type of money. On the contrary, if the supply is horizontal, then any change in demand produces a change in the quantity supplied with no impact on its price. The problem with the second generation of cryptocurrencies is that, as long as they maintain their fixed exchange rate policy, they become a substitute, but not necessarily a competitor, of other currencies. And, if they abandon the fixed exchange rate policy, they are not stable anymore. These are cryptos without their own monetary identity. They do not have an independent monetary policy. Because they are fixing themselves to another currency, they cannot provide a higher-quality monetary policy than their pegged currency. The third generation of cryptocurrencies has a more suitable constitution in terms of potentially becoming money. But, they face the challenge of deciding the behavior of their cryptocurrency supply. We may understand the principle that money supply must equal money demand to achieve monetary equilibrium. Yet, this does not mean we know how to operationalize this principle. Don’t central banks around the world face similar problems? It is straightforward to code a fixed supply of cryptocurrencies. But, it is complicated to code the rule needed to maintain monetary equilibrium. Looking at the case of Bitcoin, one gets the impression that the leading cryptocurrency may have been inspired by an incomplete picture of the gold standard. Its logo is a gold coin; Bitcoin producers are called miners, and the quantity of bitcoins follows an output function with decreasing marginal returns (just as would be the case of mining gold out of the ground). Why do I say the inspiration is incomplete? Because the gold standard, or maybe more precisely a free banking regime, did not work just with gold coins. Besides gold, there were banks that issued convertible banknotes. Money supply did not depend only on the production of gold (primary creation of money) but also on the issuance of banknotes (secondary creation of money). This secondary creation of money plays a crucial role in maintaining monetary equilibrium. It seems, once again, we have an ironic turn of events. Cryptocurrencies came to be in order to avoid financial intermediaries. Yet, these financial intermediaries play a crucial role in maintaining monetary equilibrium, the desired feature of any cryptocurrency aiming to become money rather than another payment channel or technology. The case of El Salvador: No more than a pyrrhic victory Some circles in the crypto world celebrated El Salvador’s decision to enforce the circulation of Bitcoin.3 On June 6th, 2021, El Salvador’s president, Nayib Bukele, announced a new law that would make Bitcoin the country’s official currency. That this decision took place in a dollarized country only adds to the excitement of Bitcoin gaining market share. On June 8th, the law was presented to Congress and passed as a new law. The biggest issue with Bukele’s initiative is the now-famous Article 7. This article states that every “economic agent must accept bitcoin as payment when offered to him by whoever acquires a good or service” (bolds added). An exception is allowed if the merchant does not have the technology to transact in Bitcoin. The same law, however, clarifies that the state will “promote the necessary training and mechanisms” needed for unprepared merchants to be able to accept bitcoin as payment (article 12). El Salvador’s adoption of Bitcoin is, at best, a pyrrhic victory. Suppose Bitcoin becomes a significant means of exchange in El Salvador. This outcome is so by force of law, not by an emergent choice of economic agents freely and spontaneously interacting in the market. Suppose now that Bitcoin fails to become a significant means of exchange in El Salvador. In this case, even with legal enforcement, Bitcoin cannot become a major currency. One would expect that the rise of Bitcoin to money would be driven by its own merits and benefits, not by the state’s regulatory power. Final comments For more on these topics, see the EconTalk podcast episode Jim Epstein on Bitcoin, the Blockchain, and Freedom in Latin America. See also “Cryptocurrency, Money, and Adam Smith,” by John Burrow, Adam Smith Works, January 13, 2020; and “The Economics of Bitcoin,” by Robert P. Murphy, Library of Economics and Liberty, June 3, 2013. Even though my comments may sound pessimistic, I think of them as a realistic assessment of cryptocurrencies becoming a generally (very widely) accepted means of exchange. There is much to be expected from the cryptocurrency phenomenon. Yet, any hope that a cryptocurrency will become money must be realistic regarding the challenges that this evolution implies. First-generation cryptocurrencies can evolve to become high-risk/high-return investment vehicles. Second-generation cryptocurrencies can grow to become payment technologies free of price volatility risk. Finally, the third generation of cryptocurrencies has a better chance to work more similarly to money if they manage to capture some market share and maintain monetary equilibrium (not an easy task). Footnotes [1] Satsohi Nakamoto, “Bitcoin: A Peer-to-Peer Electronic Cash System.” Bitcoin.org. PDF file. [2] Malakiva Nair and Nicolás Cachanosky, “Bitcoin and entrepreneurship: breaking the network effect,” The Review of Austrian Economics. July 18, 2016. [3] George Selgin, “The Bitcoin Law: Nayib Bukele’s Counterfeit Free Choice in Currency.” Alt-M.org. June 17, 2021. *Nicolás Cachanosky is Associate Professor of Economics at Metropolitan State University of Denver (MSU Denver) Department of Economics, Senior Fellow at the American Institute of Economic Research (AIER), and Fellow at the UCEMA Friedman-Hayek Center. As an Amazon Associate, Econlib earns from qualifying purchases. (0 COMMENTS)

The central problem in monetary policy is that the variables that a central bank can easily control on a day-to-day basis, such as the fed-funds rate, the monetary base, and the price of gold, do not reliably correlate with the things we care about, such as the CPI, unemployment, and nominal GDP. –Scott Sumner, The Money Illusion, p. 199.1 Monetary theorists write treatises. It’s who they are. It’s what they do. John Maynard Keynes published A Treatise on Money in 1930. Subsequently, he became a Keynesian, and he wrote a new treatise, The General Theory of Employment, Interest and Money, published in 1936. In 1956, Don Patinkin published Money, Interest, and Prices. In 1963, Milton Friedman and Anna J. Schwartz published A Monetary History of the United States. The latest monetary treatise is Scott Sumner’s The Money Illusion. In his book, he attempts to tackle the usual problems of explaining how changes in monetary policy affect prices, interest rates, and employment. Four Thought-experiments Sumner carefully distinguishes four effects of money on interest rates. He calls these: the price-level effect; the liquidity effect; the income effect; and the Fisher effect. Each can be illustrated with a different thought-experiment involving a monetary “expansion.” For example, consider the classic Helicopter Drop, a one-time injection of more money into the economy. If the government doubles the money supply by dropping dollar bills from a helicopter, then this should eventually double the level of prices. Suppose that prices adjust right away, so that we reach the new equilibrium right away. In that case, the interest rates stay the same. The price-level effect is zero. But if prices are sticky in the short run, the helicopter drop causes a decrease in interest rates, due to the liquidity effect. Think of this as a drop in borrowing because people have more money than they need relative to those sticky prices. Only after prices have adjusted do we arrive at the equilibrium in which interest rates return to previous levels. Suppose we try a different thought-experiment. Instead of a one-time injection of money, consider an increase in the rate of money growth. This will lead to an increase in inflation. In order to maintain the inflation-adjusted value of assets, savers will require higher interest rates. The result is the Fisher effect—the higher the rate of inflation, the higher are nominal interest rates. Faster money growth would tend to increase interest rates. As another thought-experiment, suppose that the Fed surprises the public by raising the rate of money growth. Because inflation does not immediately adjust upward, there is an economic boom, and with the boom there is an increase in interest rates. I won’t go into the reason for the boom, but an explanation can be found in Sumner’s book and elsewhere. “The bottom line is that “loose” money can result in no change in interest rates, a decrease in interest rates, or an increase in interest rates, depending on which thought-experiment we are conducting.” The bottom line is that “loose” money can result in no change in interest rates, a decrease in interest rates, or an increase in interest rates, depending on which thought-experiment we are conducting. Targets, Indicators, and Instruments In 1975, Benjamin Friedman (no relation to Milton Friedman), published an article that sought to clarify the difference between the targets of monetary policy, the indicators of monetary policy, and the instruments of monetary policy.2 A target is a variable for which the monetary authority has a desired value. In the United States, the Fed could have a desired value for the unemployment rate or for the Consumer Price Index, for example. An indicator is a variable that the Fed can use to anticipate how close it is coming to its target. An instrument is what the Fed actually does to try to move the economy toward its target. The classic textbook instruments when I was studying economics were the discount rate (the rate that the Fed charges member banks to borrow funds), the reserve requirement (the fraction of deposits that banks must hold as reserves), and open market operations, which are purchases or sales of securities by the Fed. Market monetarism, as I understand it, is the view that: (a) the appropriate target for monetary policy is a level of total spending (nominal GDP or NGDP) one year from now (say) that is in line with the long-term trend that the public has come to expect. (b) the appropriate indicator for monetary policy is the forecast for NGDP one year from now (say) as given by financial markets. If this indicator suggests that NGDP will come in below target, then the Fed should use one of its instruments in an expansionary way, and conversely. (c) the preferred instrument for monetary policy should be open market operations. Note that if interest rates on short-term government bonds drop to zero, open market operations can shift toward buying long-term bonds, private securities, or foreign exchange. This is not too different from the way that the Fed operated when I was an economist there, in the early 1980s. The difference is that the indicator that the Fed used was known as the Greenbook Forecast for NGDP and other macroeconomic variables. The forecast always was enclosed in a green cover, and it was highly confidential. The Greenbook Forecast was nominally a forecast from the Fed staff. I was nominally in charge of it at least three or four times. But I can tell you that my role, and that of the staff in general, was purely clerical. Our job was to produce the forecast that the Fed Chairman wanted to see inside that green cover. The Chairmen when I was at the Fed were Paul Volcker and then Alan Greenspan. Volcker at times appeared to delegate the supervision of the Greenbook forecast to Lyle Gramley, a former staffer who had been appointed one of the Fed governors. I recall one lunch late in 1982 when Governor Gramley sat down at a table in the staff dining room with some of us. This was almost a shocking breach of protocol, because the governors had their own executive dining room, and on no other occasion did I see a Governor eat in the staff dining room. But Governor Gramley wanted to tell us that our forecast was too conservative because, in his words, “When a recovery comes, it really comes.” Of course, we adjusted the forecast. As far as I can tell, the only change that has taken place since then is that the Fed is now much more public about forecasts. Members of the Fed’s Open Market Committee are invited to make forecasts, and the public is given a window into those forecasts, albeit with a short lag. This method of operation is known as discretionary monetary policy, because the Fed changes policy at the discretion of its top officials. Milton Friedman, John Taylor, and other leading monetarists of the late 20th century scorned discretionary policy. They argued that the Fed’s forecast was an unreliable indicator of future economic performance, and discretionary policies based on this unreliable indicator would produce volatile results. Friedman argued that a measure of the money supply was a more reliable indicator. Taylor proposed that a weighted average of the latest measures of unemployment and inflation could serve as a better indicator. Market monetarism differs from late 20th century monetarism in that it takes us back to discretionary policy. But it differs from the way the Fed uses discretion in practice by proposing that the Fed use financial market indicators to make its forecast. If I were a market monetarist, I would be trying to come up with an algorithm to forecast NGDP using indicators like stock prices, exchange rates, and the spread between the interest rates on normal bonds and inflation-indexed bonds. If we had such an algorithm, we could benchmark it against the more seat-of-the-pants forecast judgments that are currently made at the Fed. But Sumner does not propose such an algorithm, and I found this disappointing. Instead, he gives examples of where stock price declines in 2007 and 2008 indicated to him that NGDP was going to be far below target. One example he goes into at great length is a stock market decline that took place on December 11, 2007. That’s when the Fed announced a disappointingly small rate cut (0.25%, from 4.50% to 4.25%). I could write a whole book on this decision, because it has vast implications for monetary theory. But let’s start with some basic data. … The Dow Jones Industrial Average immediately plunged by almost 1.5%, and ended the day almost 2.5% below the preannouncement level. (p. 251) That is a significant decline, to be sure, but there have been much larger one-day declines in stock prices on other days. Sumner does not say, nor should he, that one-day stock price declines always indicate that NGDP is going to be below target. The vast majority of such declines were not followed by disappointing NGDP growth. So how did Scott Sumner know that this particular stock price decline, as well as those that took place in the latter part of 2008, were an indication that NGDP as going to fall well short of its target? It seems to me that unless he can articulate his algorithm, Sumner’s version of market monetarism is impossible to operationalize. If seat-of-the pants analysis of the stock market is the way to forecast NGDP, then for all we know, members of the Federal Open Market Committee may have always been implementing market monetarism. For more on these topics, see the EconTalk podcast episodes Scott Sumner on Monetary Policy and Scott Sumner on Money, Business Cycles, and Monetary Policy. See also Monetarism, by Bennett T. McCallum, Concise Encyclopedia of Economics. To get around the need to explain how to infer NGDP forecasts from financial markets, Sumner suggests using a futures market in NGDP itself. An NGDP futures market is essentially a betting market, in which individuals can go long when they have information that suggests that NGDP will turn out to be higher than the current “price” and go short when their information suggests the opposite. Would an NGDP futures market provide a reliable guide for discretionary monetary policy? That seems like an empirical question. But my guess is that if NGDP can be accurately forecast by speculators, then the market NGDP forecast can already be extracted from the above-mentioned indicators. An assertion that you made a better forecast of NGDP than the Fed did in 2007, even if that assertion is true, does not prove your case. If I were a market monetarist, articulating an NGDP forecasting algorithm derived from market indicators, and demonstrating its reliability through a variety of historical episodes, would be high on my research agenda. Footnotes [1] Scott Sumner, The Money Illusion: Market Monetarism, the Great Recession, and the Future of Monetary Policy. University of Chicago Press, 2021 [2] Benjamin Friedman, “Targets, Instruments and Indicators of Monetary Policy.” Journal of Monetary Economics. 1975. *Arnold Kling has a Ph.D. in economics from the Massachusetts Institute of Technology. He is the author of several books, including Crisis of Abundance: Rethinking How We Pay for Health Care; Invisible Wealth: The Hidden Story of How Markets Work; Unchecked and Unbalanced: How the Discrepancy Between Knowledge and Power Caused the Financial Crisis and Threatens Democracy; and Specialization and Trade: A Re-introduction to Economics. He contributed to EconLog from January 2003 through August 2012. Read more of what Arnold Kling’s been reading. For more book reviews and articles by Arnold Kling, see the Archive. As an Amazon Associate, Econlib earns from qualifying purchases. (0 COMMENTS)