Teaching Price Controls (Poorly)

Economics textbooks differ in their treatment of price controls. None of them does a great job, in my opinion. The reason is mostly due to the purpose of textbooks. Despite what you might suspect, most undergraduate textbooks are not used primarily to give students an understanding of the world. They are often used as a bound list of things to know and to create easy test questions. If a textbook has to change the assumptions of a model too much from what the balance of the chapter assumes, then the book fails to make clear what students are supposed to know for the test.

I think that this is the most charitable reason for books’ poor treatment of price controls – even graduate level books. The less charitable reasons include sloppy exposition due to author ignorance or an over-reliance on math. I honestly would have trouble believing these less charitable reasons.

I picked up 5 microeconomics text books and the below graph is typical of how they treat a price ceiling.

The books say that the price ceiling is perfectly enforced. They identify producer surplus (PS) as area C and consumer surplus (CS) as areas A & B. There are very good reasons to differ with these welfare conclusions.

Problem #1

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South Carolina Certificate of Need Repeal

The South Carolina Senate just voted 35-6 to repeal its Certificate of Need laws, which required hospitals and many other health care providers to get the permission of a state board before opening or expanding. The bill still needs to make it through the house, and these sorts of legislative fights often turn into a years-long slog, but the vote count in the senate makes me wonder if it might simply pass this year. That would make South Carolina the first state in the Southeast to fully repeal their CON laws, although Florida dramatically shrunk their CON requirements in 2019.

Source: Mercatus Center at George Mason University

This seems like good news; here at EWED we’re previously written about some of the costs of CON. I’ve written several academic papers measuring the effects of CON, finding for instance that it leads to higher health care spending. I aimed to summarize the academic literature on CON in an accessible way in this article focused on CON in North Carolina.

CON makes for strange bedfellows. Generally the main supporter of CON is the state hospital association, while the laws are opposed by economists, libertarians, Federal antitrust regulators, doctors trying to grow their practices, and most normal people who actually know they exist. CON has persisted in most states because the hospitals are especially powerful in state politics and because CON is a bigger issue for them than for most groups that oppose it. But whenever the issue becomes salient, the widespread desire for change has a real chance to overcome one special interest group fighting for the status quo. Covid may have provided that spark, as people saw full hospitals and wondered why state governments were making it harder to add hospital beds.

Remittances Eye-tracking Experiment: Meet the authors and paper

I am pleased to have been asked to discuss a paper in an ASHE (American Society of Hispanic Economists) session at the 2022 AEA meeting. Our session is “Hispanics and Finance” on Sunday January 9 at 12:15pm Eastern Time.

The paper is “Neuroeconomics for Development: Eye-Tracking to Understand Migrant Remittances”. Here is a bit about each author. Meeting in person is a benefit that I miss this time, since the meeting is virtual.

Eduardo Nakasone of Michigan State University has several papers on information and communication technologies and agricultural markets. I pondered this sentence from one of his abstracts, “Under certain situations, ICTs can improve rural households’ agricultural production, farm profitability, job opportunities, adoption of healthier practices, and risk management. All these effects have the potential to increase wellbeing and food security in rural areas of developing countries. Several challenges to effectively scaling up the use of ICTs for development remain, however.” His prior work on ICTs is relevant to the paper at hand, which is about how migrants utilize information about remittance tools.

Máximo Torero is the Chief Economist of the Food and Agriculture Organization (FAO). He has worked on development and poverty in many capacities including at the World Bank.

Angelino Viceisza, an associate professor at Spelman College, is doing interesting work at the intersection of Development and Experimental Economics. Here is his 2022 paper (Happy New Year!) published in the Journal of Development Economics.  

I am discussing their paper on how migrants choose financial services. The pre-analysis plan is public. Remittance sending is important for migrants and for the entire world economy. The authors remind us that a significant chunk of what migrants earn is “lost” to service fees. The authors are examining how migrants incorporate new information about competitive alternative services.

Some neat aspects of their work:

  • Their subject pool is migrants who send remittances, recruited in the DC area.
  • Like most experiments I am used to, the stakes are real and significant.
  • Not only can they observe which service is selected, but by using eye-tracking they can get a sense of what information was salient or persuasive.

It is potentially a big deal for migrants to compare services more rigorously and switch providers more readily. The internet, as least in theory, makes it easy to find information on transaction fees. Policy makers have even proposed subsidizing websites that compare the fees of money transfer operators (MTOs). The authors are trying to understand how such a website might impact behavior. A basic question is: does information in this format affect behavior? A small change in behavior could have a huge impact on the world economy and recipient countries. Imagine if a country currently receiving a billion dollars in remittances had 1% more next year because migrants switched to a more efficient service. Might it be cheaper to nudge people toward low-fee services than to send foreign aid?

Their experiment will reveal whether people make switches based on new information, and it also helps us start to understand which attributes of MTOs migrants consider. Their design includes a treatment manipulation that sometimes emphasizes either transfer speed or user reviews.

If you have read this far hoping for a summary of their results, I will disappoint. Their paper is not public yet and data is still being analyzed. I can say that migrant subjects do sometimes switch their choice of MTO, based on information, in some circumstances. They are more likely to make a switch when the induced stakes are higher. If you tune into the session tomorrow, you will get to hear a summary of preliminary results by the author (not free to public, requires conference registration).

Certificate of Need and Mental Health

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

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

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

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

PSNE: No More, No Less

Today marks the 27th anniversary of John Nash winning The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel for his contributions to game theory.

Opinions on game theory differ. To most of the public, it’s probably behind a shroud of mystery. To another set of the specialists, it is a natural offshoot of economics. And, finally a 3rd non-exclusive set find it silly and largely useless for real-world applications.

Regardless of the camp to which you claim membership, the Pure Strategy Nash Equilibrium (PSNE) is often misunderstood by students. In short, the PSNE is the set of all player strategy combinations that would cause no player to want to engage in a different strategy. In lay terms, it’s the list of possible choices people can make and find no benefit to changing their mind.

In class, I emphasize to my students that a Nash Equilibrium assumes that a player can control only their own actions and not those of the other players. It takes the opposing player strategies as ‘given’.

This seems simple enough. But students often implicitly suppose that a PSNE does more legwork than it can do. Below is an example of an extensive form game that illustrates a common point of student confusion. There are 2 players who play sequentially. The meaning of the letters is unimportant. If it helps, imagine that you’re playing Mortal Kombat and that Player 1 can jump or crouch. Depending on which he chooses, Player 2 will choose uppercut, block, approach, or distance. Each of the numbers that are listed at the bottom reflect the payoffs for each player that occur with each strategy combination.

Again, a PSNE is any combination of player strategies from which no player wants to deviate, given the strategies of the other players.

Students will often proceed with the following logic:

  1. Player 2 would choose B over U because 3>2.
  2. Player 2 would choose A over D because 4>1.
  3. Player 1 is faced with earning 4 if he chooses J and 3 if he chooses C. So, the PSNE is that player 1 would choose J.
  4. Therefore, the PSNE set of strategies is (J,B).

While students are entirely reasonable in their thinking, what they are doing is not finding a PSNE. First of all, (J,B) doesn’t include all of the possible strategies – it omits the entire right side of the game. How can Player 1 know whether he should change his mind if he doesn’t know what Player 2 is doing? Bottom line: A PSNE requires that *all* strategy combinations are listed.

The mistaken student says ‘Fine’ and writes that the PSNE strategies are (J, BA) and that the payoff is (4,3)*.  And it is true that they have found a PSNE. When asked why, they’ll often reiterate their logic that I enumerate above. But, their answer is woefully incomplete. In the logic above, they only identify what Player 2 would choose on the right side of the tree when Player 1 chose C. They entirely neglected whether Player 2 would be willing to choose A or D when Player 1 chooses J. Yes, it is true that neither Player 1 nor Player 2 wants to deviate from (J, BA). But it is also true that neither player wants to deviate from (J, BD). In either case the payoff is (4, 3).

This is where students get upset. “Why would Player 2 be willing to choose D?! That’s irrational. They’d never do that!” But the student is mistaken. Player 2 is willing to choose D – just not when Player 1 chooses C. In other words, Player 2 is indifferent to A or D so long as Player 1 chooses J. In order for each player to decide whether they’d want to deviate strategies given what the other player is doing, we need to identify what the other player is doing! The bottom line: A PSNE requires that neither player wants to deviate given what the other player is doing –  Not what the other player would do if one did choose to deviate.

What about when Player 1 chooses C? Then, Player 2 would choose A because 4 is a better payoff than 1. Player 2 doesn’t care whether he chooses U or B because (C, UA) and (C, BA) both provide him the same payoff of 4. We might be tempted to believe that both are PSNE. But they’re not! It’s correct that Player 2 wouldn’t deviate from (C, BA) to become better off. But we must also consider Player 1. Given (C, UA), Player 1 won’t switch to J because his payoff would be 1 rather than 3.  Given (C, BA), Player 1 would absolutely deviate from C to J in order to earn 4 rather than 3. So, (C, UA) is a PSNE and (C, BA) is not. The bottom line: Both players must have no incentive to deviate strategies in a PSNE.

There are reasons that game theory as a discipline developed beyond the idea of Nash Equilibria and Pure Strategy Nash Equilibria. Simple PSNE identify possible equilibria, but don’t narrow it down from there. PSNE are strong in that they identify the possible equilibria and firmly exclude several other possible strategy combinations and outcomes. But PSNE are weak insofar as they identify equilibria that may not be particularly likely or believable. With PSNE alone, we are left with an uneasy feeling that we are identifying too many possible strategies that we don’t quite think are relevant to real life.

These features motivated the later development of Subgame Perfect Nash Equilibria (SGPNE). Students have a good intuition that something feels not quite right about PSNE. Students anticipate SGPNE as a concept that they think is better at predicting reality. But, in so doing, they try to mistakenly attribute too much to PSNE. They want it to tell them which strategies the players would choose. They’re frustrated that it only tells them when players won’t change their mind.

Regardless of whether you get frustrated by game theory, be sure to have a drink and make toast to John Nash.

*Below is the normal form for anyone who is interested.

Lifespan / CNE Merger Economics

The largest hospital system in Rhode Island, Lifespan, is trying to merge with the second-largest hospital system in Rhode Island, Care New England. Next Wednesday I’ll be on a panel discussing the proposed merger, following a panel with the Presidents of the three institutions involved (Lifespan, CNE, and Brown University). I’ll summarize my thoughts here.

Basic economics tells us that if a company with 50% market share buys a company with 25% market share in the same industry, they have strong market power and are likely to use this monopoly position to raise prices.

The real world is often more complicated, especially when it comes to health care, but in this case I think basic economics holds up well. A wealth of empirical evidence, including studies of previous hospital mergers, suggest that reduced hospital competition leads to higher prices without bringing commensurate benefits in quality or efficiency.

I think the Federal Trade Commission will almost certainly challenge the merger, and that they will likely succeed in doing so. The FTC merger guidelines more or less demand it, and current FTC leadership if anything seems to want to be more aggressive than required on antitrust. To me the biggest question is whether they will try to stop the merger entirely, or whether they would allow it to proceed subject to conditions (e.g. spin off one or two hospitals to remain independent)- I’ll be watching with interest and letting you know how it goes.

New: Journal of Comments and Replications in Economics

I was pleased to see yesterday the announcement of a new journal, the Journal of Comments and Replications in Economics. As the name implies, it will publish articles that comment on or attempt to replicate previously published economics papers.

While empirical economics papers have in some ways become more believable over time, it is still rare for anyone to verify whether the results can actually be replicated, and formal comments on potential problems in published papers have actually become less common over time (though Econ Journal Watch has been a good outlet for comments).

The ability to independently verify and replicate findings should be at the core of science. But economists, like most other disciplines, are generally too focused on publishing original work to test whether already-published papers hold up. When we do try to replicate existing work, the results aren’t very encouraging; at best 80% of economics papers replicate.

If we want people to trust and rely on our work, we need to do better than that. The US Department of Defense agrees, and funded a huge project to determine what types of social science research hold up to scrutiny. I’ve been a bit involved in this and hope to sum up some of the results once this semester is over. For now, I’ll just say I’m happy to see the new Journal of Comments and Replications in Economics (and that it is both free and open-access, a rare combo) and I hope this represents one more small step towards economics being a real science.

The Credibility Revolution: A Nobel for Taking (some of) the CON out of Econometrics

Yesterday Jeremy pointed out that while the 2021 economics Nobelists have reached various conclusions in their study of labor economics, the prize was really awarded to the methods they developed and used.

I find the best explanation of the value of these methods to be this 2010 article by Angrist and Pischke in the Journal of Economic Perspectives: The Credibility Revolution in Empirical Economics: How Better Research Design Is Taking the Con out of Econometrics

Like Jeremy, they think that empirical economic research (that is, research using econometrics) was most quite bad up to the 1980’s; as Ed Leamer put it in his paper “Let’s take the CON out of Econometrics”:

This is a sad and decidedly unscientific state of affairs we find ourselves in. Hardly anyone takes data analyses seriously. Or perhaps more accurately, hardly anyone takes anyone else’s data analyses seriously.

Angrist and Pischke argue that the field is in much better shape today:

empirical researchers in economics have increasingly looked to the ideal of a randomized experiment to justify causal inference. In applied micro fields such as development, education, environmental economics, health, labor, and public finance, researchers seek real experiments where feasible, and useful natural experiments if real experiments seem (at least for a time) infeasible. In either case, a hallmark of contemporary applied microeconometrics is a conceptual framework that highlights specific sources of variation. These studies can be said to be design based in that they give the research design underlying any sort of study the attention it would command in a real experiment.

The econometric methods that feature most prominently in quasi-experimental studies are instrumental variables, regression discontinuity methods, and differences-in-differences-style policy analysis

Our field still has big problems: the replication crisis looms, and the credibility revolution’s focus on the experimental ideal leads economists to avoid important questions that can’t be answered by natural experiments. But I do think that the average empirical economics paper today is much more credible than one from 1980, and that the 3 Nobelists are part of the reason why, so cheers to them.

Calling Behavioral Economics a Fad

Josh Hendrickson and Brian Albrecht have a Substack called Economic Forces that is a source of economics news and examples. We have linked to EF before at EWED.

Albrecht just published an op-ed titled “Behavioral Economics Is Fine. Just Keep It Away from Our Kids”. I’ll to respond to this, just as I responded to that other blog. I think the group of people who are pitting themselves against “behavioral economics” is small. They might even think of themselves as a minority embattled against the mainstream. So, why bother responding? That’s what blogs are good for.

I agree with Albrecht’s main point. The first thing an undergraduate should learn in economics classes is the classic theory of supply and demand. Even in its simplest form, the idea that demand curves slope down and supply curves slope up is powerful and important.*

Albrecht points out that there are some results that have been published in the behavioral economics literature that turned out not to replicate or, in the recent case of Dan Ariely, might be fraudulent. Then he makes a jump from there by calling the behavioral field of inquiry a “fad”. That’s not accurate. (See Scott Alexander on Ariely and related complaints.)

In his op-ed, Albrecht names the asset bubble as a faddish behavioral idea. Vernon Smith (with Suchanek and Williams) published “Bubbles, Crashes and Endogenous Expectations in Experimental Spot Asset Markets” in Econometrica in 1988. Bubbles have been replicated all around the world many times.  There is no doubt in anyone’s mind that the “dot com” bubble had an element of speculation that became irrational at a certain point. This is not a niche topic or a very rare occurrence. Bubbles are observed in the lab and out in the naturally occurring economy.

Should we start undergrads on bubbles before explaining the normal function of capital markets? No. Lots of people think that stock markets generally work well, communicate reliable information, and should be allowed to function with minimal regulation.  Behavioral Finance is usually right where it should be in the college curriculum, which is to be offered as an upper-division elective class for finance and economics majors. I am not going to do research on this, but I looked up courses at Cornell, and there it is: Behavioral Economics is one of many advanced elective classes offered for economics students. I don’t know how they teach ECON101 at Cornell, but it would seem like they are binning most of the behavioral content into later optional courses.

In a social media exchange, Albrecht pointed me to one of the posts by Hendrickson on how they handle the situations where it seems like economic forces are not explaining everything. Currently, for example, it seems like the labor market is not clearing right now because firms want to hire but wages are not rising. The quantity supplied seems lower than the quantity demanded at the market wage. Hendrickson claims that this market condition is temporary. He says that firms are cleverly paying bonuses to attract workers so that they won’t have to lower wages in the future when conditions return to normal post-Covid. This would be a perfect time to discuss downward nominal wage rigidity, a pervasive behavioral phenomenon.** It has been studied extensively in lab settings. Nominal wage rigidity has implications for monetary policy. Wage rigidity might be a “temporary” thing, but it helps to explain unemployment. Some of the research done by behavioral economists in this area follow the Akerlof 1982 paper on the gift exchange model. It was published 40 years ago by a Nobel prize winner and cited extensively.*** The seminal lab study of that theory is Fehr et al. 1993. There have been hundreds of replications of the main result that people will trade out of equilibrium due to positive reciprocity.

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Weigh costs, benefits, and evidence quality

Living means making decisions with imperfect information. But Covid provides many examples of how people and institutions are often still bad at this. A few common errors:

  1. Imperfect evidence = perfect evidence. “Studies show Asprin prevents Covid”. OK, were the studies any good? Did any other studies find otherwise?
  2. Imperfect evidence = “no evidence” or “evidence against”. In early 2020, major institutions like the WHO said “masks don’t work” when they meant “there are no large randomized controlled trials on the effectiveness of masks”
  3. Imperfect evidence = don’t do it until you’re sure Inaction is a choice, and often a bad one. If the costs of action are low and the potential benefits of action high, you might want to do it anyway. Think masks in 2020 when the evidence for them was mediocre, or perhaps Vitamin D now.
  4. Imperfect evidence = do it, we have to do something Even in a pandemic, it is possible to over-react if the costs are high enough and/or the evidence of benefits bad enough (possibly lockdowns, definitely taking up smoking)

Any intro microeconomics class will explain the importance of weighing both costs and benefits. But how do we know what the costs and benefits are? For many everyday purchases they are usually obvious, but in other situations like medical treatments and public policies they aren’t, particularly the benefits. We have to estimate the benefits using evidence of varying quality. This creates more dimensions of tradeoffs- do you choose something with good evidence for its benefits, but high cost? Or something with worse evidence but lower costs? Graphing this properly should take at least 3 dimensions, but to keep things simple lets assume we know what the costs are, and combine benefits and evidence into a single axis called “good evidence of substantial benefit”. This yields a graph like:

Applied to Covid strategies, this yields a graph something like this:

This is not medical advice- I say this not merely as a legal disclaimer, but because my real point is the idea that we should weigh both evidence quality and costs, NOT that my estimates of the evidence quality or costs of particular strategies are better than yours

Judging the strength of the evidence for various strategies is inherently difficult, and might go beyond simply evaluating the strength of published research. But when evaluating empirical studies on Covid, my general outlook on the evidence is:

Of course, details matter, theory matters, the number of studies and how mixed their results are matters, potential fraud and bias matters, and there’s a lot it makes sense to do without seeing an academic study on it.

Dear reader, perhaps this is all obvious to you, and indeed the idea of adjusting your evidence threshold based on the cost of an intervention goes back at least to the beginnings of modern statistics in deciding how to brew Guinness. But common sense isn’t always so common, and this is my attempt to summarize it in a few pictures.