Welcome!

I am a political scientist specializing in international relations, formal theory, and political methodology. I received a PhD from the University of Rochester in 2015. Starting in September, I will be a Stanton Nuclear Security Postdoctoral Fellow at Stanford’s Center for International Security and Cooperation. If you want to know more, feel free to look around, download my CV, email me at williamspaniel@gmail.com, or use the links below as a cheat sheet:

Manuscripts

 

Bargaining Power and the Iran Deal

Today’s post is not an attempt to give a full analysis of the Iran deal.[1] Rather, I just want to make a quick point about how the structure of negotiations greatly favors the Obama administration.

Recall the equilibrium of an ultimatum game. When two parties are trying to divide a bargaining pie and one side makes a take-it-or-leave-it offer, that proposer receives the entire benefit from bargaining. In fact, even if negotiations can continue past a single offer, as long as a single person controls all of the offers, the receiver still receives none of the surplus.

This result makes a lot of people feel uncomfortable. After all, the outcomes are far from fair. Fortunately, in real life, people are rarely constrained in this way. If I don’t like the offer you propose me, I can always propose a counteroffer. And if you don’t like that, nothing stops you from making a counter-counteroffer. That type of negotiations is called Rubinstein bargaining, and it ends with a even split of the pie.

In my book on bargaining, though, I point out that there are some prominent exceptions where negotiations take the form of an ultimatum game. For example, when returning a security deposit, your former landlord can write you a check and leave it at that. You could try suggesting a counteroffer, but the landlord doesn’t have to pay attention—you already have the check, and you need to decide whether that’s better than going to court or not. This helps explain why renters often dread the move out.

Unfortunately for members of Congress, “negotiations” between the Obama administration and Congress are more like security deposits than haggling over the price of strawberries at a farmer’s market. If Congress rejects the deal (which would require overriding a presidential veto), they can’t go to Iran and negotiate a new deal for themselves. The Obama administration controls dealings with Iran, giving it all of the proposal power. Bargaining theory would therefore predict that the Obama administration will be very satisfied[2], while Congress will find the deal about as attractive as if there were no deal at all.

And that’s basically what we are seeing right now. Congress is up in arms over the deal (hehe). They are going to make a big show about what they claim is an awful agreement, but they don’t have any say about the terms beyond an up/down vote. That—combined with the fact that Obama only needs 34 senators to get this to work—means that the Obama administration is going to receivea very favorable deal for itself.

[1] Here is my take on why such deals work. The paper is a bit dated, but it gets the point across.

[2] I mean that the Obama administration will be very satisfied by the deal insofar as it relates to its disagreement with Congress. It might not be so satisfied by the deal insofar as it relates to its disagreement with Iran.

Serial and Credible Threats

[Serial Podcast Season 1 spoilers below]

I’m going to assume you have gone through the first season of Serial and know most of the background. However, some important recap:

According to Jay’s testimony, Adnan strangled Hae and then solicited the help of Jay to dispose of the body. The police wondered why Jay, an acquaintance of Adnan, would ever go along with that. Jay stated that he initially refused. But Adnan threatened to go to the cops about Jay’s pot dealings. Wanting to avoid that, Jay becomes an accessory to murder.

To me, this makes no sense at all. I could understand why Jay might prefer burying the body to having to deal with the police over some (relatively minor) marijuana, but the latter scenario would never happen. Adnan simply does not have a credible threat here. If Adnan goes to the police to turn in Jay, Jay can easily plead out of the crime by handing them Adnan. Jay has all the leverage here. Adnan has none.

Did Jay not realize this? I can’t imagine that is true. Jay is supposed to be street-smart. He might not understand the difference between Nash equilibrium and subgame perfect equilibrium, but he certainly should understand the difference between a credible threat and an incredible threat.

Would Jay not be willing to snitch on Adnan if Adnan turned him in? If so, then Adnan would not be deterred from pointing the police to Jay, and so maybe Jay would go along with it. But I can’t imagine this is true either. First, it would require Jay to not want to rat on the guy who just ratted on him, even though it would likely mean that Jay’s charges would be dropped. Second, we in fact know Jay was willing to snitch on Adnan—because he did!

This leads me to conclude that Jay’s lying. I’m not sure why or what it means, but I think it’s important.

TL;DR: Jay’s story is not subgame perfect.

Am I missing something here?

The Game Theory of the Cardinals/Astros Spying Affair

The NY Times reported today that the St. Louis Cardinals hacked the Houston Astros’ internal files, including information on the trade market. I suspect that everyone has a basic understanding why the Cardinals would find this information useful. “Knowledge is power,” as they say. Heck, the United States spends $52.6 billion each year on spying. But game theorists have figured out how to quantify this intuition is both interesting and under-appreciated. That is the topic of this post.

Why Trade?
Trades are very popular in baseball, and the market will essentially take over sports headlines as we approach the July 31 trading deadline. Teams like to trade for the same reason countries like to trade with each other. Entity A has a lot of object X but lacks Y, while Entity B has a lot of object Y but lacks X. So teams swap a shortstop for an outfielder, and bad teams exchange their best players for good teams’ prospects. Everyone wins.

However, the extent to which one side wins also matters. If the Angels trade a second baseman to the Dodgers for a pitcher, they are happier than if they have to trade that same second baseman for that same pitcher and pay an additional $1 million to the Dodgers. Figuring out exactly what to offer is straightforward when each side is aware of exactly how much the other values all the components. In fact, bargaining theory indicates that teams should reach such deals rapidly. Unfortunately, life is not so simple.

The Risk-Return Tradeoff
What does a team do when it isn’t sure of the other side’s bottom line? They face what game theorists call a risk-return tradeoff. Suppose that the Angels know that the Dodgers are not willing to trade the second baseman for the pitcher straight up. Instead, the Angels know that the Dodgers either need $1 million or $5 million to sweeten the deal. While the Angels would be willing to make the trade at either price, they are not sure exactly what the Dodgers require.

For simplicity, suppose the Angels can only make a single take-it-or-leave-it offer. They have two choices. First, they can offer the additional $5 million. This is safe and guarantees the trade. However, if the Dodgers were actually willing to accept only $1 million, the Angels unnecessarily waste $4 million.

Alternatively, the Angels could gamble that the Dodgers will take the smaller $1 million amount. If this works, the Angels receive a steal of a deal. If the Dodgers actually needed $5 million, however, the Angels burned an opportunity to complete a profitable trade.

To generalize, the risk-return tradeoff says the following: the more one offers, the more likely the other side is to accept the deal. Yet, simultaneously, the more one offers, the worse that deal becomes for a proposer. Thus, the more you risk, the greater return you receive when the gamble works, but the gamble also fails more often.

 

Knowledge Is Power
The risk-return tradeoff allows us to precisely quantify the cost of uncertainty. In the above example, offering the safe amount wastes $4 million times the probability that the Dodgers were only willing to accept $1 million. Meanwhile, making an aggressive offer wastes the amount that the Angels would value the trade times the probability the Dodgers needed $5 million to accept the deal; this is because the trade fails to occur under these circumstances. Consequently, the Angels are damned-if-they-do, and damned-if-they-don’t. The risk-return tradeoff forces them to figure out how to minimize their losses.

At this point, it should be clear why the Cardinals would value the Astros’ secret information. The more information the Cardinals have about other teams’ minimal demands, the better they will fare in trade negotiations. The Astros’ database provided such information. Some of it was about what the Astros were looking for. Some of it was about what the Astros thought others were looking for. Either way, extra information for the Cardinals organization would decrease the likelihood of miscalculating in trade negotiations. And apparently such knowledge is so valuable that it was worth the risk of getting caught.

Why Are the NBA Finals on Sundays and NHL Finals on Saturdays?

A simple answer: iterated elimination of strictly dominated strategies.

The NBA and NHL have an unfortunate scheduling issue: their finals take place at roughly the same time, and having games scheduled at the same time would hurt both of their ratings. But this isn’t a simple coordination game. Everyone wants to avoid playing on Fridays, which is the worst night for ratings. This forces one series to play games on Sundays, Tuesdays, and Thursdays, with the other on Saturdays, Mondays, and Wednesdays. The first series is far more favorable for ratings and advertisements: it avoids the dreaded Friday ans Saturday nights entirely and also hits the coveted Thursday night slot.[1]

So who gets the good slot and why?

Well, the NBA wins because of its popularity. Some sports fans will watch hockey or basketball no matter what, but a sizable share of the population would be willing to watch both. Sadly for the NHL, though, those general sports fans break heavily in favor of the NBA. This allows the NBA to choose its best choice and forces the NHL to be the follower.

A more technical answer relies on iterated elimination of strictly dominated strategies. In my textbook, I have analogous example between a couple of nightclubs, ONE and TWO.[2] Both need to decide whether to schedule a salsa or a disco theme. (This is like deciding whether to schedule games on Saturdays or Sundays.) More patrons prefer salsa to disco. However, ONE has an advantage in that it is closer to town, giving individuals a general preference for it. Thus, TWO really wants to avoid matching its choice with ONE.

We might imagine a payoff matrix like this:

bars

So TWO can still break even if it picks the same choice as ONE but needs to mismatch to make a profit.

How should TWO decide what to do? Well, it should observe that ONE ought to pick salsa regardless of TWO’s choice—no matter what TWO picks, ONE always makes more by choosing salsa in response. Deducing that ONE will pick salsa, TWO can safely fall back on disco.

In the NBA/NHL case, the NHL must recognize that the NBA knows it will draw uncommitted fans regardless of the NHL’s choice. This means that the NBA should pick Sunday regardless of what the NHL selects. In turn, the NHL can safely place hockey on Saturday. It’s not the perfect outcome, but it’s the best the NHL can do given the circumstances.

[1] Thursdays are the biggest day for ad sales because entertainment companies want to compete for leisure business (movies, theme parks, etc.) over the weekend.

[2] I used these names in the textbook not only because they represent Player ONE and Player TWO but also because Rochester (where I went to grad school) has a club called ONE. This led to an interesting conversation when the Graduate Student Association scheduled an open bar there. I was relatively new at the time and didn’t know much about the city. After hearing rumors about the vent, I asked a fellow grad student where it would be. “ONE,” she said.

“Yes, I know it’s at 1, but where is it?”

“ONE.”

The last two lines repeated more times than I would like to admit.

 

Can More Information Ever Hurt You?

The answer would seem to be no. After all, if information is bad for you, you could always ignore it, continue living your life naively, and do better. Further, it is easy to write down games where a player’s payoff increases with the amount of information he has, and there are plenty of applications positively connecting information to welfare, like Condorcet jury theorem.

In reality, the answer is yes. Unfortunately, you can’t always credible commit to ignoring that information. This can lead to other players not trusting you later on in an interaction, which ultimately leads to a lower payoff for you.

Here’s an example. We begin by flipping a coin and covering it so that neither player observes which side is facing up. Player 1 then chooses whether to quit the game or continue. Quitting ends the game and gives 0 to both players. If he continues, player 2 chooses whether to call heads, tails, or pass. If she passes, both earn 1. If she calls heads or tails, player 2 earns 3 for making the correct call and -3 for making the incorrect call, while player 1 receive -1 regardless.

Because player 2 doesn’t observe the flip, her expected payoff for calling heads or tails is 0. As such, we can write the game tree as follows:

game1

Backward induction easily gives the solution: player 2 chooses pass, so player 1 chooses continue. Both earn 1.

If information can only help, then allowing player 2 access to the result of the coin flip before she moves shouldn’t decrease her payoff. But look what happens when the coin flip is heads:

game2

Now the solution is for player 2 to choose heads and player 1 to quit. Both earn 0!

The case where the coin landed on tails is analogous. Player 2 now chooses tails and player 1 still quits. Both earn 0, meaning player 1 is worse off knowing the result of the coin flip.

What’s going on here? The issue is credible commitment. When player 2 does not know the result of the coin flip, she can credibly commit to passing; although heads or tails could provide a greater payoff, the pass option generates the higher utility in expectation. This credible commitment assuages player 1’s concern that player 2 will screw him over, so he continues even though he could guarantee himself a break even outcome by quitting.

On the other hand, when player 2 knows the result of the coin flip, she cannot credibly commit to passing. Instead, she can’t help but pick the option (heads or tails) that gives her a payoff of 3. But this results in a commitment problem, wherein player 1 quits before player 2 picks an outcome that gives player 1 a payoff of -1. Both end up worse off because of it.

Weird counterexamples like this prevent us from making sweeping claims about whether more information is inherently a good thing. I noted at the beginning that it is easy to write down games where payoffs increase for a player as his information increases. Most game theorists would probably agree that more information is usually better. But it does not appear that we can prove general claims about the relationship.

Amazon’s Clever Price Discrimination Strategy

Amazon likes to discount books. Here are some examples, starting with Game Theory 101: The Complete Textbook:

gt101

We are only looking at the print prices in this blog post. Originally $13.99, Game Theory 101 is yours for only $11.75.

It’s a similar story for The Rationality of War:

war

Down from $10.54, you can buy The Rationality of War for $9.30.

And finally, here’s Game Theory 101: Bargaining:

bargain

Originally $11.09, Bargaining now sits just under $10.

I suspect the average consumer is pleased to see these discounts. For authors who publish through CreateSpace, however, these discounts are incredibly confusing. We can set the original price. No matter how much Amazon discounts it, they pay us a set amount of money per sale. As such, we also like Amazon’s discounts. In fact, the larger discount is, the happier we are.

The problem is, the discounts are inconsistent. When you initially publish a book, Amazon will always tag it with the list price. Then, after some time and without any warning, Amazon might reduce the price. Or they might not. I have discussed this problem with other authors, and there doesn’t seem to be any explanation for what’s going on.

That said, I now have a theory. Amazon has found a clever form of price discrimination.

What Is Price Discrimination?
The maximum price any of us is willing to pay for a good or service can vary heavily. A lot of Americans will pay $10 or more to see Fifty Shades of Grey. Meanwhile, others may only be willing to pay $1 to see such a movie. We call such a maximum price an individual’s reservation value.

As a business owner, your dream is to charge everyone their reservation value. For example, suppose Fifty Shades’ potential audience consists of two people, one who is willing to pay $10 to see the film and the other who is willing to pay $1. If you could somehow charge the $10 person $10 and the $1 person $1, you would make $11. This makes you the most amount of money possible.

Of course, movie theaters cannot easily distinguish between those high value and low value types. As such, like most businesses, they offer a single blanket price of $10. The $10 person sees the film but the $1 person does not.

Despite the difficulty in price discriminating, businesses try it to varying degrees of success. Student and senior citizen discounts are perfect examples. Both of these groups live off of fixed (and small) incomes. Consequently, as a whole, they are less willing to pay high prices for entertainment. Businesses like movie theaters therefore offer cheaper prices to these groups than to people who tend to have larger disposable incomes.

Airplane flight prices work in a similar way. Vacation travelers are unwilling to pay $1000 for a flight across the United States. In contrast, many business travelers who need to get to New York on short notice are willing. Airlines thus charge relatively cheap prices on flights booked well in advance and massively jack up the prices on the days before takeoff.

Don’t let these discounts fool you. Although they may make it seem like the businesses are acting generously, the discounts exist to maximize profits.

Price Discrimination on Amazon
Broadly, people who publish through CreateSpace fall into one of two categories: vanity authors and what I will call profit makers. Vanity authors write books without the intention to make money. They simply want to “publish” a book so they can say they have. These authors will sell tens of books to friends and family, but their work will never catch on with a larger audience. They give self-publishing a bad name.

Profit makers use CreateSpace because they do not want to hand over a large share of revenue to a traditional publishing house. Vanity is not a concern here. They invest time in writing books and publishing through CreateSpace because they know their works will make a substantial amount of money.

Unfortunately for Amazon, it is very difficult to differentiate between vanity authors and profit makers. Further, there are substantially more vanity authors than profit makers out there. As such, Amazon’s best guess for any new book coming from CreateSpace is that the work is from a vanity author.

This is where I think Amazon’s price discrimination comes into play. Amazon suspects that every new book is vanity. Sales of vanity books do not operate like a normal market. Vanity authors are selling virtually all of their books friends and family. These individuals are willing to spend more money on these books because they know the author. Their reservation price is consequently higher than your average individual. In many cases, it may be substantially higher—a poorly edited vanity book is essentially worthless to the average consumer, but friends and family might be willing to spend $10 or $20 on the book.

If you are Amazon, what incentive do you have to cut the price? Any discount you offer directly hurts your bottom line, and these vanity books are not responding to standard supply and demand factors. Consequently, you don’t have any incentive to discount. The vanity books will be sold to the friends and family and no one else. No discount maximizes your profit.

Of course, Amazon suffers when the book is from a profit maker, not a vanity author. These books respond to supply and demand, so cutting prices by 10% can actually cause more people to buy them. So Amazon might want to reduce the price in these circumstances.

Put yourself in Amazon’s shoes for a moment. You want to discriminate here to maximize your profit. But how?

From my personal experience and discussion with other authors, I think Amazon has figured out a way. They start by offering no discount, under the assumption that the book is from a vanity author. They then wait. And wait and wait and wait. Vanity books will see their sales fall off a cliff after a month or two. Profit making books will see continued sales over the long term. This differentiates the type of book. Amazon thus cuts the price of books that sell, knowing that doing so will lead to even more sales.

To be clear, this is speculation backed up with some non-random observations. Still, I think there is a good chance that price discrimination explains Amazon’s strategy. Although the discounts may seem to be applied randomly, I can’t imagine a company with $88 billion in revenue is doing this without purpose. Price discrimination explains it.

Costly Signaling on House of Cards

[spoilers, obviously]

hoc1

hoc2

hoc3

Game theorists often talk about “burning money” metaphorically, but this is as close to reality as it gets. Doug Stamper wants President Frank Underwood to appoint him White House Chief of Staff. Frank is unsure whether Doug is a committed type or an uncommitted type. In the absence of any new information, Frank would be better off denying Doug the position, as it would give Doug the ability to feed sensitive information to Frank’s primary opponent. So Doug burns a scandalous journal entry that he could have sold for $2 million and notes that only a resolved type would be willing to forgo that gain. Frank hires him.

If you are wondering why political scientists like House of Cards so much, that’s why. Costly signaling at its finest.