Anti-Government Networks in Civil Conflicts: How Network Structures affect Conflictual Behavior

Submitted by Anna Schultz on January 20, 2013 - 8:49am
Metternich, Nils W, et al. In Press. “Anti-Government Networks in Civil Conflicts: How Network Structures affect Conflictual Behavior”. American Journal of Political Science tbd(tbd): tbd.

How do social networks among anti-government actors affect the decision of ruling authorities to challenge its opposition? Current literature focuses on the dyadic relationship between the government and potential challengers. We shift the focus toward exploring how network structures affect the strategic behavior of political actors. We derive and examine testable hypotheses using latent space analysis to infer actors' positions vis-a-vis each other in the network. Network structure is examined and used to test our hypotheses with data on conflicts in Thailand 1997-2010.

Learning from the past and stepping into the future: The next generation of crisis prediction

Submitted by Mike Ward on December 3, 2012 - 1:40pm

Developing political forecasting models not only increases the ability of political scientists to inform public policy decisions, but is also relevant for scientific advancement. As part of a larger project, a team at Duke University created a series of geographically informed statistical models for conflict prediction. The generated predictions have been highly accurate, with few false negative and positive categorizations. Predictions are made at the monthly level for six months periods into the future, taking into account the social-spatial context of each individual country.

Convincing State-Builders? Disaggregating International Legitimacy in Abkhazia

Submitted by Mike Ward on December 12, 2012 - 10:25am

This study investigates de facto states’ internal legitimacy—people’s confidence in the entity itself, the regime, and institutions.  Using original data from a 2010 survey in Abkhazia, we operationalize this using respondent perceptions of security, welfare, and democracy. Our findings suggest that internal legitimacy is shaped by the key Weberian state-building function of monopoly of the legitimate use of force, as well as these entities’ ability to fulfill other aspects of the social contract. 

Do Democracies Attract Portfolio Investment?

Submitted by Mike Ward on December 10, 2012 - 8:57am
Cao, Xun, and Ward, Michael D. 2013. “Do Democracies Attract Portfolio Investment?”. International Interactions.

For many, transnational capital is an important driving force of economic globalization. However, we know little about the political determinants for cross-border portfolio investments. Recent economic literature focuses upon information asymmetries. We move beyond this and intro- duce an explicitly political element into the study of international asset flows. Democratic institutions attract portfolio investments because they reduce the chances of predatory practices.

Forecasting is difficult, especially about the future: Using contentious issues to forecast interstate disputes

Submitted by Mike Ward on November 16, 2012 - 7:36am

Prediction is an important goal in the study of international conflict, but a large body of research has found that existing statistical models generally have disappointing predictive abilities. We show that most efforts build on models unlikely to be helpful for prediction.

Predicting the 2012 US Presidential Election - The Day After

Submitted by Florian Hollenbach on November 7, 2012 - 7:10pm

In our paper prepared for APSA 2012 (Here) we used Ensemble Bayesian Model Averaging to combine 9 prominent political science forecasting model into a single prediction for the 2012 presidential election. The EBMA prediction was based on the track record of these models in the past and their 2012 forecast. 

Our model predicted 50.48% of the two party popular vote for President Obama. And while that is just about right on for the popular vote percentage, it is under by 7/10 of a percent from the current figures, which give President Obama 51.2% of the two-party popular vote (Results still changing, November 8, 11:00 am EST).

The EBMA model places a lot of weight on the prediction generated by Professor Alan Abramowitz, and we’d do a lot worse without his model in the ensemble. We are likely to have under predicted President Obama's vote share because most of the models did under predict, especially those favoring a Romney victory. Both of these factors drew our aggregate prediction below what actually occurred. But not by too much.

It is now very clear that the ensemble aggregation approach, applied to polls by Drew Linzer and Simon Jackman, among others, did very well in predicting the outcome in terms of state results and electoral votes--even if one looks at their results from last summer, ignoring election eve updates. 

While the EBMA prediction is not necessarily the "best" prediction for any single observation (election), we contend that it outperforms single predictive models over many observations. Stay tuned and in four years, we’ll try again.
Tags: 
forecasting
US
elections

Gravity's Rainbow: A Dynamic Latent Space Model for the World Trade Network

Submitted by Mike Ward on October 5, 2012 - 11:19am

The gravity model, long the empirical workhorse for modeling international trade, ignores network dependencies in bilateral trade data, instead assuming that dyadic trade is independent, conditional on a hierarchy of covariates over country, time, and dyad.   We argue that there are theoretical reasons as well as empirical reasons to expect network dependencies in international trade. Consequently standard gravity models are empirically inadequate.  We combine a gravity model specification with "latent space" networks to develop a dynamic mixture model for real-valued directed graphs.

Ensemble Predictions of the 2012 US Presidential Election

Submitted by Mike Ward on September 28, 2012 - 6:54am

We use ensemble methods to combine ten various forecasts of the US election, the most recent being almost two months prior to the November 2012 election. Based on this combination, and the component models, we estimate a 0.60 probability that the popular vote for the incumbent will be greater than 50%.

Tags: 
forecasting
US
elections