Network Coevolution and Democracy: A Spatial Econometric Approach

Regime transitions are contagious according to the diffusion-of-democracy literature: a country\u27s regime is affected by others\u27 through various predefined networks (e.g. geographical proximity), as well as by the country\u27s own political, economic and social attributes (e.g. GDP levels). My account departs from the existing diffusion theory by allowing for countries\u27 self-selection into peer regime networks based on their democracy levels in the past. For example, a country can form stronger dependency ties with countries that demonstrated similar democracy levels in the past (homophily). In the longitudinal setting, the traditional diffusion mechanism with the presence of self-selection generates the co-evolutionary dynamic between country networks and democracy levels. With this recursive feedback process between tie formation and democracy levels, it becomes extremely difficult to evaluate empirically how each country\u27s level of democracy is determined, because we need to distinguish the following three processes statistically. First, country-specific attributes determine the level of democracy as in the earliest democratization studies. Second, other states\u27 democracy levels also predict a country\u27s regime as demonstrated in the conventional diffusion studies. Finally with my theory of endogenous network formation, the seeming diffusion effect is partially a consequence of their self-selection into peer networks. A newer spatial econometric model, an M-STAR + Co-Evolution model, is one of the first that allows us to test for all of these three dynamics behind democratization. In my first-cut analysis, I find that all three processes indeed exist

A Scalable MCEM Estimator for Spatio-Temporal Autoregressive Models

Very large spatio-temporal lattice data are becoming increasingly common across a variety of disciplines. However, estimating interdependence across space and time in large areal datasets remains challenging, as existing approaches are often (i) not scalable, (ii) designed for conditionally Gaussian outcome data, or (iii) are limited to cross-sectional and univariate outcomes. This paper proposes an MCEM estimation strategy for a family of latent-Gaussian multivariate spatio-temporal models that addresses these issues. The proposed estimator is applicable to a wide range of non-Gaussian outcomes, and implementations for binary and count outcomes are discussed explicitly. The methodology is illustrated on simulated data, as well as on weekly data of IS-related events in Syrian districts.Comment: 29 pages, 8 figure

Towards a More Nuanced Understanding of How International Pooling of Authority May Affect the Perceived Legitimacy of Global Governance

Recent instances of political backlash against global governance efforts as well as conventional wisdom suggest that there is a link between shifting authority from the domestic to the global level, on the one hand, and the legitimacy of global governance institutions as perceived by citizens and other stakeholders on the other. We thus investigate whether and how increasing the authority of a global governance institution affects citizens’ legitimacy perceptions, using a population-based survey experiment in Germany and the United States (N=1600 each). The empirical focus is on climate change, a costly and paradigmatic global governance effort. The results show that certain shifts of political authority, such as changes to majority decision making at the international level and automatic implementation of international decisions domestically, do not significantly affect “average” citizens’ legitimacy perceptions of global governance institutions. This result is not due to citizens’ incapacity to understand the implications of increasing authority, namely, that increasing authority results in a loss of control over climate policy in Germany and the United States. Rather, legitimacy perceptions appear to be shaped by citizens’ perceptions of procedural and performance quality of such efforts as well as by their level of cognitive mobilization, namely their interest in international politics. In brief, we find that citizens relate perceived procedural and performance quality of global governance with their evaluation of its legitimacy, but that subtle shifts of authority from the domestic to the global level do not per se affect citizens’ legitimacy perceptions

Lobbying Influence - The Role of Money, Strategies and Measurements

Comparing the results for preference attainment, self-perceived influence and reputational influence, this paper analyzes the relationship between financial resources and lobbying influence. The empirical analysis builds on data from an original survey with 312 Swiss energy policy stakeholders combined with document data from multiple policy consultation submission processes. The results show that the distribution of influence varies substantially depending on the measure. While financial resources for political purposes predict influence across all measures, the relationship is positive only for some. An analysis of indirect effects sheds light on the potential mechanisms that translate financial resources into influence

A tale of two coal regimes: An actor-oriented analysis of destabilisation and maintenance of coal regimes in Germany and Japan

Phasing out coal-fired electricity is an urgent global task, critical to efforts to mitigate climate change and air pollution. Despite the growth and increasing competitiveness of renewable energy, phase-out progress is slow, with coal-fired power even reaching an all-time global high in 2021. A key factor blocking or delaying this energy transition is the active resistance of coal regime actors with vested interests. However, there is still a lack of a systemic understanding of why some actors are more influential in shaping transition processes such as changes in policies or institutions. In this article, we present a comparative case study of the political struggle around the coal policy in Germany and Japan. We use the Endowment-Practice-Institutions (EPI) framework to analyse how actors try to destabilise or maintain the institutional arrangements underpinning the coal regimes in these countries and why some are more influential in shaping the policy outcomes. Our findings show that while actors' strategies are largely determined by the socio-political context they are embedded in, there are also certain patterns and common sequences of practices. These include commissioning a study, disseminating it through various networks and social media channels, mobilising the public through demonstrations, and engaging in advocacy with the aim of increasing the political bargaining power. Our analytical framework, which can be applied to various settings, helps to understand why certain policy outcomes occur amidst efforts to spur or stall energy transitions, and why regimes are destabilised in some case - but not in others

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\u27 self-selection into networks (by, e.g., behavioral homophily) and actors\u27 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 "Unfriending" Problem: The Consequences of Homophily in Friendship Retention for Causal Estimates of Social Influence

An increasing number of scholars are using longitudinal social network data to try to obtain estimates of peer or social influence effects. These data may provide additional statistical leverage, but they can introduce new inferential problems. In particular, while the confounding effects of homophily in friendship formation are widely appreciated, homophily in friendship retention may also confound causal estimates of social influence in longitudinal network data. We provide evidence for this claim in a Monte Carlo analysis of the statistical model used by Christakis, Fowler, and their colleagues in numerous articles estimating "contagion" effects in social networks. Our results indicate that homophily in friendship retention induces significant upward bias and decreased coverage levels in the Christakis and Fowler model if there is non-negligible friendship attrition over time.Comment: 26 pages, 4 figure

Estimating Interdependence Across Space, Time and Outcomes in Binary Choice Models Using Pseudo Maximum Likelihood Estimators

Binary outcome models are frequently used in Political Science. However, such models have proven particularly dicult in dealing with interdependent data structures, including spatial autocorrelation, temporal autocorrelation, as well as simultaneity arising from endogenous binary regressors. In each of these cases, the primary source of the estimation challenge is the fact that jointly determined error terms in the reduced-form specication are analytically intractable due to a high-dimensional integral. To deal with this problem, simulation approaches have been proposed, but these are computationally intensive and impractical for datasets with thousands of observations. As a way forward, in this paper we demonstrate how to reduce the computational burder signicantly by (i) introducing analytically tractable pseudo maximum likelihoodestimators for latent binary choice models that exhibit interdependence across space, time and/or outcomes, and by (ii) proposing an implementation strategy that increases computational eciency considerably. Monte-Carlo experiments demonstrate that our estimators perform similarly to existing alternatives in terms of error, but require only a fraction of the computational cost

Network Selection and Path-Dependent Coevolution

Scholars have increasingly become aware that actors’ self-selection into networks (e.g., homophily) is an important determinant of network-tie formation. Such self-selection adds methodological complexity to the empirical evaluation of the effects of network ties on individual behavior. Moreover, the endogenous network formation implies that network-tie structures and actors’ behavior “coevolve” over time. Therefore, in longitudinal network studies, it is very crucial for scholars to understand the nature of coevolutionary dynamics in the data, in order to explain the network-formation and the behavioral-decision-making mechanisms accurately. In this project, we claim that one of the most important aspects of the coevolutionary dynamic is its connection with history dependence. By history dependence, we primarily focus on what Page (2006) defines as “phat” and path dependence. We first establish theoretically that systems with coevolution can easily generate multiple equilibria (i.e., the steady states of the system), using a simple Markov type-interaction model that allows for endogenous tie formation. The potential of multiple equilibria posits an important and very difficult empirical question--how sensitive are equilibrium distributions (over types) to the past states? More simply put, to what extent does history matter? What is at stake in this question is not trivial. If history matters for an equilibrium attained in the society, then we can also analyze the potential policy interventions that could change the path of the social process such that it would lead to a socially optimal equilibrium. As for the empirical strategy, we start with developing a discrete-time Markov model, combining a spatial-logit and p-star model to evaluate the empirical significance of coevolutionary dynamics in the data. The strength of this empirical approach is in its direct connection with the theoretical Markov interaction model, and can provide a foundation for developing statistical tests for history dependence generated by coevolution

Equally supportive but for different reasons: Investigating public support for national energy transition goals vs. their implementation

Energy system transitions in democracies requires to reconcile national interests and central planning with the public’s preferences. To find ways of making public support for national energy strategies and technological implementation more aligned, this article investigates public support for the Swiss national energy strategy and two specific technological measures that are part of it: expansion of hydropower and deep geothermal energy. We address two research questions. First, how does public support for a national energy transition strategy differ from public support for the specific technology endorsed in the energy transition strategy? Second, are there differences in the factors influencing public support for these technologies? We investigate these questions empirically with a survey (n=640) focused on understanding the roles that energy expectations, future orientation, knowledge, and trust play in generating support for these two policy levels and between technologies. We find that while general support for an energy transition is well explained by above factors, this is true only to a much lesser extent for technology support. One conclusions is that while political ideologies play a role for the support of general energy transition goals, the support of energy technologies does not seem to be an issue that is politicized (yet?)