engleski

An empiricala analysis of voting patterns in four battleground states of the 2016 US presidential election

The results of the 2016 US Presidential Election showed the inaccuracy of the polls and the unexpected victories of the Republican candidate in Michigan, Florida and Pennsylvania, thereby allowing Donald Trump to carry the electoral vote. By using a standard Ordinary Least Squares regression, we designed predictive models for four battleground states and assessed their accuracy. The model proposed by Lewis-Beck and Tien is used as the foundation for proposing secondary models that consider macroeconomic variables. While most of these models fail to provide accurate results, the models which use macroeconomic variables correctly identify the results for Pennsylvania and Ohio.

US presidential election ; battleground states ; blue-collar states ; voting models ; OLS regression

Rad je produkt mentora-profesora i bivšeg studenta- diplomanta. Preduvjet za objavu rada bilo je plaćanje korekture teksta od strane izvornog govornika, koje je plaćeno u iznosu 200, 01 Eura.