Negative campaigning strategies were a major part of the 2016 presidential campaigns. Candidates from both major political parties attacked their opponents by spreading scandals, name-calling, and character attacks. But why are the election campaigns so negative, anyway? Psychology offers us an intuitive explanation. When humans are placed into groups, whether they are divided along with the stance on the important issues of politics, or with arbitrary identities, it is natural to accumulate antipathy for the people on sides. This study draws a casual relationship between the division along the partisan lines and the vicious attacks from political campaigns against their opponents. Specifically, I examine 29,062 tweets tweeted by the gubernatorial candidates within the last three months leading up to the 2014 gubernatorial race across 36 states. I also measure two levels of polarization: 1) party elite polarization, the division in the legislature along party lines, and 2) mass polarization, the division among the electorates along the party line. In turn, I propose two models that suggest polarization drives vicious attacks. One model considers the top-down pressure — the greater the division among party elites in a state the more likely the candidates will use negative campaigning strategies against their opponents. In parallel, the other model considers the bottom-up pressure, which establishes the same causal mechanism but instead the pressure on candidates comes from the electorates. To quantify negative campaigns on Twitter, I measure the candidates’ tweets’ viciousness based on a novel index called the Political Tweet Viciousness Index (PTVI) as well as the tweets’ affect with a set of sentiment lexicons. It is expected that both models will explain the quantity and the viciousness of the negative campaigns.

This project seeks to explore the effect of spending on state-level ballot initiative campaigns on voter turnout. Past research into the area of voter turnout has revealed evidence of relationships between campaign spending, voter turnout, and vote outcomes. Differentials in spending by competing campaigns has been demonstrated to have clear effects on vote outcomes in a variety of electoral contexts, and aggregate spending has been shown to affect levels of voter turnout as well. However, no work has in the past sought to look exclusively at the role of spending allocated to ballot initiatives in its ability to affect turnout. I anticipate higher levels of spending by pro and opposition groups correlating to higher overall voter turnout. In addition, I expect spending by opposition groups to have the greatest impact, as these groups are able to allocate funds mainly to media ads which seek to influence voter behavior through psychological aspects like fear. Using publicly disclosed data on ballot initiative spending tied to election year, the relationship between spending and voter turnout for the previous six biannual elections in four states with active ballot measure processes is investigated. Types of election, changes in voter partisanship, voter registration, and quantities and policy areas of ballot measures considered are controlled for to establish a baseline for voter turnout. The influence of campaign spending on turnout is sought after to help bridge-the-gap in relationships between spending and vote outcome, and turnout and vote outcome.

After Saudi Arabia announced its VISION2030 plan to reduce its oil dependence through economic diversification, a wide-scale crackdown on corruption was carried out. Following that was the imposition of the first tax policy in the Kingdom, a 5% value-added tax. These reforms strike a delicate balance; to develop infrastructure and new industries, particularly for an oil-dependent economy (ODE), the country must sustain high levels of foreign direct investment (FDI) among other sources of funding. Nonetheless, attracting FDI requires transparent and resilient fiscal institutions, and the presence of corruption negatively impacts FDI by conveying uncertainty and increasing costs of conducting business. ODEs may also seek to enhance non-resource taxation, providing another stable revenue stream. FDI enlarges the non-resource tax base by including new firms and increasing employment opportunities. By relying on FDI as an indicator of institutional quality, this paper tests the interaction of corruption and FDI and its impact on levels of non-oil tax revenue. I employ regression models to conduct a cross-national study of 17 ODEs, controlling for population, GDP per capita, government expenditure, oil sector ownership and oil price. I expect to find that higher levels of corruption lead to lower levels of FDI, which in turn decreases non-oil tax revenue collection. Additionally, I will use a Fiscal Reliance Measure (Haber and Menaldo, 2011) to test the same interaction’s effect on the ratio of hydrocarbon and oil revenue to total government revenue as a second proxy for economic diversification. This research contributes to the growing field of oil-dependence and economic diversification in two ways: it rejects the presence of a “resource curse” and examines the relationship between corruption and non-resource tax revenue by studying institutional state structures, and it explores the causal mechanism running from FDI to tax revenue, whereas previous literature has tested the inverse relationship.

This paper explores the relationship between both race and income-level in community mobilization efforts and the enforcement of environmental regulatory policies. I hypothesize that mobilization efforts carried out by lower-income communities of color will result in a lower rate of enforcement than those carried out by their white affluent counterparts. Prior research has taken a qualitative approach to track numerous community mobilization efforts and focused almost exclusively on environmental injustice communities. My research defines and quantifies four separate forms of mobilization and measure if their presence, both before and after exposure, impacts the rate of enforcement of regulatory policies. I focus on the Bay Area of California and the enforcement of the California Environmental Quality Act (CEQA) and the Clean Air Act (CAA). I use a multivariate analysis to empirically test the relationship between my independent variables and my dependent variables so as to determine if their relationship is statistically significant. I theorize that deliberate indifference on the part of environmental agencies to address the concerns of lower-income communities of color will result in an unequal rate of enforcement. Ultimately, institutional racism embedded within these institutions, as well as a community’s inability to combat negligence due to lack of monetary resources explains this outcome.