Militarized Interstate Disputes Research Articles

The democratic embargo: regime type and proxy war

Democracies rarely fight interstate wars against one another, but democratic dyads frequently engage in hostile acts short of war, such as militarized interstate disputes and the backing of coups. Do democracies wage proxy war against other elected regimes by aiding rebels with weapons and other assistance? Scholars have found that democracies generally avoid doing so—a phenomenon we term the “democratic embargo.” However, the democratic embargo remains under-theorized. Using both datasets and close examination of purported instances of democratic aid to rebels fighting other democracies, we show that the democratic embargo is stronger than first thought. In addition, we explain the democratic embargo by arguing that strong democratic institutions prevent elected leaders from engaging in proxy war against sister regimes, and embargo violations tend to occur when democratic institutions are weak. We test our theory in two ways. First, using large-N qualitative analysis (LNQA), we examine all potential exceptions to the democratic embargo between 1945 and 2011 to establish the external validity of our claim. Second, we use case studies of the Irish decision not to aid rebels fighting the United Kingdom in Northern Ireland and Pakistan’s decision to support rebels fighting India in Kashmir to assess the internal validity of our theoretical logic. The results provide clear support for our institutional explanation of the democratic embargo. Our argument has significant implications for the democratic peace theory, the study of proxy wars, and the capacity of democracies to fight rebellions.

Make concentrated trade not war?

AbstractIn a seminal paper, Martin, Mayer, and Thoenig, The Review of Economic Studies, 2008, 75(3), 865–900, show that bilateral trade decreases the probability of a militarized interstate dispute (MID), while multilateral trade increases it by allowing countries to decrease the opportunity cost of conflict through trade diversification. Lee and Pyun (2016) challenge this assertion by showing that both bilateral and multilateral trade flows reduce the likelihood of MID. This study develops an alternative measure of trade diversification based on Hirschman's (National power and the structure of foreign trade, 1945, Berkley: University of California Press) market concentration index and estimates its effect on the probability of MID. We find that the estimated impact of trade diversification on MID depends crucially on the model's inclusion of the trade–distance interaction terms.

Disparity and Diversion: Domestic Economic Inequality and MID Initiation

Abstract Scholarship has demonstrated that domestic economic inequality is related to a number of forms of intrastate conflict, such as civil wars and rebellions. There are good reasons to believe that it also has an impact on the initiation of militarized interstate disputes for diversionary reasons. Such use of external force may refocus popular attention and may reinforce the strong nationalist sentiment that tends to prevail in societies with substantial economic inequality. Our empirical results support this contention in democracies but, as expected, not in autocracies. At a time when domestic economic inequality is rising across the world, our findings may be timely.

A Liberal Peace?: The Growth of Liberal Norms and the Decline of Interstate Violence

How have understandings of fundamental norms of international society changed over time? How does this relate to the decline of interstate violence since 1945? Previous explanations have focused on regime type, domestic institutions, economic interdependence, relative power, and nuclear weapons, I argue that a crucial and underexplored part of the puzzle is the change in understanding of sovereignty over the same period. In this article, I propose a novel means of examining change in these norms between 1970 and 2014 by analyzing the content of UN Security Council resolutions. This analysis is then utilized in quantitative analysis of the level of violence dispute participants resorted to in all Militarized Interstate Disputes in the period. I find that as liberal understandings of fundamental norms have increased, that the average level of violence used has decreased. This points to a crucial missing component in the existing literature: that institutions can only constrain when political actors share the right norms.

Training Foreign Militaries for Peace – U.S. IMET and Militarized Interstate Disputes 1976-2007

How do U.S. International Military Education and Training programs affect the recipient states` behavior in militarized interstate disputes? While the relationship between U.S. military aid in the form of arms and equipment transfer and MID involvement has been studied extensively in international relations literature the effects of U.S. IMET programs on the same phenomena has been largely ignored. This study intends to fill some of this gap. This paper proposes that American educated and trained foreign military personnel return home with a better understanding about the role of the military as an instrument of national power, civil-military relations, and the cost of war. These military personnel advise their political masters against the use of military force during international disputes leading to a decreased probability of both MID initiation and escalation. To test this argument the analysis employs a merged dataset from the Correlates of War Projects and the most prominent U.S. IMET and coups data. Using logistic regression analysis this study finds that more U.S. IMET support a country receives the less likely it initiates MIDs. The analysis also finds that countries that receive U.S. IMET support are less likely to escalate ongoing MIDs to higher levels of hostility.

Spying from Space: Reconnaissance Satellites and Interstate Disputes

Despite considerable interest and debate, it has proven surprisingly difficult to demonstrate a systematic link between technological change and patterns of war and peace. At least part of the challenge may reside in finding the right place to “look” for such relationships. Technological change alters what nations can do to one another (capabilities), but in ways that are typically reflected by deals (diplomatic bargains) rather than actions. We theorize that reconnaissance satellites have revolutionized the use of information gleaned from spying in ways that discourage states from engaging in serious conflicts with one another. We analyze the impact of reconnaissance satellites on high-casualty militarized interstate disputes (MIDS) between dyads from 1950 to 2010. We find that when either the potential aggressor or target in a dyad possess reconnaissance satellites, they are significantly less likely to become involved in serious MIDs. This effect is especially powerful when both states possess reconnaissance satellites.

The MID5 Dataset, 2011–2014: Procedures, coding rules, and description

This article introduces the latest iteration of the most widely used dataset on interstate conflicts, the Militarized Interstate Dispute (MID) 5 dataset. We begin by outlining the data collection process used in the MID5 project. Next, we discuss some of the most challenging cases that we coded and some updates to the coding manual that resulted. Finally, we provide descriptive statistics for the new years of the MID data.

A Permutation-Based Changepoint Technique for Monitoring Effect Sizes

AbstractAcross the social sciences, scholars regularly pool effects over substantial periods of time, a practice that produces faulty inferences if the underlying data generating process is dynamic. To help researchers better perform principled analyses of time-varying processes, we develop a two-stage procedure based upon techniques for permutation testing and statistical process monitoring. Given time series cross-sectional data, we break the role of time through permutation inference and produce a null distribution that reflects a time-invariant data generating process. The null distribution then serves as a stable reference point, enabling the detection of effect changepoints. In Monte Carlo simulations, our randomization technique outperforms alternatives for changepoint analysis. A particular benefit of our method is that, by establishing the bounds for time-invariant effects before interacting with actual estimates, it is able to differentiate stochastic fluctuations from genuine changes. We demonstrate the method’s utility by applying it to a popular study on the relationship between alliances and the initiation of militarized interstate disputes. The example illustrates how the technique can help researchers make inferences about where changes occur in dynamic relationships and ask important questions about such changes.

Hot under the collar: A latent measure of interstate hostility

The majority of studies on international conflict escalation use a variety of measures of hostility including the use of force, reciprocity, and the number of fatalities. The use of different measures, however, leads to different empirical results and creates difficulties when testing existing theories of interstate conflict. Furthermore, hostility measures currently used in the conflict literature are ill suited to the task of identifying consistent predictors of international conflict escalation. This article presents a new dyadic latent measure of interstate hostility, created using a Bayesian item-response theory model and conflict data from the Militarized Interstate Dispute (MID) and Phoenix political event datasets. This model (1) provides a more granular, conceptually precise, and validated measure of hostility, which incorporates the uncertainty inherent in the latent variable; and (2) solves the problem of temporal variation in event data using a varying-intercept structure and human-coded data as a benchmark against which biases in machine-coded data are corrected. In addition, this measurement model allows for the systematic evaluation of how existing measures relate to the construct of hostility. The presented model will therefore enhance the ability of researchers to understand factors affecting conflict dynamics, including escalation and de-escalation processes.

Erratum to The Militarized Interstate Dispute Dataset: Putting Things in Perspective

Erratum to The Militarized Interstate Dispute Dataset: Putting Things in Perspective

Where do hawks and doves fly when shots are fired

This paper explores the diverging electoral impact of instigating high-hostility militarized interstate disputes (MIDs) on the votes shares of hawkish, right-wing and dovish, left-wing incumbents, ...

Where do hawks and doves fly when shots are fired?

This paper explores the diverging electoral impact of instigating high-hostility militarized interstate disputes (MIDs) on the votes shares of hawkish, right-wing and dovish, left-wing incumbents, respectively. More specifically, I propose that deploying troops electorally harms doves and benefits hawks. I test this hypothesis via two studies. Study-1 presents a macro-level analysis of an incumbent’s electoral performance in a dataset covering 389 elections in 27 democratic countries between 1950 and 2010. With the objective of capturing heterogeneity of individual voting behavior at the appropriate level, Study-2 scrutinizes cross-national survey results from Comparative Study of Electoral Systems (CSES) covering 19 elections in 6 democracies. Multilevel models across both studies concur that in times of conflict, voters become significantly less supportive of dovish, left-wing incumbents and slightly more so of hawkish, right-wing ones compared to times of peace. The results also suggest that doves lose particularly substantial support from their co-partisans and ideologically left leaners.

Biding time versus timely retreat: Asymmetric dependence, issue salience, and conflict duration

Trade-conflict studies focus on whether and how economic interdependence suppresses interstate conflict initiation. Meanwhile, formal theories of war show that conflict initiation is inherently tied to its termination. In this article, I seek to bridge the two literature by utilizing a war of attrition model to formalize the relationship between economic dependence and conflict duration. I theorize that the strategic calculation ultimately comes down to a trade-off between biding one’s time and retreating in a timely manner. In the context of economic attrition, states weigh the relative costs of suffering an additional round of economic disruption against the potential benefits of winning the disputed good. As such, economic dependence can have both coercive and informational effects and these effects are contingent upon issue salience. When the issue salience is low, the coercive effect dominates; states are more likely to quit conflicts as they suffer proportionally larger economic costs. When the issue salience is high enough, the informational effect can kick in; states are less likely to quit conflicts with increasing economic costs. I test these implications on the International Crisis Behavior (ICB) and the Militarized Interstate Dispute (MID) data, finding strong support for the informational effect and suggestive evidence for the coercive one.

Modelling militarized interstate disputes using data mining techniques: Prevention and prediction of conflicts

The use of modern data mining techniques on large datasets has become a recent phenomenon across a broad range of applications. One of the most frequent tasks is to build statistical models using historical data and utilize them to predict new, so far unclassified, cases. This article examines the problem of predicting a military interstate dispute between two states (dyad) by employing selected data mining techniques. Suitable methods are identified and applied to the existing dataset of politically relevant dyads. The result is the building of statistical models for the classification of potential dyadic conflicts. The overall performance of these models is verified and cost analysis is done based on the different impacts of incorrect classification. The results are compared with those of other published research studies in the field of conflict prediction; the models created by data mining techniques significantly outperform all rival algorithms and approaches. Finally, the last part of the article presents the results of applying data mining techniques to association, i.e. to discovering relationships and dependencies in the data.

The Militarized Interstate Dispute Dataset: Putting Things in Perspective

Abstract In their latest research note in our ongoing dialogue about the Militarized Interstate Dispute (MID) dataset, Gibler, Miller, and Little (GML) reiterate their concerns about a high error rate in the MID dataset and challenge our prior replication studies, which showed that GML's recommended changes to the dataset caused few substantive changes in the core findings of two published studies. In this rejoinder, we offer further explanation of our decision-making, put GML's claims about the error rate in context, defend our replication methodology and results, and offer advice for MID dataset users.

Globalization and wartime trade

This article argues that on balance globalization does not increase, and may even reduce, the opportunity cost of Militarized Interstate Disputes (MIDs), as measured by foregone merchandise trade. Specifically, globalization makes it easier for states to substitute trade partners, makes it difficult to employ trade sanctions, makes credit more available to states at conflict, and encourages trade-substituting horizontal Foreign Direct Investment (FDI) and sanctions-resilient vertical FDI. Hypotheses are supported using High Dimensional Fixed Effects regression, applied to a Gravity model, with two-way clustering of standard errors, and an analysis of the effect of globalization on the marginal effect of MIDs on international trade. This suggests that while wars are becoming infrequent in recent decades, due to other factors, trade’s contribution to peace is diminishing.

Using Word Order in Political Text Classification with Long Short-term Memory Models

Political scientists often wish to classify documents based on their content to measure variables, such as the ideology of political speeches or whether documents describe a Militarized Interstate Dispute. Simple classifiers often serve well in these tasks. However, if words occurring early in a document alter the meaning of words occurring later in the document, using a more complicated model that can incorporate these time-dependent relationships can increase classification accuracy. Long short-term memory (LSTM) models are a type of neural network model designed to work with data that contains time dependencies. We investigate the conditions under which these models are useful for political science text classification tasks with applications to Chinese social media posts as well as US newspaper articles. We also provide guidance for the use of LSTM models.

Territorial disputes and individual willingness to fight

Extant scholarship establishes that territorial issues are more likely than other types of issues to lead to militarized interstate disputes and war. One key premise is that a strong attachment to the material and symbolic values of the homeland makes people more willing to fight for their country in territorial disputes. However, there is no systematic evidence for this premise. Although recent studies investigate the effect of territorial conflict on individual attitudes and find that territorial issues are qualitatively different from other types of issues, researchers have not yet investigated how territorial threats influence people’s willingness to fight. By combining data on territorial claims from the Issue Correlates of War project with individual-level data from the World Values Survey, this article tests the relationship between territorial claims and individuals’ willingness to fight. My analysis reveals that respondents are more willing to fight for their country when their countries experience territorial claims. Building on the contentious issues approach, I further demonstrate the importance of issue salience and issue context in the relationship between territorial claims and willingness to fight. Last, I show that the relationship between territorial claims and willingness to fight depends on a country’s level of economic development or regime type.

Four Ways We Know the Democratic Peace Correlation Does Not Exist in the State of Knowledge

Abstract Multiple studies have shown that when advanced-market “contract-intensive” economy is considered in a regression of fatal militarized interstate disputes, crises, or wars, the democratic peace correlation, the observed dearth of militarized conflict between democratic nations, becomes near zero and insignificant. Defenders of the existence of a correlation of democracy with peace claim these studies contain multiple errors. This article examines the state of evidence behind all claims in this debate. Four crucial facts are identified: (1) There is no report in print that shows democracy significant in a regression of fatal disputes controlling for contractualist economy that is unencumbered with controversial practices; (2) Every empirical defense of democracy has been rebutted, and the rebuttals remain uncontested; (3) There is no democratic peace in the nineteenth century, when there were no contractualist dyads but were democratic dyads; and (4) New analyses with revised direct data on contractualist economy covering 94% of observations over the largest-observed 1920–2010 period show that democracy without contractualist economy has a near-zero correlation with peace. Together, these facts inform us that there are no scientific grounds for deeming the democratic peace correlation as existing in the state of knowledge.

Bayesian modeling for overdispersed event-count time series

Social scientists are frequently interested in event-count time-series data. One of the state-of-the-art methods, the Poisson exponentially weighted moving average (P-EWMA) model, leads to incorrect inference in the presence of omitted variables even if they are not confounding. To tackle this problem, this paper proposes a negative binomial integrated error [NB-I(1)] model, which can be estimated via Markov Chain Monte Carlo methods. Simulations show that when the data are generated by a P-EWMA model, but an non-confounding covariate is omitted at the stage of estimation, the P-EWMA model’s credible interval is optimistically too narrow to contain the true value at the nominal level, whereas the NB-I(1) model does not suffer this problem. To explore the models’ performance, we replicate a study on an annual count of militarized interstate disputes.