Dan Miodownik

Secessionism in Multicultural States: Does Sharing Power Prevent or Encourage It?

Institutional frameworks powerfully determine the goals, violence, and trajectories of identitarian movements—including secessionist movements. However, both small-N and large-N researchers disagree on the question of whether “power-sharing” arrangements, instead of repression, are more or less likely to mitigate threats of secessionist mobilizations by disaffected, regionally concentrated minority groups. The PS-I modeling platform was used to create a virtual country “Beita,” containing within it a disaffected, partially controlled, regionally concentrated minority. Drawing on constructivist identity theory to determine behaviors by individual agents in Beita, the most popular theoretical positions on this issue were tested. Data were drawn from batches of hundreds of Beita histories produced under rigorous experimental conditions. The results lend support to sophisticated interpretations of the effects of repression vs. responsive or representative types of power-sharing. Although in the short run repression works to suppress ethnopolitical mobilization, it does not effectively reduce the threat of secession. Power-sharing can be more effective, but it also tends to encourage larger minority identitarian movements.

Three Two Tango: Territorial Control and Selective Violence in Israel, the West Bank, and Gaza

This article extends the formal logic of Stathis Kalyvas’ theory of selective violence to account for three political actors with asymmetric capabilities. In contrast to Kalyvas’ theory, the authors’ computer simulation suggests that (1) selective violence by the stronger actor will be concentrated in areas where weaker actors exercise control; (2) the relative level of selective violence used by weaker actors will be lower because of a reduced capacity to induce civilian collaboration; and (3) areas of parity among the three actors will exhibit low levels of selective violence perpetrated primarily by the strongest actor. Results from a logistic regression, using empirical data on Israel and two rival Palestinian factions from 2006 to 2008, are consistent with these predictions: Israel was more likely to use selective violence in areas largely controlled by Palestinian factions; zones of incomplete Israeli control were not prone to selective violence; and zones of mixed control witnessed moderate levels of selective violence, mainly by Israel. Nonetheless, Palestinian violence remained consistent with Kalyvas’ predictions.

Abstractions, Ensembles, and Virtualizations Simplicity and Complexity in Agent-Based Modeling

ions, Ensembles, and Virtualizations Simplicity and Complexity in Agent-Based Modeling Ian S. Lustick and Dan Miodownik The Unique Analytic Leverage of Agent-Based Modeling Models are analytically focused metaphors. For example, “the moon is a ghostly galleon” is a metaphor. Thinking of the moon as if it were a ghostly galleon evokes particular moods and images associated with the moon and not others. Analyzing a polity as an array of competing factions arising from social and economic interests models the polity in a particular and limited way. Portraying a political struggle in exact terms as a game of chicken involves application of a formal model to highlight certain simple, highly abstract, strategic elements in a complex multilevel reality. The distinctive advantage of a formal model is that it can be expressed unambiguously. That is, the model can be written as a computer program (as can any proper algebraic formula) and run successfully without the exercise of human interpretation or discretion. Accordingly, to translate problems of scientific interest into a language a computer can understand is to model them formally. Agent-Based Modeling (ABM) is a computerassisted methodology that allows researchers to design, analyze, and investigate formal models realized as artificial worlds inhabited by agents that interact with each other following prespecified simple rules. Agent-based models vary considerably, but they all consist of arrays of autonomous, myopic units. Whether these units are modeled as states, individuals, corporations, ethnic groups, villages, or kinship groups is up to the experimenter and his or her theoretical domain of interest. Units in an ABM environment seek to adapt to their environment as they see it based on whatever goals they are programmed to pursue. Although individual actions are wholly determined at the micro level, when large numbers of such agents operate by interacting with one another, the macro state of the array as a whole is not predictable (though patterns in multiple “runs” of the array can be). As is the case in the “real” world, the specific trajectory the array will take is an empirical matter. It results from the initial condition of the array, the rules implemented to govern individual behavior of units, the complexly interdependent effects of adaptive behavior by the units, and whatever exogenous perturbations are streamed toward the array by the Comparative Politics January 2009 224 experimenter. Standard procedure is to generate large numbers of trajectories of these virtual worlds by perturbing them randomly or introducing randomized adjustments in initial conditions. By carefully calibrating these experiments, crucial experiments can be designed to bring reliable data into contact with isolated, theoretically informed claims. To the extent that the rules governing agent behavior are derived from clear, corroborated or widely accepted theories, this methodology offers a powerful technique for refining, evaluating, and testing specific theoretical claims. The visual, controlled experimental, and transparent nature of the technique, as well as the ease with which it exports results in tabulated, statistically analyzable form, also supports its use as an idea pump for the development of theory. Traditional formal modeling methods rely on algebraic formulas to translate simple relationships into mathematical expressions. But the limits of algebra prevent such techniques from incorporating many of the things known to be true of most of the worlds social scientists find interesting, including their multidimensionality, the presence of large numbers of interacting and autonomous units, and the predominance of highly irregular but nonrandomized patterns in the distribution of traits or interaction styles. The constraint of algebraic solvability therefore limits the ability of traditional formal modeling methods to capture the richness of interesting and even well-established substantive theories. Reliance only on traditional formal modeling techniques (such as game theory and rational choice) thus often entails ignoring what the modelers actually believe to be true about analytically crucial parts of the world. However, ABM, and the computer-assisted bottom-up simulations it produces, can be designed to capture beliefs about the real world embedded in or expressed by good substantive theories, thereby providing researchers with new opportunities to examine possible and probable outcomes associated with specific theory-based claims. The revolutionary potential of this technique is associated with the fact that very large numbers of alternatively possible “futures” (or “histories”) can be produced by varying initial conditions or a specific parameter setting of interest or by subjecting the theoretically specified model to random perturbations. Because of the automatic operation of the computer, every trajectory produced by a given model is consistent with the assumptions and propositions instantiated in the operating rules of the computer programs. Arising from the specific assumptions of the model, these unique counterfactual outcomes can yield reliable data about the implications of changing assumptions, boundary conditions of claims, sufficient conditions for particular outcomes, and robustness of results. The degree to which that potential is realized is a function of the empirical validity of substantive models and the degree to which these theoretical ideas have been implemented clearly and accurately. No formal tool can substitute for empirical work based on the deep study of a single case, structured comparisons of a small number of cases, and/or the statistical analysis of data in the large N tradition. But formal techniques, and especially computer-assisted ABM simulation, are powerful complements to those techniques. An important attraction of ABM is that it can be used to explore the justification for many claims that ordinarily would be impossible to evaluate, in particular in regard to rare but interesting events. Indeed, computer-assisted ABM is the most effective technique available for conducting Ian S. Lustick and Dan Miodownik 225 very large numbers of complicated but disciplined thought experiments about futures (or pasts) that could occur or could have occurred according to available theories. Careful design of artificial worlds, including exact control of all theoretically significant parameters, allows systematic manipulation of putatively significant independent variables and precise observation of the results. Using standard techniques of controlled experimentation and producing batches of theoretically consistent but unique outcomes, social scientists can expand the realms within which their variable-rich theories encounter numbers of cases much larger than the number of variables contained in the theories. However, the method of computer assisted agent-based modeling also raises new challenges, especially in the realm of research design. As is the case with informal verbal models, there are limits to the amount of complexity it may be useful to include in a study. For example, a researcher studying political participation may well believe that participation is affected by culture, aspirations to move into elite positions, beliefs about the efficacy and responsiveness of government, or alternatives available if participation opportunities are foregone. But the research design adopted will require taking only a strictly limited subset of variables into account. If the researcher were required to specify and integrate the best model he or she considered relevant for political culture, elite recruitment, government responsiveness, or exit opportunities, the complexity of the task would paralyze the project. No form of modeling should hold out as its goal the complete theoretical specification of all relevant variables and constants. On the other hand, for many problems the availability of computer-assisted simulations allows researchers not to settle for radically stylized models with key parameter values stipulated purely for analytic convenience. Computer assisted ABM can be used to integrate multiple theoretical modules, thereby leveraging the considerable knowledge available. This capability represents an enormous opportunity, but also a challenge as unfamiliar to formal modelers wedded to algebraic solvability as it is familiar to most other researchers—the problem of balancing parsimony with verisimilitude. A model that includes too many interacting modules explosively increases both the internal complexity of the model and the size of the space of possible outcomes. This sacrifice of parsimony can interfere with both confidence in theoretical operationalizations and in the interpretation of experimental results. Typically, the question of how much complexity to include in the design of a game theoretic or rational choice model is solved by the radical simplicity enforced on problem definition, dimensionality, and other features by the need for algebraic tractability. The claim or hope is then offered, implicitly or explicitly, that the solution of the game applies equally to more complex settings. However, once the move is made to computational modeling, the “algebraic tractability” constraint vanishes. The research design options open to ABM modelers are even richer thanks to the availability of cheap computer power and modeling platforms that do not require computer programming skills. The wider horizons for formal modeling opened up by ABM make the problem of research design both more important and more difficult. ABM researchers are forced to decide whether, for a particular project, the formal model to be built should be simple, complex. This article aims to help researchers cope with this problem. After consideration Comparative Politics January 2009 226 of the turn toward ABM taken by many political scientists, a typology of th

The Political Legacies of Combat: Attitudes Toward War and Peace Among Israeli Ex-Combatants

Does combat experience foster hardliner approaches to conflict, diminishing the likelihood of reconciliation? We exploit the assignment of health rankings determining combat eligibility in the Israel Defense Forces (IDF) to examine the effect of combat exposure on support for peaceful resolution of conflict. Given the centrality of the Israeli-Palestinian conflict to global affairs, and with no resolution to the conflict currently in sight, the question of the political consequences of combat becomes all the more pressing. We find that exposure to combat hardens attitudes towards the rival and reduces support for negotiation and compromise. Importantly, these attitudes translate directly into voting behavior, such that combatants are more likely to vote for hardliner parties. These findings cast doubt on research highlighting the benign effects of combat and underscore the importance of combatant reintegration for the transition from conflict to peace.

The institutionalization of identity: Micro adaptation, macro effects, and collective consequences

Constructivist approaches to the emergence and stability of collective identities are now widely accepted. But few of the assumptions of constructivist theory regarding repertoires of identities and their mutability in response to changing circumstances have been examined or even articulated. The article shows how different conditions of a fluid and changing environment affect the stabilization or institutionalization of an identity as dominant within a polity. We used the Agent-Based Identity-Repertoire (ABIR) model as a simulation tool and confined our attention to relatively simple identity situations. Strong evidence was found for the emergence of identity institutionalization, the existence of a “crystallization” threshold, the effectiveness of divide-and-rule strategies for the maintenance of an identity as dominant, the efficacy of a network of organic intellectuals, and hegemonic levels of institutionalization. Thresholds leading to hegemony were not observed. Preliminary results from experiments examining more complex identity situations have been corroborative.

Does Political Decentralization Exacerbate or Ameliorate Ethnopolitical Mobilization? A Test of Contesting Propositions

This article presents the results of an experiment that attempted the reconciliation of opposite expectations regarding the effectiveness of political decentralization on ethno-political mobilization. An agent-based model was run thousands of times to explore the effect of decentralization. The experiments suggest that the impact is nonlinear: weak and medium levels of decentralization increase the likelihood of ethno-political mobilization, while strong decentralization decreases it. The explanation derives from how minority control of political institutions affects the dynamic of minority identity ascription and the realization of the goal or the frustration of ethnic members seeking more complete political dominance of the regional ideational space.

Youth bulge and civil war: Why a country’s share of young adults explains only non-ethnic wars

Scholars agree that young men carry out most acts of political violence. Still, there is no consensus on the link between relatively large youth cohorts and the onset of violent, armed intra-state conflicts. In this paper, we examine the effect of youth bulge, a measure of the relative abundance of youth in a country, on the onset of two different types of civil wars—ethnic and non-ethnic wars. Building on and extending three datasets used by other scholars, we theoretically argue and empirically substantiate that, as a result of the negative effects of youth bulge on the economic conditions of the youth cohorts in the country, youth bulge affects the onset of non-ethnic wars, but not the onset of ethnic wars. Possible implications and directions for further research are then suggested.

Demarking Political Space: Territoriality and the Ethnoregional Party Family

In this article we revisit the notion of territoriality, suggesting that such a focus, rather than electability, increases the universe of cases available, differentiates between these and other state-wide parties, and reveals variation between ethnoregional parties competing for support in arguably the same political space. We conclude that scholars of ethnoregional politics need to apply broadly accepted understandings of the centrality of territoriality to both case-selection criteria and dimensions of “relevance” studied in order to better understand this distinct and growing political phenomenon.

Ethnic Minority Rule and Civil War Onset How Identity Salience, Fiscal Policy, and Natural Resource Profiles Moderate Outcomes

Using an agent-based computational framework designed to explore the incidence of conflict between two nominally rival ethnic groups, we demonstrate that the impact of ethnic minority rule on civil war onset could be more nuanced than posited in the literature. By testing the effects of three key moderating variables on ethnic minority rule, our analysis demonstrates that: (i) when ethnicity is assumed to be salient for all individuals, conflict onset increases with size of the minority in power, although when salience is permitted to vary, onset decreases as minority and majority approach parity; (ii) fiscal policy—the spending and investment decisions of the minority EGIP—moderates conflict; conflict decreases when leaders make sound decisions, increases under corrupt regimes, and peaks under ethno-nationalist regimes that place a premium on territorial conquest; and lastly (iii) natural resources—their type and distribution—affect the level of conflict which is lowest in agrarian economies, higher in the presence of lootable resources, and still higher when lootable resource are “diffuse”. Our analysis generates a set of propositions to be tested empirically, subject to data availability.

Studying Performance and Learning With ABIR The Effects of Knowledge, Mobilizing Agents, and Predictability

This study uses the Agent-Based Identity Repertoire model to investigate the ability of populations to adapt and learn in an unpredictable environment. The authors’ findings highlight the trade-off between adaptation and diversity in the pursuit of performance but also show that this trade-off is far from straightforward. Increasing sophistication improves the ability to adapt but reduces diversity, imposing high costs down the line. However, high levels of sophistication also produce small, stable homogeneous clusters of agents, which slow down declines in diversity. Innovative or entrepreneurial agents reacting more rapidly to environmental signals increase the prevalence of such clusters, helping diversity but hampering adaptability. The authors also show that more predictable environments facilitate successful adaptation, especially for populations of intermediate sophistication. Finally, the authors conclude that the trade-off between adaptation and diversity is such that in the present model, long-term learning is difficult to achieve.