Why was Ramirez suspended? Because he was using a banned substance, yes, but let’s unpack that. The purpose of the suspension is, presumably, to attempt to align the incentives such that a player who is tempted to use performance-enhancing drugs will find that the expected value of the marginal productivity of the drug use is lower than the expected value of the penalty. To break that down, there’s a probability π that a player who chooses to use banned substances will be detected, and a complementary probability (1-π) that he won’t be detected. As I discussed in an earlier post, we can run a regression and figure out what the values of the various statistics are worth. If the player is rational, he’ll be considering that using steroids will adjust his stats by some positive amount (i.e., that there will be a marginal product of drug use) and that will increase his salary when he next negotiates his contract. It’s also likely that the increased chance to be voted into the Hall of Fame or win a batting title, for example, will provide non-cash utility to the player, which we could also factor into MPdu. With the complementary probability, the player will be caught and will lose 50 games worth of salary (that is, the disincentive is 50*Salary/162, or 25/81 of his salary). Additionally, there will be disutility generated by the fans’ unwillingness to vote for him in the All-Star Game, for example, and the diminished likelihood of making the Hall of Fame.

If π*MPdu > (1-π)*25*Salary/81, then the player will rationally choose to use drugs.

If π*MPdu < (1-π)*25*Salary/81, then the player will rationally choose not to use drugs.

If π*MPdu = (1-π)*25*Salary/81, then the player will be indifferent between using drugs and not using drugs, so either choice makes sense based on the player’s tastes.

There are two main ways to decrease the proportion of players who use drugs – increase the probability of detection through more testing, or increase the disincentive to be caught using drugs by adding a lump-sum fine or increasing the length of the suspension (the 25 in our model) or both. I’m going to presume that 50 games was chosen as the length of the suspension for no good reason other than that it’s a nice big round number, and thus that the multiplier is essentially arbitrary. I’m also going to presume that Manny playing for the Isotopes imposes some positive externality on them and on the Dodgers – that the parent club will get better gate receipts from his appearances and that the players will benefit (probably by learning) from playing with a Major League-caliber player. The players in the Dodgers system will presumably be considered for MLB appearances at some point, and so the Dodgers benefit forM Ramirez‘s coaching function in his appearances at the AAA level.

(As a side note, a lump-sum fine would be a fine example of a Pigouvian Tax.)

It hardly seems fair that the Dodgers should benefit froM Ramirez‘s drug use. How do we solve this problem?

Auction Manny.

When a Major League player is suspended for drug use, allow him to make his 10 rehab starts. However, don’t automatically grant the right to assign him to the AAA club to the team he plays for. Instead, allow the clubs to bid on the right to have him do his rehab starts for their AAA team. Thus, Manny generates an externality on, say, the Buffalo Bisons (and therefore the Mets); however, the Mets have to pay an amount back to MLB that is, by the definition of an auction, more than anyone else was willing to pay.

A rational team will bid almost as much as they expect the player to generate in ticket sales and general utility, so the system is self-correcting with respect to the fame and ability of the player. However, MLB seems to benefit here. We can’t really allow that under a fair system, so I propose that the winning team’s bid be allocated to some combination of baseball development and drug education. Thus, every detected player loses $SuspensionMultiplier*Salary/162 in salary, some arbitrary club is granted the opportunity to profit from a shrewd bid but is unlikely to do so, and some combination of kids and drug education programs benefit about the amount that the arbitrary club feels Manny is worth to them as a AAA player.

Minor-league rehab
should not benefit users;
auction Manny off.

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On Friday, Luis Castillo committed an error in the bottom of the 9th inning with a one-run lead, two men on base, and two men out. The error was such that had Castillo made the play cleanly, the game would have ended with Francisco Rodriguez notching a save; however, Castillo’s error was directly responsible for two unearned runs scoring, giving Frankie a loss instead of a save.

The question: How much money does Castillo owe Rodriguez? I have a pretty good estimate.

Let’s assume, as usual, that clubs base their contract offers on the results the players create, that teams negotiate by placing roughly the same emphasis on the same statistics, and that the market for baseball players is competitive. It is then the case that when a player is a free agent, his stats will dictate the amount of money he’s offered in his next contract, and therefore we can model (using linear regression) the weight placed on each statistic. In this case, a linear regression model could tell us exactly how much money one save is worth come contract time.

Obviously, this is a complicated procedure, and it would take a lot of work to account for all possible variables, so to simplify matters, I did the following:

• Using Baseball-Reference.com‘s Play Index, I found all pitchers seven or more years into their careers (to avoid the inefficiencies of arbitration and rookies being locked into negotiating with their own teams and receiving the league minimum salary) who were free agents at the end of the 2007 season (the last free agency season available on Baseball Reference) and who pitched in relief in at least 80% of their appearances. There were 92.
• I threw out pitchers who did not play in 2008, to avoid distorting the salary output.
• I found the pitchers’ 2008 salaries and created a data file.
• Using that data, I ran a linear regression in R with these results.

First, the objections: there are obviously a number of vagaries in the data. We can’t, for example, easily account for popularity or clubhouse leadership, which are important factors in salary negotiations. This model has an R-squared statistic of .4174, meaning it explains 41% of the variation in salaries – not a huge number. The sample of pitchers is small, and it doesn’t account for people who might have had high reserve prices and refused to sign with any team despite having stats that would have helped solidify the model.

However, the SV (saves) statistic is highly statistically significant, and UR (unearned runs) is significant at the 90% level. Thus, we can estimate that if Frankie were to negotiate tomorrow for his contract, the figure that he was offered would be one save less and two unearned runs more than he would have been had Castillo not committed his error.

Since a save is worth $111,727, and an unearned run conceded is worth -$311,517, that would mean that Rodrigues would lose $[111727+2*(311517)] = $734,761 if he were to negotiate his contract tomorrow. Of course, he isn’t – he won’t negotiate until the end of the 2011 season. Thus, we have to discount twice.

Assuming a 20% interest rate, 734716*.8*.8 = 470,218.24 or about $470,000. (We’ll assume that teams discount the prior years’ performance and focus mainly on the immediately preceding year. 20% is a fairly high level of discounting, meaning that Frankie would be able to make up for lost stats by performing well next year and the year after.) Thus, Luis Castillo may have imposed a $470,000 externality on Francisco Rodriguez’ next contract negotiation.

If I were Luis, I’d offer him a steak dinner instead.

Luis Castillo
commits minor league error;
externality.

No, of course not. Find out why behind the cut.

It’s a tempting story – that a secret, untapped pitching ability lurks inside players known more for their bats, and the idea that someone playing in the outfield could be the world’s greatest reliever if only they’d give him the chance. Scott Spiezio pitched once for the St. Louis Cardinals and has a facebook group dedicated to his pitching prowess.

The problem is that a position player pitching has two advantages, one much stronger than the other. The weak advantage is that there’s no chance to scout a position player before he pitches, with the possible exception of a known pitching threat like Wade Boggs. Even then, it’s difficult to know what the player has been holding back. The strong advantage is that, well, position players aren’t very good pitchers.

How does that work? Intuitively, a major-league batter is used to a pitcher performing at a high level. Once he’s warmed up, he has a set of skills maximized for hitting a 90-plus-mile-per-hour ball thrown at him. Timing has become second nature. This is why changeups are so effective – a player isn’t expecting a ball being hurled slowly at him, and so he swings as if a fastball were coming. Being thrown nonstop changeups (which is effectively what a position player will do, given that he doesn’t regularly practice pitching) is jarring and will throw off the batter’s concentration. To a lesser extent, this is seen when a left-handed pitcher relieves a right-handed pitcher.

Does that make sense? Let’s make the assumption that a player at the major league level will be used where his manager assumes he will make the strongest contribution to the team, as constrained by the rest of the talent available. Thus, while Swish would make a perfectly cromulent designated hitter on some teams, and plays enough first base to be a starter for some clubs, his best fit for the Yankees is playing the corners in the outfield. It would be economically inefficient and thus irrational for Joe Girardi to start him at, say, shortstop, because he has a better shortstop (Cody Ransom).

So, almost entirely because Swisher is an outfielder, we can assume that he cannot pitch at the major league level. Unpacking this, he lacks some quality – consistency, endurance, speed, control, something like that – and therefore cannot be a consistently good pitcher. However, the payoff of using a player who can’t pitch consistently shrinks in emergency relief situations, since the cost of exhausting a real reliever outweighs the expected cost of using a non-pitcher to pitch (in most cases, giving up a few runs). However, as an outfielder, we know he has the arm strength to throw the ball. (This also explains why catchers, who have to have strong throwing arms and throwing reflexes, are often used as emergency relievers.) So, given that it makes economic sense to use Swisher instead of using, say, Mariano Rivera simply to fulfill the idea that only a relief pitcher should be used as a relief pitcher, it also makes sense that Swisher will perform somewhat well. He lacks only some of the qualities of a good pitcher, not all of them. Once you factor in the lack of preparation that the Rays had to face a jarring series of changeups, and the difficulty of making that mental adjustment, it is perfectly sensible to expect Swisher to have a good outing.

So why doesn’t Swish pitch every night? For the simple reason that if players expect to face a slow-hurling outfielder every night, there would be practice time dedicated to hitting 75-mile-per-hour fastballs. It would then become inefficient to use Swisher, when a harder-throwing real reliever could get outs with greater predictability.

Sorry, Swish. Great outing, but we won’t be using you again for a while.

Nick Swisher can pitch
Struck out Kapler with a change
Now stay in the field.

I haven’t had time to run the numbers, but I’m a bit dissatisfied with the Misery Index in this case. The most obvious issue is that while inflation is a bad thing, so is deflation; however, under the Index, a high deflation rate is seen to mitigate high unemployment. The second is that steady, targeted inflation is a sign that the economy is growing smoothly and under control.

Again, without crunching the numbers, I can’t say anything specific, but it seems to me that a formula with nicer properties might measure either the absolute rate of change from one period to the next (capturing volatility fairly cleanly) or, for the less mathematically inclined, the absolute value of the change. The problem of measuring a rate of change is that you’d need to correct for unemployment as well; measuring rates of change also leaves you sensitive to different lengths of time being measured, whereas the misery index as it stands can be seen as a snapshot.

So, a compromise: set a benchmark – perhaps 3% for inflation and 5% for unemployment, since those are numbers that are bandied about as “targets.” Snapshot the measure by measuring the absolute value of the rate minus the benchmark figure.

Misery Index
Accurate, but hamfisted
Plausible? Who knows?

Barry Bonds is, without a doubt, one of the most controversial figures in baseball. He’s currently trying, again, what he tried last year – shopping himself around for the league’s minimum salary. (Thanks to the Sports Law Blog for the link.) Inside, I’d like to briefly discuss collusion and look at the incentives involved with this situation.

Collusion in the economic sense involves an agreement to act inefficiently. To give an oversimplified stock example, suppose a competitive market for chili peppers. That is, there are many people growing chili peppers and many people who want to buy chili peppers. Each bushel of peppers costs about $1 to produce and process from seed to sale. The market is big enough that no one producer or consumer can affect the overall price of the peppers. If one person raises his prices, the others can easily undercut him, and if he wants to sell his peppers he’ll have to meet them. As a result, the sale price approaches the (marginal) cost of production ($1).

Now suppose that only one person grows chilies. They still cost $1 to produce, but the chili monopolist can maximize his profits however he chooses. (The standard assumption is that he’ll set the price equal to marginal revenue, not marginal cost.) If I had made up a demand function and were in the mood to do calculus, I could figure out exactly how many bushels he would produce, what their price would be, and how many fewer bushels that would be than the perfectly competitive market would yield, but the important thing is that monopolies derive more profit than competitive firms, at a cost to the consumer. (Let’s leave aside the idea of a natural monopoly, where high production costs make it more efficient for only one firm to produce.)

So, what’s collusion? Simply, it’s an agreement by two or more firms to act like a monopoly and split the much higher monopoly profits. This is good for the firms and (generally) bad for the consumers because there’s a loss of welfare – some people want the product but at the higher monopoly price they can’t afford it and the monopoly produces fewer goods than the competitive market.

And what does this have to do with Bonds? Consider that Bonds is a producer of runs, and production can be roughly measured by the OPS stat. (There are other methods, but I’ll follow SI’s lead.) Assume that there’s a positive relation between previous OPS and salary (that is, that when negotiating contracts you can put OPS into a formula and that formula will spit out a salary, and that most salaries more or less line up with it), and that Bonds would play either right field or DH, so defense wouldn’t impose an additional cost. A rational team, when offered Bonds’ OPS number for a significantly smaller salary than it would otherwise have to shell out for the same number, should sign Bonds for $400,000. It would be fairly easy to make the leap from this statement of rational behavior to declaring that the teams are behaving irrationally and therefore must be colluding.

SI make a good counterpoint – in economic terms, Bonds’ clubhouse demeanor and notoriety would cause high amounts of negative utility in terms of unhappy and distracted teammates in the first case and customers unwilling to buy tickets to see Bonds in the second. Both of these can affect the profit of the firms and would have to be accounted for in any analysis of the value the team can expect to derive from Bonds. Suppose the most extreme case – that all fans are so disgusted by Bonds that they refuse to attend games he plays in, and that his teammates are so distracted by his attitude that they produce zero runs. In that case Bonds will still be a high producer, but he would still have a decidedly negative effect on profit and on his team’s record.

SI also makes two suggestions I don’t agree with – that Bonds’ felony charges might provide a disincentive in that the team has a high probability of losing him, and that Bonds’ age makes him unattractive. The first assertion ignores the fact that Bonds will still probably produce more than $400,000 worth of runs in a partial season, so in a strict runs-to-salary relation he still represents a net profit. The second doesn’t take into account that at age 42 in 2007 Bonds was worth $15.5 million dollars and that he would have to have declined at an almost impossibly high rate to fail to produce $400,000 worth of runs. Bonds will be out of shape and fragile, but the comparison need not be Bonds now to Bonds in 2007. I’d much rather have an out-of-shape and fragile Barry Bonds as my designated hitter than a $400,000 wet-behind-the-ears rookie. Hell, considering how fragile David Ortiz is, I’d rather take Bonds at $400,000 than Ortiz at his market salary. (The Red Sox could spend the difference on a new fifth starter now that Curt Schilling retired.)

Collusion thus doesn’t make much sense to me in this case, since the incentive to break collusion would be so strong. Stable collusion requires some method for the colluders to punish a fellow colluder who cheats. In a market this would be by simply returning to competitive prices, depriving the undercutter of his excess profits. Here, unless Selig is directly involved (unlikely), there’s no way for the teams to punish anyone for signing Bonds. (Yes, I suppose they could start plunking the batters every time, but that’s not sustainable.) The alternative explanation that makes the most sense to me is the disutility argument – that production and ticket sales will suffer for any team that employs Bonds. If, however, the SI article is correct in its idle suggestion that Bud Selig has ordered teams not to sign Bonds, Selig should be ashamed of himself.

Inexpensive runs
will not placate angry fans.
“Cheap offense” indeed.

What I take from Sauer’s post is that plus-minus is a surrogate variable for ability to be a team player. That opens the broader question of what can be measured and whether nonmeasurable statistics are ever useful in building a team.

If it’s not measurable, does it exist? Many people believe so. Think, for example, of clutch hitting, the vaunted (alleged) ability of certain players, such as Derek Jeter and David Ortiz, to hit more reliably in situations where the team’s expectation of winning or losing is weighted more heavily. The usual clutch situation is described as “close and late.” Clutch hitting is widely regarded by statistical analysts to be a myth, largely an artifact of small sample size. (In some cases, such as Jeter’s as identified in Wikipedia,the reputation for clutch hitting isn’t supported by any stats at all, but just a long memory for isolated incidences of close-and-late production.)

Jeter, predictably, thinks people who find statistical evidence that he doesn’t live up to his reputation should be defenestrated.

My opinion is that measurable and objective statistics are essential for valuing players (and coaching staff). The article on Battier is a red herring – Battier has what is presumably an anomalous plus-minus, particularly when accounting for distortions based on the quality of his teammates. Battier does, in fact, “have stats.” “Team player ability” isn’t a soft, undefined concept, but rather the ability to act as a multiplier for other players’ ability, and it’s measurable in final production numbers (probably as a factor of the player’s specific marginal product of labor). Battier’s plus-minus stat is evidence of an increased marginal product of labor.

Jeter, on the other hand, is a defensive liability who happens to be productive offensively. He’s a perfectly good hitter, but his numbers should be allowed to stand on their own rather than being propped up by some ephemeral idea that he occasionally produces at full ability and runs the rest of the season at some lower value of his optimal productivity.

High plus-minus is
evidence of production;
clutch hitting is not.

This fellow doesn’t know it, but he’s trying to break signalling theory. Can he succeed? I don’t think so. My reasoning (second-order signalling) and a haiku behind the cut.

Given a homogeneous market (say, the job market for entry-level positions in a given industry), some candidates will be high-quality and some will be low-quality. It is in the hiring firm’s best interest to be able to differentiate between high- and low-quality job applicants, but it is not in the low-quality applicants’ best interest to communicate that they’re less than the best applicant for the job. As a result, it can be quite difficult to differentiate them.

In the same way, it is in a hunting lion’s best interest to pursue the slowest, least fit gazelle on the savannah, rather than the fastest, fittest gazelle. (This is a stock example and I think it comes from Charles Wheelan’s Naked Economics.) Obviously, the slow gazelles want to discourage lions from attacking them, and the fast gazelles want to discourage the lions from pursuing the fast gazelles. The best way to accomplish this is by showing that the gazelle can make a sacrifice and still be in better position than the others. Gazelles do this by stotting or pronging, a behavior in which the gazelle leaps high into the air several times before taking off in earnest. The gazelle sacrifices a head start from the predator, essentially showing that it can waste time and energy but still outrun the predator.

That example is a tad anthropomorphic, but the analogy holds. Signalling (or signaling – both spellings are common) is a way of undertaking a costly method of showing fitness as a way to differentiate oneself from the unwashed masses. The classic example, and the one used in Hal Varian’s Intermediate Economics: A Modern Approach, is “the Sheepskin Effect,” in which education is used as a signal of fitness for employment. Education is costly; not only is tuition required, but finishing a bachelor’s degree requires either that time be taken away from the workplace (by taking a less desirable job to get off-shift work to attend school during the day or by not working at all) or that school be attended part-time while working (siphoning resources to work from education while full-time students can devote more time and effort to their studies). Education is also selective; it’s much more difficult for a subpar student to finish a degree than for a talented student to do so. Education also serves as a sorting mechanism; generally speaking, it stands to reason that higher grades show higher levels of ability.

For this reason, many employers require college degrees for positions that don’t necessarily warrant them, and as a result, people who might not be interested in attending college do so anyway in order to avoid being signalled out of the market. For example, this gentleman attempted to signal his fitness for employment by pursuing a college degree at a for-profit institution.  My argument is that low-quality, for-profit colleges represent a method by which students attempt to circumvent the signalling mechanism of requiring degrees, and that the status of these colleges represents a second-order signalling mechanism by which these students can still be signalled out of the market.

The importance of signalling, as stated above, is that signalling is costly, selective, and a valid way of sorting. For-profit colleges are certainly costly, but they are not selective and are not a valid sorting mechanism. The signals provided by different colleges and universities are differentiable: a degree from Stanford, MIT, or the University of Chicago shows that the student had the ability to stay competitive at one of the top schools in the nation. A degree from a state school, such as the University at Buffalo, is less valuable but still signals that the student was either willing to put in a base level of effort or had a certain degree of intelligence necessary to get a degree.

A degree from the DeVry Institute or Everest College shows several things, none of which are very flattering. It shows that the student:

• is not aware of the reputation of for-profit schools (or else the student wouldn’t be representing the for-profit degree as equivalent to a standard degree);
• has trouble valuing the degrees (since many for-profit degrees are far more expensive than equivalent coursework at a community college), and either
• lacks research skills (since the reputation of the school and the extra costs associated with for-profit schools are readily determinable), or
• has poor judgment (knew these factors but decided to go with a for-profit school anyway).

As a result, this second-order signalling allows students like the subject of the video to be crowded out of the market due to his inability or refusal to understand the system by which he’s signalling his lack of true higher education. He essentially paid a tax in the form of higher tuition for his inability or unwillingness to research his options. He claims that the ease with which he could pass his New England Institute of Art courses shows that the United States can’t compete on the global stage; I think that perhaps his expense of $30,000 on a for-profit degree as opposed to spending a smaller amount on the same associate’s degree shows why he, personally, is unfit to compete.

Overpriced degree
Failed attempt at signalling
Sheepskin effect holds

According to the MLB Players Association FAQ, about 12% of filed arbitration requests actually went to arbitration since 1990. From 1974 to 2006 (inclusive), the overall record was 269 arbitration decisions in favor of the club to 199 in favor of the player. Whether that represents better statistical methods by the clubs, players overvaluing their contributions systemically, an inefficiency on the part of the arbitrators, or simply more effective rent-seeking on the part of the clubs is difficult to determine.

The 88% of cases that were filed but not arbitrated since 1990 were settled – that is, either the player and the team came to an agreement or the player was otherwise disposed of (say, in a trade).

A very simple model of negotiation involving arbitration might work like this:

1. Player and agent prepare request.
2. Team prepares first offer.
3. Agent and team negotiate.
4. If the numbers are close, a compromise can be reached through negotiation with a given amount of transaction costs.
5. If not, further negotiation, with additional costs, can reach a compromise.
6. If no compromise can be reached, arbitration is filed with team offer T and player offer P; negotiations continue, with marginal transaction costs accruing. T is considered the minimum, and P represents a marginal increase. The expected salary value is T + [(P-T)/2].
7. Each side argues at arbitration, and a solution is reached which favors one side completely over the other. Thus, (P-T) is allocated entirely either to the player in salary or to the team in surplus.

Under File-and-Go arbitration, step 6 is truncated; there is no marginal cost of additional negotiation because negotiation is stopped. Otherwise, the marginal costs are similar to the standard arbitration strategy.

Edmonds points out that the two players who are in arbitration with Tampa Bay this year, Willy Aybar and Dioner Navarro, made offers that were very close to the team’s offer. My conjecture is that they understand that the team’s probability of winning arbitration is greater than the player’s, all else being equal, and have made an effort to come close to the team’s offer. Tampa Bay, meanwhile, does not seem to be extracting rent in the form of very low offers; thinking at the margin, one of the most efficient teams in the league will likely save $550,000 by making reasonable but low offers.

The arbitrators are also likely to rely on traditional statistics, rather than more recently developed sabermetric statistics. It would be interesting to see what kind of record the Red Sox and the As have in arbitration.

Navarro and Aybar are making a departure from the strategy of my second-favorite player, inept catcher Josh Paul, who employed the tactic known to the Greeks as “asking for way too much given his history.” Paul was offered salaries near the league minimum after being best known for failing to tag AJ Pierzynski in the 2005 ALCS. The play led to Chicago defeating Paul’s Angels; Chicago then went on to win the World Series. He asked, in both cases, for roughly double the league minimum and was denied both times.

Good-faith team offers
Rewarded by arbiters
Josh Paul is inept

Here, BioEdge discusses the change to Singapore’s legislation:

Singapore is to allow compensation for kidney transplants and for eggs. A government proposal has been approved by a bioethics committee and legislation will be introduced early next year. The committee declared that reimbursement for kidney donation was acceptable as long as it is not “an undue inducement, nor amounting to organ trading”. … Other changes to Singapore’s legislation are contemplated: lifting the age of dead donors, which is now capped at 60 and allowing paired donation, in which a donor whose kidney is not a match for a relative, gives it to someone else, who also has a relative willing to give up a kidney.

I’d like to consider some of the ways in which this setup deviates from the theoretical perfect-competition model of supply, demand, and market-clearing price.

1. Most obviously, demand is perfectly inelastic. That may not be quite true, since a viable substitute good (dialysis) exists, but dialysis is both expensive and inconvenient. If the price of a kidney plus transplant was equal to the discounted present cost of continuing dialysis, I think it’s fair to say that the transplant would win every time. Bryan Caplan of Econlog agrees.
2. Supply, on the other hand, is more or less perfectly elastic. With rare exceptions, people are born with two functioning kidneys, of which, presuming they take care of themselves, they can function using only one. People have, presumably, a very high point of indifference for money versus kidney, but it exists for everyone. Therefore, supply will be entirely dependent on the government’s compensation limit.
3. Transaction costs are much higher than most goods. Black-market trade in organs to donate exists, of course, but to engage safely in a black-market kidney sale requires the cooperation of someone with at least some medical training.
4. Kidneys are not exactly fungible because of blood types, leading to a problem of double coincidence of wants. This is ameliorated in the law by allowing paired donation.
5. The government of Singapore isn’t interested in finding a fair price for kidneys. It does not want compensation to unduly influence the decision to donate an organ, nor to encourage organ trading. The problem with this position is that it doesn’t make sense. Given an enforced compensation of zero, a certain number of people are going to enter the market for kidneys for other reasons, generally in private transactions. The compensation in utility of giving a kidney to a friend or family member has, in the past, proven enough for some people; meanwhile, others will refuse.

The upshot of all of this is that there will be a substantial deadweight loss with regard to a perfectly competitive market, as in the case of any price ceiling with high transaction costs blocking a black-market escape hatch. The recipients will generate extra utility, of course, from their extended lifespans, and depending on the availability of kidneys on the black market currently, the compensation will likely induce additional organ donors to supply kidneys to the market. Since prices do not float freely, there will be no period in which prices are imperfectly determined, so those with an indifference point below the government-set price will derive additional producer surplus from selling their kidneys at above their minimum rate. Additionally, the effective price is slightly higher than the actual amount of compensation, because the government is providing long-term care, short-term life insurance, and priority status on organ donation lists.

The overall value can’t be determined without more information – the BioEdge article implies that the government will reimburse donors, but also states that the government will “allow” compensation. In the case of recipient payment, the utility gained will be offset by the payment, particularly if the price of a kidney is set and not allowed to vary. If the government behaves as a monopsony and acts as a broker for kidneys, then that cost will be spread across the taxpayers of Singapore, in which case the analysis is slightly more complicated.

As Caplan said, though, if I were on dialysis, I’d be booking my ticket right now.

Market created
Body’s filter may be sold
Elasticity