Dan Lindley

“Is War Rational?

The Extent of Miscalculation and Misperception as Causes of War”

Prepared for presentation at the American Political Science Association Conference,

Philadelphia, PA

Panel 19-10: Threat Perceptions in International Security Studies

Saturday, 10:00 am

“By every rational standard, North Korea should still be deterred. In practice, however, few wars are the result of rational calculations, managed crises, and highly intellectual escalation ladders.”

“War seems to many to be an irrational act of passion....Yet for all the emotion of the battlefield, the premeditation of war is a rational process consisting of careful and deliberate calculations.”

Who is right?

ABSTRACT

            This study aims to help answer the question: Is war a rational, deliberate, Clausewitzian pursuit of states and groups, or is war more often caused by miscalculation and misperception? Assumptions about the extent of rationality underlie policy debates on subjects ranging from deterrence and missile defense to peacekeeping. The rationality assumption also creates a large but mostly implicit scholarly debate about the causes of war. Many realists and rational choice analysts fall into the Clausewitzian camp, while political psychologists and students of bureaucratic and organizational politics fall into the miscalculation and misperception camp.

                Debates about the rationality of war remain implicit for methodological, substantive, ideological, and ‘ivory tower’ reasons. Rational choice, large-N statistical, and case study scholars often ignore or are outright hostile to each other. Scholars argue for their position more than they weigh and test arguments and counterarguments from other ideological and methodological camps. 

                 Thus, despite the manifest scholarly and public policy importance of the “Is War Rational” question, few studies weigh and test rationality versus miscalculation and misperception as causes of war. Using a variety of methods, this study has begun to conduct these tests, and join these debates.

Introduction

            Is war the rational, deliberate, and Clausewitzian pursuit of states and groups, or is war more often caused by miscalculation and misperception? This is an important question because assumptions about the extent of rationality underlie policy debates on a range of subjects from deterrence and missile defense to peacekeeping. Deterrence uses arms, alliances, and deployments to shift the costs and benefits of war away from war. Those who argue for deterrence assume that war is rational and deliberate. As rationality decreases and miscalculation and misperception increases, costs and benefits become less clear and deterrence degrades. On the other hand, arguments for greater transparency, for arms control, and against militarism and hypernationalism assume that war is rooted in miscalculation and misperception. In this view, opacity, arms races and spirals, and malignant sources of misperception should be tamed because they unnecessarily aggravate hostilities and may cause unnecessary or inadvertent wars.

            Likewise, supporters of US deployment of missile defenses often argue that ‘rogue’ states are irrational and not deterrable. Opponents of missile defense counter that ‘states of concern’ are deterrable. Light peacekeeping assumes that combatants do not really want to fight, and that peace can be kept once miscalculations and misperceptions are sorted out. On the other hand, peacekeeping must be heavy or avoided altogether if the combatants have good reasons for fighting (Betts 1994).

            Across a range of policy issues, successful prescriptions for reducing the likelihood of war depend on accurate diagnoses of the causes of war. These diagnoses in turn often rely on assumptions about the prevalence of rationality and the quality of deliberation in the leadup to war.

            Scholars could help many policy debates by assessing the rationality assumption, but they have not done so. Instead, differing assumptions about rationality constitute a huge and largely implicit debate in the causes of war. For example, in answering the “Is War Rational” question, most offensive and neo-realists, rational choice analysts, materialists, and those who believe manipulated identities cause war would argue that war tends be rational and deliberate. On the other hand, some defensive realists, constructivists and cultural analysts, students of bureaucratic and organizational politics, political psychologists, and scholars who stress ancient hatreds and hypernationalism would argue that miscalculation and misperception tend to cause war. One can view the literature on the causes of war as divided into two camps: rationalist vs. miscalculation and misperception.

            Despite the manifest scholarly and public policy importance of the “Is War Rational” question, few studies weigh and test rationality versus miscalculation and misperception as causes of war. While there are many arguments on all sides of the issue, there is little sustained and explicit intellectual combat between the camps. The best example of such an exchange was the rational deterrence debate of the late 1980s and early 1990s (Achen and Snidal 1989; Downs 1989; George and Smoke 1989; Huth and Russett 1990; Jervis 1989; Lebow and Stein 1989). There is also some scholarship contrasting rational choice and psychological models, with the central finding being that the two approaches are complimentary (Geva and Mintz 1997; McDermott and Kugler 2000; Quattrone and Tversky 1988).

            Debates about the rationality of war remain implicit for methodological, substantive, ideological, and ‘ivory tower’ reasons. Rational choice, large-N statistical, and case study scholars often ignore or are outright hostile to each other (Symposium 1999). Scholarship on interstate and internal wars seems to exist in different worlds, even though, for example, ancient hatreds and hypernationalism may have a lot in common. Realists and materialists often square off against institutionalists and ideationalists for ideological reasons, even though they have things to learn from each other about preference formation, structural influences, and policy making. Finally, it seems that many in the ivory tower do not take seriously their duty to help inform policy makers. This bias against policy relevance infects everything from questions asked to clarity of presentation.

            This paper introduces the Is War Rational? topic, which is the subject of my current research project. It is at its initial stages, so comments at this stage are very helpful. Below, I provide further justification for launching the project, review some of the most pertinent literature, an overview of methods to be used, and some preliminary quantitative results. Please keep in mind that the transition of our results into the new COW 3.0 version is incomplete, and some of this paper's results reflect the previous version of the data. Questions I am pursuing and would like help on include:

•          Are there any other ways to bring large-N analysis to bear on this issue? What questions can be asked of large-N data that help us understand the prevalence of miscalculation and misperception?

•          Is there any way to approach and code cases in such a way to convince a rationalist of the predominance of miscalculation and misperception or vice versa, or are we condemned to people writing up history as they see fit (and what does that mean for social science?).

•          How to select cases?

•          How should the project evolve and how much of this question can I really address?

            •          For example, this could become an article, and a related book might be "Trainwreck Wars: What were the Causes of the Worst Failures in War Initiation History" (ie bets that went extremely poorly, where initiators were terribly and decisively beaten).

Why This Project?

            This section describes the origins of the “Is War Rational?” project, demonstrates its centrality in the scholarship on causes of war, and specifies gaps in most relevant literatures bearing on the topic: the miscalculation and misperception, quantitative, prospect theory, and rationalist literatures. In so doing, I identify a number of contributions this study is poised to make.

            The catalyst for this project was Richard Betts' critical review of Stephen Van Evera's book, Causes of War: Power and the Roots of Conflict. Based largely on his view that war is often more deliberate and rational than many would like to believe, Betts thinks Van Evera's analysis is flawed (Van Evera 1999; Betts 1999). This led me to ask: where is the book that asks "Just how much miscalculation and misperception is there? How rational is war?" There is no such book. Despite much scholarship related to these questions, no one has tackled the issue head on. That is the purpose of this project.

            The “Is War Rational” question is central in general theoretical debates about the causes of war, and also in debates about the causes of particular wars. The following table shows how most theories about the causes of war can be sorted according the assumptions they hold about the rational, Clausewitzian nature of war. The principal cites for many of these theories or schools are in the bibliography and/or in the subsequent literature review.

            The multiple explanations for the causes of war reflect a complex world, but the extent of rationality remains an under-examined assumption of many of these explanations. Note that I am not testing each of these individual theories, but am instead examining one of their core assumptions: the extent of rationality involved in the initiation of wars. It is my hope that in identifying a significant issue where scholars and analysts talk past each other, intellectual progress can be made by explicitly clashing their arguments or assumptions, weighing the arguments of each camp, and using whatever methodologies help answer the question at hand.

            Not only can general classes of arguments about the causes of war be parsed into the rational vs. miscalculation and misperception framework, so too can many debates about the causes of specific wars. Thus, progress in coding cases for rationality and miscalculation and misperception will advance these debates and the historiography of these cases. There are debates about the rationality of the Japanese before Pearl Harbor, the extent of miscalculation in decisions by Saddam Hussein in 1990/91 and Slobodan Milosevic to go to war (Stein 1993; Gagnon 94/95). For example, Sagan argues that the Japanese ‘blank slate’ debate prior to Pearl Harbor is evidence of Japanese rationality, whereas my case coding framework quickly reveals that all options were not really on the table (Sagan 1988). On the subject of World War I, Jack Levy argues for a fairly subtle form of miscalculation: many of the Great Powers wanted war prior to WWI, but the huge scale of WWI was not what they intended or predicted. Van Evera argues that WWI was caused by a web of misperceptions that he files under the rubric “cult of the offensive.” Others blame deliberate German policy (Levy 1991; Van Evera 1985; Fischer 1967, respectively).

The Miscalculation and Misperception Literature

            Prior to Van Evera’s Causes of War, the most prominent proponent of miscalculation and misperception was Geoffrey Blainey. He wrote: “Above all, most wars were likely to end in the defeat of at least one nation which had expected victory. On the eve of each war at least one of the nations miscalculated its bargaining power” (1973, 144-145). My work has already begun to flesh out this argument. For example, the COW/MID databases shows that in interstate wars with over 1000 battle deaths, initiators have won 62% of the time in the 79 wars since the Napoleonic Wars. This figure declines to 53% in the 47 wars since 1900. Overall, this suggests that initiators have made decent bets since 1823. However, in looking at more recent war, the rate of miscalculation has increased to where victory or loss is an even bet. See below for more details.

            However, to look in more detail at the issue of whether war was still a reasonable ‘bet’ for initiators, we are filtering these data to see what the relative power of the sides were on the eve of war. To what extent does strength correlate with victory? To what extent is victory predictable? So far, we have power data using armed forces on the eve of war, and are currently examining the National Materials Capability database to look at power ratios from other perspectives. Some of our power calculations are on the attached sheet: “Attacking Originators Who Lost War.” This data helps identify cases for case studies, and offers a number of insights. For example, why did India attack China in the Sino-Indian war with only 15% of China’s strength? This seems to be a case ripe for study to figure out what was India’s calculation as it went to war. Also, one can note a number of cases (Crimea, Sinai, Persian Gulf, etc.) where the power ratio initially favored the attacker, but where the attacker got balanced against by an overwhelming coalition. This suggests that states who miscalculate often do so by not looking ahead to the size of balancing coalitions. If the data exist, we will perform parallel analyses of ethnic conflicts.

            Van Evera is now the most prominent proponent of miscalculation and misperception as causes of war. Having also written a book on methods, he is more methodologically aware than most practitioners of cases studies. Van Evera's main argument in Causes of War is that misperceptions about the structure of power are the prime cause of war. The causes of these misperceptions are militarism and nationalism. However, for all Van Evera's strengths, it is not always clear why he picked his case studies; his major case study is WWI and this is an easy war to use to advance miscalculation and misperception arguments. He is right that a case that helps one induce hypotheses is also something of a test of those hypotheses, but the validity of the test depends on the extent to which that case has similar features to the universe of cases. Here, further argumentation is needed. One benefit of my approach is that I will be able to use quantitative data to help select both easy and hard cases for further study. For example, cases where weak countries start wars and get pummeled, should be hard for rationalism and easier for miscalculation and misperception. While cases where strong countries initiate and quickly defeat lesser adversaries should be easy for rationalism and relatively hard for miscalculation and misperception.

            One area where Van Evera makes a big stride is when he is explicit about comparing the baseline reality to the misperceived reality. In a chart on page 171 he compares his assessment of whether military and other factors favored the offense or defense with what actors at the time thought. In studies of misperception, it is difficult but terribly important to compare baseline "real" reality, with mis/perceptions of reality. Unfortunately, Van Evera is only explicit about baseline vs. perceived reality in this chart on p. 171 and it is unclear why he made the judgements he did. There is not enough charity given to actors at the time, in that insufficient attention is given to the issue of how much the actors should have known and what other choices they had. While it is good to be clear when one is making post-hoc assessments, one still has to work hard to justify them, and to look at the situation through the actors' eyes.

            Van Evera's work on misperception could have benefitted from more thorough attempts at gleaning lessons from the psychological literatures to understand how others discern miscalculation and misperception. Likewise, attentiveness to the rationalist literatures would have led to addressing counterarguments from that camp. The main counterargument or line of attack from the rationalists is the question: what would the equilibrium be in the absence of miscalculation and misperception? Would there still be war? In other words, rationalists would question whether the extent of miscalculation and misperception was sufficient to cause war.

            These comments are themselves post-hoc critiques of Van Evera's book, which goes long way toward refining and knitting together a complex web of causes of war. He helped kick the can down the road, and the point of these critiques is to suggest areas for further progress. On a more general level, work incorporating combinations of methodologies is becoming accepted and encouraged in political science. Scholars have finally begun to realize that instead of wars between methodologies, methodologies should be chosen to best answer the question at hand (Levy 2002).

Quantitative Literature

            There is a huge quantitative literature that examines the causes of war. However, few scholars who do large N work grapple with miscalculation and misperception, just as few scholars who grapple with miscalculation and misperception do large N quantitative work. Quantitative researchers generally do not attempt to confront miscalculation and misperception. In Geller and Singer’s review of the findings of 500+ large-N analyses on the causes of war, they argue that miscalculation and misperception are important, that the subject can best be examined with case studies, and thereafter ignore the issue (1998, 44). A notable exception is Wang and Ray (1994).

            Where scholars have examined issues like war initiation or duration, we are using the same data to make new arguments or we have come up with new or different figures. For example, Scott Bennett and Allan Stam conducted a thorough analysis of the determinants of war duration. While they looked at a number of factors, they did not look at the issue of war duration and miscalculation and misperception. Our analysis shows when war initiators win, the average length of the war is 268 days. When they lose, duration is 608 (556 including ties) days. This dramatic difference adds a quantitative twist to the arguments of Van Evera, Blainey, and Levy (1992) that states start wars thinking they will be quick and cheap. When states calculate well and win, wars are indeed shorter than when they lose. We will shortly look at fatalities to see if initiators who lose suffer more than initiators who win.

            Several scholars have looked at the frequency with which initiators win. In one of the most helpful articles for my project, Kevin Wang and James Lee Ray begin their analysis with a discussion of how different statistics for the outcomes of wars could support arguments for or against rationality and war. They provide a number of helpful statistics related to the probability of success in war, joiners/coalitions, and war duration. However, the article only looks at great power wars (as opposed to major wars of 1000 deaths), contains no case studies, and veers away from the rationality issue and into a discussion of trends in great power wars. They calculate that initiators won 28 of 40 (70%) wars in the time period since 1800 (Wang and Ray 1994).

            Bruce Bueno de Mesquita argued in The War Trap that initiators won 42 of 58 (72%) interstate wars. He used this to support his argument that war is generally rational and Clausewitzian: “if war is unintentional, we should not expect a systematic relationship between those who start wars and those who win wars” (1981, 21-22, quote p. 19). As mentioned, our overall figures based on COW version 3.0 suggest fairly robust support for Bueno de Mesquita's claim. Our figures are that initiators have won 49 out of 79 wars, or 62%, but that the figure declines to 25 out of 47 wars or 53%, post-1900 (with 7 ties). If Bueno de Mesquita is right in using initiator victory as a proxy for rationality, and I think he is in a broad sense, then the rationality in war initiation is declining. In the previous COW/MID dataset, initiators won only 29 of 66 (44%) wars. It will be interesting to see what changed. We are trying to replicate Bueno de Mesquita's data and methods to explain our discrepancies.

Psychological Approaches to IR and the Prospect Theory Literature

            To understand miscalculation and misperception, it makes sense to mine the large literature devoted to applying psychological theories to international relations. Works here range from sweeping tomes (Jervis 1976) and specific lists of propositions (Jervis 1989), to detailed examinations of psychological processes such as analogical reasoning (Khong 1992; see also Farnham 1994; Hermann 1988; Kowert and Hermann 1997).

            Within this literature, perhaps the most sustained research program has been devoted to exploring prospect theory. The major tenet of prospect theory is that people are risk-averse with respect to gains, and risk-acceptant with respect to losses (Levy 1992, 171). As McDermott (1998) demonstrates in detailed and systematic cases, prospect theory helps explain cases of leaders picking policies that do not in fact have the highest expected utilities. Because of this, prospect theory constitutes one of the most pointed and sustained attacks on rational choice and expected utility approaches (Levy 1997; Geva and Mintz 1997).

            For my purposes, one reason to survey this literature is to catalog various forms of miscalculation and misperception to which decision-makers may fall prey. Partial results of this effort are given below in the discussion. Gathering a list of misperceptions is helpful, because it can be contrasted with rational and boundedly-rational decision-making. For example, this contrast can guide one to assessing in case studies whether leaders explored all reasonable options – a sign of rational decision making – or whether options were off the table because of one of more sources of miscalculation and misperception.

            The second reason to survey this literature is to see how experts in miscalculation and misperception identify these phenomena in case studies. How do they code cases? Are there good intersubjectively agreed-upon measures of miscalculation and misperception? Although I am not an expert in this field, and I have much more reading to do, this issue seems to be a major hurdle. Keeping in mind the caveat that this is an embryonic project, I have yet to identify sufficient analyses that lay out convincing and thorough observable implications and predictions for the psychological theories under review. One of the best analyses is Khong 1992, where decisions are traced in great detail, and the choices made and not made are laid out like extensive games. Khong is keenly aware of the range of options faced by decision-makers, and seems sensitized by the rational choice approach to look at turning points and available choices.

            It may be that some of the problems applying psychology to international relations stem from the clinical roots of study of psychology. These roots create two related problems: applying clinical findings from the lab to decision-makers in offices, and generalizing about state behavior using theories based on individual behavior.

Here is a sample list of possible forms of miscalculation and misperception:

Miscalculation and Misperception Check List

            APSA NOTE: I would greatly and especially appreciate input from the discussant on these points, especially on the development of observable implications for use in case studies of psychological theories.

Rationalist Literature

            Rationalists (rational choice practitioners) tend to assume that actors and states behave rationally (Bueno de Mesquita 1981). Because of this, the rationalist literature helps identify the criteria for what a rational decision should look like in a case study: ranked preferences, subject to the transitive property, with expected utilities based on reasonably complete information. While I do not expect to find ideal rationality in the case studies, these criteria provide useful benchmarks.

            Another benefit of the rationalist approach for my study is that most case study researchers who are proponents of miscalculation and misperception often do not deal adequately with rationalist counterarguments. The prime problem in here is that not enough attention is paid to the issue of where the equilibrium would be in the absence of miscalculation and misperception. Being aware of the rationalist approach sensitizes one to preference orders and utility calculations. If war is inevitable absent miscalculation and misperception, then miscalculation and misperception is of secondary or lesser importance.

            A final benefit comes from the need to go further than the rationalists in clarifying the moral or purposive definition of rationality. Rationalists are agnostic as to the sources and purposes of rationality. An actor or state is rational so long as they do their best to pursue their subjectively defined goals (Lake and Powell, 1999, 7). On the one hand, this approach leads to charitable interpretations of history. For example, scapegoat wars are entirely rational from a leader's perspective. It is always important to try to judge the "Is War Rational?" issue from the actor's point of view. On the other hand, I do not want to abandon purpose and morality when looking at the "Is War Rational?" issue. I think it is fair and helpful to know the extent to which wars are pursued for Clausewitzian purposes (to increase the power, security, and/or wealth of the state for the benefit of some or all its citizens and not just the leader) as compared to domestic political or other purposes. Hence, cases should be evaluated in terms of both general rationality and Clausewitzian rationality. Ideally, one would code all the COW/MID wars along these lines. For me, Is War Rational? is not just about technical agnostic rationality, but also encompasses the extent to which the causes of war deviate from Clausewitzian raison d'etat rationality.

            A critique of the rationalist approach has been that it is devoid of empirical content (Green and Shapiro 1994; Evangelista 1990). To the extent this critique is still true, I hope this study helps fill the gap. In particular, I will apply explicitly rationalist criteria to my case studies, along the lines of analytic narratives (Bates 1998; see also Khong 1992). 

            Perhaps the biggest critique of the RC approach questions the validity of the rationality assumption itself. The "Is War Rational?" project launches into the heart of this debate, and even if the question can not be definitively answered, I hope to make progress in determining the extent of rationality and in the study of rationality.

            Rationalists are coping with this critique in part by incorporating bounded rationality and uncertainty into their models. For example, James Morrow argues that prospect theory’s influences on utility functions can be modeled (Geva and Mintz 1997). And James Fearon’s work shows how uncertainty and incomplete or private information can lead to war (Morrow 1997 and Fearon 1995). A byproduct of these developments is that rationalist arguments are becoming less reflective of ideal rationality and RC models are becoming increasingly indeterminate. Ideal rationality is of course a straw target. Nonetheless, relaxing ideal rationality raises tricky coding and definitional questions: at what point is calculation based on incomplete or false information actually miscalculation?

            It may be that if RC practitioners are working prospect theory and sources of near-random outcomes into their models, then perhaps RC should more properly be called game theory. If so, this may make it less of a lightening rod for criticism, but also may decrease its parsimony, and its descriptive and predictive value.

            In any case, to the extent that rationalists insert uncertainty and what is essentially miscalculation into their models, my work should help provide empirical support for the values RC practitioners incorporate for these variables in these models. More precisely, I will help specify the conditions under which a model should have a high or low value for miscalculation, for example.

Definitions

            Misperception: There are two types of misperception. First is when incorrect data are received by the decision-maker. Incorrect data describes a situation in a way that does not correspond with objective reality. The second type of misperception occurs when the decision-maker distorts incoming information.

            Miscalculation: Miscalculation occurs when decision-makers get results from an action that are different from the actions' intended goal. In other words, if one pushes button A expecting result X but actually gets result Y, then that is miscalculation.

            Based on these definitions, my view is that it is misperception when the DM ‘looks back’ to information and distorts it (or it is incorrect to begin with), and that it is miscalculation when the DM acts on the distorted information. The juncture of misperception and miscalculation is at the point when the DM ‘looks forward’ and calculates the results of a decision, based on the distorted information. This is depicted here:

-----------info----------> DM -----------policy------>

<--------------------misperception[DM]miscalculation---------------------->

            A difficulty in this way of looking things is that it is hard or probably impossible to ID miscalculation until we post hoc know what happened with the intended action. This is because we can not tell if a leader expected X but got Y until after the fact. Then we have to be fair about why Y happened. We may have to make calls as to whether the outcome was due to luck, poor planning and miscalculation, or poor planning/luck on the adversaries’ side. Likewise, it is possible that a leader that expected X and got X had no reasonable reason to get X.

            Other questions are: Is it miscalculation to make any decision based on false information? For miscalculation to occur, does one necessarily have to get Y while expecting X?

Methods

            I am proceeding in several stages and with several methods to pursue this project. I will use statistical analyses of large-N databases for three purposes. First, I will “screen” history to get a sense of the extent of miscalculation and misperception. As rough indicators, I will see how many war initiators lost wars, how many states started wars against more powerful states (and won or lost), how many states initially won their wars, but got balanced against and ended up losing, and so forth. Second, I will use these results to help identify and select cases for the case studies. Quantitative data can help avoid selection bias in choosing, for example, only easy and clear cases of miscalculation and misperception. Third, statistical analysis may reveal that certain background conditions like economic or political turbulence make states more prone to miscalculation and misperception. Once identified, these conditions can be analyzed in more detail in the case studies. The Correlates of War and Militarized Interstate Dispute databases are our main datasets. We are looking at the National Materials Capabilities set to apply more power factors than those offered by COW.

            The case studies will include a number of interstate and perhaps internal wars. There are three criteria for choosing cases. First, they must cover the range of high, medium, and low values on rationality, or miscalculation and misperception. Finding out what cases with extreme values have in common sheds light on questions such as: what tends to cause the most malignant strains of misperception? Medium value cases help determine if extreme high/low cases really are extreme or rare and help one reach more accurate and nuanced conclusions. Second, some of the cases must be comparable. Similar cases allow one to focus on the operation of fewer independent variables. Third, the cases must be of importance to scholars and/or have real-world significance. Some cases (such as World War I) may be so often debated or researched by scholars that ignoring them would look odd and would forgo a case with rich and solid data. Cases may also be significant because many people were killed. The more deadly the war, the more intrinsic its importance.

            Some of the results below illustrate where we are with the statistical work. We are working to get it ready to use to identify case studies, and have already come up with a number of useful insights. These range from the probability of success for initiators to indications of how the duration of wars varies depending on whether the initiator wins or loses. We are trying to think of additional insights we can glean from the data we have, and what other data can be fused in to answer additional “Is War Rational?” questions.

            As mentioned above, a critical task for the case studies is to identify a range of observable implications for rational and miscalculation and misperception hypotheses. We are proceeding iteratively by combing the literatures to induce these observable implications. For example, the rationalist literature tells us to look for ranked preferences as decision makers lay out their options. We are currently developing a first cut of observable implications, and then ‘test-marketing’ them to see if they can produce agreement among me and my four RAs in a case study of Pearl Harbor. This case is chosen as a first cut mainly out of personal interest, but also because the conventional wisdom is that the Japanese blundered, while some analysts like Sagan make a rationalist argument. Students have written-up the Pearl Harbor from both rationalist and miscalculationist perspectives, and then debated their positions. In addition to Pearl Harbor/World War II in the Pacific, we have written up initial studies of the Paraguay (Lopez) war, and the Korean War. The first two were chosen to shed light on wars which were disastrous and seemed highly irrational, while the latter seemed well-planned and deliberate. By using this wide range of wars, we are trying to refine and test-market the observable implications as we continue to read across various literatures.

            The following questions are asked of each case in order to create consistent comparative case studies :

1.         Why did the initiator go to war? What state and/or self-interests were being served? What were the preferences of leaders prior to war? And how were they ordered? (ala Levy)

2.         What options were considered to pursue these same interests? This is a crucial point: if all plausible options were not considered, then some element of miscalculation is likely introduced, and one can further assess whether it was misperception that foreclosed options.

3.         What was the Theory of Victory for the war initiator? Was it based on plausible assumptions and reasonably accurate data? If not, one should again search for miscalculation and misperception. Note that one can win, and still have miscalculated. Here you must specify the military/strategic calculations that justify the war.

4.         Turning to post-hoc and counterfactual analysis, the following questions arise: was war inevitable? Why was the war won/lost? Could loss have been avoided?

5.         What was the equilibrium between adversaries in the absence of miscalculation and misperception? In other words, was miscalculation and misperception necessary or sufficient to start the war; or was it not important and the war would have happened anyway?

            Recreating the calculations and war plans of states is complex, hence I anticipate archival and interview work. Generating new historical knowledge is one goal of the “Is War Rational?” project.

            One reason that case study researchers talk past each other is that they are not explicit about how they are coding their cases. Is the actor rational based on what they knew then, or are the actor irrational because in hindsight the bet for war was a poor risk? Was the actor rational because it acted for political survival and the war was a successful scapegoat war? Or was the actor rational because war was pursued for Clausewitzian purposes to maximize power and security? What standard of rationality is the researcher using as the benchmark for whether someone is rational or not: ideal rationality or some level of bounded rationality?

            To help ensure clarity, replicability, and consistent cross case analysis, we are developing coding tables to use in assessing the cases. One may be a variant of the miscalculation and misperception table above, and two others follow. In the latter table, going from the box Ideal Rationality toward the box Dominated by Miscalculation and Misperception represents the continuum of irr/rationality, and obviously the hard thing will be figuring out a reliable way to code the difference between #2 and #3.

Overall Case Study Assessment Table:

Jervis, Robert, “War and Misperception,” The Journal of Interdisciplinary History, Vol. 18, No. 4 (Spring 1988)

Jervis, Robert, "Hypotheses on Misperception," in G. John Ikenberry, ed., American Foreign Policy: Theoretical Essays (Glenview, IL: Scott, Foresman, and Co. 1989

Jervis, Robert, “Rational Deterrence: Theory and Evidence.” World Politics Vol. 41, No. 2 (January 1989) (1989b)

Khong, Yuen Foong, Analogies at War: Korea, Munich, Dien Bien Phu, and the Vietnam Decisions of 1965 (Princeton, NJ: Princeton University Press, 1992)

Knorr, Klaus and Patrick Morgan, eds., Strategic Military Surprise: Incentives and Opportunities (New Brunswick, NJ: Transaction Books, 1983)

Kowert, Paul A. and Margaret G. Hermann, “Who Takes Risks: Daring and Caution in Foreign Policy Making,” Journal of Conflict Resolution, Vol. 41, No. 5 (October 1997).

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