We have developed a game-theory based prediction tool, named Preana, based on a promising model developed by Professor Bruce Beuno de Mesquita. The first part of this work is dedicated to exploration of the specifics of Mesquita's algorithm and reproduction of the factors and features that have not been revealed in literature. In addition, we have developed a learning mechanism to model the players' reasoning ability when it comes to taking risks. Preana can predict the outcome of any issue with multiple stake-holders who have conflicting interests in economic, business, and political sciences. We have utilized game theory, expected utility theory, Median voter theory, probability distribution and reinforcement learning. We were able to reproduce Mesquita's reported results and have included two case studies from his publications and compared his results to that of Preana. We have also applied Preana on Iran's 2013 presidential election to verify the accuracy of the prediction made by Preana.

Over the past few decades, falling voter turnout rates have induced governments to adopt compulsory voting laws, in order to mitigate issues such as the socioeconomic voter gap and to bring a broader spectrum of voters into the fold. This paper presents evidence that the introduction of mandatory voting laws increases voter turnout rates by 13 points within a particular country through an entity- and time-fixed effect panel model. Moreover, it includes a discussion of the implications of adopting mandatory voting policies within the United States, finding that compelling citizens to vote would have increased participation rates to over 90 percent in the past four presidential elections.