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Below results based on the criteria 'path dependence'
Total number of records returned: 4
Electoral Competition with Endogenous Voter Preferences
The spatial model of electoral competition first proposed by Anthony Downs and subsequently extended by many authors is a core part of formal political theory. It has been and is currently used to study a wide variety of electoral processes and political institutions and its properties under many alternative conditions are now well known. All of this work, however, maintains the assumption that voters' preferences are exogenously given and can be treated as fixed while studying the behavior of competing parties and candidates. This makes all the resulting predictions conditional on this assumption. Empirical studies of voter preferences, by contrast, have connected changes in preferences to the platforms and actions of the competing parties and candidates. The paper connects these two literatures by developing a model of electoral competition that makes preferences endogenous, meaning that they co-evolve with party platforms during the election process. The model, which has both an analytical and a simulation form, is explored to ascertain its implications for the existence of stable outcomes, for the ability to predict these outcomes based on initial conditions and assumptions about party behavior, and for its dynamic properties. The assumption of fixed preferences is treated as a special case of this general model, enabling comparisons of these implications for the two situations. The version with endogenous preferences exhibits path dependent properties, which makes it quite different from the more traditional model.
Models of Path Dependence with an Empirical Application
non-linear least squares
It is now commonplace in the social sciences to describe an outcome or process as path dependent. By path dependence, researchers generally mean that the sequence of events prior to the observation of the outcome has explanatory power. The paper develops models that have both path dependent and non-path dependent properties, depending upon the value of a particular parameter. The paper then uses non-linear least squares and a Monte Carlo simulation to explore how well this parameter can be estimated, meaning how well scholars can discriminate betwen the two processes. The methodology is applied to the evolution of attitudes on aid to minorities and partisanship between 1956 and 2000. The results are consistent with the path dependent model.
Modeling History Dependence in Network-Behavior Coevolution
Spatial interdependence--the dependence of outcomes in some units on those in others--is substantively and theoretically ubiquitous and central across the social sciences. Spatial association is also omnipresent empirically. However, spatial association may arise from three importantly distinct processes: common exposure of actors to exogenous external and internal stimuli, interdependence of outcomes/behaviors across actors (contagion), and/or the putative outcomes may affect the variable along which the clustering occurs (selection). Accurate inference about any of these processes generally requires an empirical strategy that addresses all three well. From a spatial-econometric perspective, this suggests spatiotemporal empirical models with exogenous covariates (common exposure) and spatial lags (contagion), with the spatial weights being endogenous (selection). From a longitudinal network-analytic perspective, we can identify the same three processes as potential sources of network effects and network formation. From that perspective, actors' self-selection into networks (by, e.g., behavioral homophily) and actors' behavior that is contagious through those network connections likewise demands theoretical and empirical models in which networks and behavior coevolve over time. This paper begins building such modeling by, on the theoretical side, extending a Markov type-interaction model to allow endogenous tie-formation, and, on the empirical side, merging a simple spatial-lag logit model of contagious behavior with a simple p-star logit model of network formation, building this synthetic discrete-time empirical model from the theoretical base of the modified Markov type-interaction model. One interesting consequence of network-behavior coevolution--identically: endogenous patterns of spatial interdependence--emphasized here is how it can produce history-dependent political dynamics, including equilibrium phat and path dependence (Page 2006). The paper explores these implications, and then concludes with a preliminary demonstration of the strategy applied to alliance formation and conflict behavior among the great powers in the first half of the twentieth century.
The Past is Ever-Present: The Dynamic Nature of Intrastate Conflict
Civil wars pose a grave challenge to international stability as they tend to recur frequently over time. Nevertheless, existing theory treats civil wars as independent events. I reconceptualize civil war as a dynamic process, which creates a new statistical challenge – modeling multi-stage processes through a series of transitions within a longitudinal process. To overcome this problem, I introduce a multi-state event history model, which models the entire civil war process as a series of successive stages in which previous outcomes shape subsequent events, and apply it to a dataset of all civil wars from 1950-2004. The results provide strong evidence that previous outcomes exert both a direct, and indirect effect on subsequent transitions, revealing the conditional nature of factors frequently associated with war and peace.