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This study focuses on the consequences of conspiracy theories on voter behaviour. I argue that conspiracism is not simply a tendency of populist movements but also holds instrumental value; the candidates and supporters can use conspiracy theories to demonize their opponents, thus resulting in a lower tendency of voters to cast their ballot for them. Given the lack of detailed data concerning adherence to certain conspiracy theories, search aggregate data concerning interest in the conspiracy theory from Google Trends was taken in order to overcome this. Taking the case of Donald Trump's 2016 Presidential campaign, the utilization of a multi-level regression model demonstrates that voters were less likely to vote for Clinton in states where interest in the anti-Clinton conspiracy theory was highest, testifying to a 'demonization' effect. The anti-Clinton conspiracy theories, which included allegations of high-level corruption and plots by political and financial elites, were shown to be effective on lower-income, lower-educated voter cohorts, and members of the white working-class, but not ideological conservatives. These results imply that spreading conspiracy theories finds the most success when it targets those groups which were not necessarily inclined to support a certain candidate from the outset.

This study investigates the effect that formal education, as a factor of socio-economic development, has on the intensity and forms of political protest. By way of increased socialization of democratic values, increased cognitive understanding of the society at large, and human capital to participate in protests, increases in a country's level of formal education should theoretically lead to increased levels of peaceful protest. However, increases in formal education are also theorized to play a mitigating role on the intensity of violent protests (riots) for the previously mentioned reasons as well as the fact that education acts as a strong factor in increasing social mobility. With data from 1960 to 2010 and spanning 216 countries, our empirical tests demonstrate a significant positive relationship between formal education and the intensity of anti-government protests at the early stages of socio-political development and a strong negative relationship between education and riots along the full range of data, with the later stages of development revealing a particularly strong negative correlation.

How well have populist leaders responded to the COVID-19 pandemic? There is a growing literature dedicated to populism and health outcomes. However, the ongoing pandemic provides us with a unique opportunity to study whether populist leaders fared better or worse than their non-populist counterparts by using a much larger sample size. While there has been a fruitful debate over whether populism is responsible for worse health outcomes, much of the focus has centered around the overall effect of having populist parties in power, without testing for different explanatory mechanisms. We argue that populist leaders fuel mass political polarization, which increases the overall level of hostility among the population and reduces their willingness to comply with anti-COVID measures and, more generally, contribute to public good. We test this theory using the expert-coded V-Party Dataset which contains variables for the ideological characteristics for parties around the world, as well as weekly excess mortality from the World Mortality Dataset. In addition to the OLS regression analysis, we employ a causal mediation framework to account for the order of succession of populism and political polarization. Our empirical results corroborate our main hypothesis that populism fuels political polarization, which is, in turn, associated with higher excess mortality during the ongoing pandemic. Our results are robust to alternative model specifications.

Previous studies have revealed a somewhat paradoxical strong positive correlation between per capita GDP and the intensity of anti-government demonstrations observed for the vast majority of countries (indeed, it turns out that the better people live, the more likely they are to join anti-government protests). The goal of this article is to identify possible causes of this unusual correlation. Our tests show that the processes of democratization and urbanization, as well as the expansion of formal education, are likely to be the main factors determining the positive relationship between per capita GDP and the intensity of antigovernment demonstrations, as urbanization, democratization, and expansion of education lead to an increase in the intensity of protests. Moreover, when controlling for these factors, the relationship between per capita GDP and anti-government protests becomes negative. Thus, high per capita GDP turns out to be a direct (proximate) significant negative factor affecting the intensity of anti-government demonstrations, but at thesame time it is an ultimate, even more significant positive factor in the intensity of protests. The growth of per capita GDP is quite naturally accompanied by an increase in the level of urbanization, democratization and education, which more than compensates for the direct inhibiting effect on the protests on the part of the growing per capita GDP (at least for low- and middle-income countries). In addition, the negative binomial regression model that we propose can explain not only the strong positive correlation between per capita GDP and the intensity of protests, which can be traced for a range of GDP per capita values of less than $20,000, but also the weaker negative correlation recorded for the range exceeding $20,000. The fact is that in rich countries urbanization, democratization and education indicators reach saturation levels and the vast majority of high-income countries have more or less similar levels for all three indicators. As a result, for a zone of per capita GDP values of more than $20,000, we are essentially dealing with automatic control of the correlation between GDP per capita and the intensity of protests for factors of democratization, education and urbanization, and, as our model predicts, the final effect of GDP per capita on the intensity of protests for high-income countries becomes negative, not positive.