Federal Trade Commission chair Lina Khan is interviewed by Mark Glick
INET co-sponsored "The New Roaring Twenties: The Progressive Agenda for Antitrust and Consumer Protection Law," a conference at the University of Utah, October 25-26, 2022 where it also supports the Utah Project on Antitrust and Consumer Protection.
This book traces the evolution of Charles P. Kindleberger's thinking in the context of a 'key-currency' approach to the rise of the dollar system, here revealed as the indispensable framework for global economic development since World War II.
Antitrust expert Hal Singer shows how big businesses in certain industries are taking advantage of inflation worries to jack up prices far beyond their cost increases, all the while raking in robber-baron profits.
Microeconomist Hal Singer studies the topic on everyone’s mind: prices. Singer, who teaches advanced pricing at Georgetown’s McDonough School of Business and frequently serves as an economic expert in antitrust litigation (often concerning how firms set prices), says that those who hold workers’ wages responsible for inflation are not only wrong but making the problem worse with policies that fail to hit the real mark.
His work shows that among industries dominated by a few mega-companies, bouts of inflation act as a handy cover for price hikes that have little or nothing to do with costs. You, the consumer, end up paying the price for predatory profit-seekers who have little to fear from soft antitrust laws and lax enforcement. Singer argues that when a company is making huge profits and workers’ wages aren’t keeping up with inflation, you can bet that something shady is happening – like collusion and price-gouging.
Singer spoke to the Institute for New Economic Thinking about practices that hurt consumers and argues that antitrust laws must be updated –- and enforced -- to protect us from further harm.
Lynn Parramore: As inflation worries continue, we hear a lot of people blaming the problem on wage increases for workers. You disagree. Why?
Hal Singer: I think that in the present or new economy, wages don’t really enter the calculus of pricing by the firm. You may have heard the expressions “superfirms” [very large and successful companies] or “Network Economy” [an emerging hyperconnected, digitized, interactive economic system]. The idea is that in today’s economic reality, if you’re in a high fixed-cost industry where it costs you a ton to get started and then you take over the industry, the pricing problem basically devolves into one of maximizing revenues. In that situation, costs like the wages of your staff are really secondary considerations.
LP: Can you give an example?
HS: Sure. Think of an airline setting prices on an across-the-country flight. Are they taking into consideration the salaries of the flight stewards when setting that rate? Most likely not. What about a pharmaceutical company? Does it look at the wages of its chemists when pricing the products? Again, probably not. There’s been a severing of the relationship between wages and prices in so many sectors of the economy, particularly those in which inflation is running rampant. I could go on with many examples. I’m in a hotel in New York City right now. You think they’re charging rates based on the wages of the cleaning crews that come in? Not likely. They’re revenue maximizers. They’re just looking at the demand curve. The only thing that enters the calculus is what economists call demand-side elasticity considerations. In other words, how much you can get away with on the demand side in setting prices. The costs are no longer entering the equation.
One thing that has happened in the current economy is that worker power has been completely demolished. That has been recognized by tons of economists, including those at the Federal Reserve (Fed). That lack of power has broken down the historical relationship between unemployment and inflation. Economists call it the flattening of the Phillips curve [a theory that inflation and unemployment have a stable and inverse relationship]. What it means is that it’s going to be very difficult, if not extremely painful, to arrest inflation by targeting all of our energies at the labor market. If the relationship between wages and prices has been severed by a combination of network effects, superstar firms, monopsony power [when a single firm has all the power to buy labor in a market], then employing this policy is like pushing a rope. We’ll never get to the finish line. Look, inflation is still rampant despite these rate hikes and employees are suffering as firms pull back from hiring or lay off workers. The question is, have we really done anything to arrest inflation? The answer is no.
LP: Is your approach to pricing distinct from what most students of economics are taught today?
HS: It’s distinct from neoliberal economists, who think that firms, which are setting the prices, bear no culpability on inflation and instead scapegoat workers and consumers as the problem. In my pricing class, we study the pricing decision of the firms. I guess you have to look at where the funding is coming from. It’s very convenient to let the firms off the hook.
LP: Some are blaming Biden and the stimulus. Any truth to that claim?
HS: I just saw a story to this effect and I disagree. The stimulus was largely a lump-sum $1,400 payment that occurred in 2021 and likely spent in 2021. So, the idea that it’s continuing to have ripple effects in 2022, which we’re nearly at the end of, seems preposterous. I would also note that Biden also continued a direct payment that I believe came at the end of the Trump administration. So it’s not like that policy was new, it was just a continuation. I think that it’s very hard to connect Biden’s payment in 2021 to what’s happening in terms of inflation in late 2022.
LP: When businesses raise prices now, they claim to be simply passing on rising costs to consumers. But your work shows there’s more going on, and you’ve placed blame on corporate profit-seeking for inflation. What’s the evidence?
HS: If firms were simply passing along higher costs, then we wouldn’t expect to see their profits go up. Yet profits are at a historical high right now. That’s telling you that they’re not passing along cost increases. I’m not sure that they have any cost increases. The prices are rising much more quickly that the costs. So that kind of rejects the idea in the abstract.
To be concrete, I think that electricity is a market that people should focus on. And rental markets and food. These are the largest contributors to inflation. It’s very hard to believe, when you look at the profits of the electricity firms, which are skyrocketing right now, that they’re dealing with increased costs. Really, it suggests that their costs are not going up, or to the extent that they’re going up at all, the price hikes are far outpacing those costs.
Look at rental properties. If an institutional investor bought a bunch of rental properties in a neighborhood in say, Miami or Atlanta, how have their costs been going up? What costs are they facing at the margin, exactly? Are we talking about the clean-up crew? The security guards? The prices are clearly being set on the demand side. There’s no cost to explain why rents are exploding.
LP: Why aren’t companies afraid of driving away consumers away with predatory pricing? In your work, you’ve mentioned the profit-seeking price hikes in the meat-processing industry, putting a steak dinner out of reach for many. Why isn’t the meat processor worried about driving away business?
HS: It’s hard for consumers to move away, particularly when you’re talking about food. You could change your diet, but it’s pretty hard after you’ve developed certain preferences for meat over your lifetime. It’s hard to switch on a dime. There’s a central tenet in pricing theory that the more concentrated an industry, all things being equal, the easier it is to coordinate on prices. This coordination can be happening explicitly, like you pick up the phone and you tell your competitor, hey, let’s go and do this. Or you can do it tacitly. If there are just a few of you there, you can feel your way through to higher prices.
There’s a story I love telling. I was in a courtroom in December 2021. A price-fixing case. Under oath, one of the executives said that his cartel, which concerned capacitors [energy storage components], functioned most efficiently during times of inflation! I nearly fell out of my chair. What he was basically saying was that a small dose of inflation can serve as a focal point. A way for a bunch of different firms in a concentrated industry to focus their attention on a new target to kind of move in unison, to coordinate their pricing. It occurred to me right at that moment that we’re in big trouble, given how concentrated all markets in the U.S. economy have become over the last 15 to 20 years.
The other thing that a small bout of inflation does is that it softens the beachheads, to use a war analogy about how they would drop bombs on the beaches to allow the troops to march in. Today, when a consumer goes into a restaurant, say a steakhouse, and she sees a $50 price, she’s already been conditioned to expect that the price was going to be higher. She’s more likely to go along, to just tolerate the price hikes. She doesn’t see it as evil, just something that everyone’s doing. This is another reason we don’t see people just defecting and imposing price discipline. It’s going to be very hard for consumers to defeat this by protesting en masse.
What I’m calling for is a different approach entirely to how we arrest price increases that are coming largely from a very specific segment of the economy. The analogy I give is that if there’s a fire in your guest bedroom, you don’t go and bulldoze the whole house. You don’t start spraying water in the den. You go to the source of the fire and put the fire out there. It’s hard for me just watching this unfold because we know exactly where the price hikes are coming and we think we know who is implementing them and why. And yet we’re going to try to correct it through some general prescription that involves throwing sand in the gears of the economy writ large and aimed particularly at the labor market.
LP: How is this behavior of these companies to coordinate on prices legal? Isn’t that anti-competitive?
HS: The antitrust law is soft on this area known as tacit collusion. So firms in concentrated industries kind of feel their way to price hikes tacitly as opposed to via an explicit agreement. They don’t pick up the phone and say “Hey what should we charge our customers today?” but they do it through dynamic interaction over time. I was an expert for plaintiffs in a case involving an antitrust class action against Delta and AirTran for seeking to collude to overcharge for bag fees. A CEO of AirTran told the world during an earnings call that he would never impose the first bag fee, but if Delta were to go first, AirTran would follow with certainty. So he basically made a conditional pledge to a rival over the airwaves. The judge decided that this was not in violation of the anti-trust laws because he saw it more as tacit collusion than explicit collusion.
Now, there is one place where you could stop this under the current laws: the Federal Trade Commission (FTC). The FTC has special powers to enforce what are called “invitations to collude.” That would be under Section 5 of the FTC Act. No other agency, no other private enforcer could stop invitations to collude. But we’re not seeing it yet. The FTC is doing a lot more these days. It’s more vibrant than it has been in the last 30 or 40 years, but they’re limited in their resources and I don’t think there’s a focus yet on what firms are saying during earnings calls. The Groundwork Collaborative [an economic activist group] has been documenting all the shenanigans that have been taking place during earning calls where rivals are effectively cajoling their compatriots to reduce capacity or raise prices with them. You’ll hear an executive say, “oh, there’s too much capacity in this industry.” Or, “we’re going to take the lead on this.” They’re suggesting that others should follow without explicitly asking for it.
We don’t think that companies should be discussing their future pricing or capacity plans via conference calls. The Department of Justice (DOJ) and FTC’s Collaboration Guidelines say that this is likely to be anti-competitive. But there’s really nothing that we can do short of the FTC prosecuting under Section 5 of the FTC Act to stop it from happening.
LP: We’re hearing some economists asserting that their research shows no link between market concentration and producer price inflation. Why are they wrong?
HS: Well, I guess we’re in a world of dueling studies, but I and others have found the opposite. I was looking for the relationship between concentration and prices in 2020 and I found that the most highly concentrated industries were the source of the biggest price hikes in 2021. And the relationship was pretty robust. Concentration in industries in 2020 predicted price hikes in 2021. I did it again for an earlier time using a larger data set and I found the same relationship.
LP: Some economists even hold that market concentration is not a bad thing.
HS: Yeah, there’s a fight between neoconservative and progressive economists. Neoconservatives would argue that concentration is a reflection of some kind of superstar firms taking over with lower costs, and those savings will all rebound to the benefit of consumers. That’s not my view.
LP: What can be done in terms of regulation and the legal framework to curb collusion and price-fixing?
HS: One thing that we need to look at is how to deconcentrate the economy generally. There have been studies, including by the Fed, showing that in a (pre-Covid) city where institutional investors own more of the rental properties, the rental prices were higher than what would be expected. There was a story that came out this week in ProPublica about an algorithm that’s being used by rental property owners to coordinate price hikes. I’m also worried that in addition to institutional ownership in general, there could be a concentration of ownership – the same institutional equity firms buying up a large swathe of properties in a given neighborhood. No one has studied it yet but it’s something that I want to move to next. It seems to me that if we can establish a linkage between concentration and rental inflation at the neighborhood level, the simple fix would be that no individual owner could, say, control more than 5% of the properties in a given neighborhood.
That would be a fairly sensible rule. After deconcentrating the economy, which I realize is easier said than done, the next thing, I think, is price controls. There are a lot of economists, like Isabella Weber at the University of Massachusetts, who now are coming out and saying it. The idea here is that we do have a tradition of price controls in this country. Some of them have been more successful than others.
LP: Can you say a bit about what worked and what didn’t?
HS: During wartime, in the forties, we used price controls fairly effectively. In the seventies under Nixon, we tried again, and those seem to have been considered less successful. But Weber has explained that she didn’t feel that Nixon put full faith and effort of the White House behind it. In any event, I think that as a short-term targeted fix, say, in the rental example, it could work. If it was going to take us a few years to deconcentrate holdings of rental properties, then I think it would make a lot of sense to subject the institutional owners to some sort of price cap for the rate at which they could accelerate rents while they were divesting their properties. And I know that this is, in fact, being tried in certain countries, such as France, where rents have skyrocketed. I feel like we’re heading in that direction. Folks are basically just being priced out of these rental properties.
LP: How do you assess what Biden has done on inflation? What should he do going forward?
HS: I would give him a strong B+. His heart is in the right place. The Inflation Reduction Act is a good bill but the problem is that it isn’t really going to take effect until way out in the future. The list of drugs – the ones Medicare could bargain over -- was shrunk down and it won’t take effect until years from now. So for me, that prescription, while helpful, isn’t going to bring the immediate relief that we need.
I don’t think that Biden uses the bully pulpit as effectively as he could. There’s a great episode where President Kennedy, at the onset of his administration, called out steel makers who were engaging in a massive collective price increase and effectively called them un-American. I realize that’s fairly harsh, but you can use the bully pulpit to call out certain firms that are engaging in outrageous profit-taking. And I feel like Biden would be well-served to pick on certain industries in particular and basically say, look, you’re causing a bunch of suffering, you’re making huge profits, and if you don’t knock it off, we’re going to start to consider everything, including price controls. We’ll have congressional hearings and we’ll call up your CEOs. I don’t feel like there’s been any serious threat leveled at executives either in the electricity industry or with these rental properties. They’re just getting away with murder and they’re going to continue to do so until someone calls them out.
LP: You mentioned action in France. Any other notes to take from other countries?
HS: We’re seeing price controls in the U.K. with respect to electricity and France with respect to rent, and I also saw a clever idea in Spain where I think they’re giving away train tickets to encourage people to stop getting in cars and driving. The point is that the FTC could use its powers to enforce invitations to collude. We could tweak the antitrust laws in a way that allows the DOJ and the attorneys general to go after firms for tacitly colluding. There’s this whole array of policies outside of the Fed’s rate hikes that could be tried to curb inflation in the U.S. but aren’t. So, as much as I’m upset with what the Fed is doing, they’re looking out and they don’t think that anyone’s going to give them help with this problem. They think they’re the only ones and they only have one tool and they’re using it. There’s this weird stand-off where no one is communicating to the Fed that we will pursue alternative remedies.
The Royal Swedish Academy of Sciences has awarded the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel 2022 to Ben S. Bernanke, Douglas W. Diamond, and Philip H. Dybvig for having “significantly improved our understanding of the role of banks in the economy, particularly during financial crises” (Royal Swedish Academy of Sciences 2022a).
The main justification for Diamond and Dybvig's (DD) award is given by a paper published in 1983: “In an article from 1983, Diamond and Dybvig develop a theoretical model that explains how banks create liquidity for savers, while borrowers can access long-term financing” (Royal Swedish Academy of Sciences 2022b, p.4).
A short exposition of the model
Based on Diamond (2007), the model can be described relatively easily. The 2-period model assumes an economy populated by two types of agents. While type 1 agents must consume at the end of period 1 (T=1), type 2 agents only consume at the end of period 2 (T=2). At the beginning of period 1 (in T=0), agents do not know whether they will be type 1 or 2 at the end of the period.
The agents are equipped with one unit each of an all-purpose asset that can be consumed and also invested. If the asset is invested in T=0 it can be switched into a consumption good at zero costs at T=1. If the asset is not used for consumption in T=1, it yields a return at the end of period 2. Thus, in T=0 it is always optimal to invest the asset.
For type 1 agents, this return profile implies that they will not receive a return for their investment at T=1. This raises the question for an institutional design that would allow type 1 agents to participate in the return that is generated in the second period. The model of Diamond and Dybvig shows that banks can provide an implicit insurance for agents against the unlucky outcome of being a type 1 agent.
Depositing the all-purpose asset with a bank at T=0 allows for a pooling, which enables the bank to pay an interest rate (r1) already in T=1 so that the type 1 agents can participate in the return that is generated in the second period. This indirect insurance requires that the bank knows ex-ante the share of type 1 agents in the population so that it can calculate the interest rate in a way that the return for type 2 agents (r2) is always higher than for type 1 agents (r1).
While an explicit insurance against being type 1 would only allow type 1 agents to withdraw in period 1, the DD bank allows all agents to withdraw in T=1 with a return r1. This is due to the assumption that the risk of being type 1 is not publicly verifiable. Thus, the implicit insurance provided by banks suffers from the fact that it cannot exclude type 2 agents that do not require insurance in T=1.
With this design, the DD-Bank is inherently unstable. By offering an interest payment to all agents at T=1, the bank becomes insolvent as it has not yet received a return from its asset side. This built-in insolvency of the DD-Bank is not a problem if type 2 agents are not aware of it. But if they doubt the ability of the bank to generate a higher return for them at T=2 than at T=1, they will withdraw in T=1, whereby the insolvency actually occurs.
Does the DD-Bank use demand deposits to finance long-term investments?
But do Diamond and Dybvig “show that this process is how banks create liquidity” (Royal Swedish Academy of Sciences 2022b, p.4)? Does their model show that “the bank is an intermediary that transforms assets with long maturity into bank accounts with short maturity“? (Royal Swedish Academy of Sciences 2022b, p.4)
What the DD-bank does in the model is a pooling of the all-purpose asset. But it does not transform it into long-term investment goods. When the bank pays it out to the agents at T=1, the asset has not changed its character compared to a situation where the agents have invested it by themselves. As the balance sheet of the DD-Bank (Figure 1) shows, the maturity of assets and liabilities is identical. The only problem is the loss created by the premature paying of interest. Thus, the Academy gets it wrong when it states:
“The bank’s assets have a long maturity because it promises borrowers that they will not need to pay back their loans early. On the other hand, the bank’s liabilities have a short maturity.” (Royal Swedish Academy of Sciences 2022b, p.4)
Figure 1: Balance sheet of the DD-Bank at T=1
Assets | Liabilities |
100 APA | 100 (1+r) APA |
Loss: r 100 APA |
This leads to the concept of “liquidity creation,” which plays a decisive role in the model. Due to its nature, the all-purpose asset can always be transformed anytime from an investment good into a consumption good. In this sense, it is highly liquid. As the amount of this asset has not changed, the liquidity or the money stock has not changed. This is only the case with the specific definition of liquidity of DD, which implies that the interest payment on the all-purpose good has transformed it from an illiquid into a liquid asset.
The role of the banks is therefore limited to a redistribution of the all-purpose good to type 1 agents at a time when no investment returns have been generated. Equating this early participation in future earnings with the “creation of liquidity” by banks is a concept that, as we shall show, has nothing to do with reality.
Is the provision of interest payments to depositors before bank earnings are generated a typical feature of banking so that the DD-model “captures the central mechanisms of banking” (Royal Swedish Academy of Sciences 2022b, p.4)? In reality, banks typically do not pay interest, or only very marginal interest, on highly liquid bank accounts. Without the interest payment in T=1, the DD-bank becomes perfectly stable as its liability side is matched by investments in the all-purpose good that can be transformed at zero costs for consumption purposes. But in this case, banks would no longer provide any benefit for the economy.
A model that fits the arguments of the Royal Swedish Academy
Thus, the DD model is not able to explain the decisive function of maturity transformation by banks. This is due to a feature of the model which is difficult to reconcile with reality. The model assumes that if the all-purpose asset is “invested” in T=0, it can be withdrawn at T=1 and consumed at zero costs. Thus, it has not been transformed into a long-term investment good. It is still liquid in the sense that it can be consumed at T=1.
A more realistic assumption would be that by investing the good at T=0, it cannot be paid out and consumed at T=1. This is only possible at T=2. With this assumption, the model has two different assets:
- a liquid asset, i.e. the all-purpose asset has not been invested in T=0 and it can be consumed at T=1,
- an illiquid asset, i.e. the all-purpose asset been invested in T=0 and can only be consumed at T=2.
Without banks, risk-averse agents would not be able to participate in the returns of the investment good. As they all are confronted with the risk of being type 1, it would be very risky to invest the commodity. In T=1, Type 1 agents would then not be able to consume.
In such a model, banks can provide an obvious improvement if one assumes again that they know the share of type 1 and type 2 agents. In T=0, all agents deposit their endowment of the commodity with the bank. Assuming that the share of type 1 agents is 25 %, the bank keeps 25 % of the all-purpose asset unchanged and invests 75 % as illiquid long-term investment. It thus performs maturity transformation by transforming liquid assets into illiquid assets (Figure 2).
Figure 2: Balance of a bank with maturity transformation at T=0 and T=1
Assets | Liabilities |
25 APA | 100 APA |
75 Investment Good |
To safeguard the solvency of the bank, no interest is paid for deposits that are withdrawn after period 1. This arrangement is still an improvement for the agents as they have a chance to be type 2. In this case, they can participate in the returns of the investment without running the risk of being illiquid in period 1.
As long as the shares of type 1 and type 2 agents are stable and known to the public, there is no run risk in this model. This is different if the share of type 1 agents is higher than the share of liquid assets or if the agents doubt the solvency of liquidity of the bank. Thus, in this model, there is only a liquidity risk, but not a solvency risk as in the DD-bank.
In sum, by slightly modifying the assumptions of the DD-model one gets a model which perfectly fits the description of the Royal Swedish Academy of Sciences (2022b, p.4):
“The money in the depositors’ accounts is a liability for the bank, while the bank’s assets consist of loans to long-term projects. The bank’s assets have a long maturity because it promises borrowers that they will not need to pay back their loans early. On the other hand, the bank’s liabilities have a short maturity; depositors can access their money whenever they want. The bank is an intermediary that transforms assets with long maturity into bank accounts with short maturity. This is usually called maturity transformation.”
How do banks create liquidity?
But even this model does not show how banks create liquidity. In the DD model, the amount of the all-purpose asset remains constant. In the modified model, maturity transformation reduces the amount of the all-purpose asset, which is the liquid asset in this model. -
The difficulty of such models to explain liquidity or money creation reflects the fundamental weakness of models which are based on the assumption of an all-purpose asset. In this setting with an exogenous amount of the all-purpose good, there is no room for money as an independent asset that can be created by banks.
In reality and in monetary models, such as the IS/LM model, the creation of liquidity is simple. Whenever a bank provides a loan to a customer, it credits the account of the customer with the amount of the loan. Thus, the amount of liquid assets in the economy (money stock M1 or M3) increases with each act of bank lending. In such a monetary model, the creation of liquidity is identical with maturity transformation as the maturity of the loans is typically longer than the maturity of deposits. A comprehensive description of the money supply process in a monetary model is provided by the Bank of England (McLeay et al. 2014) and Deutsche Bundesbank (2017). Both institutions speak of the intermediation view as “a popular misperception.”
The role of the “lender of last resort”
In contrast to the DD model, monetary models differentiate between solvency and liquidity risks. In the DD model, the built-in insolvency is the cause of illiquidity. In a monetary model, even a solvent bank can become illiquid if depositors are in a panic. In this context one should mention that the risks of maturity transformation were identified a very long time ago, above all by Otto Hübner (1854):
“One cannot give the long loan when one has received only the short one without running the great risk of not being able to return the latter. This is the fact, the non-observance of which was the simple cause of the failure of old banks and will be that of most of the new ones. They procured large sums against notes or certificates of deposit, or on current account, which could be recalled at any time, and discounted against them bills of exchange, which had months to run, indeed they left the credit received on daily notice, on long irredeemable terms, sometimes for years, to the industrial landowners or governments.”
In a monetary model, the solution to bank runs is not deposit insurance but the central bank as the lender of last resort. In the DD model, the deposit insurance simply redistributes the all-purpose asset from those who withdraw in T=1 to type 2 agents. In a monetary model, bank depositors require an exchange of bank deposits into central bank money, which does not exist in the vaults of the banks. The required additional supply of cash can only be provided by the central bank. Walter Bagehot, in his 1873 book "Lombard Street", therefore pointed out the need for the central bank to take action in the event of a bank run, as a "lender of last resort":
“The holders of the cash reserve must be ready not only to keep it for their own liabilities but to advance it most freely for the liabilities of others. They must lend to merchants, to minor bankers, to 'this man and that man,' whenever the security is good.” (Bagehot 1873, p. 51.)
Summary
The DD model presents a flawed model of banking: The DD bank does not transform the liquidity of the assets on the asset side of its balance sheet. Instead, it pays interest to depositors in T=1 before a return on the asset side has been generated. This built-in insolvency of the DD bank is the main cause for the instability of the DD bank, not the maturity transformation of bank assets.
Thus, the Academy praises the DD model for a maturity transformation that is not taking place in the model. With a simple modification of the DD model, i.e., that an investment return excludes the conversion of the investment good in consumption T=1, one can construct a model with maturity transformation, but without a built-in insolvency.
At a more general level, the difficulty of analyzing liquidity or money creation, which is a central function of banks, can be related to the attempt to analyze the financial sphere with models without money. In monetary models, these mechanisms can be explained easily.
Due to the flawed structure, the DD model leads to flawed policy implications. It assumes that deposit insurance which redistributes the existing assets is the adequate approach to bank runs. In a monetary analysis, a bank run can only be stopped by the central bank which as a lender of last resort must increase the amount of central bank money to stop the panic.
Thus, in contrast to the Krugman-Tweet mentioned at the beginning, in the DD model there is no room for a lender of last resort which was the key message by Bagehot. DD blew smoke on the clear and very simple insights of Bagehot.
References
Bagehot, W. (1873). Lombard Street: A Description of the Money Market, London, Henry S. King.
Deutsche Bundesbank. (2017). The role of banks, non-banks and the central bank in the money creation process. Monthly Report, 69(4), 13-34, April.
Diamond, D. W., & Dybvig, P. H. (1983). Bank runs, deposit insurance, and liquidity. Journal of political economy, 91(3), 401-419.
Diamond, D. W. (2007). Banks and liquidity creation: a simple exposition of the Diamond-Dybvig model. FRB Richmond Economic Quarterly, 93(2), 189-200.
Hübner, O. (1854). Die Banken. Verlag von Heinrich Hübner, Leipzig.
McLeay, M., Radia, A., & Thomas, R. (2014). Money creation in the modern economy. Bank of England Quarterly Bulletin, Q1.
Royal Swedish Academy of Sciences (2022a). The Prize in Economic Sciences 2022. Press Release October 10. https://www.nobelprize.org/pri...
Royal Swedish Academy of Sciences (2022b). The Prize in Economic Sciences 2022. Popular Science Background. https://www.nobelprize.org/pri...
In the 1983 paper cited as the basis for Bernanke’s Nobel award, the first footnote states: “I have received useful comments from too many people to list here by name, but I am grateful to each of them.” One of those unnamed commenters was Charles P. Kindleberger, who taught at MIT full-time until mandatory retirement in 1976 and then half-time for another five years. Bernanke himself earned his MIT Ph.D. in 1979, whereupon he shifted to Stanford as Assistant Professor. Thus it was natural for him to send his paper to Kindleberger for comment, and perhaps also natural for Kindleberger to respond.
As it happens, the carbon copy of that letter has been preserved in the Kindleberger Papers at MIT, and that copy is reproduced below as possibly of contemporary interest. All footnotes are mine, referencing the specific passages of the published paper, a draft copy of which Kindleberger is apparently addressing, and filling in context that would have been familiar to both Bernanke and Kindleberger but may not be to a modern reader. With these explanatory notes, the text speaks for itself and requires no further commentary from me.
“May 1, 1982
Dr. Ben Bernanke
Graduate School of Business
Stanford University
Stanford, CA 94305
Dear Dr. Bernanke,
Thank you for sending me your paper on the great depression. You ask for comments, and I assume this is not merely ceremonial. I am afraid you will not in fact welcome them.
I think you have provided a most ingenious solution to a non-problem.[1] The necessity to demonstrate that financial crisis can be deleterious to production arises only in the scholastic precincts of the Chicago school with what Reder called in the last JEL its tight priors, or TP.[2] If one believes in rational expectations, a natural rate of unemployment, efficient markets, exchange rates continuously at purchasing power parities, there is not much that can be explained about business cycles or financial crises. For a Chicagoan, you are courageous to depart from the assumption of complete markets.[3]
You wave away Minsky and me for departing from rational assumptions.[4] Would you not accept that it is possible for each participant in a market to be rational but for the market as a whole to be irrational because of the fallacy of composition? If not, how can you explain chain letters, betting on lotteries, panics in burning theatres, stock market and commodity bubbles as the Hunts in silver, the world in gold, etc... Assume that the bootblack, waiters, office boys etc of 1929 were rational and Paul Warburg who said the market was too high in February 1929 was not entitled to such an opinion. Each person hoping to get in an[d] out in time may be rational, but not all can accomplish it.
Your data are most interesting and useful. It was not Temin who pointed to the spread (your DIF) between governts [sic] and Baa bond yields, but Friedman and Schwartz.[5] Column 4 also interests me for its behavior in 1929. It would be interesting to disaggregate between loans on securities on the one hand and loans and discounts on the other.
Your rejection of money illusion (on the ground of rationality) throws out any role for price changes. I think this is a mistake on account at least of lags and dynamics. No one of the Chicago stripe pays attention to the sharp drop in commodity prices in the last quarter of 1929, caused by the banks, in their concern over loans on securities, to finance commodities sold in New York on consignment (and auto loans).[6] This put the pressure on banks in areas with loans on commodities. The gainers from the price declines were slow in realizing their increases. The banks of the losers failed. Those of the ultimate winners did not expand.
Note, too, the increase in failures, the decrease in credit and the rise in DIF in the last four of five months of 1931.[7] Much of this, after September 21, was the consequence of the appreciation of the dollar from $4.86 to $3.25.[8] Your international section takes no account of this because prices don’t count in your analysis. In The World in Depression, 1929-1939, which you do not list,[9] I make much of this structural deflation, the mirror analogue of structural inflation today from core inflation and the oil shock. But your priors do not permit you to think them of any importance.
Sincerely yours,
[Charles P. Kindleberger]”
References
Bernanke, Ben S. 1983. “Nonmonetary Effects of the Financial Crisis in the Propagation of the Great Depression.” American Economic Review 73 No 3 (June): 257-276.
Kindleberger, Charles P. 1973. The World in Depression, 1929-1939. Berkeley CA: University of California Press.
Kindleberger, Charles P. 1978. Manias, Panics and Crashes: A History of Financial Crises. New York: Basic Books.
Kindleberger, Charles P. 1985. Keynesianism vs. Monetarism and Other Essays in Financial History. London: George Allen and Unwin.
Kindleberger. Charles P. and Jean-Pierre Laffargue, eds. 1982. Financial crises: Theory, History, and Policy. Cambridge: Cambridge University Press.
Mehrling, Perry. 2022. Money and Empire: Charles P. Kindleberger and the Dollar System. Cambridge: Cambridge University Press.
Notes
[1] Bernanke (1983, 258): “reconciliation of the obvious inefficiency of the depression with the postulate of rational private behavior”.
[2] Reder, Melvin W. “Chicago Economics: Permanence and Change.” Journal of Economic Literature 20 No. 1 (March 1982): 1-38. Bernanke (1983, 257) states explicitly, “the present paper builds on the Friedman-Schwartz work…”
[3] Bernanke (1983, 257): “The basic premise is that, because markets for financial claims are incomplete, intermediation between some classes of borrowers and lenders requires nontrivial market-making and information-gathering services.” And again at p. 263: “We shall clearly not be interested in economies of the sort described by Eugene Fama (1980), in which financial markets are complete and information/transactions costs can be neglected.”
[4] Bernanke (1983, 258): “Hyman Minsky (1977) and Charles Kindleberger (1978) have in several places argued for the inherent instability of the financial system, but in doing so have had to depart from the assumption of rational economic behavior.” It is perhaps relevant to observe that elsewhere Kindleberger takes pains to point out the limitations of the Minsky model for explaining the great depression: “it is limited to the United States; there are no capital movements, no exchange rates, no international commodity prices, nor even any impact of price changes on bank liquidity for domestic commodities; all assets are financial.” (Kindleberger 1985, 302) This passage appears in Kindleberger’s contribution to a 1981 conference sponsored by the Banca di Roma and MIT’s Sloan School of Management, which followed on a 1979 Bad Homburg conference that also included both men, which proceedings were published as Financial Crises: Theory, History and Policy (Cambridge 1982).
[5] Bernanke (1983, 262): “DIF = difference (in percentage points) between yields on Baa corporate bonds and long-term U.S. government bonds”.
[6] It is exactly the sharp drop in commodity prices that Kindleberger puts at the center of his explanation of why the depression was worldwide since commodity prices are world prices. Kindleberger (1973, 104): “The view taken here is that symmetry may obtain in the scholar’s study, but that it is hard to find in the real world. The reason is partly money illusion, which hides the fact of the gain in purchasing power from the consumer countries facing lower prices; and partly the dynamics of deflation, which produce an immediate response in the country of falling prices, and a slow one, often overtaken by spreading deflation, in the country with improved terms of trade, i.e. lower import prices.”
[7] Bernanke’s Table 1 cites August-December DIF figures as follows: 4.29, 4.82, 5.41, 5.30, 6.49.
[8] September 21 is of course the date when the Bank of England took sterling off gold, see Kindleberger (1973, 167-170).
[9] The published version, Bernanke (1983), still does not list Kindleberger (1973), citing only Kindleberger (1978), Manias, Panics, and Crashes. Notably, the full title of that book includes also the words “A History of Financial Crises.” Kindleberger himself quite explicitly frames Manias as an extension of the Depression book, now including all of the international financial crises he can find. Later commentary however follows Bernanke in viewing Kindleberger (1978) as instead an extension of Minsky’s essentially domestic Financial Instability Hypothesis, which is not correct. On this point see footnote 4, and more generally, Chapter 8 of my book Money and Empire (Cambridge 2022).
Ben Bernanke, Douglas Diamond, and Philip Dybvig were honored for their work on financial instability
Congratulations to Ben Bernanke, Douglas Diamond, and Philip Dybvig for winning the 2022 Nobel Memorial Prize in Economic Sciences (2022). “I have had the great pleasure of working with Bernanke and Dybvig, and all three economists have impressed me with their pioneering research on banks and financial crises,” said INET President Rob Johnson on the occasion of the award’s announcement. INET Research Director Thomas Ferguson echoed the sentiment, commenting that "financial stability has been a key concern of our organization from the beginning and that the research of these economists had helped advance the field."
At the end of July, Microsoft and Google’s parent company, Alphabet, presented their latest and relatively disappointing economic results blaming it on the macroeconomic distress. What may have gone unnoticed is that both companies referred to their clouds as the main engines of growth. The cloud was also responsible for Amazon’s better-than-expected quarterly results.
The cloud refers to computing services, including software, hardware, and platforms offered as services through the Internet instead of running locally on individual computers. By 2025, 45% of the world’s data storage will be on the cloud. We are constantly storing information and accessing online applications through the cloud.
Moving operations to the cloud is also crucial for companies. Yet, this mass transfer of information technology from inside organizations to the cloud is a very recent phenomenon. In 2012, firms spent just USD 6.5b on cloud infrastructure services; by 2021, investments had jumped to USD 178b (representing an increase of 2,638%). While the Cloud is used by all sorts of companies and public sector organizations, its ownership is overwhelmingly dominated by just three firms. Together, Amazon, Microsoft, and Google concentrate around 65% of cloud infrastructure services.
This market dominance matters more than concentration in other markets because it entrenches tech giants’ control of digital technologies, which reinforces their global power and the value they capture from other businesses in the form of intellectual rents paid to use those digital technologies. Companies developing specific artificial intelligence (AI) applications, for example, are dependent on tech giants’ cloud services including access to cleaned big databases to train their specific AI models. They also rent generic AI solutions, like facial recognition or autocomplete for written text, that are integrated into their targeted or specific applications.
Netflix recently stated that it relies on services provided by Amazon’s cloud (Amazon Web Services, AWS) and that it could not easily switch to another cloud provider. Other platform companies like Uber -- which can only operate accessing Google Maps -- and Booking made similar claims concerning technological dependence on big tech companies.
Since the same lines of code can be simultaneously used by many, the reproduction costs of selling AI algorithms as cloud services tend to zero. Hence, as Amazon, Microsoft, and Google expand their client base, profits increase exponentially, to the point where AWS is Amazon’s most profitable business. Furthermore, since the AI code rented as a service includes deep learning algorithms that learn as they process data, the more these algorithms are lent, the more they will learn and self-improve, thus reinforcing these three giants’ digital leadership.
And this is not all. The cloud offers tech giants a chance to sneak into (and copycat) thousands of organizations around the world. Like Amazon’s marketplace, AWS not only sells Amazon computing developments as services. AWS is also a platform that enables other companies to sell their own computing services. Among them, Elastic offered its products Elasticsearch and Kibana through AWS. As their popularity grew, AWS started offering its own version of these services, displacing Elastic from the market.
Cloud computing is also a strategic industry. It allows the identification of promising businesses early by identifying growth in companies’ consumption of data storage space and processing power as well as greater use of different AI services. As a result, the three market leaders use information gathered from their Clouds to identify, and eventually fund existing businesses, or start new promising ones. As other companies first fail or succeed, big tech companies thus reduce their investment risks while keeping long-term economic profits.
Microsoft’s acquisition of Nuance, a cloud-based system for medical transcription services, for USD 19.7 billion is a case in point. Nuance was already running services on Microsoft’s infrastructure before the acquisition. Acquiring Nuance represents a way to make a strong foothold in cloud services for the healthcare industry, which is a source of colossal datasets to be exploited with artificial intelligence. No wonder why, when the acquisition was announced, Microsoft’s CEO, Satya Nadella, tweeted: “AI is technology’s most important priority, and healthcare is its most urgent application.” Yet, the acquisition also expanded Microsoft’s intellectual monopoly beyond healthcare, reinforcing its overall business, in particular, its cloud because it gave Microsoft access to Nuance’s more than 1,000 patents and secretly kept knowledge that had placed the latter at the frontier of speech recognition.
The tendency towards market dominance that is premised on privileged access to data is exacerbated by the fact that the code underpinning cloud services is not made accessible to customers. Customers become ‘locked-in’ and dependent on the cloud services provided by the dominant cloud service providers. This constrains the opportunities for customers to learn by accessing the code they purchase as a cloud service. Customers know what certain services can be used for, but they cannot learn from the rented code since they cannot access the actual algorithms that are making those things happen. This, even if part of those algorithms were developed by universities and public research organizations.
This is true even when those customers are other major corporations. Siemens, for example, is the European leader when it comes to the number of AI patents it has been granted. But Siemens is also dependent on big tech cloud, including for the most advanced generic AI required to apply more specific applications that Siemens integrates into its medical imaging, energy, and transportation products. Only a year after launching Siemens MindSphere, a cloud platform for storing and analyzing data retrieved with IoT from its sold equipment, AWS took over part of this platform’s development. AWS provides computing services that Siemens cannot develop in-house and that it needs to provide AI-specific solutions to its clients.
This form of technological dependence is risky at least for two reasons. First, Google, Amazon, and Microsoft have already entered Siemens's medical business with the potential of becoming serious rivals. Second, unlike the first ICT wave, where technology adopters could learn by using and adapting technologies leading to complementary innovations, cloud computing offers technology as a black box. Therefore, it limits users’ learning and generates a form of long-term technological dependence with no visible ways of moving beyond it. All this, while tech giants' algorithms self-improve by processing the data harvested by companies like Siemens, thus further expanding the technological gap between cloud providers and other firms. As this technological dependence expands vis-à-vis the digital leadership of tech giants, Siemens may keep reducing its own development of MindSphere, relying instead on services accessed directly through tech giants’ clouds.
Siemens is one of the thousands of companies that are basing their digital transition on analytics, database and IoT provided as cloud services by tech giants. As the use of these forms of the platform as a service accelerates -- they have the highest growth rate within the cloud infrastructure services market -- we may expect the reinforcement of tech giants’ leadership based on expanding technology enclosures. As firms lose their technical autonomy and subordinate to cloud solutions, value transfers in the form of intellectual rents to tech giants paid to use but not really access digital technologies will expand. These rents deepen polarization among firms and, in turn, foster wealth and income inequalities. This scenario points to forms of economic power that elude existing regulatory frameworks.
Regulating the cloud
The European Union’s Digital Markets Act is probably the world’s most advanced digital policy, thus the right place to look for cloud computing regulations. This Act aims to expand the EU’s bargaining power against core platform companies by unifying member states’ digital economy rules and carrying out market investigations at the EU level that may lead to sanctions for non-compliant behavior.
It is still to be seen whether the European Commission will be able to enforce this Act. Its past fines charged to Google for several antitrust cases -- Google Shopping (2010), Google’s Android (2015), and Google AdSense (2016) -- were never cashed. The European Commission also ruled against Apple and Ireland for illegal state aid through selective tax breaks, but the EU general court annulled the decision.
There is an additional limitation of special relevance for regulating the cloud. Although the Digital Markets Act identifies platforms’ potential role as gatekeepers even when they are not dominant in competition law terms, it remains focused on markets. Core platforms will be fined only if they are found to be market gatekeepers. For instance, if they systematically privilege their own products and place third-party ones in lower positions in customers’ searches on their platforms.
The term “cloud” appears only 14 times in the 193-page latest provisional public version of this legislation. The cloud is only introduced as an example of a platform with potential market gatekeepers. Not a word is said about how Amazon, Microsoft, and Google operate this business, expanding their knowledge appropriation while subordinating other organizations. These giants are not only market gatekeepers but also knowledge and information gatekeepers. If the European Commission and its member and other states seriously want to introduce legislation that can counterbalance these firms’ power, this form of gatekeeping must be prevented.
The emergence of private competition, as recognized by European leading corporations, is limited by the tangible capital -- in particular infrastructure -- intensive nature of the cloud. But even more challenging is the fact that competition is not the best solution for the cloud. Artificial intelligence algorithms sold as services in the cloud self-adjust and learn -- thus improving -- the more data they process. More competition would come at the expense of efficiency (each algorithm will process less data, thus producing less digital intelligence) and, therefore, potentially lower prices. This is a textbook case of what the economics literature calls a natural monopoly.
Just like other natural monopolies like electricity, accessing computing services on the cloud is becoming crucial for businesses. Yet, unlike electricity, whose main regulatory dimension is tariff regulation, prices are not the most sensitive side of the cloud business but knowledge and information. Since it is impossible to limit digital learning when processing third-party data, corporations should not be the main and certainly not the only cloud providers. On the contrary, a solution could be to build a cloud operated democratically as an international public consortium. This might be one way to effectively tackle global knowledge and information gatekeeping in the digital world. It could also set a precedent for knowledge and information sharing in other fields and set some real limits to monopoly pricing, not just by its direct effects on pricing, but by making codes more available.
Medhora has served on INET’s Board since 2012 and is a distinguished fellow and former president of the Centre for International Governance Innovation (CIGI).
October 4, 2022, (New York City) — The Institute for New Economic Thinking (INET) is pleased to announce the appointment of the new Chair of its Board of Directors.
“On behalf of the Board of Directors, I’m delighted to announce Rohinton P. Medhora as the Chair of the Board, who will be instrumental in the next phase of INET,” said INET’s President Rob Johnson (09-30-22).
INET’s outgoing Chair, Chris Canavan, served on the board for over a decade and as chair for four years. "We are grateful for his diligent service and Chairmanship,” said Johnson.
The new Chair of the Board, Rohinton P. Medhora has served on INET’s Board since 2012 and is a distinguished fellow and former president of the Centre for International Governance Innovation (CIGI) (2012–2022). He also served on CIGI’s former International Board of Governors from 2009 to 2014. Previously, he was vice president of programs at Canada’s International Development Research Centre. His fields of expertise are monetary and trade policy, international economic relations, and development economics.
Rohinton also sits on The Lancet and Financial Times Commission on Governing Health Futures 2030 and on INET’s Commission on Global Economic Transformation, co-chaired by Nobel economics laureates Michael Spence and Joseph Stiglitz. In addition, he is Vice-Chair at the McLuhan Foundation and on the advisory boards of the WTO Chairs Programme, UNU-MERIT, and the Global Health Centre. In 2021-22, Rohinton chaired the Ontario Workplace Recovery Advisory Committee.
Rohinton received his doctorate in economics in 1988 from the University of Toronto, where he subsequently taught. In addition to his Ph.D., Rohinton earned his B.A. and M.A. at the University of Toronto, where he majored in economics. He has published extensively in professional and non-technical journals and has published several books: Finance and Competitiveness in Developing Countries (Routledge, 2001) and Financial Reform in Developing Countries (Macmillan, 1998), which he co-edited with José Fanelli. In 2013, he was co-editor of Canada-Africa Relations: Looking Back, Looking Ahead, which is volume 27 in the influential Canada Among Nations book series. In 2014, he co-edited International Development: Ideas, Experience, and Prospects (Oxford University Press) and Crisis and Reform: Canada and the International Financial System, which is volume 28 in the Canada Among Nations book series.
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