Tag Archives: Political Science

Does Increasing the Costs of Conflict Decrease the Probability of War?

According to many popular theories of war, the answer is yes. In fact, this is the textbook relationship for standard stories about why states would do well to pursue increased trade ties, alliances, and nuclear weapons. (I am guilty here, too.)

It is easy to understand why this is the conventional wisdom. Consider the bargaining model of war. In the standard set-up, one side expects to receive p portion of the good in dispute, while the other receives 1-p. But because war is costly, both sides are willing to take less than their expected share to avoid conflict. This gives rise to the famous bargaining range:

Notice that when you increase the costs of war for both sides, the bargaining range grows bigger:

Thus, in theory, the reason that increasing the costs of conflict decreases the probability of war is because it makes the set of mutually preferable alternatives larger. In turn, it should be easier to identify one such settlement. Even if no one is being strategic, if you randomly throw a dart on the line, additional costs makes you more likely to hit the range.

Nevertheless, history often yields international crises that run counter to this logic like trade ties before World War I. Intuition based on some formalization is not the same as solving for equilibrium strategies and taking comparative statics. Further, while it is true that increasing the costs of conflict decrease the probability of war for most mechanisms, this is not a universal law.

Such is the topic of a new working paper by Iris Malone and myself. In it, we show that when one state is uncertain about its opponent’s resolve, increasing the costs of war can also increase the probability of war.

The intuition comes from the risk-return tradeoff. If I do not know what your bottom line is, I can take one of two approaches to negotiations.

First, I can make a small offer that only an unresolved type will accept. This works great for me when you are an unresolved type because I capture a large share of the stakes. But if also backfires against a resolved type—they fight, leading to inefficient costs of war.

Second, I can make a large offer that all types will accept. The benefit here is that I assuredly avoid paying the costs of war. The downside is that I am essentially leaving money on the table for the unresolved type.

Many factors determine which is the superior option—the relative likelihoods of each type, my risk propensity, and my costs of war, for example. But one under-appreciated determinant is the relative difference between the resolved type’s reservation value (the minimum it is willing to accept) and the unresolved type’s.

Consider the left side of the above figure. Here, the difference between the reservation values of the resolved and unresolved types is fairly small. Thus, if I make the risky offer that only the unresolved type is willing to accept (the underlined x), I’m only stealing slightly more if I made the safe offer that both types are willing to accept (the bar x). Gambling is not particularly attractive in this case, since I am risking my own costs of war to attempt to take a only a tiny additional amount of the pie.

Now consider the right side of the figure. Here, the difference in types is much greater. Thus, gambling looks comparatively more attractive this time around.

But note that increasing the military/opportunity costs of war has this precise effect of increasing the gap in the types’ reservation values. This is because unresolved types—by definition—view incremental increases to the military/opportunity costs of war as larger than the resolved type. As a result, increasing the costs of conflict can increase the probability of war.

What’s going on here? The core of the problem is that inflating costs simultaneously exacerbates the information problem that the proposer faces. This is because the proposer faces no uncertainty whatsoever when the types have identical reservation values. But increasing costs simultaneously increases the bandwidth of the proposer’s uncertainty. Thus, while increasing costs ought to have a pacifying effect, the countervailing increased uncertainty can sometimes predominate.

The good news for proponents of economic interdependence theory and mutually assured destruction is that this is only a short-term effect. In the long term, the probability of war eventually goes down. This is because sufficiently high costs of war makes each type willing to accept an offer of 0, at which point the proposer will offer an amount that both types assuredly accept.

The above figure illustrates this non-monotonic effect, with the x-axis representing the relative influence of the new costs of war as compared to the old. Note that this has important implications for both economic interdependence and nuclear weapons research. Just because two groups are trading with each other at record levels (say, on the eve of World War I) does not mean that the probability of war will go down. In fact, the parameters for which war occurs with positive probability may increase if the new costs are sufficiently low compared to the already existing costs.

Meanwhile, the figure also shows that nuclear weapons might not have a pacifying effect in the short-run. While the potential damage of 1000 nuclear weapons may push the effect into the guaranteed peace region on the right, the short-run effect of a handful of nuclear weapons might increase the circumstances under which war occurs. This is particularly concerning when thinking about a country like North Korea, which only has a handful of nuclear weapons currently.

As a further caveat, the increased costs only cause more war when the ratio between the receiver’s new costs and the proposer’s costs is sufficiently great compared to that same ratio of the old costs. This is because if the proposer faces massively increased costs compared to its baseline risk-return tradeoff, it is less likely to pursue the risky option even if there is a larger difference between the two types’ reservation values.

Fortunately, this caveat gives a nice comparative static to work with. In the paper, we investigate relations between India and China from 1949 up through the start of the 1962 Sino-Indian War. Interestingly, we show that military tensions boiled over just as trade technologies were increasing their costs for fighting; cooler heads prevailed once again in the 1980s and beyond as potential trade grew to unprecedented levels. Uncertainty over resolve played a big role here, with Indian leadership (falsely) believing that China would back down rather than risk disrupting their trade relationship. We further identify that the critical ratio discussed above held—that is, the lost trade—evenly impacted the two countries, while the status quo costs of war were much smaller for China due to their massive (10:1 in personnel alone!) military advantage.

Again, you can view the paper here. Please send me an email if you have some comments!

Abstract. International relations bargaining theory predicts that increasing the costs of war makes conflict less likely, but some crises emerge after the potential costs of conflict have increased. Why? We show that a non-monotonic relationship exists between the costs of conflict and the probability of war when there is uncertainty about resolve. Under these conditions, increasing the costs of an uninformed party’s opponent has a second-order effect of exacerbating informational asymmetries. We derive precise conditions under which fighting can occur more frequently and empirically showcase the model’s implications through a case study of Sino-Indian relations from 1949 to 2007. As the model predicts, we show that the 1962 Sino-Indian war occurred after a major trade agreement went into effect because uncertainty over Chinese resolve led India to issue aggressive screening offers over a border dispute and gamble on the risk of conflict.

Why Appoint Someone More Extreme than You?

From Appointing Extremists, by Michael Bailey and Matthew Spitzer:

Given their long tenure and broad powers, Supreme Court Justices are among the most powerful actors in American politics. The nomination process is hard to predict and nominee characteristics are often chalked up to idiosyncratic features of each appointment. In this paper, we present a nomination and confirmation game that highlights…important features of the nomination process that have received little emphasis in the formal literature . . . . [U]ncertainty about justice preferences can lead a President to prefer a nominee with preferences more extreme than his preferences.

Wait, what? WHAT!? That cannot possibly be right. Someone with your ideal point can always mimic what you would want them to do. An extremist, on the other hand, might try to impose a policy further away from your optimal outcome.

But Bailey and Spitzer will have you convinced within a few pages. I will try to get the logic down to two pictures, inspired by the figures from their paper. Imagine the Supreme Court consists of just three justices. One has retired, leaving two justices with ideal points J_1 and J_2. You are the president, and you have ideal point P with standard single-peaked preferences. You can pick a nominee with any expected ideological positioning. Call that position N. Due to uncertainty, though, the actual realization of that justice’s ideal point is distributed uniformly on the interval [N – u, N + u]. Also, let’s pretend that the Senate doesn’t exist, because a potential veto is completely irrelevant to the point.

Here are two options. First, you could nominate someone on top of his ideal point in expectation:

n

Or you could nominate someone further to the right in expectation:

nprime

The first one is always better, right? After all, the nominee will be a lot closer to you on average.

Not so fast. Think about the logic of the median voter. If you nominate the more extreme justice (N’), you guarantee that J_2 will be the median voter on all future cases. If you nominate the justice you expect to match your ideological position, you will often get J_2 as the median voter. But sometimes your nominee will actually fall to the left of J_2. And when that’s the case, your nominee becomes the median voter at a position less attractive than J_2. Thus, to hedge against this circumstance, you should nominate a justice who is more extreme (on average) than you are. Very nice!

Obviously, this was a simple example. Nevertheless, the incentive to nominate someone more extreme still influences the president under a wide variety of circumstances, whether he has a Senate to contend with or he has to worry about future nominations. Bailey and Spitzer cover a lot of these concerns toward the end of their manuscript.

I like this paper a lot. Part of why it appeals to me is that they relax the assumption that ideal points are common knowledge. This is certainly a useful assumption to make for a lot of models. For whatever reason, though, both the American politics and IR literatures have almost made this certainty axiomatic. Some of my recent work—on judicial nominees with Maya Sen and crisis bargaining (parts one and two) with Peter Bils—has relaxed this and found interesting results. Adding Bailey and Spitzer to the mix, it appears that there might be a lot of room to grow here.

Understanding the Iran Deal: A Model of Nuclear Reversal

Most of the discussion surrounding the Joint Comprehensive Plan of Action (JCPOA, or the “Iran Deal”) has focused on mechanisms that monitor Iranian compliance. How can we be sure Iran is using this facility for scientific research? When can weapons inspectors show up? Who gets to take the soil samples? These kinds of questions seem to be the focus.

Fewer people have noted Iran’s nuclear divestment built into the deal. Yet Iran is doing a lot here. To wit, here are some of the features of the JCPOA:

  • At the Arak facility, the reactor under construction will be filled with concrete, and the redesigned reactor will not be suitable for weapons-grade plutonium. Excess heavy water supplies will be shipped out of the country. Existing centrifuges will be removed and stored under round-the-clock IAEA supervision at Natanz.
  • The Fordow Fuel Enrichment Plant will be converted to a nuclear, physics, and technology center. Many of its centrifuges will be removed and sent to Natanz under IAEA supervision. Existing cascades will be modified to produce stable isotopes instead of uranium hexafluoride. The associated pipework for the enrichment will also be sent Natanz.
  • All enriched uranium hexafluoride in excess of 300 kilograms will be downblended to 3.67% or sold on the international market.

Though such features are fairly common in arms agreements, they are nevertheless puzzling. None of this makes proliferation impossible, so the terms cannot be for that purpose. But they clearly make proliferating more expensive, which seems like a bad move for Iran if it truly wants to build a weapon. On the other hand, if Iran only wants to use the proliferation threat to coerce concessions out of the United States, this still seems like a bad move. After all, in bargaining, the deals you receive are commensurate with your outside options; make your outside options worse, and the amount of stuff you get goes down as well.

The JCPOA, perhaps the worst formatted treaty ever.

The JCPOA, perhaps the most poorly formatted treaty ever.

What gives? In a new working paper, I argue that undergoing such a reversal works to the benefit of potential proliferators. Indeed, potential proliferators can extract the entire surplus by divesting in this manner.

In short, the logic is as follows. Opponents (like the United States versus Iran) can deal with the proliferation problem in one of two ways. First, they can give “carrots” by striking a deal with the nuclearizing state. These types of deals provide enough benefits to potential proliferators that building weapons is no longer profitable. Consequently, and perhaps surprisingly, they are credible even in the absence of effective monitoring institutions.

Second, opponents can leverage the “stick” in the form of preventive war. The monitoring problem makes this difficult, though. Sometimes following through on the preventive war threat shuts down a real project. Sometimes preventive war just a bluff. Sometimes opponents end up fighting a target that was not even investing in proliferation. Sometimes the potential proliferator can successfully and secretly obtain a nuclear weapon. No matter what, though, this is a mess of inefficiency, both from the cost of war and the cost of proliferation.

Naturally, the opponent chooses the option that is cheaper for it. So if the cost of preventive war is sufficiently low, it goes in that direction. In contrast, if the price of concessions is relatively lower, carrots are preferable.

Note that one determinant of the opponent’s choice is the cost of proliferating. When building weapons is cheap, the concessions necessary to convince the potential proliferator not to build are very high. But if proliferation is very expensive, then making the deal looks very attractive to the opponent.

This is where nuclear reversals like those built into the JCPOA come into play. Think about the exact proliferation cost that flips the opponent’s preference from sticks to carrots. Below that line, the inefficiency weighs down everyone’s payoff. Right above that line, efficiency reigns supreme. But the opponent is right at indifference at this point. Thus, the entire surplus shifts to the potential proliferator!

The following payoff graph drives home this point. A is the potential proliferator; B is the opponent; k* is the exact value that flips the opponent from the stick strategy to the carrot strategy:

Making proliferation more difficult can work in your favor.

Making proliferation more difficult can work in your favor.

If you are below k*, the opponent opts for the preventive war threat, weighing down everyone’s payoff. But jump above k*, and suddenly the opponent wants to make a deal. Note that everyone’s payoff is greater under these circumstances because there is no deadweight loss built into the system.

Thus, imagine that you are a potential proliferator living in a world below k*. If you do nothing, your opponent is going to credibly threaten preventive war against you. However, if you increase the cost of proliferating—say, by agreeing to measures like those in the JCPOA—suddenly you make out like a bandit. As such, you obviously divest your program.

What does this say about Iran? Well, it indicates that a lot of the policy discussion is misplaced for a few of reasons:

  1. These sorts of agreements work even in the absence of effective monitoring institutions. So while monitoring might be nice, it is definitely not necessary to avoid a nuclear Iran. (The paper clarifies exactly why this works, which could be the subject of its own blog post.)
  2. Iranian refusal to agree to further restrictions is not proof positive of some secret plan to proliferate. Looking back at the graph, note that while some reversal works to Iran’s benefit, anything past k* decreases its payoff. As such, by standing firm, Iran may be playing a delicate balancing game to get exactly to k* and no further.
  3. These deals primarily benefit potential proliferators. This might come as a surprise. After all, potential proliferators do not have nuclear weapons at the start of the interaction, have to pay costs to acquire those weapons, and can have their efforts erased if the opponent decides to initiate a preventive war. Yet the potential proliferators can extract all of the surplus from a deal if they are careful.
  4. In light of (3), it is not surprising that a majority of Americans believe that Iran got the better end of the deal. But that’s not inherently because Washington bungled the negotiations. Rather, despite all the military power the United States has, these types of interactions inherently deal us a losing hand.

The paper works through the logic of the above argument and discusses the empirical implications in greater depth. Please take a look at it; I’d love to hear you comments.

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.

Bribery and Cartel Violence in Mexico

Mexico has a massive murder problem. 2012 alone saw more than 26,000 homicides in the country, the fourth most of any state in the world. Why?

Drug violence and the interaction between cartels is a major factor. In a new working paper, Paul Zachary (UCSD) and I argue that uncertainty about local leaders has a great impact on that cartel violence. Cartels benefit from using violence to eliminate rivals. Politicians, however, have a vested interest in limiting that violence. This causes tension between cartels and officials, which cartels often attempt to resolve by bribing the officials to look the other way.

Why does uncertainty matter here? Paul and I investigate a model involving two rival cartels—a status quo and a challenger—and a local politician. The cartels want to capture as much of the drug rents as feasible; the local politician wants to minimize violence, but he is willing to look the other way if he receives a large enough bribe. The game begins with the status quo cartel offering a bribe to the politician to minimize enforcement. If the politician rejects, he chooses an amount of effort to exert to reduce the effectiveness of violence, which undermines the status quo cartel’s ability to maintain its drug rents. After, both cartels choose an amount of costly violence, which determines what percentage of the drug rents each receives.

We find that successful bribes lead to higher levels of violence. This is for two reasons. First, and most obviously, additional enforcement intercepts an additional percentage of violence. But there is an important second-order effect as well. The interception of violence functionally increases the marginal cost of violence for the status quo cartel. Consequently, more enforcement not only quashes violence in action but deters some of its production as well.

The above logic leads us to investigate what might lead to bargaining failure during the bribery stage. We show that the status quo cartel’s knowledge of the politician’s level of corruption is key here. When the cartel knows the politician’s minimally sufficient bribe (which is a function of the level of corruption), it can very easily come to terms. But when the cartel can only guess from a wide range of possibilities, it might ultimately offer a bribe that isn’t big enough for the politician to bite. In expectation, this leads to higher levels of enforcement and less subsequent violence.

Our theoretical argument has a noteworthy empirical prediction. Uncertainty leads to less violence, and some work in IR indicates that there is more uncertainty about newer leaders than older leaders. Thus, in Mexico, we would expect municipalities that the same political party has controlled for longer periods to be more violent than municipalities with greater turnover. (In the absence of our argument, this would be odd: the retrospective voting literature would suggest that less violence should correlate with greater tenure, as voters should be rewarding politicians who keep the streets safe.) The data support our theory. Indeed, we estimate that an increase of one year in tenure is associated with roughly one additional murder within a municipality. Although this might not seem like much, with so many municipalities in Mexico, a countrywide increase of one year in tenure matches up with about 2300 more murders. This number is on par with the 2011 murder totals in France, Germany, United Kingdom, Netherlands, and Belgium combined but still only a fraction of the overall number of murders in Mexico in every given year.

Again, you can download the paper here. This is the abstract:

What role do politicians have in bargaining with violent non-state actors to determine the level of violence in their districts? Although some studies address this question in the context of civil war, it is unclear whether their findings generalize to organizations that do not want to overthrow the state. Unlike political actors, criminal groups monopolize markets by using violence to eliminate rivals. In the context of the Mexican Drug War, we argue that increased time in office increases cartels’ knowledge about local political elites’ willingness to accept bribes. With bribes accepted and levels of police enforcement low, cartels endogenously ratchet up levels of violence because its marginal value is greater under these conditions. We formalize our claims with a model and then test its implications with a novel dataset on violent incidents and political tenure in Mexico. We find that each additional year after an official initially takes office is associated with an additional 2,300 violent deaths countrywide.

It’s a working paper, so we’d love your feedback!

My APSA 2014 Presentation: Policy Bargaining and International Conflict

If you are looking for something to do on Friday from 10:15 to noon, head over to the Marriott Jefferson room to see my presentation on Ideology Matters: Policy Bargaining and International Conflict. It is based on a joint project with Peter Bils. Here is the abstract:

Studies of bargaining and war generally focus on two sources of incomplete information: uncertainty about the probability of victory and uncertainty about the costs of fighting. We introduce a third: ideological preferences of a spatial policy. Under these conditions, standard results from the bargaining model of war break down: peace can be inefficient and it may be impossible to avoid war. We then extend the model to allow for cheap talk pre-play communications. Whereas incentives to misrepresent normally render cheap talk irrelevant, here communication can cause peace and ensure that agreements are efficient. Moreover, peace can become more likely when the proposer becomes more uncertain about the opposing state. Our results indicate one major purpose of diplomacy during a crisis is simply to communicate preferences and that such communications can be credible.

If you can’t make it, you can download the paper here, view the slides here, or watch the presentation below:

Cheap Talk Causes Peace: Policy Bargaining and International Conflict

(Paper here.)

Here are two observations about international diplomacy:

First, crises are often the result of uncertainty about policy preferences. Currently, this is most apparent with the United States, Russia, and Ukraine. It remains unclear exactly how much influence Putin wants over Ukrainian politics. He might have expansionary aims or he may just want moderate control, aware that too much sway over Ukraine will cost Russia too much in subsidies in the long term. In the former case, the United States has reason to worry. In the latter case, the United States can relax.

Second, diplomatic conferences often discuss preferred policies. That is, the parties sit in a room and talk about what they want and what they don’t want. For scholars of crisis bargaining, this is weird. War, after all, is supposed to be the result of uncertainty about power or resolve or credible commitment. These types of discussions are seemingly cheap talk and are therefore supposed to have no effect on bargaining behavior.

In a new working paper, Peter Bils and I help explain these stylized facts. The first observation leads us to set aside the traditional sources of uncertainty–power and resolve–and instead focus on uncertainty over policy preferences on a real line, similar to the spatial model in American politics. The second observation suggests that we should study how cheap talk affects bargaining outcomes in such a world.

Our results are striking and run in contrast to the standard bargaining model of war. Rather than standardize policy preferences on a [0, 1] interval, we allow the winner of a war to endogenously decide what policy to implement afterward. This forces the parties to not only think about how likely they are to win a war and how much it will cost but also consider the quality of their post-conflict outcomes.

Without communication, we find that war may be inevitable–if your opponent’s preferred policy could range from moderate to very extreme, it is impossible to construct an offer to simultaneously appease all types. But if the range possibilities is smaller, peace can be inefficient. This is because the proposer may want to offer an amount that all types are willing to accept. Yet, in doing so, both the proposer and some types of the opponent would be both better off implementing a more moderate policy instead.

We then allow for cheap talk pre-play communication. Normally, cheap talk fails to cause meaningful change because weaker types have incentives to misrepresent; that is, they want to mimic stronger types to receive more generous demands. In some situations, this remains true in our setup. However, cheap talk can occasionally work when the uncertainty is about policy preferences. This is because moderate types sometimes do not want to bluff extremism since doing so would result in an intolerably extremist offer. As a result, where war was previously inevitable and peace was inefficient, peace always works and is efficient as well.

Empirically, this suggests that diplomacy is useful, which helps explain why states spend so much time and effort on it. And despite all of the incentives to lie, cheat, and bluff, those exchanges can sometimes be taken at face value.

Here’s the abstract from the paper:

Studies of bargaining and war generally focus on two sources of incomplete information: uncertainty about the probability of victory and uncertainty about the costs of fighting. We introduce a third: ideological preferences of a spatial policy. Under these conditions, standard results from the bargaining model of war break down: peace can be inefficient and it may be impossible to avoid war. We then extend the model to allow for cheap talk pre-play communications. Whereas incentives to misrepresent normally render cheap talk irrelevant, here communication can cause peace and ensure that agreements are efficient. Moreover, peace can become more likely when the proposer becomes more uncertain about the opposing state. Our results indicate one major purpose of diplomacy during a crisis is simply to communicate preferences and that such communications can be credible.

Sanctions, Uncertainty, and Consolidation of Power

The imposition of economic sanctions is curious. If sanctions have coercive power, powerful sanctions ought to deter rivals from pursuing objectionable policies. On the other hand, if sanctions will be ineffective in a particular case, would-be imposers ought to give up and not lose out on the gains of trade. Why, then, do we see sanctions at all?

In a new working paper from Brad Smith and myself, we argue that asymmetric information about a leader’s consolidation of power plays a critical role in the coercive process. (Edit: I am happy to report that the paper has officially been accepted International Studies Quarterly!) Sanctions ostensibly turn a subset of the selectorate against the current regime. Whether that subset will be pivotal in sparking regime change is critical to determining the effectiveness of sanctions. Because local leaders know their own political predicaments better than foreign adversaries, would-be imposers sometimes have to guess whether sanctions will be worthwhile or not.

Brad and I analyze such a predicament using a formal model. When the potential imposer is sufficiently certain that the target is robust to sanctions, it backs down so as to avoid the economic damage of ineffective sanctions. In contrast, if the imposer believes that the target is vulnerable, weaker opponents sometimes concede the policy issue and sometimes bluff strength. The imposer then sometimes calls potential bluffs (to stop the weaker types from cheating too much) and sometimes backs down (to avoid sanctions a tougher target).

While the outcomes are vastly different, we find an important result regarding the imposer’s quality of information. As the imposer becomes sufficiently certain that its target is weak or strong, the probability of sanctions imposition goes to 0. This is either because the imposer backs down at the beginning (thinking it is facing a tougher type) or because the weaker types have less incentive to bluff toughness. In turn, sanctions are most likely when the imposer is less confident about his opponent’s consolidation of power. This yields a clear testable hypothesis: we should observe fewer sanctions as quality of information increases.

Of course, information (i.e., quality of intelligence estimates) is very difficult to measure. Fortunately, recent works from Scott Wolford and Toby Rider indicate that leader tenure is a useful proxy. Leaders earlier in their careers represent greater unknowns. Over time, publicly observable actions and intelligence gathering improves intelligence estimates. Thus, we expect the likelihood of sanctions to be decreasing in the length of a target’s tenure.

Sure enough, the data support this hypothesis. Moreover, tenure is substantively significant. The plot below shows the predicted probability of sanctions given a crisis as a function of logged leader tenure, holding other observable factors at their medians. A crisis occurring four years into a leader’s term, for example, is 22% less likely to end in sanctions than if the crisis occurred at the beginning.

daysplot

Further, the effect is strongest for autocratic regimes. This fits with the theory. After all, compared to democracies, it is harder to tell who the winning coalition is in an autocracy. Increases in tenure thus generate more information about an autocrat’s vulnerability to sanctions, which in turn more precipitously drops the probability of sanction implementation.

Beyond the theoretical and substantive results, we think a key takeaway is further confirmation of tenure as a proxy for uncertainty. We encourage other scholars to consider using it in empirical models where asymmetric information affects outcomes.

Once again, here’s the paper. The abstract is below.

When do states impose sanctions on their rivals? We develop a formal model of domestic power consolidation, threats, escalation, and imposition of sanctions. With complete information, the target regime’s consolidation of power determines the result—leaders with stable control can weather sanctions and thus deter their imposition, while vulnerable leaders concede the issue. However, when an imposer is uncertain of a foreign leader’s consolidation, vulnerable types have incentive to bluff strength. Foreign powers sometimes respond by imposing sanctions, even though the parties would have resolved the crisis earlier with complete information. We then hypothesize that opponents of newer leaders—particularly in autocracies—are more likely to suffer from this information problem. Employing the Threat and Imposition of Sanctions (TIES) dataset and carefully addressing selection problems common to the sanctions literature, we show that sanctioners are indeed more likely to follow through on threats against such leaders.

New Version of “War Exhaustion and the Credibility of Arms Treaties”

I just updated the manuscript as a standalone paper. Here’s the abstract:

Why do some states agree to arms treaties while others fail to come to terms? I argue that the changing credibility of preventive war is an important determinant of arms treaty stability. If preventive war is never an option, states can reach settlements that both prefer to costly arms construction. However, if preventive war is incredible today but will be credible in the future, a commitment problem results: the state considering investment faces a “window of opportunity” and must build the arms or it will not receive concessions later on. Thus, arms treaties fail under these conditions. I then apply the theoretical findings to the Soviet Union’s decision to build nuclear weapons in 1949. War exhaustion made preventive war incredible for the United States immediately following World War II, but lingering concerns about future preventive action caused Moscow to proliferate.

Download the full paper here.

Interpret Your Cutpoints

Here is a bad research design I see way too frequently.* The author presents a model. The model shows that if sufficient amounts of x exist, then y follows. The author then provides a case study, showing that x existed and y occurred. Done.

Do you see the problem there? I removed “sufficient” as a qualifier for x from one sentence to the next. Unfortunately, by doing so, I have made the case study worthless. In fact, such case studies often undermine the exact point the author was trying to make with the model!

Let me illustrate my point with the following (intentionally ridiculous) example. Consider the standard bargaining model of war. State A and State B are in negotiations. If bargaining breaks down, A prevails militarily and takes the entire good the parties are bargaining over with probability p_A; B prevails with complementary probability, or 1 – p_A. War is costly, however; states pay respective costs c_A and c_B > 0.

That is the standard model. Now let me spice it up. One thing that the model does not consider is the cost of the stationery**, ink, and paper necessary to sign a peaceful agreement. Let’s call that cost s, and let’s suppose (without loss of generality) that state A necessarily pays the stationery costs.

Can the parties reach a peaceful agreement? Well, let x be A’s share of a peaceful settlement. A prefers a settlement if it pays more than war, or x – s > p_A – c_A. We can rewrite this as x > p_A – c_A + s.

Meanwhile, B prefers a settlement if the remainder pays better than war, or 1 – x > 1 – p_A – c_B. This reduces to x < p_A + c_B.

Stringing these inequalities together, mutually preferable peaceful settlements exist if p_A – c_A + s < x < p_A + c_B. In turn, such an x exists if s < c_A + c_B.

Nice! I have found a new rationalist explanation for war! You see, if the costs of stationery exceed the costs of war (or s > c_A + c_B), at least one state would always prefer war to peace. Thus, peace is unsustainable.

Of course, my argument is completely ridiculous–stationery does not cost that much. My theory remains valid, it just lacksĀ empirical plausibility.

And, yet, formal theorists too often fail to substantively interpret their cutpoints in this way. That is, they do not ask if real-life parameters could ever sustain the conditions necessary to lead to the behavior described.

Instead, you will get case studies that look like the following:

I presented a model that shows that the costs of stationery can lead to war. In analyzing the historical record of World War I, it becomes clear that the stationery of the bargained resolution would have been very expensive, as the ball point pen had only been invented 25 years ago and was still prohibitively costly. Thus, World War I started.

Completely ridiculous! And, in fact, the case study demonstrated the opposite of what the author had intended. That is, if you actually analyze the cutpoint, you will see that the cost of stationery was much lower than the costs of war, and thus the cost of stationery (at best) had a negligible causal connection to the conflict.

In sum, please, please interpret your cutpoints. Your model only provides useful insight if its parameters match what occurred in reality. It is not sufficient to say that cost existed; rather, you must show that the cost was sufficiently high (or low) compared to the other parameters of your model.

* This blog post is the result of presentations I observed at ISA and Midwest, though I have seen some published papers like this as well.

** I am resisting the urge to make this an infinite horizon model so I can solve for the stationary MPE of a stationery game.